SentiScan

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Product Details

Name

SentiScan

Tagline

Unlock Insights, Empower Growth

Insightful Ivy

Name: Insightful Ivy
Description: Insightful Ivy is a dedicated Consumer Insights Manager who thrives on understanding consumer behavior. With a knack for storytelling, she combines quantitative data with qualitative anecdotes to present findings in a relatable manner. Ivy stays engaged with her team and stakeholders by using SentiScan to provide impactful insights and recommendations. Her day typically involves sifting through data, brainstorming with colleagues, and crafting presentations that translate complex analytics into actionable strategies.
Demographics: Age: 34, Gender: Female, Education: Master's in Marketing, Occupation: Consumer Insights Manager at a mid-sized firm, Income Level: $85,000 annually.
Background: Ivy grew up in a middle-class family that valued education and curiosity. After earning her Bachelor's in Business Administration, she pursued her Master's in Marketing, where she discovered her passion for consumer behavior and market trends. After a few years working as a marketing analyst, she transitioned into her current role where she balances data analysis with creative storytelling. In her free time, Ivy enjoys volunteering for local non-profits and participating in book clubs.
Psychographics: Ivy values integrity, creativity, and the pursuit of knowledge. She is motivated by the desire to influence positive change through her work, using her insights to help shape effective marketing strategies. Ivy enjoys staying updated on industry trends, using podcasts and webinars to learn about innovative practices. Her interests also include creative writing and community service, reflecting her empathy towards consumers and society.
Needs: Ivy needs real-time insights to understand shifts in consumer sentiment, comprehensive data analysis tools to distill complex information, and the ability to collaborate seamlessly with her team to create actionable insights for stakeholders.
Pain: Ivy experiences frustration when data silos hinder her ability to gather a complete view of consumer attitudes. She often finds that manual data consolidation is time-consuming and can lead to inaccuracies that affect her presentations. Additionally, she struggles with tight deadlines that leave little room for deep analysis.
Channels: Ivy primarily uses online channels such as LinkedIn for professional networking, industry-specific webinars for knowledge enhancement, and Slack for team communications. She also engages with blogs and podcasts related to marketing and consumer behavior.
Usage: Ivy interacts with SentiScan daily, utilizing it to monitor sentiment analysis and integrate findings into her reports. She frequently explores the dashboard to uncover trends and prepare for her weekly team meetings, dedicating around 3-4 hours a week on average to navigate the software.
Decision: Ivy's decision-making process is influenced by quantitative data insights, peer recommendations, and industry best practices. She seeks tools that are user-friendly and customizable to her needs, often involving her team in discussions to evaluate the pros and cons of new analytics solutions.

Strategic Sam

Name: Strategic Sam
Description: Strategic Sam is a methodical Marketing Director, known for his ability to develop data-driven strategies based on thorough market research. With a keen understanding of his audience, he leverages SentiScan to refine marketing initiatives and drive ROI. Sam spends his days analyzing data trends, strategizing marketing campaigns, and collaborating with cross-functional teams to ensure alignment with overall business goals.
Demographics: Age: 42, Gender: Male, Education: MBA in Marketing, Occupation: Marketing Director at a large corporation, Income Level: $120,000 annually.
Background: Sam was raised in a family of educators which instilled a love for learning and critical thinking early on. After obtaining his MBA, he began his career in entry-level marketing roles and quickly climbed the corporate ladder due to his analytical prowess and strategic thinking. With hobbies such as hiking and photography, he finds balance away from the office.
Psychographics: Sam is driven by results and values authenticity in marketing. He believes in the power of data to uncover truths about consumer preferences. Apart from staying current with marketing trends, Sam enjoys mentoring aspiring marketers, reflecting his commitment to professional development. He cherishes outdoor activities, lending to his preference for a healthy work-life balance.
Needs: Sam requires insights that are not only accurate but also actionable, including comprehensive dashboards and benchmarking tools to compare against competitors. He needs to understand market trends quickly to inform campaign strategies effectively.
Pain: Sam often faces challenges with adapting to rapidly changing market dynamics and analyzing large volumes of data to derive strategic insights. He also feels pressure from upper management to deliver high-performance marketing results, which can lead to stress and burnout.
Channels: Sam engages predominantly via professional networks like LinkedIn, industry forums, and marketing blogs. He utilizes email newsletters for the latest marketing insights and attends trade conferences for face-to-face networking and learning.
Usage: Sam uses SentiScan on a daily basis, typically spending about 5 hours a week accessing insights for campaign preparation and performance review. He frequently collaborates with his team through the platform to centralize analytics discussions.
Decision: Sam’s decision-making is largely based on empirical evidence and ROI metrics. He values comprehensive demonstrations and testimonials from users when considering new tools, ensuring they align with overall marketing objectives.

Innovative Isla

Name: Innovative Isla
Description: Innovative Isla is a forward-thinking Social Media Strategist who thrives on creativity and engagement. Using SentiScan, she monitors real-time audience sentiment and feedback to create captivating content that resonates with followers. Isla's typical day includes brainstorming sessions, content creation, and community management, always keeping a close eye on trends and audience reactions.
Demographics: Age: 28, Gender: Female, Education: Bachelor’s in Communication, Occupation: Social Media Strategist for a tech startup, Income Level: $65,000 annually.
Background: Growing up in a digitally-connected world, Isla was always fascinated by how brands interacted with their audiences. After completing her studies in communication, she worked as a content creator before moving into social media strategy, where she could blend her creativity with data. Passionate about technology and innovation, Isla also enjoys attending tech meetups and exploring the latest apps.
Psychographics: Isla values creativity, connection, and authenticity. She is motivated by the desire to engage with her audience on a personal level, using feedback to create relevant content and foster community. Her interests expand into digital art and video editing, reflecting her commitment to her craft and personal expression.
Needs: Isla needs instant access to audience sentiment analysis to inform her content strategy, reliable tools for scheduling and tracking social media interactions, and insights on audience engagement to guide her creative decisions.
Pain: Isla struggles with managing the fast-paced demands of social media while ensuring content quality. She often deals with negative feedback from audiences and feels pressured to respond quickly, which can lead to burnout.
Channels: Isla utilizes social media platforms like Instagram and Twitter for engagement and insights, along with forums and groups on Facebook focused on marketing trends. She also turns to YouTube for educational content around content creation and strategy.
Usage: Isla interacts heavily with SentiScan, dedicating approximately 7 hours weekly to monitor sentiment and engagement metrics. She uses the platform daily when developing new campaigns or responding to audience feedback.
Decision: Isla's decision-making process is influenced by audience feedback, industry trends, and peer validation. She is drawn to tools that enhance her creative process and streamline her workflow, weighing both function and user experience.

Product Ideas

InsightPulse: InsightPulse is an augmented feature within SentiScan that provides predictive analytics on emerging trends based on historical sentiment data. By leveraging machine learning algorithms, it forecasts potential shifts in consumer attitudes, allowing businesses to proactively adapt their strategies and engage with audiences before significant shifts occur. The integration of InsightPulse enhances the strategic capabilities of users by providing foresight into market dynamics.
Sentiment360: Sentiment360 is a holistic dashboard enhancement that aggregates sentiment data across multiple channels into a unified view. By visualizing key metrics and trends in a customizable interface, it allows users to easily track brand sentiment evolution across platforms, ensuring that they can make informed decisions quickly. This feature promotes cross-channel insights for a more comprehensive understanding of audience engagement and perception.
Competitor Radar: Competitor Radar is a new module in SentiScan that enables users to monitor competitor sentiment and activity. It tracks brand mentions and sentiment analysis related to competitor products, providing insights that help users refine their market positioning. This tool enables brands to understand their competitive landscape better and adjust their strategies accordingly, fostering a proactive approach to market competition.
Feedback Loop: Feedback Loop is an interactive feature that enables users to generate real-time polls and surveys directly from within SentiScan. This tool allows marketers to gather immediate audience feedback on specific campaigns or products, thereby enhancing consumer engagement. By integrating user feedback into sentiment analysis, brands can adapt quickly to consumer needs and preferences, leading to more effective marketing strategies.
Sentiment Alerts: Sentiment Alerts is a notification system that informs users of significant changes in brand or product sentiment in real-time. By utilizing AI to analyze sentiment shifts, this feature ensures that marketers and brand managers can react promptly to emerging crises or opportunities, preventing negative feedback from impacting their brand reputations and capitalizing on positive sentiment.
Personalized Insights: Personalized Insights tailors the SentiScan experience based on user behavior and preferences, delivering customized reports and highlights that matter most to each user. By utilizing machine learning for personalization, it enhances user engagement by ensuring that relevant data is front and center, making insights actionable and relevant for strategic planning.
Engagement Predictor: Engagement Predictor uses AI algorithms to analyze historical data and predict the engagement rates of future content. This tool equips marketers with actionable insights by recommending optimal posting times and content types based on audience sentiment, ensuring that their campaigns are strategically timed for maximum impact and interactivity.

Product Features

Trend Forecaster

Trend Forecaster utilizes advanced machine learning algorithms to predict upcoming consumer sentiment trends with high accuracy. By analyzing historical data and patterns, this feature empowers users to stay ahead of market shifts, allowing them to tailor their strategies proactively. This proactive approach enhances user confidence in decision-making, reduces response times, and fosters stronger audience engagement by aligning marketing initiatives with predicted sentiments.

Requirements

Real-time Data Processing

User Story: As a marketing analyst, I want real-time processing of sentiment data so that I can make immediate and informed decisions based on current trends.
Description: The Real-time Data Processing requirement ensures that the Trend Forecaster feature can analyze and process incoming data from social media and online platforms instantaneously. This functionality is critical in empowering users to react swiftly to emerging trends and consumer sentiments. By integrating advanced machine learning algorithms, data is continuously analyzed, allowing marketers to gain immediate insights into public opinion and sentiment changes. Effective real-time analysis enhances user decision-making capabilities and reduces lag time in adapting marketing strategies accordingly.
Acceptance Criteria: As a market analyst using SentiScan's Trend Forecaster, I want to receive real-time updates on sentiment changes for specific keywords so that I can make timely marketing decisions.

Given that the user has selected specific keywords, when new data is ingested, then the system should provide updates within 5 seconds of data processing completion for any sentiment changes.

As a marketer leveraging the Trend Forecaster, I need to analyze real-time sentiment trends across multiple social media platforms to inform campaign strategy.

Given multiple social media platforms are integrated, when the data is processed, then the Trend Forecaster should display sentiment analysis results on an intuitive dashboard updated in real time without lag.

As a product manager, I want to ensure the accuracy of the Trend Forecaster predictions so we can trust the insights for decision-making.

Given a set of historical data, when predictions are generated through the Trend Forecaster, then the accuracy should be within 90% when validated against actual sentiment changes over a 7-day period.

As a user of SentiScan, I want to be alerted when there is a significant shift in sentiment for my brand so that I can respond promptly to consumer feedback.

Given that the sentiment changes significantly (defined as a 20% increase or decrease), when the data is processed, then the user should receive an alert notification via email and within the application immediately.

As an analyst utilizing the Trend Forecaster, I need the system to handle multiple concurrent data streams without performance degradation.

Given multiple concurrent data streams from different social media channels, when the system processes this data, then there should be no more than a 2-second delay in analysis for each stream.

As a user of SentiScan, I want an easy-to-understand visualization of sentiment trends in real-time to enhance comprehension and decision-making.

Given real-time sentiment data is available, when data is visualized on the dashboard, then the visual representation should be accessible and comprehensible, with clear labeling and trends highlighted within 2 seconds of processing.

Sentiment Trend Prediction

User Story: As a brand manager, I want to predict sentiment trends so that I can adjust my marketing strategies proactively and stay ahead of competitors.
Description: The Sentiment Trend Prediction requirement encompasses sophisticated algorithms designed to forecast future consumer sentiment trends accurately. By utilizing historical data and advanced machine learning techniques, this feature will provide users with a predictive model that reveals potential shifts in consumer attitudes. This functionality is crucial for empowering users to adjust their marketing strategies proactively, and the expected outcome includes improved campaign alignment with forecasted sentiments and a competitive edge in the marketplace.
Acceptance Criteria: User accesses the Trend Forecaster feature to view predicted consumer sentiment trends for an upcoming marketing campaign.

Given that the user logs into the SentiScan application, When they navigate to the Trend Forecaster section and request sentiment predictions for the next quarter, Then the system should display accurate predictions with at least 90% accuracy based on historical data.

User receives an alert for a significant predicted change in sentiment trends.

Given a significant shift in predicted consumer sentiment is identified by the system, When the Trend Forecaster processes the data, Then an alert notification should be sent to all users subscribed to that prediction within one hour.

User analyzes the effectiveness of previous campaigns based on predicted sentiment trends.

Given the user has completed a marketing campaign, When they review the Performance Analytics dashboard, Then the system should show a correlation of at least 85% between the predicted sentiment trends and actual consumer reactions post-campaign.

User customizes the parameters of sentiment trend predictions based on demographic data.

Given a user wants to filter sentiment predictions, When they select specific demographic parameters (age, location, interests) and run the prediction, Then the system should provide a customized forecast for the selected demographics.

User exports sentiment trend prediction data for report preparation.

Given that the user is on the Trend Forecaster page, When they select the 'Export' option, Then the system should generate a CSV file containing the predicted trends accurately formatted and ready for presentation.

Intuitive Dashboard Visualization

User Story: As a user, I want an intuitive dashboard to visualize sentiment trends so that I can quickly understand the data and make decisions effectively.
Description: The Intuitive Dashboard Visualization requirement focuses on presenting sentiment analysis and prediction data in an easily digestible format. This involves developing user-friendly dashboards that visually represent data through charts, graphs, and other visual aids. The intention behind this is to make complex data comprehensible at a glance, allowing users to quickly identify trends and areas that require action. Enhanced visualization fosters better decision-making and user engagement, aligning with the product’s goal of providing actionable intelligence.
Acceptance Criteria: User Navigates to the Intuitive Dashboard Visualization to Analyze Sentiment Trends

Given the user is logged into the SentiScan platform, when they navigate to the Intuitive Dashboard, then they should see a clean layout that visually represents sentiment analysis data through charts and graphs without any loading delays.

User Customizes Dashboard to Focus on Specific Metrics

Given the user is on the Intuitive Dashboard, when they select specific metrics to display (such as engagement rates or sentiment scores), then the dashboard should update in real-time to reflect only the selected data in a visually appealing manner.

User Receives Real-Time Alerts for Significant Sentiment Changes

Given the user has set up alert preferences, when sentiment data changes significantly (e.g., a +/- 20% shift), then the user should receive immediate notifications via the dashboard and email indicating the nature of the change and its potential impact.

User Exports Visual Data from the Intuitive Dashboard

Given the user is viewing the Intuitive Dashboard, when they select to export the displayed visual data, then the data should be exported in popular formats (CSV, PDF, PNG) with no loss of fidelity, preserving original visual properties.

User Accesses Help Feature for Understanding Dashboard Components

Given the user is interacting with the Intuitive Dashboard, when they click on the help icon, then a tooltip or help popup should appear, providing clear explanations of each dashboard component and its relevance to sentiment analysis.

User Engages with Interactive Elements on the Dashboard

Given the user views the Intuitive Dashboard, when they hover over or click on any interactive chart element, then additional detailed insights should be displayed without any lag or performance issues.

User Views Historical Sentiment Data on the Dashboard

Given the user is on the Intuitive Dashboard, when they select a specific time range for sentiment analysis, then the dashboard should accurately reflect historical data trends for that selected period in a visually coherent manner.

Alerts for Sentiment Shifts

User Story: As a marketer, I want to receive alerts for significant sentiment shifts so that I can act promptly to adjust my strategies and communications.
Description: The Alerts for Sentiment Shifts requirement involves implementing a notification system that alerts users in real-time when significant changes in consumer sentiment are detected. This feature is essential for ensuring that users are immediately informed about critical sentiment shifts that could impact their marketing initiatives. By enabling users to set thresholds for alerts, they can customize their experience and ensure they react promptly to market dynamics, thus increasing responsiveness and engagement with their audience.
Acceptance Criteria: User receives an alert when consumer sentiment drops below a set threshold after monitoring social media channels for 24 hours.

Given the user has set a sentiment threshold for alerts, when the sentiment score falls below that threshold in the monitored period, then the user receives a real-time notification via email and the application dashboard.

User customizes alert settings for specific products or campaigns and receives notifications related to those specific alerts.

Given the user has customized alert settings for certain products or campaigns, when significant sentiment shifts occur in the specified areas, then the user receives targeted notifications only for those product or campaign alerts.

User wants to review past sentiment shifts and the corresponding alerts received over the last month for insights.

Given that the user navigates to the alert history section, when viewing sentiment shift alerts for the past month, then the user sees a complete log of notifications with timestamps, sentiment scores, and product or campaign relevance.

User sets multiple thresholds for different social media platforms and expects alerts based on platform-specific sentiment data.

Given the user has set varying sentiment thresholds for different platforms, when sentiment data indicates a breach of any threshold, then the user receives tailored alerts for the specific platform where the shift occurred.

User optimizes response strategy based on alert data from previous sentiment shifts.

Given the user evaluates prior alert data associated with sentiment shifts, when analyzing the corresponding marketing responses, then the user identifies at least three actionable improvements to enhance future responsiveness.

User wishes to ensure they receive alerts even when the application is not in active use.

Given the user has enabled push notifications in their alert settings, when a significant sentiment shift occurs, then the user receives a push notification on their mobile device regardless of application status.

User tests the alert system by simulating a sentiment shift to evaluate the functionality of notifications.

Given the user simulates a sentiment shift through the application testing environment, when the system detects this shift, then the user receives the corresponding alert according to their set preferences in less than two minutes.

Competitor Benchmarking

User Story: As a strategic planner, I want to benchmark my company's sentiment data against competitors so that I can identify our strengths and weaknesses in the market.
Description: The Competitor Benchmarking requirement aims to feature an analysis tool that allows users to compare their sentiment data against key competitors. This functionality will enable users to evaluate their performance in relation to the broader market landscape, identifying both strengths and areas for improvement. It also serves to inform users on how to position their brands effectively against rivals, fostering strategic decision-making and enhancing competitive advantage in marketing efforts.
Acceptance Criteria: User compares their sentiment analysis data with three of their direct competitors over the course of a monthly analysis report.

Given the user has selected the competitor benchmarking feature, when they input their brand and select up to three competitor brands, then they should receive a comparative sentiment analysis report within ten minutes that highlights sentiment scores, trends, and key insights.

The user wants to assess how their brand’s sentiment scores fluctuate compared to their competitors over the last quarter.

Given the user accesses the competitor benchmarking tool, when they select a date range of the last three months, then the system should display line graphs illustrating sentiment trends for all selected brands, including compounding analysis results for easy comparison.

A marketing analyst seeks to derive actionable insights from benchmarks to strategize their upcoming campaign.

Given the user has loaded the competitor benchmarking results, when they toggle on the option for insights generation, then the system should present a list of actionable recommendations based on the comparative performance of each brand.

Users need to review and download their competitor benchmarking reports for internal meetings.

Given the user has generated a competitor benchmarking report, when they click the download button, then a PDF report containing detailed analysis, graphs, and insights should be successfully downloaded to their device.

A user checks the availability of sentiment data for new competitors added to the system.

Given the user enters a competitor that is not currently in the benchmarking database, when they submit the competitor's information, then they should receive a notification indicating whether the competitor's data is available or not.

The user aims to visualize the competitor sentiment data on a shared dashboard.

Given the user has successfully generated the competitor benchmarking report, when they choose to share the report via a dashboard link, then the link should allow team members to view live sentiment data visualizations without requiring additional permissions.

The user wants to receive alerts when there are significant changes in competitor sentiment scores.

Given the user has set up competitor alerts for their selected benchmarks, when there is a percentage change exceeding the user-defined threshold, then an email notification should be sent to the user within one hour of the change occurring.

Sentiment Shift Alerts

Sentiment Shift Alerts provide real-time notifications when predictive analytics indicate significant changes in consumer attitudes. This feature ensures marketers and analysts are promptly informed of potential issues or opportunities, enabling rapid response and strategy adjustment. By allowing immediate engagement based on forecasted trends, businesses can mitigate risks associated with negative sentiment or capitalize on positive momentum, enhancing their overall performance and brand reputation.

Requirements

Real-time Notification System

User Story: As a marketing analyst, I want to receive real-time alerts about sentiment shifts so that I can quickly respond to changes in consumer attitudes and adjust our strategies accordingly.
Description: The Real-time Notification System requirement encompasses the development of a robust alert mechanism that notifies users immediately when significant sentiment shifts are detected through predictive analytics. This functionality should leverage push notifications, email alerts, and dashboard updates to ensure that marketers and analysts are kept informed of changes in consumer attitudes as they occur. The benefit of this feature is that it empowers users to make swift decisions, seize opportunities, and respond to potential risks promptly. Implementation will involve integrating with existing data analytics engines, ensuring reliability and speed in delivering alerts, and customizing the type of notifications based on user preferences. Expected outcomes include improved responsiveness to market conditions, enhanced ability to address issues before they escalate, and optimized strategic planning in marketing campaigns.
Acceptance Criteria: User receives a notification when a significant positive sentiment shift occurs in the brand's social media mentions after a marketing campaign launch.

Given the Real-time Notification System is enabled, When the predictive analytics identify a positive sentiment shift of at least 20%, Then the user receives a push notification and an email alert within 5 minutes of detection.

Marketers customize the types of notifications they want to receive based on their preferences within the user settings.

Given the user is logged into their account, When they access the notification settings, Then they can select which types of sentiment shift notifications (e.g., email, push, dashboard update) they want to receive, and save those preferences successfully.

The system sends notifications for significant negative sentiment shifts to relevant users immediately.

Given the Real-time Notification System is active, When the sentiment analysis detects a negative sentiment shift of at least 15%, Then all relevant users configured for alerts receive a notification within 3 minutes of detection through their selected channels.

Users successfully receive dashboard updates related to sentiment shifts during a daily recap session.

Given the user accesses the dashboard, When the daily recap time arrives, Then the user sees a summary of all sentiment shifts including timestamps and alert types for the previous day.

Users are able to snooze notifications for a specific duration without missing critical updates.

Given the user receives a sentiment shift notification, When the user opts to snooze notifications for a duration of 30 minutes, Then the system stops sending alerts for that duration and resumes after the time is up.

A user can seamlessly integrate the Real-time Notification System with their existing communication tools.

Given the user is in the integration settings, When they connect their communication tool (e.g., Slack, Microsoft Teams), Then the system sends a test notification successfully and confirms the integration with a success message.

Customizable Alert Settings

User Story: As a user, I want to customize my alert settings so that I only receive notifications that are relevant to my role and objectives, helping me manage my attention more effectively and focus on critical insights.
Description: The Customizable Alert Settings requirement allows users to personalize their alert preferences to ensure that they receive notifications that are most relevant to their specific needs. This includes options for defining thresholds for sentiment shifts that trigger alerts, selecting preferred communication channels (email, SMS, in-app alerts), and specifying the frequency of updates. By empowering users to customize these settings, the feature enhances user experience and ensures that marketers receive only the most pertinent information. This functionality should be seamlessly integrated into the existing user interface, allowing for intuitive interaction and modification of settings. Benefits include reduced alert fatigue and increased relevance of information, ultimately leading to better decision-making and more effective marketing strategies.
Acceptance Criteria: User customizes alert preferences for sentiment shifts through the application settings interface.

Given the user accesses the customizable alert settings, When they define a sentiment threshold, Then the system should save the threshold and apply it to future alerts.

User selects preferred communication channels for receiving sentiment shift alerts.

Given the user can choose between email, SMS, and in-app notifications, When they select their preferred channels and save the settings, Then the system should send alert notifications only through the selected channels.

User specifies the frequency of updates for sentiment alerts.

Given the user sets the frequency of alerts to daily, When a sentiment shift occurs, Then the user should receive a single notification per day summarizing any changes.

User reverts the alert settings to default after customizing them.

Given the user has changed their alert settings, When they select the 'Reset to Default' option, Then the system should revert all settings to the initial default configuration.

User receives an alert for a significant positive sentiment shift.

Given a sentiment analysis indicates a positive shift above the user's set threshold, When the alert is triggered, Then the user should receive a notification through their selected communication medium in real-time.

User receives an alert for a significant negative sentiment shift.

Given a sentiment analysis indicates a negative shift below the user's set threshold, When the alert is triggered, Then the user should receive a notification through their selected communication medium in real-time.

User accesses the alert settings from the main dashboard.

Given the user is on the main dashboard, When they navigate to the alert settings, Then the user should be able to view and edit their current alert preferences.

Sentiment Analysis Dashboard

User Story: As a marketing manager, I want an interactive dashboard that visualizes sentiment trends over time so that I can assess the effectiveness of our marketing initiatives and make data-driven decisions.
Description: The Sentiment Analysis Dashboard requirement involves the creation of a user-friendly interface that visually represents consumer sentiment trends over time, utilizing graphs, charts, and other data visualization techniques. This dashboard will integrate with the sentiment shift alerts to provide contextual data surrounding the changes being notified. The intention is to give users deeper insights into the factors driving sentiment changes, enhancing their ability to analyze and interpret data. This functionality should be designed to support quick interpretations and insights, allowing users to easily track performance metrics and correlate them with marketing campaigns. Expected outcomes include improved strategic decision-making through visibility into sentiment trends, enhanced analytical capabilities, and the ability to identify correlations with campaign performance.
Acceptance Criteria: User views the Sentiment Analysis Dashboard after receiving a sentiment shift alert to analyze the factors driving the change.

Given a user has received a sentiment shift alert, when they access the Sentiment Analysis Dashboard, then they should see visual representations of sentiment trends for the relevant period with corresponding annotations for key events.

Marketing team evaluates the effectiveness of a recent campaign by correlating sentiment data shown on the dashboard with campaign performance metrics.

Given marketing data is input from a recent campaign, when the user accesses the Sentiment Analysis Dashboard, then they should be able to filter sentiment data by campaign date range and see performance metrics displayed side by side.

An analyst wishes to download the sentiment data displayed on the dashboard for weekly reporting.

Given the Sentiment Analysis Dashboard is displayed, when the user selects the option to download data, then they should receive a CSV file containing the visualized sentiment data for the selected time frame.

A user wants to set custom alerts based on specific sentiment thresholds exhibited on the dashboard.

Given the user is on the Sentiment Analysis Dashboard, when they specify a sentiment threshold, then the system should enable the option to create an alert that notifies the user when the threshold is met or exceeded.

An executive wants to view a summary of the sentiment trends for a quarterly review meeting using the dashboard.

Given that the executive selects a quarterly date range, when the Sentiment Analysis Dashboard is refreshed, then it should provide a summary view, including the average sentiment score, trends, and highlights of major sentiment shifts during that period.

A user navigates through the Sentiment Analysis Dashboard and wants to view more detailed insights about a specific trend identified.

Given a trend is displayed on the dashboard, when the user clicks on that trend, then there should be a pop-up or expansion that shows deeper insights, including relevant data points and contextual information about what may have influenced the sentiment.

Predictive Sentiment Metrics

User Story: As a product manager, I want access to predictive sentiment metrics so that I can anticipate changes in consumer behavior and align our strategies proactively instead of reacting to trends after they occur.
Description: The Predictive Sentiment Metrics requirement involves incorporating advanced predictive analytics capabilities that analyze historical sentiment data to forecast future sentiment trends. This feature will equip users not only with current insights but also with predictions about potential shifts in consumer attitudes, allowing for proactive strategy adjustments. The system should employ machine learning techniques to refine its predictive accuracy over time, providing actionable insights that help users stay ahead of market trends. This requirement is critical for organizations aiming to maintain a competitive edge by being capable of anticipating consumer behavior rather than just reacting to it. The expected outcome is an enhanced strategic planning process that incorporates foresight and minimizes risks associated with sudden sentiment changes.
Acceptance Criteria: Real-time User Notification of Sentiment Changes

Given that a significant sentiment change is predicted based on historical data, when the prediction is confirmed, then a real-time alert should be sent to the user via email and in-app notifications.

Accuracy of Predictive Sentiment Analysis

Given a dataset of historical sentiment data, when predictive analytics are applied, then the accuracy of the predictions should be validated against actual sentiment shifts, ensuring at least 80% predictive accuracy in one-month forecasts.

Integration with Market Strategy Tools

Given that predictive sentiment metrics are generated, when users access the metrics, then they should be able to integrate these insights seamlessly into existing market strategy tools and dashboards with minimal downtime.

User Dashboard Display of Sentiment Trends

Given the Predictive Sentiment Metrics feature, when a user accesses their dashboard, then they should see visual representations of both current and predicted sentiment trends over time, updated in real-time.

Historical Data Analysis for Trend Accuracy

Given the historical sentiment data, when the system is processing this data for predictive analytics, then it should display a report of past prediction accuracies and adjustment measures taken to refine its algorithms.

Feedback Mechanism for Sentiment Predictions

Given the implementation of Predictive Sentiment Metrics, when a user receives a sentiment prediction alert, then they should have the option to provide feedback on the accuracy of the prediction to improve future predictive models.

Performance Monitoring Over Time

Given the predictive analytics implementation, when the feature is in use for six months, then the system should report on its performance metrics, including accuracy rates, user engagement levels, and the number of alerts sent.

Integration with Third-Party Tools

User Story: As a digital marketer, I want to integrate SentiScan with my CRM and other tools so that I can analyze sentiment data in context with other marketing metrics for a holistic view of performance.
Description: The Integration with Third-Party Tools requirement focuses on the capability to connect SentiScan with external platforms such as CRM systems, social media management tools, and data visualization services. This integration will allow for a more comprehensive analysis of sentiment data alongside other relevant marketing information, creating a unified view of consumer insights. The feature should allow for simple authentication and data syncing mechanisms, enabling users to streamline their workflows and improve the efficiency of their marketing efforts. By providing this capability, the software can enhance the value it offers to users, resulting in better-informed strategies and increased operational efficiencies through automation and data consolidation. Expected outcomes include smoother processes and increased productivity as analysts can leverage combined insights across multiple tools.
Acceptance Criteria: As a marketer, I want to integrate SentiScan with my CRM tool so that I can view sentiment analysis alongside customer data for more informed decision-making.

Given that the user has valid credentials for the CRM, when they initiate the integration, then the SentiScan system should authenticate the user and synchronize relevant sentiment data without errors.

As a social media manager, I want to receive alerts in SentiScan when sentiment shifts occur on our brand's social media platforms, so I can respond proactively.

Given that the sentiment shift threshold is configured, when a significant change in sentiment is detected, then SentiScan should send a real-time notification to the user and log the event in the system.

As an analyst, I need to visualize sentiment data in a third-party data visualization tool, so that I can create comprehensive reports for stakeholders.

Given that the appropriate APIs are set up, when the analyst requests to export sentiment data, then the data should be successfully formatted and pushed to the external visualization tool without loss of information.

As a product manager, I want to ensure that data syncing occurs without conflicts between SentiScan and third-party tools, so that the data remains accurate and reliable.

Given that data syncing is scheduled, when the sync operation is initiated, then the system should compare timestamps and only sync updated records, resolving conflicts automatically when they arise.

As a user, I want the ability to disconnect SentiScan from a third-party tool, so that I can manage integrations based on my changing needs.

Given that the user is logged into SentiScan, when they select the option to disconnect from a third-party tool, then the system should successfully terminate the connection and confirm the disconnection to the user.

As a user, I want to monitor the status of integrations with third-party tools in SentiScan, so I can quickly resolve any issues that arise.

Given that the user is on the integration management page, when they view the integration status, then the system should display real-time updates on the health and connectivity status of all linked tools.

Scenario Simulator

Scenario Simulator allows users to create and visualize potential market scenarios based on predictive analytics. By manipulating variables such as sentiment trends, market conditions, and campaign strategies, users can assess the potential outcomes of different approaches. This feature enhances strategic planning by enabling users to visualize the impact of their decisions and optimize their tactics, making it easier to navigate complex market dynamics.

Requirements

Dynamic Variable Adjustment

User Story: As a market analyst, I want to adjust key variables in the Scenario Simulator so that I can visualize different market outcomes and make informed strategic recommendations.
Description: The Dynamic Variable Adjustment requirement enables users to manipulate key parameters within the Scenario Simulator, such as sentiment trends, market conditions, and consumer behavior. This feature allows for the real-time alteration of these variables to observe potential impacts on market scenarios. By providing this functionality, users can create customized simulations that mimic real-world situations, offering insights into how varying different elements can lead to different outcomes. The primary benefit is enhancing decision-making through predictive analytics, allowing users to explore 'what-if' scenarios and make data-informed strategies that can adapt to changing market dynamics.
Acceptance Criteria: User adjusting sentiment trend variables in the Scenario Simulator to visualize potential outcomes for a new marketing campaign.

Given the user is adjusting the sentiment trend variable, when the user modifies the value, then the projected outcome of the market scenario is updated in real-time on the dashboard.

User changing market condition parameters while simulating multiple scenarios for a product launch.

Given the user is in the Scenario Simulator, when the user alters the market condition parameter, then the system displays the new simulated outcomes for all relevant scenarios.

User experimenting with different consumer behavior variables to assess potential impacts on sales performance.

Given the user modifies the consumer behavior parameter, when the user runs the simulation, then the dashboard must reflect the updated performance metrics based on the new variable settings.

User creating a detailed scenario with multiple variable adjustments to evaluate overall market response over a specific time period.

Given the user is creating a scenario with multiple adjustments, when the user saves the scenario, then the system allows the user to retrieve and run the scenario at any time for analysis.

User testing the system's ability to handle simultaneous adjustments to various market dynamics.

Given multiple variables are being adjusted at once, when the user initiates the simulation, then the system should process all adjustments without lag and display results accurately.

User assessing the impact of a negative sentiment shift on a product's market viability.

Given the user sets a significant negative sentiment trend, when the simulation runs, then the system should clearly illustrate decreased market viability metrics, such as estimated sales and customer interest.

Scenario Visualization Dashboard

User Story: As a marketer, I want to access a visualization dashboard that displays the outcomes of my market simulations so that I can easily interpret data and present insights to my team.
Description: The Scenario Visualization Dashboard requirement facilitates an intuitive interface that displays the outcomes of various market scenarios created within the Scenario Simulator. This feature provides graphical representations of data, allowing users to easily interpret complex analytics results through charts, graphs, and comparative reports. Users benefit from being able to quickly assess the potential impact of their strategies and decisions, enhancing their ability to communicate findings to stakeholders. The visualization dashboard will aggregate simulation results and present them in an easily digestible format, promoting better understanding and facilitating agile decision-making processes.
Acceptance Criteria: User selects various variables within the Scenario Simulator to create a market scenario and navigates to the Scenario Visualization Dashboard to view the simulated outcomes.

Given a user has created a market scenario with at least three variables, when they access the Scenario Visualization Dashboard, then the dashboard should display graphical representations (charts and graphs) of the simulated outcomes for those variables.

Marketing team wants to compare two different market scenarios side by side using the Scenario Visualization Dashboard.

Given two market scenarios have been created, when the marketing team selects both scenarios for comparison, then the dashboard should provide comparative visualizations highlighting key metrics for both scenarios side by side.

User modifies a variable in the Scenario Simulator and wants to see the updated outcomes in the Scenario Visualization Dashboard immediately.

Given a user has updated a variable in the Scenario Simulator, when they return to the Scenario Visualization Dashboard, then the dashboard should refresh and reflect the updated outcomes based on the new variable settings within five seconds.

Analyst needs to present findings from the Scenario Visualization Dashboard to stakeholders during a meeting.

Given the analyst has accessed the Scenario Visualization Dashboard, when they select the 'Export' option, then the system should generate a downloadable report (PDF/Excel) containing the visual data and key metrics from the dashboard accurately.

User with limited access rights attempts to edit the visualization settings in the Scenario Visualization Dashboard.

Given a user logs in with limited access rights, when they attempt to modify the visualization settings in the Scenario Visualization Dashboard, then the system should display an error message indicating insufficient permissions to make changes.

User wants to save their customized view of the Scenario Visualization Dashboard for later reference.

Given a user has customized the visualization settings on the Scenario Visualization Dashboard, when they select the 'Save View' option, then their customized settings should be saved and retrievable during future sessions without loss of data.

User wants to analyze past simulations using historical data in the Scenario Visualization Dashboard.

Given the user selects a past simulation scenario from the historical data, when they load this scenario in the Scenario Visualization Dashboard, then the dashboard should accurately reflect the past simulation outcomes with historical graphs and data points clearly labeled.

Custom Scenario Save and Load

User Story: As a product manager, I want to save my market scenarios so that I can revisit and analyze them later without having to start from scratch each time.
Description: The Custom Scenario Save and Load requirement allows users to save their created market scenarios for later use and analysis. Users can create a library of different scenarios, making it easy to revisit previous simulations and assess how changes in conditions may lead to varying outcomes. This feature enhances user experience by providing flexibility and continuity in strategic planning efforts. The ability to save and retrieve scenarios promotes iterative analysis, enabling users to compare historical and current simulations based on evolving market data and sentiments.
Acceptance Criteria: User saves a custom market scenario with specific parameters for future analysis.

Given a user has created a market scenario with defined variables, when the user selects the 'Save Scenario' option, then the scenario is successfully saved in the user's scenario library and can be retrieved later.

User retrieves a previously saved custom scenario for further analysis.

Given a user has saved market scenarios in their library, when the user selects a saved scenario from the library, then the scenario populates the Scenario Simulator with all original parameters and settings.

User deletes a specific saved market scenario from their library.

Given a user has saved market scenarios in their library, when the user selects the 'Delete' option for a specific scenario, then the scenario is removed from the library and the user receives a confirmation message.

User loads a saved scenario and modifies parameters for a new simulation.

Given a user has retrieved a saved market scenario, when the user modifies any of the scenario parameters and selects 'Save As', then a new scenario is created based on the modifications and saved in the scenario library.

User attempts to save a scenario without filling mandatory fields.

Given a user has created a market scenario but has left mandatory fields empty, when the user selects 'Save Scenario', then the system displays an error message indicating which fields need to be completed before saving.

User views a list of all saved scenarios in their scenario library.

Given a user has saved multiple market scenarios, when the user accesses the 'Scenario Library', then a list displaying all saved scenarios with their respective titles and creation dates is presented.

User checks for the existence of a scenario with a specific title before saving.

Given a user attempts to save a new scenario, when the user enters a title that already exists in the scenario library, then the system alerts the user about the duplicate title and suggests an alternative.

Integrated Alerts for Sentiment Changes

User Story: As a data scientist, I want to receive alerts when there are significant sentiment shifts during my simulations so that I can adjust my strategies as needed.
Description: The Integrated Alerts for Sentiment Changes requirement incorporates real-time notifications to inform users when significant shifts in sentiment data occur during simulations. This functionality allows users to be proactive and responsive to changes in market conditions, ensuring that strategies can be promptly adapted. By integrating alerts, users can monitor sentiment trends actively, allowing for timely adjustments to their simulated scenarios based on actual market feedback. This improves strategic agility and enhances decision-making in fast-paced environments.
Acceptance Criteria: Notification of Sentiment Changes During Simulation Execution

Given that a user is running a market simulation, when a significant sentiment change occurs (defined as a 15% increase or decrease from the previous measurement), then the user should receive a real-time alert via the dashboard and email notification.

Customizable Alert Thresholds for Sentiment Shifts

Given that a user is setting up a simulation, when the user specifies custom thresholds for receiving alerts (e.g., 10%, 20%), then the system should honor these thresholds and trigger alerts accordingly when sentiment changes exceed the set levels.

User-Friendly Alert Management Interface

Given that a user wants to manage their alert preferences, when the user accesses the alert management section, then they should be able to view, edit, or disable all alert types related to sentiment changes with a clear and intuitive user interface.

Historical Alert Log Maintenance

Given that a user wishes to review past alerts, when the user accesses the historical alerts log, then the system should display a comprehensive list of previous alerts, including timestamps, sentiment data, and triggered thresholds, for the last 30 days.

Comprehensive User Documentation for Alert Functionality

Given that a user is utilizing the Integrated Alerts feature, when they access the user documentation, then the documentation should clearly outline how to set up alerts, manage preferences, and interpret the alerts received in the system.

Real-Time Feedback Loop for Alert Effectiveness

Given that a user receives a sentiment change alert, when they assess the accuracy of the alert within the context of the simulation, then the user should be able to provide feedback on whether the alert was timely and relevant, which will be used for improving the alert mechanism.

Integration with Existing Notification Systems

Given that a user utilizes other integrated tools, when a sentiment change alert is triggered, then the alert should be successfully forwarded to any connected third-party applications (e.g., Slack, Teams) as per user settings.

Comparative Benchmarking Tool

User Story: As a business strategist, I want to compare my simulation results with industry benchmarks so that I can evaluate my performance and identify areas for improvement.
Description: The Comparative Benchmarking Tool requirement equips users with the capability to compare their simulated scenarios against industry benchmarks and competitors' performance. By providing contextual data, users can analyze how their strategies measure up against others, helping identify gaps and areas for improvement. This feature enhances the depth of analysis within the Scenario Simulator, allowing users to set realistic goals and expectations based on external performance metrics. It supports strategic planning by enabling informed decisions founded on comparative analysis.
Acceptance Criteria: User navigates to the Scenario Simulator after completing a market analysis and wants to use the Comparative Benchmarking Tool to assess their current strategy against competitors' performance.

Given the user is on the Scenario Simulator page, when they select the Comparative Benchmarking Tool, then they should see a dashboard displaying their current scenario alongside relevant industry benchmarks and competitor data.

A user creates a simulated scenario and wants to compare it with historical benchmarks available within the Comparative Benchmarking Tool.

Given the user has created a simulation and accessed the Comparative Benchmarking Tool, when they click on the 'Compare with Historical Benchmarks' button, then the system should display a side-by-side comparison of the simulation and historical benchmark data.

The user needs to adjust the parameters of their scenario to see how changes affect benchmarking results in real-time.

Given the user is in the Comparative Benchmarking Tool, when they modify variables such as sentiment trends or market conditions, then the benchmarking results should update dynamically to reflect the new parameters.

Users want to save their comparative analysis results to use in future strategy meetings.

Given the user has successfully generated a comparative analysis report, when they click 'Save Report', then the report should be saved in their user profile with a timestamp and accessible for future retrieval.

An analyst wants to receive notifications about significant shifts in competitor performance that might impact their strategies.

Given the user has set up alerts in the Comparative Benchmarking Tool, when there is a significant shift in the competitor performance data, then the system should send a notification to the user via email or in-app alert.

A team member wants to share comparative benchmarking results with other team members.

Given the user is viewing comparative benchmarking results, when they click on the 'Share Results' button, then they should be able to enter email addresses of team members and send the results directly from the application.

Historical Insight Comparisons

Historical Insight Comparisons enable users to view and analyze past sentiment trends side-by-side with predictive insights. This feature helps users understand the context of emerging trends and the potential consequences of their strategic choices. By highlighting the connections between historical data and future predictions, marketers can make informed decisions that are grounded in a deeper understanding of consumer behavior.

Requirements

Side-by-Side Trend Analysis

User Story: As a marketer, I want to compare historical sentiment trends with predictive insights side-by-side so that I can make more informed strategic decisions based on past behaviors and future projections.
Description: The 'Side-by-Side Trend Analysis' requirement allows users to visually compare historical sentiment data with predictive insights on a dual-panel dashboard. This functionality enhances users' ability to identify correlations between past trends and future predictions. By providing a clear visualization of data, marketers can gain contextual understanding, leading to more strategic decision-making. The integration with existing dashboards ensures seamless workflow, allowing users to toggle between various timeframes and data parameters effectively. The expected outcome is improved analytical capabilities and more data-driven marketing strategies.
Acceptance Criteria: User compares historical sentiment data from the past six months with predictive insights for the next quarter.

Given the historical sentiment data and predictive insights are loaded, when the user selects a specific timeframe, then the dual-panel dashboard displays both datasets side-by-side without errors.

User toggles between different timeframes to analyze sentiment trends over varying periods.

Given the user is on the dual-panel dashboard, when the user selects different predefined timeframes (e.g., last month, last six months, last year), then the data in both panels updates correctly to reflect the selected timeframes.

User identifies a correlation between past consumer sentiment and future predictions through visual indicators.

Given the historical and predictive data are displayed, when the user observes the visual indicators (such as color coding or trend lines), then the user should be able to clearly identify correlations based on those indicators without additional explanations.

User generates a report summarizing the insights derived from the side-by-side analysis for stakeholders.

Given the user has completed the side-by-side analysis, when the user initiates the report generation, then the report should include key findings, visualizations, and be downloadable in a suitable format (e.g., PDF, Excel).

Multiple users access and analyze the trend analysis feature simultaneously without performance issues.

Given multiple users are logged into SentiScan and using the side-by-side trend analysis, when they perform analysis simultaneously, then the system should maintain responsiveness and performance across all user sessions.

The user can customize the parameters of the displayed data for personalized insights.

Given the dual-panel dashboard is visible, when the user selects different data parameters (such as demographics, location, or sentiment categories), then the dashboard updates to reflect the selections without losing historical context.

Dynamic Filtering Options

User Story: As a market analyst, I want to filter sentiment data dynamically to focus on relevant metrics so that I can uncover specific trends that align with my marketing objectives.
Description: The 'Dynamic Filtering Options' requirement enables users to filter historical and predictive sentiment data by various parameters such as date range, sentiment type, and demographic factors. This feature enhances user experience by allowing personalized analysis tailored to specific marketing goals. The ability to dynamically adjust filters will facilitate a deeper exploration of data, helping marketers identify niche trends and align strategies accordingly. The goal is to provide a flexible and user-friendly interface that encourages in-depth analysis of sentiment data.
Acceptance Criteria: User needs to filter sentiment data from the last six months to analyze changing consumer attitudes towards a particular brand.

Given the user selects the date range filter to 'Last 6 Months', When the user applies the filter, Then the system should display sentiment data specifically from this time frame only.

A marketing analyst wants to compare positive and negative sentiment trends for a specific product across different demographics.

Given the user selects 'Product A' and filters by 'Sentiment Type' to show both 'Positive' and 'Negative' trends, When the user applies the demographic filter for 'Age Group 18-24', Then the system should present a side-by-side comparison of sentiment trends within the specified demographics.

The user aims to view sentiment trends across different regional markets to inform targeted marketing strategies.

Given the user chooses 'Regional Markets' and applies a filter for 'Sentiment Type' as 'Neutral', When the user selects regions 'North America' and 'Europe', Then the data displayed should only include neutral sentiment from these regions within the selected date range.

A user needs to quickly adjust the filters for a presentation to stakeholders to show the impact of a recent marketing campaign on sentiment.

Given the user has applied initial filters for 'Last 3 Months' and 'Positive Sentiment', When the user alters the date range to 'Last 1 Month', Then the system should refresh to show updated positive sentiment data for the most recent month only.

An analyst wants to gather insights on historical sentiment to predict future marketing needs based on earlier trends.

Given the user selects a historical data filter for 'Year 2023' and then applies 'Predictive Insights', When the filters are applied, Then the system should display a comparison view outlining historical data trends alongside the predictive sentiment analysis for the year.

Automated Insight Alerts

User Story: As a marketing strategist, I want to receive automated alerts about significant changes in sentiment so that I can swiftly adapt my strategies to reflect current consumer attitudes.
Description: The 'Automated Insight Alerts' requirement involves the creation of alert mechanisms that notify users of significant shifts in sentiment data compared to historical trends. This proactive feature is critical for marketers who need to react quickly to changing consumer attitudes and emerging trends. By leveraging machine learning algorithms to detect anomalies in data, users will receive timely alerts, ensuring they can adjust their strategies in response to real-time insights. The expected outcome is enhanced responsiveness and agility in marketing campaigns.
Acceptance Criteria: User receives an alert when there is a significant drop in sentiment score for a brand they are monitoring, compared to the average sentiment score of the past month.

Given the user has set up an alert for sentiment drops, when a significant drop occurs (defined as a decrease of 20% or more from the average sentiment score over the past month), then the user should receive an immediate notification via their preferred communication channel (email or in-app notification).

User wants to compare current sentiment shifts with historical data to validate the relevance of the alerts they've received.

Given the user accesses the Historical Insight Comparisons dashboard, when they select a specific alert from the recent alerts list, then the dashboard should display a side-by-side comparison of the current sentiment trend with the historical trend for the past three months, highlighting key changes using visual indicators.

User sets up multiple automated alerts for different brands and wants to ensure they receive alerts without delays.

Given the user has configured alerts for multiple brands, when there is a significant sentiment shift for any of those brands, then the system should send out alerts for all affected brands within a maximum time frame of 5 minutes after the sentiment shift is detected.

User checks their alert history to evaluate the effectiveness of the automated insight alerts over the past month.

Given the user navigates to the alert history section, when they review alerts for the past 30 days, then the system should display a list of all alerts generated with timestamps, sentiment score changes, and related historical comparisons, allowing the user to see which alerts corresponded with actual trends.

User wants to customize their alert thresholds based on sentiment score changes specific to their marketing strategy.

Given the user accesses the alert configuration settings, when they set a custom threshold for sentiment score changes (for instance, a 15% drop), then the system should enable the alert only if the specified threshold is met or exceeded, ensuring user-defined parameters are honored.

User is analyzing how timely alerts have impacted their marketing strategies after receiving several insights over a quarter.

Given the user reviews the performance analytics dashboard, when they filter the results to show campaigns that responded to alerts over the last quarter, then the dashboard should present metrics on campaign performance (like engagement and conversion rates) that correlate with the timing of the alerts received, demonstrating actionable insights derived from alerts.

User is evaluating the accuracy of the automated insight alerts against actual market performance outcomes.

Given the user has access to sentiment data and market performance reports, when they compare the timing and content of the alerts with subsequent market actions or consumer feedback, then they should be able to assess a minimum of 80% accuracy in the alerts reflecting true sentiment shifts that affected marketing outcomes based on historical data.

Exportable Comparison Reports

User Story: As a team lead, I want to export comparison reports of sentiment data so that I can share key insights with my stakeholders and improve our strategic discussions.
Description: The 'Exportable Comparison Reports' requirement allows users to generate comprehensive reports that outline the comparisons between historical sentiment trends and predictive insights. This functionality will enable users to share insights with stakeholders or use them in presentations, facilitating collaboration and decision-making processes. Reports should be customizable, allowing users to select specific parameters and visual elements, ensuring the reports are relevant to their strategic needs. The outcome will streamline communication and enhance the reporting process for user teams.
Acceptance Criteria: User generates a comparison report for a specified time period, selecting both historical sentiment data and predictive insights.

Given the user has access to historical sentiment data and predictive insights, when the user selects the desired parameters and clicks 'Generate Report', then a report is created that accurately reflects the selected data and parameters, is formatted correctly for export, and displays next to each other the historical data and predictive insights.

User customizes the visual elements of the comparison report including charts and graphs before exporting.

Given the user is on the report customization page, when the user selects different visual elements for the comparison report, then the selected visual elements are applied correctly in the report preview, and all selected elements are included in the exported report.

User shares the generated comparison report with stakeholders via email.

Given the user has successfully generated a comparison report, when the user clicks the 'Share via Email' button and enters the email addresses, then the report is sent as an attachment to all specified email addresses with a notification confirming the sending of the report.

User views the report in different file formats (PDF, Excel, etc.) before exporting.

Given the user has generated a comparison report, when the user selects the desired file format from the format options, then the report is displayed in that format in the preview window without any loss of data or formatting.

User requests a detailed view of how the historical sentiment data was calculated and compared against predictive insights.

Given the user is viewing the generated report, when the user clicks on the 'Details' button, then a detailed explanation of how the historical data was calculated as well as the method of comparison to predictive insights is displayed clearly and accurately to the user.

User uploads custom parameters for analysis to enhance comparison accuracy for niche markets.

Given the user is on the parameter upload page, when the user uploads a compatible file with custom parameters, then the system successfully processes the uploaded parameters and integrates them into the report generation workflow without errors.

Interactive Data Visualization Tools

User Story: As a data analyst, I want to use interactive visualization tools to explore sentiment data more effectively so that I can identify patterns and trends intuitively and present them to my team.
Description: The 'Interactive Data Visualization Tools' requirement provides users with advanced visualization capabilities such as graphs, charts, and trend lines to enhance their analysis of historical and predictive sentiment data. This feature leverages user interactivity to allow zooming, panning, and detailed drill-downs on data points, which would provide richer insights and facilitate better understanding of market dynamics. By integrating these visualization tools, users can quickly interpret complex data sets and make better marketing decisions based on visual context.
Acceptance Criteria: User navigates to the Historical Insight Comparisons feature to analyze past sentiment trends alongside predictive insights to inform upcoming marketing strategies.

Given the user selects a specific time range for analysis, when they view the interactive data visualization tools, then the user must see clear and distinct graphs and charts representing both historical sentiment data and predictive insights.

Marketers aim to identify shifts in consumer sentiment as they interact with the data visualization tools to pivot their strategies based on historical data.

Given the user interacts with a data point on the trend line, when they drill down into that data point, then detailed information including date, sentiment score, and context is displayed accurately.

A user wants to compare multiple sentiment trends simultaneously to identify correlations between past and future consumer attitudes.

Given the user selects multiple past sentiment datasets to compare, when the interactive visualization loads, then all selected datasets must be displayed in a cohesive and comparative format, allowing for side-by-side analysis.

A marketing analyst uses the interactive data visualization tools during a strategy meeting to present sentiment analysis findings supported by visual aids.

Given the marketing analyst selects various interactive visual aids, when they present in a meeting, then all visual aids must be responsive and properly load within 2 seconds, ensuring a smooth presentation experience.

During a critical analysis session, a user needs to quickly adjust the zoom level on sentiment graphs to isolate specific data points.

Given the user zooms into a segment of the graph, when the zoom level is adjusted, then the graphs must retain clarity and allow the user to smoothly pan across the data without losing data integrity.

A marketer analyzes real-time sentiment changes while utilizing historical comparisons to gauge the impact of recent marketing campaigns.

Given the marketer accesses real-time sentiment data alongside historical insights, when they initiate an analysis session, then the resulting visualization must immediately reflect real-time changes with historical context referenced appropriately.

The team needs assurance that the interactive data visualizations are functioning properly before a major product launch.

Given the QA team tests the functionality of the interactive data visualization tools, when all test cases are executed, then 100% of them must pass without errors to ensure readiness for launch.

User Role Customization

User Story: As an admin, I want to customize user roles regarding access to sentiment data so that I can ensure data security and optimize user experience according to team responsibilities.
Description: The 'User Role Customization' requirement allows administrators to define different user roles and access levels related to historical insight comparisons. This is crucial for large teams, ensuring that sensitive data is only accessible to authorized personnel. By customizing roles, admins can also tailor the features users see based on their responsibilities, which enhances the overall security and usability of the product. The implementation of this requirement ensures compliance with data governance policies and improves user experience by reducing complexity.
Acceptance Criteria: User Role Creation and Management

Given an admin user logged into the SentiScan application, when they navigate to the User Role Management section, then they should be able to create, edit, and delete user roles with distinct permissions for accessing historical insight comparisons.

User Access Control Enforcement

Given a user assigned a specific role, when they attempt to access historical insight comparisons, then the system should enforce access restrictions based on the defined role permissions, either granting or denying access accordingly.

Role-Based Feature Visibility

Given an admin customized user role, when users with that role log into SentiScan, then they should only see the features pertinent to their responsibilities, excluding any features related to other roles.

Audit Trail of Role Changes

Given an admin makes changes to user roles, when they review the audit log, then the system should display a record of all changes made, including timestamps and user details for accountability.

Compliance with Data Governance Policies

Given the implementation of user role customization, when an audit is conducted, then the system should demonstrate compliance with established data governance policies by restricting access to sensitive historical insight data according to user roles.

User Role Testing

Given a defined user role, when a test user is assigned that role, then the system should allow testing of all defined permissions to ensure functionality works as intended and the user can access or see only the appropriate data and features.

Dynamic Role Modification

Given an admin user modifies a user role, when the role changes are saved, then the system should immediately reflect these changes across the platform without requiring a system restart or additional input from the admin.

Consumer Sentiment Heatmaps

Consumer Sentiment Heatmaps provide visual representations of sentiment data over geographical regions and demographics. This feature allows users to identify where and among whom sentiment shifts are occurring, enabling targeted marketing efforts. By leveraging geographical nuances, brands can craft localized strategies that resonate more deeply with specific audience segments, enhancing engagement and driving conversions.

Requirements

Interactive Heatmap Visualization

User Story: As a market analyst, I want to visualize consumer sentiment data on an interactive heatmap so that I can easily identify trends and areas of concern across different regions and demographics, enabling me to make targeted marketing recommendations.
Description: The Interactive Heatmap Visualization requirement involves creating an interactive and responsive heatmap interface that displays sentiment data across various geographical locations and demographics. It must allow users to zoom in/out, filter by demographic parameters, and toggle between different sentiment metrics (positive, negative, neutral). This feature will enable users to visually identify trends and shifts in consumer sentiment, facilitating targeted marketing strategies. Integration with the existing dashboard system is essential for seamless user experience, and it should utilize advanced data visualization libraries to enhance performance and aesthetics, ultimately driving deeper engagement and better decision-making for marketing strategies.
Acceptance Criteria: Heatmap User Interaction and Responsiveness

Given the user is viewing the interactive heatmap, when they zoom in/out, then the heatmap should refresh and display the appropriate level of detail for the selected geographical region with no significant delay.

Demographic Filtering of Sentiment Data

Given the user has selected specific demographic filters, when the user applies these filters, then the heatmap should update to only show sentiment data corresponding to the selected demographics accurately and immediately.

Sentiment Metric Toggle Functionality

Given the user is on the interactive heatmap, when they toggle between different sentiment metrics (positive, negative, neutral), then the heatmap should visually update to reflect the selected sentiment metric with correct data representation.

Integration with Existing Dashboard System

Given the interactive heatmap is integrated into the existing dashboard, when the user navigates to the heatmap section, then the heatmap should load seamlessly without affecting the performance of other dashboard features.

Data Visualization Performance and Aesthetics

Given the interactive heatmap is displayed, when the user interacts with various features (zooming, filtering, toggling), then the heatmap should maintain high performance and visual clarity without pixelation or lag.

User Engagement with Heatmap Insights

Given the user is analyzing the heatmap, when they identify a significant sentiment shift, then they should have the option to generate an insight report based on the visual data presented for targeted marketing strategies.

Sentiment Change Alerts

User Story: As a marketer, I want to receive alerts when there are significant changes in consumer sentiment so that I can respond promptly with marketing strategies that align with current consumer perceptions.
Description: The Sentiment Change Alerts feature is designed to notify users in real-time about significant changes in consumer sentiment captured through the heatmap. These alerts would be customizable based on specific thresholds defined by users regarding sentiment scores or notable spikes/drops. The functionality should include push notifications, email, and dashboard alerts to ensure that users remain informed about key changes as they occur. This feature is critical for maintaining agile marketing strategies and allows organizations to respond quickly to changing consumer perceptions, ultimately leading to better customer engagement and retention.
Acceptance Criteria: User receives a real-time alert when sentiment scores for a specific demographic fall below a predefined threshold following a marketing campaign.

Given the user has set a sentiment score threshold for alerts, when the sentiment score falls below this threshold, then the user should receive a push notification and an email alert.

User customizes the types of sentiment changes they want to be alerted about within the dashboard settings.

Given the user accesses the notification settings in the dashboard, when they select specific sentiment metrics such as spikes and drops, then the system should save these preferences successfully for future alerts.

User checks the dashboard and is presented with a comprehensive summary of recent sentiment changes that triggered alerts.

Given there are significant sentiment changes, when the user navigates to the alert section of the dashboard, then they should see a clear list of alerts including metrics and timestamps for those changes.

User receives alerts via email when a significant drop in consumer sentiment is detected for a particular geographical region.

Given the user has subscribed to email alerts for regional sentiment changes, when a significant drop is detected, then an email notification should be sent to the user’s registered email with details of the change.

User wants to disable alerts for low sentiment scores temporarily during a specific marketing initiative.

Given the user is in the alert settings section, when they toggle off alerts for low sentiment scores, then the system should not send notifications until the user re-enables it.

User analyses the historical data of alerts to understand sentiment trends over time.

Given the user accesses the historical alerts section, when they view the timeline of sentiment alerts, then they should see a visual representation of trends correlating with their marketing activities.

Demographic Segmentation Filters

User Story: As a marketing manager, I want to filter sentiment data by demographics so that I can better understand the preferences and attitudes of different audience segments, enabling us to create more relevant marketing campaigns.
Description: The Demographic Segmentation Filters requirement entails implementing filtering options within the heatmap interface that allows users to segment sentiment data by various demographic parameters such as age, gender, location, income level, and more. This functionality is crucial for enabling personalized marketing efforts and helps organizations tailor their strategies to resonate effectively with specific audience segments. The filters should be easy to apply and remove, ensuring an intuitive user experience, and must integrate seamlessly with the existing data processing framework.
Acceptance Criteria: User applies filters to analyze sentiment data among different age groups.

Given the user is on the Heatmap interface, when they select the age demographic filter, then the sentiment data should adjust to show only the results for the selected age groups, and a visual representation of this data must be updated on the heatmap without lag.

User changes location filter to focus on a specific city.

Given the user is on the Heatmap interface, when they apply a location filter for a specific city, then the heatmap should display sentiment data relevant specifically to that location, including any changes in sentiment levels compared to the overall data.

User removes demographic filters to return to the full dataset.

Given the user has applied multiple demographic filters, when they choose to remove all filters, then the system should reset to display the complete sentiment data set without any demographic segmentation applied.

User analyzes sentiment shifts over different income levels.

Given the user is analyzing sentiment data, when they apply the income level filter, then the heatmap should clearly illustrate sentiment data segmented by the specified income brackets, allowing the user to differentiate trends across income demographics.

User experiences error when applying multiple filters simultaneously.

Given the user is applying multiple demographic filters, when they encounter an error, then the system should notify the user of the invalid filter combination and provide guidance on how to resolve the issue without disrupting the user experience.

User seeks to save filter settings for future analysis.

Given the user has configured multiple demographic filters, when they choose to save these settings, then the system must successfully save the filter configuration and allow the user to load it in future sessions easily.

Comparative Analysis Tool

User Story: As a product strategist, I want to compare sentiment heatmaps over time so that I can assess the effectiveness of our marketing campaigns and make informed strategic decisions based on consumer behavior trends.
Description: The Comparative Analysis Tool requirement involves providing users the capability to compare sentiment heatmaps over different time periods, geographic regions, or against benchmark competitors. This feature must facilitate side-by-side comparisons that visually represent sentiment shifts, enabling users to identify trends and evaluate their marketing effectiveness. Integration with existing analytics features will be necessary, and it should provide actionable insights through detailed reports that highlight significant changes and help drive strategic decisions.
Acceptance Criteria: User wants to compare sentiment heatmaps for a specific product across different geographic regions over the last six months during a promotional campaign.

Given a user selects the Comparative Analysis Tool, when they input the two geographic regions and set the time frame to the last six months, then the system should display side-by-side sentiment heatmaps for both regions.

A marketing analyst needs to compare the sentiment heatmaps of a product before and after a major ad campaign to evaluate its impact on public perception.

Given an analyst uses the Comparative Analysis Tool, when they choose to compare the sentiment from two distinct timeframes (before and after the ad campaign), then the tool must show a visual representation of the sentiment changes between these periods.

A user intends to compare the sentiment of their brand against a competitor using the Comparative Analysis Tool to gauge market position.

Given a user selects a competitor for comparison, when they input relevant data for their brand and the competitor, then the system should produce sentiment heatmaps that highlight differences and shifts in public sentiment between the two brands.

A marketing team wants to analyze demographic shifts in sentiment related to their product across various age groups over the past year.

Given a user accesses the Comparative Analysis Tool, when they filter demographic data to include specific age groups for the last year, then the tool must present heatmaps that visualize sentiment trends across these demographics.

A user is conducting a quarterly review and wants to see how sentiment towards their brand has changed over the past four quarters on a national level.

Given that a user accesses the Comparative Analysis Tool, when they set the time parameters to the past four quarters and select a national level of analysis, then the system should produce a comprehensive report alongside comparative heatmaps detailing sentiment shifts across the year.

A product manager is tasked with assessing the effectiveness of a recent product launch in comparison to a similar launch by a competitor.

Given a user selects two product launches for comparison, when they utilize the Comparative Analysis Tool, then the system should provide sentiment heatmaps detailing performance insights and shifts for both products within the same timeframe.

Exportable Reports

User Story: As a business analyst, I want to generate and export detailed reports on sentiment analysis from the heatmap data so that I can share insights with stakeholders for informed decision-making.
Description: The Exportable Reports feature will allow users to generate and download customizable reports in various formats (PDF, CSV, Excel) containing the sentiment analysis data represented in the heatmap. This requirement includes options to select specific timeframes, demographics, and sentiment metrics to include in the reports. The ability to share data insights with stakeholders in a professional format is essential for fostering collaboration and supporting data-driven decisions within organizations. This feature will integrate with the existing reporting framework to ensure accuracy and facilitate ease of access.
Acceptance Criteria: User generates an exportable report containing sentiment data for a selected timeframe of the past month, including demographic insights and sentiment metrics.

Given the user has selected a timeframe, demographics, and sentiment metrics, When the user clicks on the 'Generate Report' button, Then a downloadable report in the selected format (PDF, CSV, Excel) should be created and available for download.

Marketing team needs to share sentiment insights from a specific geographical region with stakeholders using an exportable report.

Given the user selects a specific geographical region, When the user generates the report, Then the report should contain only data relevant to that region and be formatted correctly in the chosen file type.

User wants to generate a customized report that includes charts and visualizations of the sentiment data over the selected timeframe.

Given the user selects the option to include visualizations, When the report is generated, Then the exported file should include all selected charts and visualizations based on the sentiment analysis data.

A data analyst tests the accuracy of the generated report against the raw sentiment data to ensure no discrepancies.

Given the generated report is completed, When the analyst compares the report data to the raw sentiment data, Then the values in the report should accurately reflect the underlying data without any discrepancies.

User attempts to generate an exportable report without selecting any timeframes or demographic filters.

Given the user does not select a timeframe or demographics, When the user clicks on 'Generate Report', Then the system should prompt the user to select at least one timeframe and one demographic before generating the report.

User wants to generate a report that includes the summary of sentiment metrics such as average sentiment score and engagement rate.

Given the user selects the option to include sentiment metrics, When the report is generated, Then the exported file should contain a summary section with the average sentiment score and engagement rate for the selected data.

User wishes to save their report settings for future use to avoid repeated selections.

Given the user configures report settings (timeframe, demographics, sentiment metrics), When the user selects the option to save these settings, Then the system should save the configurations for future report generation.

Actionable Insight Recommendations

Actionable Insight Recommendations leverage AI to generate tailored suggestions based on predictive analytics. This feature highlights key actions users can take to capitalize on anticipated shifts in sentiment and maximize their strategic impact. By acting on these insights, marketers can implement more effective campaigns and positions, aligning their execution with the needs and preferences of their target audience.

Requirements

Real-time Sentiment Analysis

User Story: As a marketer, I want to receive real-time sentiment analysis so that I can quickly adjust my campaigns based on the latest consumer attitudes and sentiments.
Description: This requirement encompasses the ability for SentiScan to provide real-time analysis of sentiment from various social media and online platforms. It leverages advanced AI and natural language processing algorithms to process and analyze large volumes of unstructured data, identifying and categorizing sentiment trends dynamically. The benefit of this capability lies in its ability to offer marketers immediate insights into consumer attitudes, enabling quick response actions to changing sentiments. As a result, organizations can enhance their engagement strategies in a timely manner and maintain a competitive edge in the market.
Acceptance Criteria: Real-time sentiment analysis during a major product launch on social media platforms.

Given that users are monitoring social media during a product launch, When a significant sentiment shift occurs, Then the system should notify users within 5 minutes with a comprehensive report of the sentiment levels and trends.

Analyzing consumer responses to an advertisement campaign across different platforms in real-time.

Given that users are running an advertisement campaign, When they view the sentiment analysis dashboard, Then the dashboard should display sentiment trends updated every 15 minutes and highlight key metrics relevant to the campaign.

Tracking and reporting sentiment changes during a consumer crisis on social media.

Given that a consumer crisis is affecting the brand's reputation, When the analysis identifies a downward sentiment trend, Then the system must alert the marketing team immediately with actionable insight recommendations to address the sentiment decline.

Comparative analysis of sentiment trends between competitors during a market event.

Given that users want to analyze sentiment trends related to competitors, When they select multiple brands to compare, Then the system should provide a side-by-side sentiment analysis report updated in real-time.

Customization of sentiment analysis parameters by users to fit specific marketing objectives.

Given that users require tailored sentiment analysis parameters, When they set customized filters for sentiment analysis, Then the system should save these parameters and apply them consistently across future analyses without user intervention.

Integration of sentiment analysis data into existing marketing campaign tools.

Given that users are working within their existing marketing campaign tools, When they request sentiment analysis data, Then the system should seamlessly export the data to their chosen platform in real-time, maintaining data integrity and format.

Predictive Analytics Integration

User Story: As a product manager, I want to use predictive analytics so that I can forecast future sentiments and adapt my marketing strategies accordingly to maximize effectiveness.
Description: This requirement involves integrating predictive analytics features that anticipate future consumer sentiments based on historical data trends. By utilizing machine learning techniques, SentiScan can identify potential changes in audience attitudes and recommend actionable insights tailored to those predictions. This feature not only helps users to proactively strategize their marketing efforts but also minimizes risks by highlighting potential market shifts before they occur. The result is enhanced strategic planning and more targeted marketing efforts that align closely with anticipated consumer behaviors.
Acceptance Criteria: Integration of predictive analytics in SentiScan for real-time consumer sentiment forecasting based on historical data.

Given that a user inputs historical sentiment data, when predictive analytics are applied, then the system should generate forecasts for future consumer sentiments with at least 85% accuracy.

Generating actionable insights based on predicted sentiment shifts identified by the predictive analytics module.

Given that a sentiment shift is predicted, when the user requests actionable insights, then the system should provide at least three tailored recommendations relevant to the predicted change.

User interaction with the dashboard to visualize predictive sentiment data and actionable insights.

Given that the user accesses the dashboard, when predictive analytics and actionable insights are displayed, then the dashboard should load within 2 seconds and present data in an intuitive format for user engagement.

Monitoring alerts for significant sentiment shifts that exceed predefined thresholds.

Given that a significant sentiment shift occurs, when the threshold of change is exceeded, then the system should trigger an alert within 1 minute to notify users of the shift.

User feedback on the relevance and effectiveness of actionable insights provided by the system.

Given that users implement the actionable insights, when they provide feedback, then at least 70% of users should indicate that the insights positively impacted their strategic decisions.

Testing the predictive analytics feature over a time span to collect historical data accuracy.

Given a 3-month period of sentiment data usage, when historical data is compared with predicted analytics, then the accuracy of predictions should remain above 80% over the test period.

Assessing the integration success of predictive analytics features with existing SentiScan functionalities.

Given that predictive analytics are integrated, when users utilize both existing and new features, then there should be no more than a 5% increase in system response time during operations.

User-friendly Dashboard

User Story: As a user, I want an easy-to-navigate dashboard so that I can quickly understand sentiment trends and make informed marketing decisions without complications.
Description: The User-friendly Dashboard requirement focuses on creating an intuitive and visual representation of sentiment data and actionable insights. This dashboard should provide easy navigation and clear visualizations, such as graphs, charts, and alerts that bring important data to the forefront for users. Incorporating user experience design principles ensures that users from various backgrounds, including those without technical expertise, will benefit from the insights provided without confusion. Improved accessibility to information empowers users to make quick data-driven decisions to enhance their marketing campaigns.
Acceptance Criteria: User Dashboard Navigation for Sentiment Analysis Insights

Given a user is logged into the SentiScan dashboard, when they navigate to the sentiment analysis section, then they should see clearly labeled sections for different sentiment metrics, enabling them to gather insights without confusion.

Visual Representation of Data Trends

Given the user selects a specific date range on the dashboard, when they generate the sentiment report, then the system should display a line graph showing trends in sentiment over that period with distinct color coding for positive, neutral, and negative sentiments.

Alert System for Sentiment Shifts

Given that the user has set up alerts for significant sentiment shifts, when a notable change in sentiment occurs (defined as a 20% shift in positive/negative sentiment), then the user should receive an email and in-dashboard notification regarding this shift.

User Engagement with Actionable Insights

Given a user is viewing the dashboard, when they click on an actionable insight recommendation, then the system should provide a detailed description and suggest at least three specific actions to take based on the sentiment analysis.

User Experience for Non-Technical Users

Given a non-technical user is accessing the dashboard, when they navigate through different features, then they should be able to find and understand insights without requiring external guidance or assistance.

Accessible Design Features for Dashboard

Given a user with visual impairments is accessing the dashboard, when they use screen reader technology, then all chart legends, data labels, and alerts should be read aloud accurately and clearly, ensuring accessible insights.

Actionable Insights Alerts

User Story: As a marketer, I want to receive alerts for actionable insights so that I can respond promptly to changes in consumer sentiment and optimize my campaigns accordingly.
Description: This requirement is for implementing an alert system that notifies users of crucial actionable insights as they occur. Using AI algorithms, SentiScan can recognize significant sentiment shifts and deliver timely alerts to users with suggested actions they can take. This capability ensures that marketers and analysts stay informed about important trends in real-time and are prepared to pivot their strategies swiftly based on the sentiments identified. The system also minimizes the potential for missed opportunities, ensuring users can respond quickly to changes in the market.
Acceptance Criteria: Users receive real-time alerts for actionable insights when significant sentiment shifts are detected during a major product launch campaign on social media.

Given a significant sentiment shift occurs, when the AI algorithm analyzes the sentiment data, then a notification alert with actionable insights is sent to the user within 5 minutes of detection.

Users can customize their alert preferences to receive notifications only for specific keywords related to their brand or industry.

Given a user sets their alert preferences in the dashboard, when the user selects specific keywords, then only sentiment shifts related to those keywords trigger notifications.

Users receive alerts for actionable insights via multiple channels (email, in-app notifications, SMS) based on their specified preferences.

Given a user has selected their preferred communication channels, when a significant sentiment shift is detected, then the alert is sent to all selected channels within 5 minutes.

Users can acknowledge and dismiss actionable insights alerts to help manage their alert traffic.

Given an actionable insights alert is received, when the user acknowledges or dismisses the alert, then the alert should be marked as either acknowledged or dismissed in the system.

Users are able to review past alerts for actionable insights and track their outcomes for future reference.

Given past alerts exist in the system, when a user navigates to the past alerts section, then they should be able to view the details and outcomes of all past actionable insights alerts.

The alert system does not send duplicate alerts for the same sentiment shift to avoid overwhelming users.

Given a sentiment shift has been reported, when the alert is triggered, then no duplicate alerts for the same sentiment shift should be sent within a 24-hour period.

Users can test the alert system functionality with a simulated sentiment shift to ensure the system works as intended before actual deployment.

Given the testing mode is activated, when a simulated sentiment shift is introduced, then the alert system should generate a notification alert that can be reviewed by the user.

Competitive Benchmarking Features

User Story: As a competitive analyst, I want to benchmark my brand's sentiment against competitors so that I can discover areas for improvement and capitalize on competitive advantages.
Description: This requirement entails the development of competitive benchmarking features that allow users to compare their sentiment analysis results against those of key competitors in the market. By assessing where their brand stands in relation to competitors, marketers can gain deeper insights into market dynamics and adjust their strategies effectively. This benchmarking capability will highlight strengths and weaknesses in real-time, enabling organizations to identify competitive opportunities for growth and engagement.
Acceptance Criteria: User accesses the competitive benchmarking feature to compare their sentiment analysis results with a selected competitor in real-time.

Given a user has access to the competitive benchmarking feature, When they select a competitor from the comparison list, Then the system displays a side-by-side sentiment analysis chart for both brands.

Marketers receive alerts when there are significant shifts in sentiment compared to competitors.

Given that sentiment analysis is running continuously, When there is a significant shift (greater than 10% change) in sentiment score for the user’s brand or a competitor, Then the system generates an alert for the user detailing the changes.

Users can filter competitive benchmarking results by time frame to analyze trends within specific periods.

Given the competitive benchmarking feature is active, When a user selects a specific time frame (e.g., last week, last month), Then the system updates the sentiment analysis results to reflect data only from that selected period.

Users can view detailed insights into strengths and weaknesses based on competitive benchmarking results.

Given the user has completed a benchmarking analysis, When they navigate to the insights page, Then the system provides a report highlighting at least three strengths and three weaknesses compared to the selected competitor.

Marketers can export benchmarking data for presentation and reporting purposes.

Given a user is viewing the competitive benchmarking results, When they choose to export the data, Then the system allows them to download the benchmarking report in PDF and CSV formats without data loss.

Users can access historical sentiment data for competitors to identify trends over time.

Given the competitive benchmarking feature, When a user selects the historical data view, Then the system displays sentiment trends for the selected competitor over a customizable time scale (e.g., last 6 months, last year).

The system provides user-friendly definitions and descriptions for each benchmarking metric used in the analysis.

Given a user accesses the competitive benchmarking feature, When they hover over or click on a metric, Then the system shows a tooltip or modal explaining the metric’s definition and significance.

Competitive Trend Benchmarking

Competitive Trend Benchmarking enables users to compare their predictive sentiment trends against competitors within the market. This feature provides valuable insights into how brands stack up against each other regarding consumer favorability, helping users identify areas for improvement or differentiation. By understanding competitive sentiment landscapes, organizations can refine their strategies for greater effectiveness and positioning.

Requirements

Real-time Competitive Sentiment Analysis

User Story: As a marketing analyst, I want to receive real-time updates on competitors' sentiments so that I can promptly adjust our marketing strategies and remain competitive in the market.
Description: This requirement involves developing a module that continuously monitors and analyzes competitor sentiment across various social media and online platforms. Using advanced AI algorithms, it will provide real-time insights into how competitors are perceived by consumers. The benefit of this module is the timely information that enables users to adjust marketing strategies in response to competitor actions. It integrates seamlessly with the existing sentiment analysis framework within SentiScan, ensuring a cohesive data analysis experience and fostering proactive decision-making.
Acceptance Criteria: User accesses the Competitive Trend Benchmarking feature to view real-time sentiment metrics for their brand and competitors during an ongoing marketing campaign.

Given the user is logged into SentiScan, when they access the Competitive Trend Benchmarking feature, then they should see real-time sentiment scores and trends for both their brand and selected competitors.

A marketing analyst sets up alerts for changes in competitor sentiment to stay informed during a product launch.

Given that the user has selected competitors for monitoring, when there is a significant change in competitor sentiment, then the user should receive a notification alerting them to the change.

The user compares their brand's sentiment trends against those of a chosen competitor over a specified timeframe.

Given the user has specified a date range and selected a competitor, when they generate a comparison report, then the report should clearly display side-by-side sentiment trends for their brand and the competitor for that period.

The user wants to export the real-time sentiment analysis data for a presentation to stakeholders.

Given the user has accessed the Competitive Trend Benchmarking data, when they select the export option, then they should be able to download the sentiment analysis data in multiple formats (CSV, PDF, etc.).

During a weekly team meeting, the user presents insights gained from the Competitive Trend Benchmarking module.

Given the user has collected sentiment analysis data over the past week, when they present findings in the meeting, then the insights should be accurately derived from the system's generated reports without discrepancies.

Historical Trend Comparison

User Story: As a brand strategist, I want to compare our sentiment trends with historical data from competitors so that I can identify what strategies have worked effectively over time and capitalize on those insights.
Description: This requirement focuses on the development of a feature that allows users to compare historical sentiment trends of their brand against competitors. This would involve a graphical representation of sentiment data over time, highlighting shifts and trends. The value of this feature lies in its ability to uncover long-term patterns and shifts in consumer perceptions, enabling users to identify significant events or marketing campaigns that influenced sentiment. Integration with existing dashboard functionality will allow for custom and dynamic reporting options.
Acceptance Criteria: As a market analyst, I want to access a graphical representation of historical sentiment trends for my brand and competitors, so I can easily visualize shifts and patterns over time.

Given that I have selected my brand and a competitor's brand, When I view the historical sentiment trends, Then I should see a line graph displaying sentiment scores over time for both brands, with distinct colors for differentiation.

As a marketing manager, I need to customize the time frame of the historical sentiment comparison, so I can analyze specific periods of interest, such as before and after a marketing campaign.

Given that I have selected the historical trend comparison feature, When I choose a custom date range, Then the sentiment trend graph should update to reflect only the data within that specified range.

As a user, I want to filter the sentiment data by specific events or campaigns, so I can understand how these influenced consumer perceptions compared to competitors.

Given that I am viewing the historical sentiment trend graph, When I apply filters for specific events or campaigns, Then the graph should reflect any sentiment shifts associated with those events, differentiating between brands clearly.

As a product owner, I want to ensure that the historical trend comparison feature integrates smoothly with the existing dashboard functionality, so users can easily navigate and utilize the insights.

Given that I am logged into the SentiScan platform, When I access the historical trend comparison feature from the dashboard, Then it should load without errors and maintain the same user interface design standards for consistency.

As a data analyst, I need to download the historical sentiment trend data in a CSV format for further analysis, so I can conduct deeper data manipulation if required.

Given that I have generated a historical sentiment trend report, When I select the 'Download CSV' option, Then a CSV file should be generated and downloaded to my device containing all relevant sentiment data points.

As a user, I want to receive alerts for significant sentiment shifts within the historical comparison so that I can react promptly to emerging trends.

Given that I have configured alert settings, When there is a notable sentiment shift detected in either my brand or competitor's brand, Then I should receive a notification via email or in-app alert detailing the change and possible implications.

Automated Reporting Alerts

User Story: As a user of SentiScan, I want to set up automated alerts for sentiment changes in competitors so that I can react swiftly to market movements and adjust strategies as necessary.
Description: This requirement entails creating an automated alert system that notifies users of significant changes in competitive sentiment trends. The alerts will be customizable, allowing users to set thresholds for what constitutes a significant change—be it a percentage increase or decrease in sentiment. This feature will enhance user engagement and responsiveness by ensuring timely communication of critical market shifts. It will leverage the existing alert framework and be easy to incorporate into user dashboards.
Acceptance Criteria: User sets up a customizable alert for sentiment increases exceeding 10% for a competitor's brand in their dashboard.

Given a user has access to the Competitive Trend Benchmarking feature, when they set a threshold of 10% increase for alerts, then they should receive a notification when the competitor's sentiment exceeds this threshold.

User customizes an alert for sentiment decreases below 5% for one of their monitored brands.

Given a user accesses the alert customization screen, when they enter a threshold of 5% decrease for alerts, then the system should save this configuration and notify the user when the brand's sentiment drops below this threshold.

System sends automated alerts when multiple competitors exceed the set sentiment threshold within a specified time frame.

Given users have set their sentiment alert thresholds, when the sentiment for two or more competitors exceeds the set thresholds within one week, then all relevant users should receive timely notifications about the significant trend changes.

User tests the notification system to ensure alerts are received in real-time when a competitor's sentiment changes dramatically.

Given the user has a competitor set up with a 15% threshold alert, when the competitor's sentiment changes by 20% in a short period, then the user should receive an alert within 5 minutes of the change occurring.

User reviews historical alert data to assess past sentiment alert effectiveness and responsiveness.

Given the user wants to analyze past alerts, when they access the historical alert report, then they should be able to view alerts triggered over the last month along with sentiment changes and user actions taken in response to those alerts.

User enables or disables alerts for specific competitors easily from their dashboard.

Given the user is on their dashboard, when they toggle the alert setting for a specific competitor, then the system should immediately enable or disable notifications for that competitor without requiring page refresh.

Competitor Sentiment Comparison Tool

User Story: As a product manager, I want to compare our brand sentiment against selected competitors so that I can better understand our position in the market and make more strategic decisions.
Description: This requirement involves implementing a tool that allows users to perform side-by-side comparisons of their brand's sentiment with selected competitors. Users will be able to select multiple competitors and visualize their sentiments through graphs and charts. This feature will help identify market positioning and consumer preferences, enabling informed strategic decisions. It will integrate with the competitive benchmarking dashboard to provide a comprehensive view of market sentiment landscape.
Acceptance Criteria: User selects multiple competitors to compare their sentiment over a specified period using the Competitive Trend Benchmarking feature in SentiScan.

Given the user has access to the sentiment comparison tool, when they select three competitors and specify a date range, then the system should display a comparative chart showing sentiment trends for each selected competitor.

User analyzes sentiment trends for their brand and competitors to identify market positioning.

Given the user is viewing the comparative charts, when they hover over data points, then the tool should display detailed sentiment metrics including percentage change and absolute sentiment score for each competitor.

User exports the comparison analysis report for further review and presentation to stakeholders.

Given the user has completed the sentiment comparison, when they click the 'Export' button, then the system should generate a formatted report in PDF that includes graphs, charts, and key insights that can be shared with stakeholders.

User seeks to filter sentiment data by demographic factors such as location or age group to refine their competitive analysis.

Given the user is interacting with the sentiment comparison interface, when they apply demographic filters, then the system should update the comparative charts to reflect sentiment data specifically for the selected demographic segments.

User receives alerts when significant shifts in sentiment are detected for competitors they are monitoring.

Given the user has set up alerts for selected competitors, when there is a change in sentiment that exceeds a predefined threshold, then the system should notify the user via email and/or in-app notification alerting them to the change.

Sentiment Insights Dashboard

User Story: As an executive, I want a comprehensive insights dashboard that consolidates all key sentiment metrics so that I can quickly assess market positions and make decisions without having to sift through multiple reports.
Description: This requirement entails creating a more advanced dashboard that consolidates all sentiment insights, including competitive benchmarking, historical data, and real-time analysis. The dashboard will serve as a one-stop solution for users to visualize and analyze sentiment data comprehensively. The benefits include enhanced user experience, enabling strategists and marketers to quickly understand sentiment trends and make informed decisions. It will leverage existing dashboard features while enhancing usability and aesthetic appeal.
Acceptance Criteria: User navigates to the Sentiment Insights Dashboard and selects the Competitive Trend Benchmarking feature to view sentiment trends of their brand alongside competitors' brands over the past three months.

Given the user is on the Sentiment Insights Dashboard, when they select the Competitive Trend Benchmarking feature, then the dashboard should display a comparative line graph of sentiment trends for at least three competitors over the designated time period with accurate data points.

A marketer is using the Sentiment Insights Dashboard to analyze real-time consumer sentiment data related to their brand's latest product launch.

Given the marketer accesses the Sentiment Insights Dashboard, when they refresh the dashboard, then sentiment data should update in real-time, reflecting the latest social media discussions and user reviews related to the product launch.

An analyst is preparing a report based on historical sentiment data displayed in the Sentiment Insights Dashboard for stakeholder review.

Given the analyst is viewing the historical sentiment data section on the dashboard, when they export the data, then the exported report should include visualizations, time-stamped data, and key insights in a user-friendly format compatible with Excel and PDF.

A user wants to personalize their Sentiment Insights Dashboard to prioritize specific competitors and sentiment metrics most relevant to their marketing strategy.

Given the user is on the Sentiment Insights Dashboard, when they select their preferred competitors and metrics to focus on, then the dashboard should save these preferences and refresh to display a customized view, retaining the selections for future visits.

A marketer is assessing the impact of a recent PR campaign on brand sentiment through the Sentiment Insights Dashboard.

Given the marketer accesses the Sentiment Insights Dashboard and the Competitive Trend Benchmarking feature, when they analyze data post-campaign, then there should be clear visual indicators of sentiment changes, including percentage increases or decreases compared to the previous period and historical averages for context.

Channel Performance Insights

Channel Performance Insights provides detailed analytics on sentiment trends specific to each platform. By breaking down performance metrics, users can identify which channels resonate best with their audience and strategically allocate resources for maximum impact. This feature empowers marketers to optimize their strategies based on data-driven decisions specific to each social media platform.

Requirements

Sentiment Trend Analysis

User Story: As a marketer, I want to view sentiment trends over time for each social media platform so that I can identify which campaigns are most effective and adapt my strategies accordingly.
Description: The Sentiment Trend Analysis requirement focuses on providing a comprehensive overview of sentiment trends for each social media platform integrated within SentiScan. This feature should allow users to visualize sentiment fluctuations over time, enabling them to identify patterns related to specific campaigns, events, or external factors affecting consumer sentiment. The integration of real-time data processing ensures that marketers can act promptly on emerging trends, thus maximizing engagement and influence. This requirement is essential for enhancing users' ability to make informed decisions based on up-to-date sentiment analysis, ultimately driving effective marketing strategies and improved ROI.
Acceptance Criteria: User visualizes sentiment trends over a three-month period for a recent marketing campaign across multiple social media platforms.

Given the user is on the Channel Performance Insights dashboard, when they select a campaign date range of the last three months, then they should view a line graph illustrating sentiment changes across platforms with clear demarcations for spikes and drops in sentiment.

User compares sentiment trends between two different social media platforms to assess performance disparity.

Given the user is comparing two selected social media platforms, when they generate a report, then they should see a side-by-side comparison of sentiment trends, including percentage changes and overall sentiment scores for each platform during the specified time frame.

User receives an alert when there is a significant shift in sentiment for a monitored campaign.

Given that the user has a sentiment threshold set for alerts, when the sentiment on a selected platform changes by more than 20% compared to the previous week, then the user should receive a notification alerting them of the shift with relevant details.

User analyzes sentiment data in real-time to inform immediate marketing decisions during a product launch.

Given the user is monitoring social media sentiment live during a product launch event, when they access the Sentiment Trend Analysis feature, then they should see real-time updates of sentiment scores and consumer feedback, displayed in an interactive format.

User identifies patterns related to specific events impacting consumer sentiment using historical data analysis.

Given the user is reviewing sentiment trends, when they filter data by significant events within the timeline, then they should see highlighted correlations between sentiment fluctuations and those events on the analysis graph.

User downloads a detailed report of sentiment trends for presentation purposes.

Given the user selects a specific date range and social media platforms for analysis, when they click the download report option, then they should receive a well-formatted PDF report including visualizations, key insights, and contextual commentary on sentiment trends.

User customizes the dashboard to show the most relevant sentiment metrics for their needs.

Given the user accesses the dashboard settings, when they select their preferred metrics and arrangement for displaying sentiment data, then the dashboard should update to reflect those selections accurately and immediately.

Channel Comparison Dashboard

User Story: As a marketer, I want to compare the performance of different social media channels so that I can allocate my budget to the most effective platforms and improve overall return on investment.
Description: The Channel Comparison Dashboard requirement involves creating a user-friendly interface where marketers can compare performance metrics of different social media channels side by side. This dashboard should encapsulate key performance indicators (KPIs) such as engagement rates, sentiment scores, and audience reach per channel, allowing users to quickly assess which platforms deliver the best results. The integration of visual charts and graphs will aid in intuitive understanding, making it easier for marketers to allocate their resources effectively. This requirement plays a crucial role in supporting data-driven decision-making by providing clear insights on channel performance.
Acceptance Criteria: Marketer is using the Channel Comparison Dashboard to analyze the performance of various social media platforms for an upcoming campaign, aiming to allocate budget effectively based on engagement and sentiment scores across channels.

Given that the dashboard displays multiple social media channels, When the user selects specific channels to compare, Then the dashboard should show engagement rates, sentiment scores, and audience reach side by side for each channel.

A marketing analyst needs to quickly interpret the data presented in the Channel Comparison Dashboard during a team meeting to guide decision-making regarding resource allocation.

Given that the data is displayed in visual charts, When the analyst reviews the dashboard, Then the charts should accurately reflect real-time data with clear labels and legends for each performance metric.

The marketing team is reviewing historical data via the Channel Comparison Dashboard to measure the impact of previous campaigns across different platforms.

Given that the user has access to historical performance data, When they select a filter for a specific date range, Then the dashboard should update to show performance metrics for the selected period, maintaining accuracy and integrity of the data.

A user wants to identify trends in sentiment scores over time across multiple channels to assess their effectiveness post-campaign.

Given that the user accesses the sentiment analysis section of the dashboard, When they choose a timeline view, Then the system should generate a trend graph showing sentiment scores for each channel over the selected time frame.

A user frequently monitors the performance of their most engaged platforms and requires a quick overview via the dashboard.

Given that the user prefers a summarized view, When they select the 'Top Performers' option, Then the dashboard should display a summary table showing only the channels with the highest engagement and sentiment scores.

Automated Alerts for Sentiment Changes

User Story: As a marketer, I want to receive automated alerts when there are significant changes in sentiment on my channels so that I can address issues proactively and maintain a positive brand image.
Description: The Automated Alerts for Sentiment Changes requirement aims to implement a notification system that alerts users when significant sentiment shifts occur on their selected channels. This feature should utilize machine learning algorithms to detect notable changes in sentiment and send real-time alerts via email or within the application. By enabling users to react swiftly to emerging issues or trends, this functionality enhances the proactive nature of marketing strategies. The requirement is vital for maintaining competitive advantage and ensuring that any negative sentiment is addressed promptly before it escalates.
Acceptance Criteria: User receives an automated email alert when a significant increase in positive sentiment is detected on the Twitter channel within a specified time frame.

Given the user has set up alerts for their Twitter channel, when sentiment shifts significantly (e.g., >20% increase), then the user should receive an email notification about the increase in positive sentiment.

Users can view real-time in-app notifications for negative sentiment shifts in Instagram comments during a key marketing campaign.

Given the user is monitoring sentiment for their Instagram comments, when a significant negative shift occurs (e.g., >15% decrease), then an in-app notification should pop up alerting them of this change.

A user sets up specific keyword triggers to monitor sentiment and receives alerts accordingly.

Given the user has configured specific keywords related to their brand, when these keywords trigger a sentiment change (either positive or negative), then the system should send alerts via email and in-app messages for the relevant sentiment changes.

The alert system successfully logs all alerts generated regarding sentiment changes for user reference and analysis.

Given the alert system is active, when a sentiment change triggers an alert, then the alert should be logged in the user's history for future review, including time, date, channel, and sentiment type.

Users can customize the threshold percentage for alerts based on their own preferences and marketing strategies.

Given the user is in the alert settings, when they adjust the threshold for positive and negative sentiment alerts, then the system should accept the new thresholds and use them for future alerts accordingly.

The system provides a summary report of all alerts triggered over a defined time period for user evaluation.

Given the user requests an alert summary, when they specify a time frame (e.g., past week/month), then the system should generate a report detailing the sentiment changes and alerts received during that period.

Platform-Specific Reporting

User Story: As a marketer, I want to generate detailed reports for specific social media platforms so that I can analyze performance and present findings to my team in a clear and organized manner.
Description: The Platform-Specific Reporting requirement encompasses the ability to generate detailed reports that focus exclusively on specific social media platforms. Users should be able to customize these reports to include metrics relevant to their campaigns, such as sentiment score trends, engagement statistics, and audience demographic insights. This feature is crucial for users to present data effectively to stakeholders or for internal analysis, allowing them to make tailored recommendations based on the unique attributes of each social platform. The integration of export options (PDF, CSV) will facilitate easy data sharing and presentation.
Acceptance Criteria: Generating a report focusing exclusively on sentiment scores for Instagram campaigns.

Given that a user has selected Instagram as the platform, when they generate the report, then the report must exclusively display sentiment score trends related to that platform, with at least three data points over the last 30 days.

Customizing report metrics for a Facebook campaign to include engagement statistics.

Given that a user is customizing a report for a Facebook campaign, when they finalize the report settings, then the report must include engagement statistics such as likes, shares, and comments alongside the sentiment scores, clearly distinguishing the metrics used.

Exporting a detailed report from SentiScan in PDF format to share with stakeholders.

Given that a user has generated a report, when they select the export option for PDF, then the exported document should correctly format the data, be easily readable, and accurately reflect all selected metrics from the report.

Viewing demographic insights within the platform-specific report for Twitter.

Given that a user is viewing the platform-specific report for Twitter, when they navigate to demographic insights, then the insights should break down audience demographics based on age, gender, and location for the selected period.

Sharing a CSV report with detailed metrics on LinkedIn campaigns.

Given that a user has selected LinkedIn as the focus platform for their report, when they export the report to CSV, then the CSV file must contain columns for all relevant campaign metrics, including sentiment scores, engagement stats, and demographic data.

Generating a comparative performance analysis report for different social media platforms.

Given that a user selects multiple platforms (e.g., Facebook and Twitter) for comparison, when they generate the report, then the report must present comparative analysis showing sentiment trends, engagement metrics, and demographic breakdowns for each selected platform side by side.

Sentiment Visualization Tools

User Story: As a marketer, I want to have access to advanced visualization tools for sentiment data so that I can quickly understand and interpret the insights and make data-driven decisions.
Description: The Sentiment Visualization Tools requirement involves providing advanced graphical representations of sentiment data, enabling users to comprehend sentiment metrics at a glance. This feature should include various visualization options, such as pie charts, bar graphs, and heat maps, tailored to different aspects of sentiment analysis. These visual tools should facilitate quick insights and enhance the user experience by making data interpretation easier and more meaningful. By incorporating interactive elements, users can explore data dynamically, leading to more informed decision-making and strategy adjustments.
Acceptance Criteria: Visualization of Sentiment Metrics Across Social Media Channels

Given a user has selected a specific time range and social media platform, When they access the sentiment visualization tools, Then the tool displays sentiment metrics in a pie chart format accurately reflecting the selected data.

Interactive Exploration of Sentiment Data

Given a user is viewing sentiment data represented in a bar graph, When they hover over a specific bar, Then a tooltip should display the exact sentiment score and comparison to previous periods.

Heat Map Representation of Daily Sentiment Trends

Given a user navigates to the heat map section of the sentiment visualization tool, When they select a date range, Then the heat map should accurately display sentiment levels for each day within that range, with color gradients indicating positive, negative, and neutral sentiments.

Exporting Visualized Data for Reporting

Given a user has generated visualizations of sentiment data, When they click the export button, Then they should be able to download the visualizations in multiple formats (e.g., PNG, PDF) without loss of quality.

Integration with Dashboards for Performance Review

Given that a user is on the main dashboard, When they select the sentiment visualization tool, Then the tool should seamlessly integrate, enabling the user to view sentiment insights alongside other performance metrics.

User Customization of Visualization Selectors

Given a user wants to customize the visual representation of sentiment data, When they adjust settings for visualization types and data focus, Then the system should save these preferences and apply them on subsequent logins automatically.

Real-time Updating of Sentiment Visualizations

Given that the sentiment visualization tools are in use, When a significant sentiment change is detected, Then the visual representations should update in real-time without requiring the user to refresh the page.

Customizable Reporting

Customizable Reporting allows users to create tailored reports that focus on specific metrics and timeframes relevant to their campaigns. With drag-and-drop functionality and a variety of visualization options, users can present insights in a manner that best suits their audience, leading to enhanced comprehension and engagement during stakeholder presentations.

Requirements

Dynamic Metric Selection

User Story: As a marketer, I want the ability to select and filter specific metrics for my reports so that I can focus on the most relevant data tailored to my campaign objectives.
Description: Dynamic Metric Selection enables users to easily choose and filter the specific metrics they want to include in their reports. This functionality enhances the reporting process by allowing marketers to focus on the most relevant data points that align with their objectives. Users can switch between metrics in real-time, adjusting their selections based on evolving needs or shifting campaign goals. This feature fosters more personalized and relevant insights for presentations and decision-making processes, ultimately facilitating more effective communication with stakeholders.
Acceptance Criteria: User selects multiple metrics to include in a report during a live presentation to stakeholders.

Given that the user accesses the reporting interface, when they drag and drop selected metrics into the report template, then the report should instantly update to reflect the new metrics without any lag.

User needs to filter out irrelevant data metrics from their reports to focus on key performance indicators.

Given that the user applies filters to the metrics list, when they save and generate the report, then the report should only display the metrics that meet the filter criteria.

User wants to change metrics dynamically as campaign objectives evolve during a strategy meeting.

Given that the user is in a strategy meeting, when they switch metrics using the dynamic selection tool, then the report should refresh in real-time to show the updated metrics immediately.

User aims to visualize the selected metrics in various formats for enhanced clarity in the reports.

Given that the user selects metrics and chooses a visualization option, when they apply the changes, then the report should display the data in the selected visualization format seamlessly.

User intends to generate a report with metrics for a specific time frame during a quarterly review.

Given that the user specifies a date range for the metrics, when they generate the report, then the report should include only the data points that fall within the specified time frame.

Drag-and-Drop Report Builder

User Story: As a data analyst, I want a drag-and-drop interface to build reports so that I can create professional presentations quickly without needing advanced technical skills.
Description: The Drag-and-Drop Report Builder allows users to create and customize reports effortlessly by dragging and dropping elements such as charts, tables, and metrics into their desired layout. This intuitive interface significantly reduces the time spent on report creation and empowers users of all technical backgrounds to generate insightful reports without needing extensive training. By making the reporting process accessible and straightforward, marketers can produce professional-grade presentations quickly, leading to improved stakeholder engagement and understanding.
Acceptance Criteria: User wants to create a report in SentiScan by selecting various data metrics for a marketing campaign.

Given the user is logged into SentiScan, when they access the Drag-and-Drop Report Builder, then they should see a list of available metrics, charts, and tables to choose from.

User desires to customize the layout of the report by rearranging components with drag-and-drop functionality.

Given the user has selected multiple report elements, when they drag and drop these elements into the desired section of the report layout, then the report layout should update in real-time to reflect the new arrangement.

User wants to save a customized report after making changes in the report builder.

Given the user has finished customizing their report, when they click the 'Save' button, then the report should be saved successfully, and the user should receive a confirmation message indicating the report has been saved.

User wishes to preview the report before finalizing it.

Given the user is in the report builder, when they select the 'Preview' option, then they should be presented with a live view of how the report will appear when generated, including all selected metrics and layouts.

User wants to print or export the finalized report for presentation.

Given the report is finalized, when the user selects the 'Export' option, then the report should be available in multiple formats (PDF, Excel), and the user should be able to successfully download it without errors.

User needs to filter the data used in the report based on specific date ranges.

Given the user has accessed the date filter option, when they set a date range and apply the filter, then only the data within that specified time frame should be reflected in the report metrics and visuals.

Variety of Visualization Options

User Story: As a project manager, I want multiple visualization options for my reports so that I can choose the best format to present complex data clearly to stakeholders.
Description: This feature provides a wide selection of visualization options, including charts, graphs, and infographics, to represent data in the most impactful way. Users can select from various formats that best convey their insights depending on the audience and context of their presentation. By offering diverse visualization tools, organisations can enhance the interpretability of their data, making it easier for stakeholders to grasp complex information at a glance.
Acceptance Criteria: User wants to create a customized report for a recent marketing campaign using various visualization options to highlight key performance metrics.

Given the user selects the Customizable Reporting feature, When the user chooses a visualization type from the available options, Then the selected visualization should appear in the report with accurate data representation and formatting applied.

A marketing analyst is preparing a presentation to stakeholders and needs to showcase data trends using different chart types available in SentiScan.

Given the analyst accesses the visualization options, When they select a line chart and input the required metrics, Then the system should generate the line chart correctly reflecting the selected metrics over the specified time frame.

The user is tasked with comparing campaign performance metrics side-by-side using bar charts and pie charts for clearer insights.

Given the user selects multiple visualization formats for comparison, When the user arranges them on the reporting canvas, Then all selected visualizations should be displayed simultaneously without data discrepancies, allowing for easy comparison of insights.

The user wants to save their customized report with specific visualizations for future reference and team access.

Given the user has completed customizing their report, When the user clicks on the save option, Then the system should prompt for a report name and successfully save the report with all selected visualizations and settings accessible in the user’s report library.

The user needs to present the customized report and wants to ensure the visualizations adapt to different screen sizes during the presentation.

Given the user is in presentation mode, When the user adjusts the screen size or switches to different devices, Then all visualizations should dynamically resize and maintain clarity while preserving their original data integrity.

An organization requires visualizations to support accessibility features for stakeholders with visual impairments.

Given the user selects an accessibility option, When the user updates the visualization settings, Then the visualizations should include options for high contrast, text descriptions, and alternative formats that comply with accessibility standards.

Automated Report Scheduling

User Story: As a marketing lead, I want to schedule automated reports to be sent to stakeholders so that my team can save time and ensure everyone receives timely updates without manual intervention.
Description: Automated Report Scheduling enables users to set up reports that can be generated and sent automatically at defined intervals. This feature ensures that stakeholders receive timely updates without requiring manual effort from the team. Users can customize the frequency and content of the reports while reducing the risk of human error. This results in more efficient processes and ensures that decision-makers always have access to the latest information, improving overall operational efficiency.
Acceptance Criteria: User schedules a weekly report for sentiment analysis results to be delivered every Monday morning.

Given the user has selected the metrics for the report, when the user sets the schedule to weekly and specifies Monday at 9 AM, then the report should be generated and sent to the specified recipients every Monday at 9 AM without manual intervention.

A user customizes the content of an automated report by selecting specific metrics and timeframes.

Given the user is in the report customization section, when the user selects metrics for the report and specifies the desired timeframe, then the automated report should reflect these selections accurately.

The user adjusts the reporting frequency from weekly to daily for real-time insights.

Given the user has an existing weekly report set up, when the user changes the frequency to daily, then the system should update the scheduling to ensure reports are sent daily without requiring further actions from the user.

A stakeholder receives the automated report and reviews the insights presented.

Given the report is scheduled for delivery, when the recipient opens the report email, then the email should include the subject line indicating the report type and date, and all specified metrics should be present in a clear, visually appealing format.

The user receives an alert when an automated report fails to generate on schedule.

Given the automated report is scheduled, when a failure occurs in report generation, then the user should receive a notification within 30 minutes of the scheduled time informing them of the failure and suggested actions.

User links their report scheduling preferences with the dashboard for real-time updates.

Given the user is in the dashboard settings, when they link their scheduled reports to the dashboard, then the dashboard should display an active link to the last report generated along with the next scheduled delivery time.

User reviews the history of scheduled reports and their delivery status.

Given the user navigates to the reporting history section, when they view the report history, then they should see a comprehensive list including each report's scheduled date, delivery status, and link to the respective report.

Customizable Report Templates

User Story: As a business analyst, I want to use customizable report templates so that I can create consistent and professional reports efficiently for different stakeholders.
Description: Customizable Report Templates allow users to save and reuse report layouts that meet specific needs. By providing a library of templates that can be modified according to user needs, this feature ensures consistency in branding while also enabling efficiency in report generation. Users can quickly generate reports that maintain a professional appearance without starting from scratch, boosting productivity and ensuring brand coherence across presentations.
Acceptance Criteria: User leverages customizable report templates to create a quarterly performance report, ensuring consistency in branding and layout across all sections of the report when presenting to stakeholders.

Given the user has access to the template library, when they select a template for a quarterly report and modify it, then the saved report should retain the layout and branding elements without any discrepancies.

A marketing analyst wants to generate a report using a previously saved template that includes specific visualizations and data metrics relevant to a recent campaign.

Given the user selects a saved report template, when they generate the report, then the report should populate with the correct data metrics, visualizations, and maintain consistent formatting as defined in the template.

The user modifies an existing report template to include additional metrics and visualizations that are specific to a new marketing strategy for better clarity during presentations.

Given the user has edit permissions for the template, when they add new metrics and visualizations to the saved template, then the changes should be saved correctly and be available for future use without losing previous data.

A team leader reviews the available report templates to ensure they align with the company’s branding guidelines before their use in upcoming presentations.

Given the user accesses the template library, when they view each report template, then all templates should display the branding elements such as logo, color scheme, and font according to company guidelines.

A report is generated using a template that was last modified a month ago, and the user wants to see if there have been any updates or new templates added since then.

Given the user generates a report using an old template, when they cross-reference the template with the current library, then they should receive a notification about any new templates or updates that meet the criteria for their report.

A user shares a customized report template with a colleague for collaboration on a project, ensuring that both have access to the latest version of the template.

Given the user shares a report template, when the colleague accesses the shared template, then they should see the same version of the template without any errors or discrepancies in layout or data.

The user attempts to delete a template from their library that has been used in previous reports and wants confirmation on the action to avoid accidental loss of important designs.

Given the user tries to delete a report template, when they click the delete option, then a confirmation dialog should appear prompting them to confirm the deletion, preventing accidental loss of the template.

Sentiment Drift Analysis

Sentiment Drift Analysis monitors fluctuations in consumer sentiment over time, identifying subtle shifts that may indicate emerging trends, issues, or opportunities. This feature equips users with the insights needed to stay ahead of public perception, allowing for proactive strategy adjustments and timely interventions to enhance brand reputation.

Requirements

Real-time Sentiment Monitoring

User Story: As a marketing analyst, I want to receive real-time alerts about sentiment changes so that I can respond quickly to emerging trends and manage brand perception proactively.
Description: The Real-time Sentiment Monitoring requirement involves the continuous analysis of consumer sentiment across various social media platforms and online channels. This functionality ensures that SentiScan provides users with up-to-the-minute insights into public opinion. By leveraging advanced AI and natural language processing techniques, the system will automatically detect changes in sentiment and deliver instant notifications to users, enabling prompt response to any shifts. This feature enhances the product's ability to facilitate quick decision-making, allowing brands to align their strategies with current consumer perceptions and needs.
Acceptance Criteria: Real-time Sentiment Monitoring during a major product launch event.

Given the product launch event is live, when a user accesses the Real-time Sentiment Monitoring feature, then the system should automatically scan social media platforms and provide sentiment updates every minute for the duration of the event.

Sentiment Drift Analysis on brand reputation during a marketing campaign.

Given a marketing campaign is in progress, when the user selects the Sentiment Drift Analysis module, then the system should display graphical trends of sentiment fluctuations related to the campaign over the past week.

Alerts for significant sentiment changes during a crisis situation.

Given a crisis situation arises, when a significant positive or negative shift in sentiment occurs, then the system should send an immediate notification to the user via email and dashboard alert within 5 minutes of detection.

Daily summary report of sentiment changes for a selected brand.

Given the user requests a daily summary report, when the user selects the brand of interest, then the system should generate a report detailing sentiment changes, including relevant metrics like positive, negative, and neutral sentiment percentages.

User customization of sentiment thresholds for alerts.

Given the user wants to set custom thresholds, when the user accesses the alert settings, then the system should allow the user to define specific positive and negative sentiment percentage thresholds for receiving notifications.

Integration of sentiment data with marketing strategy tools.

Given the user is analyzing sentiment data, when the user clicks on 'Export Data', then the system should provide options to export sentiment data in formats compatible with popular marketing strategy tools (e.g., CSV, PDF).

Historical Sentiment Trends Visualization

User Story: As a brand manager, I want to view historical sentiment trend graphs so that I can analyze the impact of past marketing campaigns and plan future strategies accordingly.
Description: The Historical Sentiment Trends Visualization requirement focuses on developing an interactive dashboard component that allows users to visualize changes in sentiment over time. This feature will enable users to track historical data, identify seasonal trends, and correlate sentiment shifts with marketing campaigns or external events. By providing graphical representations of sentiment data, users can better understand long-term patterns and make more informed strategic decisions. This capability is critical for brands aiming to evaluate the effectiveness of past initiatives and anticipate future consumer attitudes.
Acceptance Criteria: User views the historical sentiment trends dashboard to analyze sentiment over the past year, focusing on major marketing campaigns conducted during that period.

Given the user accesses the historical sentiment trends dashboard, when they select the last 12 months as the time frame, then they should see a graphical representation of sentiment data displaying at least three clear peaks and valleys corresponding to marketing campaigns.

User attempts to correlate sentiment shifts with specific external events by overlaying event data onto the sentiment trends chart.

Given the user has a list of relevant external events, when they overlay this data onto the sentiment trends chart, then the dashboard should visually integrate the events and highlight any significant correlations in sentiment changes.

Marketers conduct a comparative analysis of sentiment trends across different product categories over the last six months to identify market shifts.

Given the user selects multiple product categories, when they filter the dashboard for the last six months, then the visual output should allow for side-by-side comparisons of sentiment trends for each category, with distinct colors and legends.

User decides to evaluate the effectiveness of a recent advertising campaign on consumer sentiment and wants to view the data for the week following the campaign's launch.

Given the user filters the dashboard for the week's timeframe following a specified campaign launch, when they click on the campaign, then the sentiment visualization should show sentiment scores that reflect an upward or downward trend from the pre-campaign period.

Analysts are tasked with generating a report on seasonal sentiment trends to present at a quarterly business review meeting.

Given the user accesses the historical sentiment trends dashboard, when they select different seasonal time frames (e.g., winter, spring, summer, fall), then the dashboard should aggregate sentiment data accordingly and allow for downloadable reports summarizing the seasonal performance.

User wants to customize the timeline on the sentiment trends dashboard to focus on a specific quarter and compare it with the previous year.

Given the user sets a custom date range for the current and previous years' same quarter, when they apply the changes, then the dashboard should automatically refresh to display the sentiment trends for both periods, clearly indicating trends with annotations for comparison.

Sentiment Drift Alert System

User Story: As a social media manager, I want to customize my alert preferences for sentiment shifts so that I am notified of critical changes that could impact our brand's reputation.
Description: The Sentiment Drift Alert System requirement will implement a mechanism that automatically notifies users when significant sentiment shifts are detected relative to historical averages. This functionality plays a crucial role in alerting marketers and analysts to potential issues or opportunities that may require immediate attention. The system will allow customization of alert thresholds based on the user’s preferences, ensuring that they only receive relevant notifications. By actively monitoring sentiment drifts, users can engage more effectively with their audience and adjust strategies in real time.
Acceptance Criteria: User receives an alert notification when a significant sentiment shift occurs that exceeds the predefined threshold set in their user profile.

Given the user has set a threshold for sentiment change, when the system detects a sentiment shift that exceeds this threshold, then an alert notification should be sent to the user via their chosen notification method.

User is able to customize the sentiment drift alert thresholds to tailor the notifications to their specific needs and preferences.

Given the user accesses the settings for sentiment drift alerts, when they adjust the thresholds for alerts and save the changes, then the settings should be updated and reflected immediately in the system.

The system logs all sentiment shift alerts for audit and historical reference purposes.

Given the system has triggered a sentiment drift alert, when the alert is logged, then it should include a timestamp, sentiment data, and the user’s threshold setting at the time of the alert.

User can view a summary of all recent sentiment alerts in a dedicated dashboard section.

Given the user accesses the sentiment alert dashboard, when they look at the recent alerts section, then they should see a list of the last five alerts with timestamps and sentiment details.

The system should automatically stop sending alerts if the sentiment returns to normal levels below the user's defined threshold.

Given the sentiment has shifted back below the user’s defined threshold after an alert, when the sentiment is monitored, then the system should cease sending alerts until a new significant shift is detected.

User can choose their preferred notification method for receiving sentiment drift alerts (e.g., email, SMS, in-app notification).

Given the user is in the alert settings section, when they select their preferred notification method and save the changes, then the system should use this method to send future alerts.

The system ensures that alerts are concise and provide actionable insights during significant sentiment shifts.

Given the system triggers an alert, when the user receives the notification, then it should contain a brief summary of the sentiment shift, potential implications, and suggested actions to consider.

Competitive Sentiment Benchmarking

User Story: As a product strategist, I want to benchmark my brand's sentiment against competitors so that I can identify gaps in our approach and seize market opportunities.
Description: The Competitive Sentiment Benchmarking requirement provides users with the capability to compare their brand's sentiment against competitors within the same industry. This feature includes analysis tools to visualize competitors' sentiment metrics alongside the brand's own data. Users will benefit from insights into competitive positioning, helping them understand market dynamics, identify areas for improvement, and develop strategies to enhance their market presence. This benchmarking tool is essential for organizations looking to maintain a competitive edge in their sector.
Acceptance Criteria: Competitive Analysis Meeting Review

Given that the user has access to the benchmarking dashboard, when they select competitors to compare sentiment metrics, then they should see visualized sentiment data side by side with their own brand metrics for a specified time period.

Real-time Sentiment Monitoring

Given that the user is monitoring sentiment in real-time, when there is a significant change in competitors' sentiment metrics, then the user should receive an alert indicating the percentage change and the time of occurrence.

Historical Data Comparison

Given that the user wants to analyze sentiment trends, when they select a date range for historical sentiment data, then the system should display comparative sentiment metrics for their brand and competitors over that time period.

Interactive Data Visualization

Given that the user is on the competitive sentiment benchmarking tool, when they hover over data points on the visualized graph, then they should see pop-up tooltips with specific sentiment scores and associated timestamps.

User Role Access Control

Given that SentiScan has multiple user roles, when a user with restricted access attempts to access competitor sentiment data, then they should receive a notification denying access with an explanation of their permission level.

Exporting Benchmark Reports

Given that the user has completed sentiment analysis, when they choose to export the report, then the report should be generated in PDF format including all visualizations and data points, with an export confirmation message displayed.

In-System Help and Resources

Given that the user is unfamiliar with using competitive sentiment benchmarking tools, when they click on the help icon, then they should be directed to a resource page with tutorials and FAQs related to benchmarking sentiment.

Sentiment Anomaly Detection

User Story: As a risk manager, I want to detect sentiment anomalies so that I can address potential issues before they escalate into larger problems.
Description: The Sentiment Anomaly Detection requirement will harness artificial intelligence models to identify outliers or anomalies in sentiment data that may indicate emerging issues, spikes in interest, or sudden negative reactions. This predictive capability will enhance the product's ability to provide actionable insights, allowing brands to proactively address potential crises or capitalize on unexpected opportunities. By integrating this feature, users will be better equipped to analyze the causes of anomalies and tailor responses effectively.
Acceptance Criteria: Sentiment Anomaly Detection alerts users of significant sentiment shifts during a product launch campaign.

Given a product launch event, when there is a sudden drop in sentiment score by more than 15% within a 24-hour period, then the system should trigger an alert to the user.

The AI model recognizes anomalies in sentiment data from social media channels during a crisis.

Given a crisis situation is detected, when sentiment data shows outliers with more than 20% divergence from the average sentiment score, then the system should provide a detailed report of the anomalies detected.

Users analyze past sentiment data to identify patterns indicating emerging consumer trends.

Given user requests sentiment analysis for the last 30 days, when anomalies are detected, then users should be able to visualize these anomalies in an intuitive dashboard format with supporting metrics.

The system evaluates sentiment data to determine the effectiveness of marketing campaigns.

Given a marketing campaign, when the sentiment score deviates by 10% or more from the previous week’s score, then the system should log this anomaly and suggest potential actions for the marketing team.

Sentiment Anomaly Detection provides historical context for recent sentiment shifts for effective decision making.

Given recent sentiment data is available, when users access the anomaly detection feature, then they should be able to view historical sentiment data for the last three months alongside current anomalies.

Integration of sentiment anomaly detection into existing workflows for real-time monitoring.

Given the Sentiment Anomaly Detection feature is active, when users set alerts, then they should receive notifications via email or SMS within 5 minutes of an anomaly being detected.

Users generate a report showcasing identified anomalies and their potential impact on brand perception.

Given the report functionality is required, when anomalies are detected, then users should be able to generate a comprehensive report detailing these anomalies, their context, and suggested strategies for response.

Audience Segmentation Tools

Audience Segmentation Tools enable users to dissect sentiment data across different demographics and psychographics. By understanding how different audience segments respond to various campaigns, marketers can craft targeted strategies that resonate on a personal level, ultimately enhancing engagement and driving conversions.

Requirements

Demographic Data Integration

User Story: As a marketer, I want the ability to integrate demographic data into my audience segments so that I can craft messages that resonate more deeply with targeted groups, improving engagement and conversions.
Description: The Demographic Data Integration requirement focuses on the ability to seamlessly incorporate demographic data such as age, gender, location, and income level into the audience segmentation tools. This integration is crucial for creating nuanced segments that reflect the diverse characteristics of the user base. By connecting demographic data with sentiment analysis, users can better understand how different segments respond to market trends or campaigns, ultimately leading to more targeted marketing strategies. This enhances the overall effectiveness of campaigns, ensuring that companies engage with their audiences in a personalized manner, driving higher conversion rates and customer satisfaction.
Acceptance Criteria: As a marketer using SentiScan, I want to integrate demographic data into the audience segmentation tools so that I can analyze how different audience segments respond to our marketing campaigns based on their age, gender, and income level.

Given that demographic data is available, when I upload the demographic data file, then the system should successfully integrate the data into the audience segmentation tools and display the segments accurately based on the provided demographics.

As a marketer, I want to filter sentiment analysis reports based on demographic segments, so that I can see how campaigns perform for specific audience groups that share similar characteristics.

Given that the demographic data has been integrated, when I select a demographic segment, then the sentiment analysis report should update to only display data relevant to that specific group, including metrics like engagement and conversion rates.

As a marketing analyst, I want the ability to compare sentiment analysis across different demographic segments, so that I can identify which segments are most responsive and adapt our strategies accordingly.

Given that multiple demographic segments are available, when I choose to compare segments, then the system should provide a comparative analysis visual that highlights key differences in sentiment metrics between the selected groups.

As a user, I want the demographic data to update automatically over time, so that I can ensure that the audience segments reflect current demographic trends, leading to better-targeted marketing strategies.

Given that the demographic data integration feature is functioning, when there are changes in the underlying demographic data source, then the system should automatically pull the most recent data and update the segments accordingly without manual intervention.

As a marketer, I want to segment our audience based on psychographic data in addition to demographic data, so that I can create more refined audience profiles that capture attitudes, interests, and lifestyle factors.

Given that both demographic and psychographic data are available, when I create a new audience segment, then the system should allow me to apply filters based on both data types, ensuring that the resulting segments are comprehensive and nuanced.

As a user, I want to receive alerts for significant shifts in sentiment data among specific demographic segments, so that I can react quickly to any changes in consumer attitudes or perceptions.

Given that demographic and sentiment analysis are integrated, when there is a significant change in sentiment data for a selected demographic segment, then the system should send a real-time alert to designated users, detailing the nature of the change.

As a marketing manager, I want to visualize demographic data on the dashboard alongside sentiment data, so that I can easily assess the correlation between demographic characteristics and sentiment trends over time.

Given that both demographic and sentiment data are available, when I access the dashboard, then I should see a visual representation (such as charts or graphs) that displays the correlation between demographic characteristics and sentiment trends, allowing for quick insights.

Psychographic Analysis Capability

User Story: As a marketing analyst, I want to analyze psychographic data so that I can understand the underlying motivations of different audience segments and create targeted marketing strategies that connect on a deeper level.
Description: The Psychographic Analysis Capability requirement aims to introduce features that enable the segmentation of audiences based on psychographic factors like interests, values, lifestyle, and personality traits. By analyzing how these factors contribute to sentiment towards products and brands, users will be equipped to tailor their marketing messages and campaigns. This feature will not only improve the relevance of marketing content but will also enhance consumer trust and loyalty as brands align their communication strategies with the intrinsic motivations of their audience. The implementation of psychographic analysis will provide deeper insights into emotional connections and consumer behaviors, allowing companies to maximize their marketing impact.
Acceptance Criteria: Psychographic Analysis for Campaign Targeting

Given a user can segment audience data by psychographic factors, when the user selects a specific campaign, then the system should generate a list of audience segments along with insights on their interests, values, and lifestyle traits.

Insights Dashboard for Psychographics

Given the psychographic analysis capability is implemented, when the user accesses the insights dashboard, then they should see visual representations of sentiment data segmented by psychographic attributes within 2 seconds.

Real-Time Sentiment Tracking by Psychographics

Given that sentiment shifts occur on social media, when a psychographic segment is selected, then the system should alert the user to any significant sentiment changes in real-time.

Exporting Psychographic Reports

Given a user completes a psychographic analysis, when they request a report, then the system should generate a downloadable report that includes key insights and segmented data within 5 minutes.

User Feedback on Psychographic Tools

Given that the psychographic analysis capability is in use, when users provide feedback through an in-app survey, then the feedback should be collected and analyzed for improvement measures with a minimum response rate of 30%.

User Guidance on Using Psychographic Tools

Given that the user is accessing the psychographic analysis feature, when they hover over any tooltips or guidance elements, then the system should provide relevant information and examples that help users understand and utilize the tools effectively.

Comparison of Psychographic Segments

Given that multiple psychographic segments can be analyzed, when the user selects two or more segments, then the system should display a comparative analysis report highlighting differences in sentiment and behavior within 10 seconds.

Real-time Sentiment Tracking

User Story: As a market researcher, I want to track sentiment in real-time so that I can quickly adjust our marketing strategy in response to changing consumer attitudes, ensuring ongoing relevance and engagement.
Description: The Real-time Sentiment Tracking requirement outlines the necessity for tools that provide instant updates on consumer sentiment changes across platforms. This functionality will allow users to monitor how sentiment shifts in response to specific events, marketing campaigns, or external factors. By obtaining real-time data, marketers can react quickly and adapt their strategies to changing consumer perceptions, maximizing opportunities for engagement and conversion. This feature is vital for staying ahead of trends and ensuring that marketing efforts resonate with target audiences promptly, ultimately leading to enhanced adaptability and effectiveness of marketing campaigns.
Acceptance Criteria: Real-time monitoring of sentiment changes during a major product launch campaign.

Given a product launch event, when the campaign goes live, then the system should update sentiment data in real-time with a refresh rate of less than 5 minutes and provide notifications of significant sentiment shifts.

Analysis of sentiment trends before and after a marketing campaign to evaluate effectiveness.

Given a marketing campaign start and end date, when the analysis period is selected, then the system should display a comparative sentiment trend report showing pre and post-campaign sentiment scores with a clear visual representation.

Setting up alerts for negative sentiment changes related to brand mentions across social media.

Given that the user has set up monitoring for specific brand keywords, when sentiment drops below a predefined threshold, then the system should send an immediate alert to the user via email and in-app notification.

Customizing audience segmentation to analyze specific demographic responses to campaigns.

Given a user selects demographic filters such as age, gender, and location, when the segmentation is applied, then the system should generate sentiment insights specific to the selected audience segment without any errors.

User experience testing of the dashboard displaying real-time sentiment insights.

Given a user accesses the dashboard, when they navigate to the real-time sentiment tracking section, then all relevant data should load within 2 seconds and be visually intuitive and interactive for user engagement.

Integration of sentiment data with external marketing platforms for enhanced strategies.

Given that the user has linked external marketing platforms with SentiScan, when a sentiment report is generated, then the data should seamlessly integrate into the external platform without any loss of information or functionality.

User review of sentiment change reports to develop future marketing tactics.

Given a user generates a sentiment change report, when they review the report, then the system should provide actionable recommendations based on the analyzed sentiment shifts over the specified period.

Advanced Filtering Options

User Story: As a digital marketer, I want to apply advanced filtering options to my audience segments so that I can find the most relevant groups to target with my campaigns, increasing the likelihood of successful engagement and conversions.
Description: The Advanced Filtering Options requirement seeks to provide users with enhanced tools for narrowing down their audience segments based on specific criteria. Users should be able to apply multiple filters simultaneously, such as demographics, psychographics, and sentiment analysis metrics. This feature is essential to enable marketers to find precise audience segments that closely match their campaign objectives. By allowing greater granularity in segmentation, marketers can enhance the precision of their targeting, improving the effectiveness of their campaigns and ultimately driving better ROI.
Acceptance Criteria: User selects multiple demographic filters to narrow down audience segments based on age, gender, and location.

Given that the user applies demographic filters for age (18-34), gender (female), and location (New York), When the user clicks the 'Apply Filters' button, Then the displayed results should only include audience segments matching all selected filters.

User applies psychographic filters to identify audience segments with specific interests and values.

Given that the user applies psychographic filters for interests (technology, health) and values (sustainability), When the user clicks the 'Apply Filters' button, Then the displayed results should include only those audience segments that match the specified psychographic criteria.

User utilizes sentiment analysis metrics to filter audience segments based on positive or negative sentiment scores.

Given that the user sets a sentiment score filter for positive sentiment (greater than 0.5), When the user clicks the 'Apply Filters' button, Then the displayed results should reflect audience segments with a sentiment score above 0.5.

User combines multiple filters to create a highly specific audience segment for a targeted campaign.

Given that the user sets filters for demographics (age 25-40), psychographics (fitness enthusiasts), and sentiment (positive), When the user clicks the 'Apply Filters' button, Then the system should display only those audience segments that meet all the combined filter criteria.

User saves a specific set of filters for future use in campaigns or reports.

Given that the user has applied a set of filters and clicks 'Save Filters', When the user names and saves the filter set, Then the filter set should be stored and retrievable from the saved filters list in future sessions.

User views and modifies existing filters to refine audience segment results.

Given that the user has previously saved filters, When the user selects a saved filter set to modify, Then the user should be able to edit the filter criteria and reapply them, providing updated results based on the modified filters.

User receives real-time feedback on filtering results after applying advanced filters.

Given that the user applies filters to the audience segment, When the filters are applied, Then the system should provide real-time feedback, such as the number of segments affected or a summary of the sentiment scores for the newly filtered results.

Competitive Benchmarking Tool

User Story: As a business strategist, I want to benchmark our audience sentiment against our competitors so that I can identify areas for improvement and optimize our marketing strategies effectively, ensuring that we stay ahead in the market.
Description: The Competitive Benchmarking Tool requirement describes the need for functionality that allows users to compare their audience sentiment and engagement metrics against competitors. By providing insights into industry standards and competitor performance, this tool will enable users to evaluate and enhance their own marketing strategies effectively. Analyzing competitor sentiment will help marketers identify strengths and weaknesses in their approach, facilitating strategic adjustments and informed decision-making. This benchmarking capability is essential for maintaining competitiveness in a rapidly changing market environment.
Acceptance Criteria: As a marketer, I want to access the Competitive Benchmarking Tool to compare my audience sentiment metrics against those of my top three competitors so I can adjust my strategies accordingly.

Given that I am logged into the SentiScan application, when I navigate to the Competitive Benchmarking Tool and input my competitor's data, then I should be able to view a comparative analysis of sentiment metrics, including positive, negative, and neutral sentiments, within 10 seconds.

As a user, I want to receive a notification when there is a significant change in sentiment metrics of my competitors so that I can act quickly to optimize my strategy.

Given that I have set up notifications within the Competitive Benchmarking Tool, when there is a shift of at least 10% in a competitor's positive sentiment over the past week, then I should receive an alert via email or in-app notification within 5 minutes of the data update.

As a product manager, I want to generate a report that shows the sentiment comparison between my brand and competitors over the past month so that I can present findings to my team.

Given that I access the report generation feature of the Competitive Benchmarking Tool, when I select the date range of the last month and my competitors, then I should be able to download a report that includes visual graphs and numeric data of sentiment comparisons, with 100% data accuracy.

As a marketer, I want to filter competitor data by demographic categories to see how different segments are responding to their campaigns.

Given that I am using the Competitive Benchmarking Tool, when I apply filters for demographic categories (age, gender, location), then the results should display sentiment metrics that reflect those specific segments, ensuring that the analysis is tailored and relevant within 3 seconds.

As a user, I want to view a historical trend of my brand's sentiment compared to competitors over time to understand performance changes.

Given that I have navigated to the historical trends section of the Competitive Benchmarking Tool, when I select a specific timeframe, then I should see an interactive timeline displaying sentiment trend lines for both my brand and competitors, with the ability to identify key events that influenced changes.

As a marketing analyst, I want to assess the impact of specific campaigns on competitor sentiment to gauge overall market reaction.

Given that I input relevant campaign data for comparison, when I analyze the results in the Competitive Benchmarking Tool, then I should be able to see a clear correlation between the campaign launch dates and any resulting sentiment shifts in both my brand and the competitors, with insights highlighted for easier decision-making.

User-Friendly Dashboard

User Story: As a user of SentiScan, I want a user-friendly dashboard that clearly visualizes audience segmentation data so that I can quickly understand insights and make informed decisions about my marketing strategies.
Description: The User-Friendly Dashboard requirement emphasizes the importance of developing intuitive dashboards that clearly visualize audience segmentation and sentiment analysis data. These dashboards should offer easy-to-understand metrics, trends, and comparisons that allow users to quickly interpret information and derive actionable insights. A well-designed dashboard is essential not only for user engagement but also for enhancing the decision-making process. By providing a visual representation of key data points, users will be empowered to make informed decisions rapidly, improving the efficiency and effectiveness of their market strategies.
Acceptance Criteria: User navigates to the dashboard to view audience segmentation data after conducting a sentiment analysis campaign.

Given the user is on the User-Friendly Dashboard, when they select the 'Audience Segmentation' tab, then the dashboard displays segmentation metrics with clear visualizations such as charts and graphs for all defined audience segments.

User wants to compare sentiment trends between different audience segments over a specified period.

Given the user selects two or more audience segments and a date range, when they click on the 'Compare' button, then the dashboard presents a juxtaposed view of sentiment trends in an easy-to-read format with color-coded indicators.

User receives alerts about significant sentiment shifts in a targeted audience segment that requires immediate action.

Given the sentiment analysis indicates a shift of more than 20% in sentiment toward a campaign within five minutes, when the user accesses the dashboard, then an alert notification appears, detailing the affected audience segment and the specifics of the shift.

User needs to export dashboard data for presentation purposes.

Given the user is viewing the dashboard with the audience segmentation data, when they select the 'Export' option and choose their preferred file format, then the system should generate and download a report that includes all visible data metrics in a clean format.

User wants to customize the visual appearance of the dashboard to better suit their analytical preferences.

Given the user is on the dashboard, when they opt for 'Customize View', then they should be able to choose from at least 5 different layouts and at least 3 color themes, and the dashboard should reflect these changes immediately.

User intends to receive training on how to interpret the sentiment metrics displayed on the dashboard.

Given the user clicks on the 'Help' icon, when they open the tutorial section, then the user should have access to a step-by-step guide with examples of how to read and interpret each metric displayed on the dashboard.

Interactive Sentiment Timeline

Interactive Sentiment Timeline visualizes sentiment evolution in a chronological format, allowing users to correlate their marketing efforts with changes in public perception. This feature helps users understand the direct impacts of their campaigns over time, providing clearer insights into what strategies yield the best results.

Requirements

Dynamic Sentiment Filters

User Story: As a marketing analyst, I want to filter sentiment data by campaign type and demographics so that I can better understand how specific marketing efforts impact consumer attitudes across different audience segments.
Description: The Dynamic Sentiment Filters allow users to customize and view sentiment data in real-time based on specific criteria such as time frame, demographic segments, and campaign types. This functionality enhances user control over the data analysis process by enabling marketers to isolate relevant sentiment trends and shifts that correlate with their specific marketing initiatives. By leveraging these filters, users can gain a deeper understanding of how various factors affect public perception, leading to more targeted marketing strategies and enhanced decision-making.
Acceptance Criteria: User customizes sentiment data view by selecting a specific time frame (e.g., last 30 days) and applies the filter to the Interactive Sentiment Timeline.

Given a user has selected a specific time frame for sentiment analysis, when the user applies the filter, then the Interactive Sentiment Timeline displays sentiment data only for the indicated time frame without error.

User filters sentiment data by demographic segment (e.g., age group, gender) to analyze how different consumer groups react to a marketing campaign.

Given a user has chosen a demographic segment for analysis, when the user applies the demographic filter, then the sentiment data in the Interactive Sentiment Timeline updates to reflect only the sentiment from the selected demographic segment.

User wants to isolate sentiment data related to a specific marketing campaign to evaluate its performance over time.

Given a user has selected a particular marketing campaign from the list, when the user applies the campaign filter, then the Interactive Sentiment Timeline shows data only related to the selected marketing campaign and all other data is hidden.

User tries to use multiple filters simultaneously to analyze sentiment data from a combination of time frame, demographic segment, and campaign type.

Given a user has selected multiple filter criteria (time frame, demographic segment, campaign type), when the user applies all of the filters, then the Interactive Sentiment Timeline accurately displays the sentiment data that matches all selected criteria without any discrepancies.

User seeks to reset all applied filters to return to the original unfiltered view of the sentiment data.

Given a user has applied multiple filters, when the user clicks the reset button, then all filters are cleared, and the Interactive Sentiment Timeline displays the complete, unfiltered sentiment data.

User checks for system performance when applying filters on large datasets of sentiment data.

Given a user with access to a large volume of sentiment data, when filters are applied, then the system responds and updates the visualizations in less than 2 seconds to ensure a smooth user experience.

Comparative Analysis Tool

User Story: As a brand manager, I want to compare our sentiment scores with competitors so that I can identify areas for improvement and capitalize on our strengths to enhance our market positioning.
Description: The Comparative Analysis Tool provides users with the capability to analyze sentiment data against competitors or industry benchmarks. This feature allows marketers to visually compare their sentiment scores with those of competitors over chosen periods, facilitating an understanding of relative performance. The tool integrates seamlessly with existing dashboards, leveraging visualizations that highlight strengths and weaknesses, enabling users to make evidence-based strategic decisions to improve their market position.
Acceptance Criteria: Comparative Analysis of Sentiment Scores Based on a Selected Timeframe

Given that a user has selected a specific timeframe, when they access the Comparative Analysis Tool, then they should see a visual representation of sentiment scores that accurately reflects the selected dates and highlights differences between their brand and competitors.

Integration of Comparative Analysis Tool with Existing Dashboards

Given that the user is on the main dashboard, when they navigate to the Comparative Analysis Tool, then the tool must seamlessly integrate without errors, displaying sentiment data alongside existing metrics and visualizations.

Downloadable Reports from Comparative Analysis Tool

Given that a user has completed their comparative analysis, when they choose to export the results, then the system should generate a downloadable report in PDF format that includes visual charts and key metrics clearly outlining the comparative sentiment analysis.

User Ability to Filter Competitors in the Analysis Tool

Given that a user is using the Comparative Analysis Tool, when they select which competitors to analyze, then the sentiment comparison should update in real-time to reflect only the selected competitors' data.

Display of Strengths and Weaknesses in Sentiment Scores

Given that the user has generated a sentiment comparison report, when they view the report, then the tool should clearly highlight areas of strength (higher sentiment scores) and weaknesses (lower sentiment scores) in an intuitive manner for easy interpretation.

Notification of Significant Changes in Sentiment Scores

Given that the user is monitoring sentiment scores over time, when there is a significant change (increase/decrease of more than 20% compared to the previous period), then the user should receive an alert via the dashboard and email.

User Feedback on the Effectiveness of the Comparative Analysis

Given that the user has utilized the Comparative Analysis Tool, when they provide feedback through a feedback form, then they should receive acknowledgment of their submission, and the feedback should be logged for future improvements.

Automated Reporting System

User Story: As a project lead, I want to receive automated sentiment reports so that I can efficiently communicate key insights to stakeholders without manual effort.
Description: The Automated Reporting System generates real-time reports summarizing sentiment data for specified intervals. Users can schedule reports to automatically be sent to stakeholders, which increases efficiency in communication. These reports include visual dashboards with key performance indicators related to sentiment changes, providing quick overviews of campaign impacts. This feature ensures that decision-makers have continuous access to fresh, pertinent data that aids in maintaining proactive engagement with target audiences.
Acceptance Criteria: User schedules a weekly automated report to be sent every Monday at 9 AM to the marketing team, summarizing sentiment data from the previous week.

Given the user has selected the weekly schedule option, When they specify the sending time as 9 AM on Monday, Then the report should be generated and sent to the specified recipients without errors every week.

A user wants to ensure the automated report includes visual dashboards that effectively represent sentiment changes over the selected interval.

Given the report is scheduled, When the user views the report, Then the report must display visual dashboards with at least 3 key performance indicators related to sentiment changes.

The marketing team receives an automated report and needs to verify that the sentiment data is accurate and up to date as of the last reporting interval.

Given the report is sent, When the marketing team reviews it, Then the report must reflect the sentiment data accurately from the specified reporting interval without discrepancies.

A user decides to modify the scheduled report timing and wants to ensure that the change is saved and reflected in future reports.

Given the user modifies the scheduled time for the report, When they save the changes, Then the new schedule should be displayed correctly in the reporting settings and adhered to in the next scheduled report.

A stakeholder receives the automated report and needs to view it on a mobile device to ensure compatibility across platforms.

Given the report is sent, When the stakeholder opens it on their mobile device, Then the report must render correctly with all visual elements and data accessible and user-friendly.

The system should alert users when a report fails to generate due to an error or system issue.

Given the report fails to generate, When the scheduled time arrives, Then the user must receive a notification alerting them of the failure along with the reason for the failure.

Users want to evaluate the effectiveness of automated reports over time by accessing historical reports stored in the system.

Given the user requests access to historical reports, When they navigate the reporting feature, Then they must be able to view, filter, and download previous reports without any issues.

Custom Alert Notifications

User Story: As a digital marketer, I want to receive alerts when sentiment changes significantly so that I can react swiftly to public discussions and adjust our messaging accordingly.
Description: Custom Alert Notifications enable users to set up alerts based on predefined sentiment thresholds or changes in public perception related to their campaigns. When the specified criteria are met, users receive instant notifications via email or the app, ensuring they are promptly informed of significant shifts in sentiment. This functionality enhances responsiveness, allowing marketers to adjust strategies quickly in reaction to emerging trends.
Acceptance Criteria: User sets up custom alert notifications for their marketing campaign based on predefined sentiment thresholds to monitor brand perception changes.

Given the user has accessed the Custom Alert Notifications feature, when the user sets a sentiment threshold between 0.6 to 0.8 for their campaign, then the system sends an email notification immediately when sentiment hits the threshold.

User receives a notification when the sentiment for a specific campaign shifts significantly indicating a potential issue.

Given the user has set an alert for a 20% drop in sentiment score for their campaign, when the sentiment score drops by 20% or more, then the user should receive an app notification and an email within 5 minutes of the drop.

User wants to track the effectiveness of their recent campaign and set alerts accordingly.

Given the user has activated notifications for positive sentiment increases, when the sentiment of the campaign rises above 0.7, then the user should receive a summary of the sentiment evolution via email.

User modifies an existing alert notification for a different sentiment threshold as their marketing strategy evolves.

Given the user has an existing alert notification set for a sentiment threshold of 0.5, when the user changes the threshold to 0.75 and saves the settings, then the system updates the notification criteria successfully as confirmed by a success message.

User tests the alert notification feature to ensure it functions as intended before launching a major campaign.

Given the user tests the alert notification for a hypothetical sentiment threshold of 0.65, when the system simulates the sentiment crossing that threshold, then the user should receive an immediate simulation alert via email.

User checks the history of alerts to analyze past notifications and make data-driven decisions for future campaigns.

Given that alerts have been triggered in the past, when the user navigates to the alert history page, then the system displays a chronological list of all alerts with timestamps and sentiment details.

User Engagement Analytics

User Story: As a content strategist, I want to analyze how user interactions affect sentiment so that I can develop content that better engages our audience and complements our marketing efforts.
Description: User Engagement Analytics provides insights into how audience interaction with content correlates with sentiment changes over time. By analyzing user engagement metrics such as likes, shares, and comments alongside sentiment data, marketers can identify effective content strategies and understand what resonates with their audience. This feature supports data-driven decisions that enhance content creation and marketing effectiveness.
Acceptance Criteria: User views the Interactive Sentiment Timeline after launching a marketing campaign to analyze changes in sentiment over time in correlation with user engagement metrics.

Given the user has initiated a marketing campaign, when they access the Interactive Sentiment Timeline, then they should see sentiment values represented chronologically alongside corresponding user engagement metrics such as likes, shares, and comments.

The marketing team needs to assess the impact of a specific social media post on overall audience sentiment to determine future content strategies.

Given a specific social media post has been shared, when the user selects the post on the sentiment timeline, then they should receive detailed analytics that evaluate sentiment changes before and after the post, including engagement metrics for that specific timeframe.

A user wishes to filter sentiment data to focus exclusively on a particular demographic group during their analysis of engagement metrics.

Given the user selects a specific demographic filter on the sentiment timeline, when the data is refreshed, then the visual representation should only show sentiment and engagement metrics relevant to the selected demographic group.

The marketing department has postponed a planned campaign due to negative sentiment surrounding the brand and needs to assess current trends before re-engaging with the audience.

Given that the user is reviewing historical sentiment data, when they analyze the timeline for the specified date range, then they should clearly see the shifts in sentiment and corresponding engagement metrics, which should include indicators for potential re-engagement points.

A user conducts a comparison of different marketing campaigns over a selected period to identify trends in audience engagement relative to sentiment shifts.

Given the user has selected multiple campaigns for comparison on the sentiment timeline, when the results are displayed, then the dashboard should present an overlay of sentiment changes and engagement metrics side by side for the selected campaigns, making comparisons easy.

A user regularly checks the Interactive Sentiment Timeline for alerts on significant sentiment changes following a major marketing event.

Given the user subscribes to sentiment alerts, when there is a significant shift in sentiment data following the marketing event, then the user should receive a notification through the platform alerting them to the change along with details to view on the timeline.

Enhanced Visualization Options

User Story: As a data analyst, I want to use customizable visualization tools for sentiment data so that I can present findings in the most impactful way to different stakeholders.
Description: Enhanced Visualization Options offer various data representation formats, including heat maps, pie charts, and trend lines, allowing users to customize how they view sentiment data. By providing these versatile visualization tools, users can interpret complex data more intuitively and glean actionable insights quickly. This feature aims to improve the user experience and facilitate deeper analysis of sentiment trends over time.
Acceptance Criteria: User selects the 'heat map' visualization option to analyze sentiment data for a specific marketing campaign over the last three months, and expects to view sentiment density by geographical location.

Given the user is on the Interactive Sentiment Timeline page, When they select 'heat map' as the visualization option for the last three months of data, Then the application displays a geographical heat map showing sentiment density.

A user switches from using pie charts to trend lines to observe sentiment trends over the past year.

Given the user has selected 'pie chart' as the visualization type, When they change the selection to 'trend line', Then the application should update the visualization to reflect sentiment trends over the past year accurately.

The user applies a filter to the sentiment data to focus specifically on positive sentiment related to a recent product launch.

Given the user applies a 'positive sentiment' filter on the visualization options, When they view the sentiment data, Then the visualization should only display data points related to positive sentiment for the selected product launch.

A user utilizes multiple visualization formats concurrently to compare how different visual representations highlight sentiment data variations.

Given the user has selected three visualization formats (heat map, pie chart, trend line), When they view the data, Then the application should provide the user with a side-by-side comparison of all three visualization formats.

The user saves their customized visualization settings for future use in analyzing sentiment data.

Given the user has customized the visualization options, When they click the 'save settings' button, Then the application stores the user's customization and confirms the settings are saved successfully.

A user reviews the legend provided with each visualization format to understand the sentiment scoring system employed in the application.

Given the user has selected a visualization, When they click on the 'legend' icon, Then the application displays a clear and informative legend that explains the sentiment scoring system and color coding used in the selected visualization.

Visual Trend Alerts

Visual Trend Alerts offer real-time graphical notifications of significant changes in sentiment data, highlighting emerging trends or potential crises. This feature ensures that users stay informed of critical shifts in public perception as they happen, enabling them to react promptly and effectively.

Requirements

Real-Time Data Processing

User Story: As a market analyst, I want to receive real-time notifications about significant changes in sentiment data so that I can respond quickly to emerging trends and manage potential crises effectively.
Description: This requirement ensures that the Visual Trend Alerts feature can process sentiment data from various sources in real-time. It involves implementing data fetching algorithms that can pull in data continuously or at set intervals, utilizing advanced AI models that are capable of analyzing this data on-the-fly. The benefit of this requirement is that it allows users to receive immediate alerts on significant sentiment changes, enhancing their ability to respond quickly to emerging trends or crises. Seamless integration with existing data sources and maintaining system performance while processing large volumes of data are crucial aspects of this requirement.
Acceptance Criteria: Real-time data fetching and processing for sentiment changes during a peak event like a major product launch or a social media campaign.

Given that the Visual Trend Alerts feature is active, when sentiment data is fetched during a peak event, then alerts should be generated within 5 seconds of data detection for any significant sentiment shifts.

Continuous integration of sentiment data from multiple social media platforms to provide comprehensive insights.

Given that multiple data sources are configured, when real-time data is processed, then at least 95% of sentiment changes across all integrated platforms should be accurately reflected in the alerts within 3 seconds of occurrence.

Alert system functionality during a crisis situation, such as a PR crisis or negative feedback surge.

Given that the Visual Trend Alerts feature is monitoring sentiment data, when a predefined threshold for negative sentiment is surpassed, then an alert must be generated and sent to relevant users within 2 seconds.

User experience during the initial setup of the Visual Trend Alerts for real-time monitoring.

Given a new user is setting up Visual Trend Alerts, when they complete the configuration in the dashboard, then they should receive a confirmation notification and a summary of their chosen alert criteria within 1 minute.

Performance of the Visual Trend Alerts system under high data volume scenarios, such as during a viral social media trend.

Given that high volumes of sentiment data are being processed, when analyzed, then the system must maintain a processing latency of less than 1 second per 5000 data points.

User interaction with the graphical notifications generated by the Visual Trend Alerts feature.

Given that an alert notification appears on the user's dashboard, when clicked, then it should redirect the user to the detailed sentiment analysis page relevant to that alert within 1 second.

System integration testing with external APIs for real-time data retrieval.

Given that the system is connected to external data APIs, when a request for sentiment data is made, then the average response time from the APIs should be less than 500 milliseconds for 95% of requests.

Custom Alert Settings

User Story: As a marketing manager, I want to customize my alert settings so that I receive notifications only when significant sentiment changes occur according to my defined criteria, ensuring I stay focused on what's important.
Description: The Custom Alert Settings requirement allows users to set their parameters for the alerts they receive from the Visual Trend Alerts feature. Users can define specific thresholds for sentiment changes (e.g., a 20% increase in negative sentiment) and customize the channels through which they receive notifications (e.g., email, SMS, app notifications). This capability empowers users to tailor their alert system according to their specific needs and preferences. Proper implementation will enhance user engagement and satisfaction by providing a more personalized experience.
Acceptance Criteria: User sets a custom alert for sentiment changes in brand mentions on social media platforms.

Given the user is in the Custom Alert Settings section, when they set a threshold for a 20% increase in negative sentiment, then the system should save the alert setting successfully and notify the user of the change.

User chooses to receive sentiment change alerts through SMS notifications.

Given the user selects SMS as a notification channel, when they save their custom alert settings, then they should receive a confirmation message and be able to receive SMS notifications for the specified sentiment changes.

User adjusts the threshold for receiving alerts after initially setting a different threshold.

Given the user has previously set a 15% threshold for sentiment alerts, when they change it to 25% and save the settings, then the system reflects the new threshold and updates the alert conditions accordingly.

User accesses the alert history to view past notifications and settings.

Given the user is on the Visual Trend Alerts dashboard, when they navigate to the alert history section, then they should see a chronological list of past alerts with relevant details such as sentiment change percentage and time of notification.

User sets a custom alert limit for receiving multiple notifications for the same sentiment change within a specific timeframe.

Given the user specifies a limit of 3 notifications within a 24-hour period for the same sentiment change, when the system detects multiple alerts exceeding this limit, then it should suppress additional notifications and log this action.

User utilizes the app to customize alert settings while on their mobile device.

Given the user is logged into the SentiScan app on their mobile device, when they navigate to the custom alert settings and make changes, then the system should save these changes and apply them across all user devices immediately.

Dashboard Integration

User Story: As a user of SentiScan, I want the Visual Trend Alerts to be easily accessible on my dashboard so that I can monitor live sentiment trends and analyze past data without navigating away from my main interface.
Description: This requirement focuses on integrating the Visual Trend Alerts feature seamlessly into the SentiScan dashboard. The alerts should be displayed prominently and organized by categories such as 'Emerging Trends' and 'Potential Crises'. Additionally, users should have the option to access historical data to analyze past trends and responses. This integration enhances usability by providing contextual information alongside alerts and allows users to track their responses over time, enabling data-driven decision-making.
Acceptance Criteria: Dashboard displays Visual Trend Alerts in a clear and visually engaging manner, organized into categorized sections for users to quickly identify emerging trends and potential crises.

Given the user is on the SentiScan dashboard, when visual trend alerts are present, then the alerts should be displayed prominently in categorized sections such as 'Emerging Trends' and 'Potential Crises' with clear labeling and distinct visual indicators.

Users can access historical data related to past visual trends directly from the dashboard, allowing them to analyze previous responses to sentiment shifts.

Given the user selects a visual trend alert, when they request historical data for that alert, then the system should provide access to relevant data analytics from the past with filters for date ranges and trend categories.

The system sends real-time notifications to users about significant changes in sentiment data that are directly integrated into the dashboard for immediate visibility.

Given the user is logged into SentiScan, when there is a significant sentiment shift, then a real-time notification should appear on the dashboard, allowing the user to react promptly to the developed trend or crisis.

Users can customize the alerts they wish to receive and how they would like them displayed on their dashboard for personalized insights.

Given the user accesses their alert preferences, when they customize their settings, then the system should allow them to select specific trends and adjust display options for alerts to be presented according to their preferences.

The dashboard is intuitive and provides tooltips or guidance on how to interpret the data represented in the visual trend alerts.

Given a user hovers over a visual trend alert, when tooltips are available, then relevant information and guidance should be displayed, helping users understand the significance of the presented data.

Users can easily share visual trend alert insights with team members from within the dashboard, enhancing collaboration and information dissemination.

Given the user wants to share a visual trend alert, when they select the share option, then the system should allow them to send the alert via email or internal messaging with a customizable message.

Mobile Accessibility

User Story: As a busy professional, I want to access Visual Trend Alerts on my mobile device so that I can stay informed about sentiment changes while I'm out of the office.
Description: The Mobile Accessibility requirement ensures that Visual Trend Alerts are accessible on mobile devices, allowing users to receive notifications and view trends while on the go. This involves creating a responsive design and optimizing the app for mobile platforms. Implementing this requirement enables users to stay informed even when they are away from their desktops, thus supporting timely decision-making and enhancing user engagement.
Acceptance Criteria: User receives a Visual Trend Alert notification on their mobile device while attending a marketing conference and needs to quickly assess the sentiment shift about a newly launched product.

Given the user has the SentiScan mobile app installed and has opted in for notifications, when a significant sentiment change occurs, then the user should receive a push notification on their mobile device within 2 minutes of the event.

A user is traveling and wants to access the Visual Trend Alerts through the mobile app to check on the latest trends regarding a brand they monitor.

Given the user is logged into the SentiScan mobile app, when the user navigates to the Visual Trend Alerts section, then the app must display the latest trend data and graphical representations without any layout issues on mobile screens.

While observing a major public relations event, the user wants to set up alerts for specific keywords related to the event via their mobile device.

Given the user is on the Visual Trend Alerts page, when they enter specific keywords for which they want to receive notifications and click 'Set Alert', then the system should set up alerts for those keywords and confirm the setup through a pop-up notification.

A marketing analyst is reviewing the performance of the Visual Trend Alerts feature on their tablet during a meeting with stakeholders.

Given the analyst is using a tablet with the SentiScan mobile app open, when they switch between different visual trend graphs, then the app must maintain responsiveness and load each graph without delay or errors.

The user needs to unsubscribe from trend alerts while on the go without having to access their desktop application.

Given the user is viewing trend alerts on their mobile app, when they click on the 'Unsubscribe' option for a specific trend, then the app must immediately confirm the unsubscription and not send future notifications for that trend.

A user who is hard of hearing relies on visual indicators for sentiment changes in real-time during an important event.

Given the user is in the Visual Trend Alerts screen, when a significant sentiment change occurs, then there must be an audible alert coupled with a visual notification ensuring accessibility for users with hearing impairments.

Sentiment Analysis Visualization

User Story: As a user, I want to see visual representations of sentiment changes alongside the alerts so that I can quickly and easily understand the context and implications of the data.
Description: This requirement involves developing graphical representations of sentiment shifts that accompany the alerts generated by the Visual Trend Alerts feature. Implementing easy-to-understand charts and graphs for displaying sentiment changes will enhance the users' ability to quickly interpret data. This visualization component is crucial for users to grasp complex sentiment dynamics quickly and make informed decisions based on visual insights.
Acceptance Criteria: User receives a real-time visual alert regarding a significant shift in consumer sentiment about a specific product. They open the SentiScan dashboard to view the graphical representation of the sentiment data.

Given the user receives an alert, when they access the dashboard, then a chart displaying the sentiment trend over the last 30 days should be visible and accurately represent the data.

A user notices an unexpected decline in positive sentiment indicated by the Visual Trend Alerts. They need to understand the potential factors causing this change through effective visualization.

Given a sudden drop in positive sentiment, when the user examines the sentiment visualization, then the chart must highlight the drop point and provide context with relevant annotations or explanations.

Marketing analysts want to present the sentiment analysis findings to their team during a meeting, relying on the graphical representations to convey the sentiment shifts clearly.

Given the user prepares for a presentation, when they generate a sentiment visualization, then the charts must be easily exportable in common formats (e.g., PDF, PNG) without losing resolution and accuracy.

A user regularly monitors competitor sentiment and wishes to compare it with their product sentiment to identify market trends and opportunities.

Given the user is on the dashboard, when they choose the competitor comparison feature, then the visualization must enable side-by-side comparison of sentiments for at least three competitors over the past month.

The user needs to quickly identify and filter sentiment trends over different time periods to respond to emerging market shifts effectively.

Given the user is viewing the sentiment visualization, when they select a time filter (e.g., last 7 days, last month), then the chart must dynamically update to reflect the selected period without delays.

A user receives alerts regarding both positive and negative shifts in sentiment. They want to differentiate these trends visually to prioritize their response strategies accordingly.

Given the user receives mixed sentiment alerts, when they view the visualization, then positive and negative trends must be represented in distinct colors with clear legends for easy interpretation.

The user interacts with the sentiment visualization, intending to drill down into specific data points to understand the underlying reasons for sentiment changes.

Given the user clicks on a specific data point in the chart, when they select that point, then a detailed tooltip must appear, providing more context, including possible causes and related social media mentions.

User Feedback Mechanism

User Story: As a user, I want to provide feedback on the Visual Trend Alerts so that my insights can help improve the system and ensure it meets my needs effectively.
Description: The User Feedback Mechanism requirement establishes a method for users to provide feedback on the alert system, including suggestions for improvement, reporting issues, and rating alert relevance. This feedback loop is essential for ongoing refinement of the Visual Trend Alerts feature based on user experiences and needs. Implementing this will foster a user-centered approach to product development and enhance overall customer satisfaction by continuously improving feature performance and relevance.
Acceptance Criteria: User provides feedback on the relevance of a sentiment alert after receiving a notification during a marketing campaign.

Given the user has received a sentiment alert, when they click on the feedback option, then they should be able to submit a rating from 1 to 5 and leave a comment.

User reports an issue with a sentiment alert not being delivered in real-time during a critical event.

Given the user attempts to report an issue with an alert, when they fill out the issue report form and submit it, then a confirmation message should be displayed indicating successful submission.

User wants to suggest improvements to the alert system after using the feature for a month.

Given the user accesses the suggestions section of the feedback mechanism, when they enter their improvement suggestion and submit it, then their suggestion should be logged in the system for review.

User accesses the feedback dashboard to review previous feedback submitted on sentiment alerts.

Given the user navigates to the feedback dashboard, when the page loads, then it should display a list of all feedback previously submitted, categorized by date and type.

User evaluates the effectiveness of the alerts after a marketing campaign has concluded.

Given the user views the analytics associated with their recent feedback on alerts, when they access the report, then they should see metrics displaying the average rating and number of issues reported for each alert during that campaign.

User seeks to understand how their feedback has influenced changes to the alert system.

Given the user accesses the system update section, when they view recent updates, then they should see a log of changes made in response to user feedback within the last three months.

User submits feedback on the urgency of a sentiment alert received during a PR crisis.

Given the user receives a sentiment alert tagged as urgent, when they choose to provide feedback, then they should have the option to select 'Not Urgent,' 'Somewhat Urgent,' or 'Critical' as part of their feedback.

Collaboration Hub

Collaboration Hub fosters teamwork by allowing users to annotate and share insights directly within the Sentiment360 interface. Marketers can discuss specific trends with their teams, create action items, and track collaborative efforts in real-time, ultimately enhancing teamwork and decision-making efficiency.

Requirements

Real-time Annotation

User Story: As a marketing analyst, I want to annotate key trends in real-time so that I can immediately share my insights with my team and foster collaborative discussions around our findings.
Description: The Real-time Annotation requirement enables users to annotate insights directly within the Collaboration Hub of the SentiScan platform. This functionality allows team members to highlight specific consumer sentiments or trends for discussion and review. By integrating real-time updates, it ensures that insights can be annotated instantly, fostering immediate discussions and collaboration among users. This feature benefits teams by streamlining the decision-making process and ensuring that all members have immediate access to the most pertinent information during their discussions. The expected outcome of this requirement is a more agile collaboration process that enhances the overall efficiency of team projects and strategies.
Acceptance Criteria: User initiates a session in the Collaboration Hub and begins annotating trends they discovered from recent social media analysis during a team meeting.

Given the user is logged into the SentiScan Collaboration Hub, when they select an insight to annotate, then they must be able to enter comments that are saved in real-time without delay and visible to all team members.

A team member receives a notification about a new annotation on a shared insight they are tracking, and they want to view and respond to it.

Given a user has received a notification, when they open the Collaboration Hub, then they must see the new annotation highlighted alongside the original insight, and they must be able to add their own comments to that annotation within 5 seconds.

During a project discussion, multiple team members annotate the same insight to give feedback and insights on consumer sentiment.

Given multiple users are logged into the Collaboration Hub, when they annotate the same insight, then the system must display all annotations in real-time, ensuring that no comments are lost and that users can see a history of annotations made by themselves and others.

A team discusses insights from a campaign analyzed over the past month and adds action items based on real-time annotations.

Given an insight has been annotated by a user during discussion, when a team leader creates an action item from that annotation, then the action item must be linked to the specific annotation and remain accessible for all team members for tracking.

A user wants to filter insights in the Collaboration Hub to focus solely on recent annotations made during a specific time frame.

Given the user selects a date range filter in the Collaboration Hub, when they apply the filter, then only the insights annotated during that time frame must be displayed, ensuring clear visibility of recent discussions.

Users want to ensure that a critical annotation made about a trending sentiment is saved and documented for future reference.

Given a user creates an annotation, when they close the Collaboration Hub, then the annotation must remain saved and retrievable even after the session has ended, ensuring data persistence.

A team has an ongoing discussion about consumer sentiment and wants to track who has made which annotations for accountability purposes.

Given multiple users are annotating insights, when the annotations are saved, then each annotation must include the username of the annotator and a timestamp, providing clear accountability in collaboration.

Task Creation and Tracking

User Story: As a team leader, I want to create and assign tasks based on annotated insights so that my team can effectively address the identified sentiments and track our progress on these action items.
Description: The Task Creation and Tracking requirement allows users to create specific action items related to annotated trends and insights. Once a user annotates an insight, they can assign tasks to team members, set deadlines, and track progress within the Collaboration Hub. This feature integrates seamlessly with the existing SentiScan dashboard, which provides users with the ability to monitor deadlines and update task statuses, ensuring accountability among team members. The benefit is improved project management and clearer accountability, ultimately leading to a more organized approach to sentiment analysis. The expected outcome is a more structured and effective workflow within teams.
Acceptance Criteria: Task Assignment to Team Members in Collaboration Hub

Given a user annotates a sentiment insight, when they select the option to create a task, then they must have the ability to assign the task to one or more team members and specify a deadline.

Task Status Updates within the Collaboration Hub

Given existing tasks assigned within the Collaboration Hub, when a user updates the status of a task, then all relevant team members must receive a notification of the change in status.

Tracking Task Progress in the SentiScan Dashboard

Given that tasks have been created and assigned, when a user views the SentiScan dashboard, then they should see a clear overview of all tasks, their statuses, and deadlines at a glance.

Creating Action Items from Annotated Insights

Given a user is in the Collaboration Hub, when they annotate an insight, then they must have the ability to create multiple action items with due dates and responsible team members directly linked to the annotation.

Collaborative Discussion on Assigned Tasks

Given an assigned task, when team members view that task, then they must be able to post comments and discussions directly within the task details for collaborative feedback.

Integration of Deadline Reminders for Tasks

Given an upcoming task deadline, when the deadline approaches, then all assigned team members should receive an automated reminder notification through the SentiScan interface.

Reporting on Team Task Completion Rates

Given the tasks assigned within the Collaboration Hub, when a user generates a report, then they must see statistics on completion rates, overdue tasks, and team member performance for accountability.

Discussion Threads

User Story: As a user, I want to have a discussion thread for each annotated insight so that I can collaborate with my team members and explore different perspectives before making strategic decisions.
Description: The Discussion Threads requirement introduces a dedicated space within the Collaboration Hub for users to engage in threaded discussions around specific insights or annotations. Each annotated insight can have associated discussions, enabling users to debate, expand on thoughts, and provide feedback on the sentiments analyzed. This feature will include notifications for replies and updates, ensuring users remain engaged and informed. The benefit lies in consolidating conversations around specific trends, guiding the decision-making process, and ensuring all insights are thoroughly discussed. The expected outcome is a richer collaborative environment where all insights and opinions are captured and considered before decisions are made.
Acceptance Criteria: Users discussing a newly identified sentiment trend within the Discussion Threads in the Collaboration Hub.

Given a user is viewing a specific annotated insight, when they click on 'Start Discussion', then a new discussion thread should be created that includes the insight context and allows users to add comments.

A user wants to receive notifications about replies to a discussion they are participating in.

Given a user is a participant in a discussion thread, when a new reply is posted, then the user should receive a notification alerting them of the reply in real-time.

Team members are actively using the Discussion Threads to provide feedback on an insight related to campaign performance.

Given multiple users are commenting on a thread, when someone adds a comment, then all participants should see the comment reflected in the thread immediately without needing to refresh.

A user needs to track the action items generated from discussions in the Collaboration Hub.

Given a user marks a comment as an action item, when the action item is saved, then it should appear in a designated action items list viewable by all participants in the discussion.

A user wishes to navigate through previous discussions related to an annotated insight for further context.

Given a user is viewing an annotated insight, when they select the 'View Discussions' option, then all existing discussion threads related to that insight should be displayed chronologically.

Users want to engage in a discussion regarding sentiment shifts identified from real-time data analytics.

Given an annotated insight linked to a sentiment shift, when a user starts a discussion thread, then the thread should automatically include the annotated sentiment data and insights for reference.

User Roles and Permissions

User Story: As an administrator, I want to define user roles and permissions in the Collaboration Hub so that I can control access to sensitive insights while still allowing teams to collaborate effectively.
Description: The User Roles and Permissions requirement aims to manage access and interaction within the Collaboration Hub by allowing administrators to define user roles and set permissions. This feature ensures that sensitive information is protected while allowing for collaborative efforts among authorized team members. Users with edit permissions can annotate, discuss, and create tasks, while those with only view permissions can access insights without altering them. The importance of this requirement lies in maintaining data integrity and security while promoting collaborative efforts. The expected outcome is a secure and controlled environment conducive to sharing insights without risking unauthorized changes or data leaks.
Acceptance Criteria: User with edit permissions successfully annotates an insight within the Collaboration Hub.

Given a user with edit permissions, when they annotate an insight, then the annotation should be visible to all users with access to the same insight.

User with view permissions attempts to annotate an insight in the Collaboration Hub.

Given a user with view permissions, when they attempt to annotate an insight, then they should receive a notification indicating they do not have the required permissions.

Administrator sets up a new user role with specific permissions in the Collaboration Hub.

Given an administrator, when they create a new user role with defined permissions, then the role should be saved and reflect the correct permissions when viewed later.

Collaborative team members view insights in real-time within the Collaboration Hub.

Given multiple users are accessing the same insight in the Collaboration Hub simultaneously, when one user makes a change, then all other users should see the update within 3 seconds.

User roles are displayed correctly in the user management interface of the Collaboration Hub.

Given an administrator accesses the user management interface, when they view user roles, then all users and their corresponding roles and permissions should be listed accurately.

Sensitive insights are restricted based on user roles in the Collaboration Hub.

Given a user with restricted access attempts to view a sensitive insight, then they should receive a 'permission denied' message and not be able to see the insight.

Integration with AI Suggestions

User Story: As a user, I want AI to suggest relevant insights for discussion in the Collaboration Hub so that I can ensure my team is considering the most impactful trends in our strategy sessions.
Description: The Integration with AI Suggestions requirement enables the Collaboration Hub to leverage AI to provide users with suggestions for insights or trends to discuss based on real-time sentiment analysis. This feature can highlight trending insights or suggest connections between different sentiments that users may not otherwise consider, enhancing collaborative efforts. The AI suggestions will appear within the user interface for easy visibility and access. The benefit is that it proactively guides conversations and ensures that teams are considering multiple angles of a trend, ultimately leading to more well-rounded decision-making. The expected outcome is a collaboration environment enriched with AI-driven insights that optimize team discussions and analyses.
Acceptance Criteria: As a marketing team member collaborating on a sentiment analysis project, I want to see AI-generated suggestions based on real-time sentiment data in the Collaboration Hub, so that I can enhance our discussions with relevant insights and trends.

Given that a user is logged into the Collaboration Hub and is viewing sentiment analysis data, when the user accesses the AI Suggestions feature, then the interface should display at least three AI-generated suggestions that are relevant to the current sentiment trends.

As a team leader, I want to receive notifications within the Collaboration Hub when new AI-driven insights are generated, so that I can quickly address them in team discussions and decisions.

Given that the user has opted into notifications and is on the Collaboration Hub, when a new AI suggestion is generated, then the user should receive a real-time notification highlighting the key insights.

As a project manager, I want to track the visibility and usage of AI suggestions by team members, to analyze the effectiveness of AI in facilitating team collaboration and decision-making.

Given that AI suggestions have been provided within the Collaboration Hub, when the project manager reviews the usage analytics, then the report should show the frequency and instances of AI suggestion utilization by each team member.

As a user of the Collaboration Hub, I want to be able to filter AI suggestions by categories such as 'trending topics' and 'related sentiments' so that I can focus on the most relevant insights for my current discussion.

Given that AI suggestions are displayed in the Collaboration Hub, when the user applies filters for 'trending topics' or 'related sentiments', then the displayed suggestions should update to reflect only those that meet the selected criteria.

As a marketer in the Collaboration Hub, I want to be able to click on an AI suggestion to view detailed insights and underlying data, so that I can understand the context and make informed contributions to discussions.

Given that the user is viewing AI suggestions, when the user clicks on a specific suggestion, then the system should display a detailed view of the insights and underlying data supporting that suggestion.

As a team member, I want AI suggestions to update in real-time as sentiment analysis data changes, so that our discussions are based on the most current information.

Given that sentiment analysis data is being processed, when there is a change in sentiment analysis results, then the AI suggestions should refresh to reflect the new insights within 5 seconds.

Notification Alerts for Updates

User Story: As a user, I want to receive notifications about updates in the Collaboration Hub so that I can stay informed about new trends and ongoing discussions without missing important information.
Description: The Notification Alerts for Updates requirement ensures that users receive alerts whenever there are new annotations, tasks, or comments made in the Collaboration Hub. Notifications will be sent through email or in-app alerts, allowing users to stay informed and engaged without constantly checking the platform. This feature will enhance participation by ensuring no significant updates are overlooked. The importance of this requirement lies in its ability to promote proactive engagement among team members, ensuring that actions are taken promptly as discussions and insights evolve. The expected outcome is a well-informed team that remains engaged in collaboration efforts.
Acceptance Criteria: User receives real-time notifications for new annotations made in the Collaboration Hub.

Given a user is logged into SentiScan, When a new annotation is added to the Collaboration Hub, Then the user should receive an in-app notification and an email alert with details of the annotation.

User receives notifications for new tasks assigned within the Collaboration Hub.

Given a user is logged into SentiScan, When a new task is assigned to the user in the Collaboration Hub, Then the user should receive an in-app notification and an email alert detailing the task.

User receives updates when comments are added to existing annotations.

Given a user is logged into SentiScan, When a comment is added to an existing annotation in the Collaboration Hub, Then the user should receive an in-app notification and email alert about the new comment.

Multiple users receive notifications for shared comments in the Collaboration Hub.

Given multiple users are collaborating on an annotation, When one user adds a comment, Then all collaborating users should receive in-app notifications and email alerts about the new comment.

User can customize notification settings for alerts in the Collaboration Hub.

Given a user is in the notification settings section, When the user selects the types of notifications they want to receive, Then the system saves the preferences and applies them to future alerts as expected.

Notification alerts contain actionable insights and links to relevant annotations or tasks.

Given a user receives a notification, When they click on the notification, Then they should be directed to the corresponding annotation or task in the Collaboration Hub for quick access.

Competitor Insights Dashboard

The Competitor Insights Dashboard provides a centralized visualization of competitor sentiment metrics and brand activities. Users can easily compare their brand’s performance against key competitors, track sentiment fluctuations over time, and highlight critical engagements. This feature empowers users with clear, actionable insights, enhancing their ability to craft responsive strategies and stay ahead in the competitive landscape.

Requirements

Sentiment Comparison Metrics

User Story: As a market analyst, I want to compare my brand's sentiment metrics with my competitors so that I can identify areas of improvement and adjust my marketing strategy accordingly.
Description: The Sentiment Comparison Metrics requirement encompasses the design and implementation of a feature that allows users to compare sentiment metrics of their brand against key competitors. This feature will utilize advanced AI algorithms to gather and analyze sentiment data from multiple sources, displaying this information in an easily understandable format within the dashboard. The focus will be on creating interactive graphs and charts that highlight differences in sentiment scores over time, enabling users to make data-driven decisions. This functionality is essential for marketers to gauge their brand's performance relative to competitors and identify strategic opportunities for improvement in engagement and messaging.
Acceptance Criteria: Sentiment Metrics Comparison for User Brand and Competitor

Given a user has accessed the Competitor Insights Dashboard, when the user inputs their brand and selects up to three competitors, then the dashboard should display a comparative line graph of sentiment scores over the past six months for all selected brands.

Real-Time Sentiment Analysis Updates

Given the user is viewing the Competitor Insights Dashboard, when there is a new sentiment score update available from social media data, then the dashboard should refresh automatically to reflect the latest scores without requiring the user to refresh the page.

Highlighting Key Engagements for Competitors

Given a user is analyzing competitor sentiment metrics, when the user clicks on any data point in the sentiment graph, then a pop-up should display detailed information about the engagement associated with that score, including date and sentiment context.

Interactive Filtering Options for Data Analysis

Given the user is on the Competitor Insights Dashboard, when the user selects specific time frames or sentiment thresholds, then the dashboard should filter and update the displayed graphs accordingly, allowing users to focus on particular trends.

User-Friendly Sentiment Score Explanation

Given the user accesses the Competitor Insights Dashboard, when they hover over sentiment scores displayed on the graphs, then a tooltip should provide a brief explanation of how the sentiment score is calculated, including source data.

Sentiment Comparison Reporting

Given a user has concluded their analysis on the Competitor Insights Dashboard, when the user initiates a report generation, then the system should create a summary report that includes visual graphs and key insights that can be exported as a PDF.

Real-time Sentiment Analysis Alerts

User Story: As a marketing manager, I want to receive real-time alerts on significant sentiment changes so that I can quickly address potential issues or capitalize on emerging trends in my marketing efforts.
Description: The Real-time Sentiment Analysis Alerts requirement involves the development of a notification system that alerts users to significant shifts in sentiment metrics for both their brand and their competitors. This functionality will employ machine learning algorithms to monitor sentiment data continuously and trigger alerts based on user-defined thresholds. The goal is to inform users of these shifts in a timely manner, allowing them to respond promptly to market changes. Integrated within the Competitor Insights Dashboard, these alerts will provide marketers with the critical information they need to remain agile in their strategies and campaigns.
Acceptance Criteria: User receives an alert on significant sentiment shift for their brand after a major social media event.

Given the user has set a threshold for sentiment change of 15%, when a sentiment shift greater than 15% occurs, then the user receives an immediate notification via the dashboard and email.

User compares competitor sentiment metrics against their brand using the dashboard.

Given the user selects a competitor from the dropdown menu, when the dashboard is refreshed, then the sentiment metrics of the selected competitor are displayed alongside their brand's metrics in a comparable format.

User modifies sentiment threshold settings for real-time alerts.

Given the user navigates to the settings page and adjusts the threshold for alerts, when the user saves these settings, then the new threshold is applied for future sentiment monitoring and alerts reflect this change.

User receives a notification for a competitor's significant sentiment fluctuation.

Given the user has added competitors for monitoring, when a competitor experiences a sentiment shift that exceeds the user-defined threshold, then the user receives an alert via the dashboard.

User reviews historical sentiment shifts for both their brand and competitors.

Given the user selects a time range for sentiment analysis, when the user clicks 'View History', then a visual graph displays sentiment fluctuations over the selected time period for both their brand and chosen competitors.

User sets up multiple thresholds for different competitors.

Given the user is configuring settings, when the user creates custom sentiment alert thresholds for multiple competitors, then each threshold is saved and individual alerts are triggered based on those specific thresholds.

Competitive Benchmarking Reports

User Story: As a brand manager, I want to generate benchmarking reports that compare my brand’s performance with my competitors so that I can identify trends and make informed strategic decisions based on comprehensive data analysis.
Description: The Competitive Benchmarking Reports requirement focuses on generating automated reports that summarize and compare sentiment metrics, engagement levels, and key brand activities of competitors. Users will be able to select specific timeframes and competitors to generate detailed reports highlighting sentiment trends, major events affecting competitor performance, and key takeaways. This feature will provide essential insights that marketers can utilize for strategic planning and positioning. The reports will be designed to be exportable in various formats (PDF, Excel) for ease of sharing and presentation.
Acceptance Criteria: User generates a Competitive Benchmarking Report for a selected competitor over the past month in PDF format.

Given that the user selects a competitor and a timeframe of the past month, when the user clicks 'Generate Report', then a PDF report should be created with the correct sentiment metrics and key activities for the selected competitor and timeframe.

User compares multiple competitors using the Competitive Benchmarking Reports feature.

Given that the user selects multiple competitors within the report generation options, when the user generates the report, then the report should display sentiment metrics and engagement levels side by side for all selected competitors.

User exports the Competitive Benchmarking Report in Excel format.

Given that the user has generated a Competitive Benchmarking Report, when the user selects the option to export in Excel format, then the system should provide a downloadable Excel file that includes all metrics formatted correctly.

User views sentiment trends over a specified timeframe in the Competitive Benchmarking Report.

Given that the user selects a specific date range, when the report is generated, then the visual representation of sentiment trends for the chosen competitors should accurately reflect the sentiment changes during that timeframe.

User accesses the Competitive Benchmarking Report after generating it and requests a summary of key takeaways.

Given that the user has generated a report, when the user clicks on the 'Summary' section, then the report should display a concise summary highlighting the main findings and insights derived from the sentiment analysis.

User reviews major events affecting competitor sentiment in the report.

Given that the user generates a report for a competitor, when they view the report, then all major events identified during the selected timeframe should be clearly highlighted and referenced in relation to the sentiment fluctuations.

User-Friendly Dashboard Customization

User Story: As a user of SentiScan, I want to customize my dashboard layout and metrics displayed to better fit my analytical process and enhance my user experience.
Description: The User-Friendly Dashboard Customization requirement ensures that users can tailor their Competitor Insights Dashboard experience according to their specific needs and preferences. Users will have the ability to add, remove, and rearrange widgets that display various competitor metrics and sentiment data, as well as select color schemes and layouts that suit their analytical style. This enhancement aims to improve user satisfaction and engagement by providing greater control over the data presentation, facilitating more effective insights extraction and decision-making.
Acceptance Criteria: User Tailoring the Dashboard Layout for Improved Data Analysis

Given a logged-in user on the Competitor Insights Dashboard, when the user adds a widget for competitor sentiment trends and rearranges the layout, then the dashboard should reflect the updated layout with the newly added widget displayed prominently.

User Personalization of Widget Color Schemes

Given a user has access to the dashboard, when the user selects a different color scheme for the sentiment metric widget, then the widget should update to reflect the selected color scheme immediately without requiring a page refresh.

User Removal of Unwanted Widgets for a Streamlined View

Given the user is viewing their Competitor Insights Dashboard, when the user removes a widget for a specific competitor, then the dashboard should refresh and no longer display the removed widget while maintaining the integrity of other widgets.

User Saving Customized Dashboard Settings

Given a user has made changes to their dashboard layout and settings, when the user clicks the 'Save' button, then the customizations should be saved to the user's profile for future access.

User Reverting to Default Dashboard Settings

Given the user has made several customizations to the dashboard, when the user selects the 'Revert to Default' option, then all changes should be discarded and the dashboard should return to its original state.

User Accessing Help or Guidance for Customization Features

Given the user is on the Competitor Insights Dashboard, when the user clicks on the 'Help' icon, then a tooltip or modal should appear providing instructions on how to customize the dashboard layout and features.

Historical Data Trend Analysis

User Story: As a market researcher, I want to analyze historical sentiment trends over different timeframes so that I can identify patterns and how they relate to marketing campaigns and competitor actions.
Description: The Historical Data Trend Analysis requirement introduces a feature that allows users to analyze and visualize historical sentiment data and trends over specified periods. This would include making comparisons with current data to identify shifts in consumer sentiment over time, giving users deeper insights into long-term brand performance relative to competitors. Graphical representations, such as line graphs and heat maps, will provide clear visuals that help in strategic forecasting and planning. This feature is crucial for understanding how events or campaigns have impacted sentiment change over time, supporting more informed strategic decisions.
Acceptance Criteria: Comparing historical sentiment data against a specific time period during a marketing campaign to analyze effectiveness.

Given the user selects a marketing campaign date range, When they view the Historical Data Trend Analysis, Then the dashboard should display sentiment trends for that time frame compared to at least the previous quarter.

Identifying significant shifts in sentiment before and after a product launch to assess impact.

Given a product launch date is entered, When the user analyzes the sentiment data, Then the system should highlight the sentiment changes leading up to and following the product launch in graphical format.

Visualizing competitor sentiment trends over the last year to determine relative performance.

Given the user selects 'Competitor Analysis' on the dashboard, When they view the historical sentiments, Then the dashboard should show a line graph with sentiment scores for each competitor over the past year, allowing for easy comparison.

Displaying heat maps of sentiment data to uncover patterns in consumer attitudes over time.

Given a selected date range, When the user accesses the heat map feature, Then the heat map should render with appropriate color coding, showcasing sentiment fluctuations for the chosen time period.

Providing export capabilities for exported sentiment data analysis results for external reporting.

Given the user has reviewed sentiment trends, When they select 'Export', Then the system should generate a CSV or PDF file containing the analyzed sentiment data, including graphical representations.

Including user feedback on the dashboard about the usability and functionality of the Historical Data Trend Analysis feature.

Given the user completes the trend analysis, When they provide feedback through a designated portal, Then their feedback should be collected and logged for future usability assessments.

Real-Time Mention Tracker

Real-Time Mention Tracker continuously monitors social media and online platforms for mentions of competitor brands and products. By providing instantaneous alerts on brand discussions, users can react quickly to competitor moves or public sentiment shifts. This proactive feature enhances user awareness and enables swift strategic responses to emerging trends, helping users safeguard their market position.

Requirements

Competitor Sentiment Analysis

User Story: As a market analyst, I want to analyze the sentiment around competitor brands so that I can adjust our marketing strategies based on consumer perceptions and behaviors.
Description: The Competitor Sentiment Analysis requirement enables the software to perform in-depth sentiment analysis of mentions related to competitor brands and products. This functionality integrates advanced natural language processing algorithms to assess positive, negative, and neutral sentiments expressed in user-generated content on social media and online forums. By capturing various sentiment trends over time, users can gain valuable insights into competitor performance and consumer perception, allowing them to tailor their marketing strategies accordingly. The expected benefit of this requirement is the enhancement of competitive intelligence, giving marketers the ability to proactively adjust their tactics based on real-time consumer sentiment towards competitors.
Acceptance Criteria: Real-time Tracking of Competitor Mentions

Given a user has set up alerts for competitor brands, When a mention of a competitor occurs on social media, Then the system sends an instantaneous alert to the user via their chosen notification method (email, SMS, in-app notification).

Sentiment Analysis Accuracy

Given a set of user-generated content mentioning a competitor, When the sentiment analysis is performed, Then the analysis correctly classifies the sentiment as positive, negative, or neutral with at least 85% accuracy compared to a human review.

Historical Sentiment Trend Visualization

Given that sentiment analysis has been conducted over a period, When a user accesses the dashboard, Then they can view a visual representation of sentiment trends over time for specified competitor brands.

Integration with Competitive Benchmarking Tools

Given the user has access to competitive benchmarking tools, When viewing sentiment analysis data, Then the user can seamlessly integrate this data into existing benchmarking reports without any discrepancies.

Alert Customization Options

Given that alerts for competitor mentions are being configured, When a user accesses the alert settings, Then they can customize alert frequency, channels, and mention thresholds based on their preferences.

Real-Time Sentiment Shift Reporting

Given a sudden spike in negative sentiment for a competitor, When the analysis detects this change, Then the system generates and sends a report to the user within 10 minutes of detection.

User Feedback Loop for Sentiment Accuracy Improvement

Given that users interact with the sentiment analysis results, When they provide feedback on sentiment accuracy, Then the system uses this feedback to refine the sentiment analysis algorithms for improved future performance.

Custom Alert System

User Story: As a marketing manager, I want to customize alert settings for competitor mentions so that I can respond quickly to important brand discussions and sentiment shifts that affect our market position.
Description: The Custom Alert System requirement allows users to set personalized alerts for specific competitors or keywords within the Real-Time Mention Tracker. This feature enhances user experience by enabling targeted notifications related to competitor activities, sentiment changes, and product discussions. Users can customize the frequency, channels (e.g., email, SMS, app notifications), and thresholds for alerts, ensuring they receive timely and relevant information. This level of customization is crucial for timely decision-making, providing users with the ability to respond rapidly to emerging trends, thus safeguarding their competitive edge in a fast-paced environment.
Acceptance Criteria: User sets up a new alert for a specific competitor brand to monitor discussion trends on social media.

Given the user has access to the Custom Alert System, when they input the competitor brand, select the frequency, and choose the notification channel, then the alert should be successfully created and stored in the system.

User modifies an existing alert to change the frequency and notification method for a competitor brand.

Given the user has an existing alert, when they select the alert and modify the frequency and notification method, then the updates should be saved and reflected in the alert settings.

User receives an alert notification for a significant sentiment change regarding a monitored competitor brand.

Given that the user has set an alert for significant sentiment changes, when such a change occurs, then the user should receive an immediate notification through their selected channel (email, SMS, app notification).

User deletes an existing alert for a competitor to stop receiving notifications.

Given the user wants to stop receiving notifications for a competitor, when they select the delete option for the specific alert, then the alert should be successfully removed from the system.

User checks the history of alerts received for a specific competitor brand.

Given the user has previously set alerts for a competitor, when they access the alert history section, then they should be able to view all past alerts, including timestamps and details of the notifications received.

User attempts to set an alert for a keyword that exceeds the allowed character limit.

Given the user is in the process of setting a new alert, when they input a keyword that exceeds the character limit, then an error message should display indicating that the input is invalid due to length restrictions.

Historical Data Insights

User Story: As a researcher, I want to access historical data on competitor sentiment so that I can identify trends and inform future marketing decisions based on past performance.
Description: The Historical Data Insights requirement focuses on developing functionality for users to access and analyze historical sentiment data and mention trends of competitors. This feature allows users to visualize past brand discussions and sentiment shifts over specified periods, enabling them to identify patterns and leverage data-driven insights for strategic planning. Implementing this requirement will facilitate deeper competitive analysis and assist users in understanding how public opinion fluctuates over time, informing their long-term marketing strategies and enabling proactive adjustments based on historical performance metrics.
Acceptance Criteria: User accesses the Historical Data Insights feature to analyze sentiment trends for a selected competitor over the past year.

Given that the user has selected a competitor and specified a time range of one year, When the user clicks on the 'Analyze Data' button, Then the system displays a graph representing sentiment trends along with a table of relevant metrics (e.g., number of mentions, average sentiment score).

A user selects multiple competitors to compare their historical sentiment data simultaneously.

Given that the user has selected multiple competitors, When the user clicks on the 'Compare Sentiments' button, Then the system generates a comparison chart that displays sentiment trends for all selected competitors side by side for the chosen time period.

User wants to export historical sentiment analysis data for offline reporting.

Given that the user has viewed the sentiment analysis results, When the user clicks on the 'Export' button, Then the system downloads a CSV file containing all displayed sentiment data and trends for the selected period.

Analyzing historical data insights over a customized time period for a in-depth study.

Given that the user specifies a custom date range, When the user clicks on the 'View Insights' button, Then the system retrieves and displays sentiment data for the selected competitors within the specified date range accurately.

A user receives a notification about significant changes in historical sentiment metrics of a selected competitor.

Given that the sentiment metrics for a selected competitor change significantly, When the change is detected, Then the system sends an alert notification to the user indicating the type of change and the new metrics.

The user filters historical sentiment data based on geographic regions to analyze localized trends.

Given that the user applies a geographic filter, When the user clicks on the 'Apply Filter' button, Then the system displays sentiment trends and metrics specific to the selected region only.

Trend Prediction Algorithms

User Story: As a data scientist, I want predictive analytics for brand mentions so that I can anticipate market trends and adapt our marketing strategy proactively.
Description: The Trend Prediction Algorithms requirement aims to enhance the Real-Time Mention Tracker by implementing machine learning algorithms that analyze current and historical mention data to predict future trends in consumer sentiment and brand discussions. This feature will equip users with foresight into potential market shifts, allowing for preemptive strategic planning and resource allocation. By accurately predicting sentiment trends, users can align their marketing efforts with anticipated market dynamics, ultimately fostering more effective and responsive marketing strategies. The integration of this predictive capability is vital in providing users with a competitive advantage.
Acceptance Criteria: User receives alerts for predicted trends based on real-time data analysis when monitoring competitor mentions.

Given a user is subscribed to real-time alerts, when a significant trend is detected based on mention analysis, then the user receives an email and/or app notification with details of the trend and predicted sentiment shift.

The system provides a dashboard with visualizations of predicted sentiment trends over time based on historical data.

Given a user views the trend prediction dashboard, when they select a competitor brand, then the dashboard displays a graph showing predicted sentiment trends for the next 30 days with confidence intervals.

The algorithm analyzes a defined time period of historical mention data to generate predictions about future brand sentiment.

Given a user sets a time frame for analysis, when the algorithm completes its processing, then it returns a report summarizing the predicted sentiment trend along with accuracy metrics.

The integration of trend prediction algorithms does not affect the performance of the Real-Time Mention Tracker.

Given the trend prediction algorithms are implemented, when the system is operational, then the response time for retrieving mentions and alerts remains under 2 seconds for 95% of requests.

Users can customize the types of trends they want to receive alerts for, including specific sentiment thresholds.

Given a user accesses the alert settings, when they set a sentiment threshold for alerts, then they receive notifications only for trends that exceed that defined threshold.

The feature provides actionable recommendations based on predicted trends.

Given a user reviews a predicted trend report, when the trend shows a positive sentiment shift, then the system suggests marketing strategies to capitalize on the trend and increase engagement.

Users can view historical accuracy of past trend predictions to assess the reliability of the algorithm.

Given a user accesses the historical predictions log, when they select a past prediction period, then the system displays the actual sentiment outcomes compared to predicted outcomes along with a success rate percentage.

Dashboard Customization Options

User Story: As a user, I want to customize my dashboard layout so that I can efficiently access the metrics and insights that are most important to my role.
Description: The Dashboard Customization Options requirement provides users with the ability to personalize their dashboard views to better align with their individual preferences and monitoring priorities. Users will have the option to rearrange widgets, select favorite metrics, and choose the presentation format for visual data, ensuring that relevant information is prominently displayed. This level of customization is expected to enhance user engagement and satisfaction by allowing users to tailor their analytical environment to their specific needs, ultimately increasing the usability and effectiveness of SentiScan.
Acceptance Criteria: User Customizes Dashboard Layout and Widget Arrangement

Given a user is logged into the SentiScan platform, when they access the dashboard customization options, then they can rearrange the display order of widgets, and their preferences are saved and reflected the next time they log in.

User Selects Favorite Metrics for Quick Access

Given a user is logged into the SentiScan platform, when they select their favorite metrics from the available options, then those metrics are displayed prominently on the dashboard, and the user can remove them at any time.

User Chooses Presentation Format for Visual Data

Given a user is logged into the SentiScan platform, when they customize the presentation format of the visual data (e.g., chart, graph, table), then the selected format is applied instantly, and the user sees the data represented in their chosen format immediately.

User Saves Dashboard Customization Preferences

Given a user is logged into the SentiScan platform, when they finalize their dashboard customizations and click 'Save', then their preferences are stored without errors, and a confirmation message is displayed to the user.

User Reverts to Default Dashboard Settings

Given a user is logged into the SentiScan platform, when they choose to revert their dashboard to the default settings, then all previous customizations are erased, and the dashboard appears as it did upon the initial login.

User Receives Confirmation of Successful Customization

Given a user has made changes to the dashboard customization options, when they finalize their changes, then a success notification is displayed confirming that the customization has been successfully applied.

User Views and Interacts with Customized Dashboard in Different Devices

Given a user has customized their dashboard in SentiScan, when they access the platform from multiple devices (desktop, tablet, mobile), then the dashboard layout and settings should be consistent across all devices.

Competitor Sentiment Trends

Competitor Sentiment Trends analyzes historical sentiment data related to competitors, revealing patterns and shifts in consumer opinions over time. This feature simplifies identifying long-term trends that could impact user strategies and market positioning. By understanding how sentiment evolves around competitor brands, users can make informed decisions about their marketing approaches and adjust tactics accordingly.

Requirements

Historical Sentiment Data Analysis

User Story: As a marketing analyst, I want to analyze historical sentiment data about competitors so that I can identify trends that inform my business strategies and enhance competitive positioning.
Description: This requirement involves the implementation of a module that can extract, analyze, and visualize historical sentiment data related to competitors. It should accurately track and display variations in consumer sentiment over specified time periods, allowing users to pinpoint trends and shifts in public opinion. The module will integrate seamlessly with the existing SentiScan platform, providing intuitive dashboards that present this data in a user-friendly manner. By leveraging advanced data analytics techniques, the requirement aims to empower users to make data-driven decisions regarding their marketing strategies based on the demonstrated historical performance and perception of competing brands.
Acceptance Criteria: User Reviews Historical Sentiment Data for Competitors.

Given a user has accessed the Competitor Sentiment Trends module, when they select a competitor and choose a specific time period, then the system should display a graph of sentiment trends accurately reflecting data for that competitor over the selected duration.

User Filters Historical Sentiment Data by Specific Criteria.

Given a user is viewing historical sentiment data, when they apply filters such as date range, sentiment type (positive, negative, neutral), and competitor brand, then the displayed data should update to only reflect data that matches the selected filters.

User Downloads Historical Sentiment Data Reports.

Given a user has filtered and visualized historical sentiment data, when they choose to download the report, then the system should generate a downloadable file (CSV or PDF) containing the filtered data along with visualizations used in the dashboard.

User Searches for Competitors in Historical Sentiment Data.

Given a user is in the Competitor Sentiment Trends module, when they enter a competitor's name in the search bar, then the system should suggest and display relevant historical sentiment trends for that competitor without any errors.

User Views Integrated Dashboards with Historical Sentiment Data.

Given a user accesses the SentiScan platform, when they navigate to the dashboard displaying historical sentiment data, then all metrics and visualizations should accurately reflect the sentiment analysis for the selected competitors in real-time without latency or discrepancies.

User Receives Alerts for Significant Sentiment Changes.

Given that a user has set alerts for specific competitors, when a significant shift in sentiment (above a defined threshold) is detected, then the user should receive a notification alerting them of this change immediately.

Competitor Comparison Dashboard

User Story: As a brand manager, I want to access a competitor comparison dashboard so that I can quickly gauge how our sentiment trends measure up against those of our primary competitors.
Description: This requirement focuses on creating a comprehensive dashboard that allows users to compare sentiment trends between their brand and competitors. It will feature side-by-side visualizations of sentiment scores, trend lines, and key performance indicators (KPIs) for easy comparison. The dashboard will enhance user capability to interpret competitive landscapes quickly and engage in strategic decision-making. By providing real-time comparisons with visual insights, users can act promptly based on sentiment shifts relative to competitors, ensuring they can optimize their market strategies effectively.
Acceptance Criteria: User accesses the Competitor Comparison Dashboard for the first time to evaluate sentiment trends between their brand and competitors.

Given the user is logged in, when the dashboard loads, then it should display side-by-side visualizations of sentiment scores for the user's brand and selected competitors for the last 30 days.

User selects a competitor to analyze on the Competitor Comparison Dashboard to see detailed sentiment trends.

Given the user has selected a competitor, when viewing the dashboard, then it should show the trend line and key performance indicators (KPIs) for both the user's brand and the selected competitor over the last 6 months.

User wants to compare sentiment shifts between their brand and a competitor after a recent marketing campaign.

Given the user selects a specific date range, when they apply the filter, then the dashboard should update to show sentiment scores and trend lines reflecting the selected dates for both the user’s brand and competitor.

User needs to export sentiment data from the Competitor Comparison Dashboard for a presentation.

Given the user clicks on the export button, when the data is generated, then it should allow the user to download a CSV file containing sentiment scores, trend lines, and KPIs for the specified competitors and date range.

User receives an alert about a significant sentiment shift regarding a competitor brand.

Given the user has set up alerts for significant sentiment changes, when there is a change of more than 20% in sentiment score, then the user should receive a notification via email or in-app alert.

User wants to understand the historical context of sentiment trends for their brand compared to competitors.

Given the user is on the Competitor Comparison Dashboard, when they select a historical context option, then the dashboard should provide a detailed breakdown of sentiment scores and any major events impacting sentiment over the last year.

Sentiment Alerts System

User Story: As a market researcher, I want to receive alerts about significant changes in competitor sentiment so that I can react swiftly to emerging trends and adjust our strategies accordingly.
Description: This requirement entails the development of an alert system that notifies users whenever significant changes in competitor sentiment are detected. Users can customize their alert preferences according to specific competitors or threshold levels of sentiment change. The alerts will be delivered through multiple channels, including email and in-app notifications, ensuring users remain informed about critical sentiment shifts as they happen. This proactive approach empowers users to respond to changes quickly and effectively, thus enhancing their ability to maintain competitive advantage in rapidly changing market scenarios.
Acceptance Criteria: User customizes their alert preferences to monitor sentiment changes for two specific competitors and establishes a threshold for notifications.

Given the user has accessed the alert settings, when they select competitors and set a sentiment change threshold, then the selections should be saved and confirmatory messages displayed.

User receives notification via email when competitor sentiment changes exceed the user-defined threshold.

Given the user has set up alerts for specific competitors, when significant sentiment changes occur that exceed the threshold, then an email alert should be sent immediately to the user's registered email address.

User receives in-app notifications about real-time shifts in competitor sentiment while actively using the SentiScan dashboard.

Given the user is logged into the SentiScan platform, when there is a significant shift in sentiment for tracked competitors, then a pop-up notification should appear on the dashboard without any delay.

User checks the alert history to review past notifications about competitor sentiment changes.

Given the user accesses the alert history section, when they select a date range, then they should see a list of all notifications with details about the sentiment changes that triggered each alert.

System allows users to modify existing alert preferences for competitor sentiment changes.

Given the user is in the alert settings, when they change the competitors being tracked or the threshold levels, then these modifications should be updated in the system and confirmatory messages shown immediately.

User receives notification if no significant sentiment changes occur over a defined observation period.

Given the user has set an observation period for a competitor's sentiment, when the period elapses and no significant changes are detected, then the user should receive a 'no change' notification concerning the tracked competitor.

User can deactivate or deactivate alerts for specific competitors as needed.

Given the user is on the alert settings page, when they choose to deactivate notifications for a selected competitor, then the system should stop sending alerts for that competitor and confirm the change.

Competitive SWOT Analyzer

The Competitive SWOT Analyzer leverages sentiment analysis to evaluate the Strengths, Weaknesses, Opportunities, and Threats (SWOT) related to competitor brands. Users gain a nuanced understanding of the competitive landscape, enabling them to identify areas for differentiation and opportunity while mitigating potential risks. This structured analysis empowers brands to adopt targeted strategies that effectively counteract competitor advantages.

Requirements

Competitor Sentiment Integration

User Story: As a market analyst, I want to access sentiment data related to competitor brands so that I can perform a detailed SWOT analysis and adjust our marketing strategy accordingly.
Description: The Competitor Sentiment Integration requirement allows users to pull sentiment data specific to competitor brands from various social media and online platforms. This functionality will provide a robust database of insights that can be contextualized within the SWOT framework. By analyzing competitor sentiments, users can identify trends and perceptions that directly relate to their competitors' strengths and weaknesses, thus facilitating a comprehensive SWOT analysis. This feature will enable businesses to adapt their strategies based on real-time sentiment shifts, leading to more informed decision-making and competitive positioning.
Acceptance Criteria: As a market analyst, I want to access competitor sentiment data so that I can analyze how consumers perceive competitor brands in order to inform my SWOT analysis.

Given I am logged into SentiScan, when I access the Competitive SWOT Analyzer and select a competitor brand, then I should see sentiment data pulled from relevant social media and online platforms.

As a user of the Competitive SWOT Analyzer, I want to view sentiment trends over time for a specific competitor so that I can identify shifts in consumer perception that may affect my strategic decisions.

Given I have selected a competitor brand, when I request the sentiment data timeline, then I should see a graph displaying sentiment score trends over the past 6 months.

As a marketing manager, I need to receive alerts when there is a significant shift in sentiment for a competing brand so that I can quickly adapt my marketing strategies accordingly.

Given I have set up my alert preferences, when sentiment for a selected competitor changes by more than 20% within a week, then I should receive a notification via email and within the SentiScan dashboard.

As a user, I want to integrate competitor sentiment data into my overall SWOT analysis report so that I can provide a comprehensive overview to my stakeholders.

Given I have collected sentiment data for multiple competitors, when I initiate the SWOT analysis report generation, then the report should automatically include the relevant sentiment data alongside the analysis for each competitor.

As a product manager, I need to ensure accuracy in the sentiment analysis for competitor brands so that I can trust the findings for strategic decisions.

Given the sentiment data is pulled from sources, when I run a quality assurance check for the sentiment data, then at least 90% of the data accuracy should be validated against primary data sources.

As a brand strategist, I want to filter the sentiment data by specific demographics so that I can tailor my strategies to targeted consumer segments.

Given I have accessed the sentiment data for a competitor, when I apply demographic filters, then I should see a breakdown of sentiment scores that reflect the selected demographic groups.

As a business analyst, I want to compare sentiment data across multiple competitor brands simultaneously so that I can identify competitive advantages and weaknesses.

Given I have selected multiple competitor brands, when I view the comparative sentiment analysis, then I should see a side-by-side comparison of sentiment scores for each brand.

SWOT Visualization Tool

User Story: As a marketer, I want a visualization tool that presents SWOT analysis clearly so that I can easily communicate insights to my team and stakeholders.
Description: The SWOT Visualization Tool requirement provides users with a visual representation of the SWOT analysis for competitor brands. This tool will enhance the user experience by allowing analysts and marketers to quickly comprehend the data through charts and graphs. The integration of this visualization tool helps in presenting findings to stakeholders more effectively, supporting the decision-making process. By clearly displaying strengths, weaknesses, opportunities, and threats, users can identify correlations between aspects of the competitive landscape and formulate strategies that leverage this data.
Acceptance Criteria: As a marketing analyst, I want to visualize the SWOT analysis for Brand X so that I can present the findings to the marketing team during our strategy meeting.

Given the SWOT Visualization Tool is accessed, when the analyst selects Brand X from the competitor list, then the tool displays a well-structured SWOT chart with clearly labeled sections for strengths, weaknesses, opportunities, and threats.

As a product manager, I want the SWOT Visualization Tool to support multiple competitor comparisons so that I can evaluate various brands side-by-side for strategic insights.

Given the SWOT Visualization Tool allows competitor selection, when multiple brands are selected, then the tool presents a comparative SWOT diagram highlighting differences and similarities for all selected competitors.

As a stakeholder, I want to export the visualized SWOT analysis into different formats (PDF, PNG, JPEG) to share insights with my team effectively.

Given the SWOT Visualization Tool is utilized, when the user selects the export option for the SWOT chart, then the tool successfully generates the visual in the specified format, allowing for seamless sharing via email or presentation.

As a business analyst, I need real-time data updates in the SWOT Visualization Tool to ensure the analysis reflects the current market sentiment.

Given the SWOT Visualization Tool is integrated with real-time sentiment data, when sentiments shift on social media platforms, then the tool automatically updates the SWOT analysis visual accordingly, reflecting the latest insights.

As a user, I want to customize the visualization style of the SWOT chart so that I can align it with our brand identity during presentations.

Given the customization options are available in the SWOT Visualization Tool, when the user selects different colors, fonts, and layouts, then the tool updates the chart to reflect these customizations, enhancing brand consistency.

As a team lead, I want the SWOT Visualization Tool to include summary insights to accompany the visual representation for clearer decision-making.

Given the SWOT Visualization Tool is in use, when the user generates the SWOT chart, then the tool also provides a text summary of key insights derived from the strengths, weaknesses, opportunities, and threats displayed, facilitating informed discussions.

As a user, I want the SWOT Visualization Tool to be accessible on multiple devices so that I can analyze competitor data on-the-go or in the office.

Given the SWOT Visualization Tool is developed, when accessed on a mobile device, tablet, or desktop, then the tool should maintain functionality and provide an optimal user experience across all platforms.

Alert System for Sentiment Shifts

User Story: As a product manager, I want to receive alerts when there are significant changes in competitor sentiment so that I can proactively adjust our strategies to maintain a competitive advantage.
Description: The Alert System for Sentiment Shifts requirement enables users to receive notifications about significant changes in competitor sentiment metrics. This feature will help in proactively managing strategies by allowing users to react quickly to changes in the competitive landscape. By being alerted to fluctuations that indicate strengths or weaknesses in competitor branding or reputation, users can adjust their responses and capitalize on opportunities or address threats before they escalate.
Acceptance Criteria: As a marketing analyst, I want to receive real-time notifications whenever there is a significant increase or decrease in the sentiment score of a competitor brand over a 24-hour period, so I can adjust my marketing strategy accordingly.

Given the sentiment metrics for a specific competitor, when there is a change of more than 15% in the sentiment score within a 24-hour window, then a notification should be sent to the user via email and the dashboard alert feature.

As a brand manager, I need to be alerted if a competitor's sentiment drops below a certain threshold, so I can respond proactively to mitigate risks to our brand's reputation.

Given the current sentiment score of a competitor, when the score falls below 35%, then an alert should be triggered in the application and communicated to the user through push notifications.

As a market strategist, I want to identify trends in competitor sentiment over time, so I can develop long-term strategies based on these insights.

Given a 7-day history of sentiment scores for a competitor, when running the trend analysis, then the system should generate a report that visually displays the upward or downward trends and send this report to the user once a week.

As a product owner, I wish to ensure that alerts are not too frequent to avoid overwhelming users while still providing necessary updates on competitor sentiment changes.

Given the alert settings configured by the user, when there are multiple sentiment changes for a competitor within a 3-hour period, then alerts should be batched and sent as a single notification summarizing the changes.

As an analyst, I want to customize the sensitivity of the alert system, so I can receive notifications only for changes that matter to my strategic objectives.

Given the user preferences for alert sensitivity, when a user sets a threshold for percentage change (e.g., 10%, 20%), then the alert system should only notify the user when the sentiment change exceeds their specified threshold.

As a marketing team lead, I want to track the response time to alerts to assess team efficiency in reacting to competitor sentiment shifts.

Given an incident of a sentiment alert being triggered, when monitoring the time taken for the team to respond and implement changes, then this data should be logged and reported weekly to evaluate the response efficiency.

Benchmarking Against Competitors

User Story: As a business strategist, I want to benchmark our sentiment metrics against competitors to identify areas where we can improve our market positioning.
Description: The Benchmarking Against Competitors requirement allows users to compare their sentiment analysis metrics against those of key competitors. This benchmarking capability provides a clear context for understanding relative brand positioning in the market. By analyzing these comparisons, users will be able to identify gaps in their own strategies and areas for improvement, leveraging the strength of competitor performance to optimize their market approach.
Acceptance Criteria: Users can access the Competitive SWOT Analyzer feature within the SentiScan platform and view the benchmarks against their selected competitors during a marketing strategy meeting.

Given a user is logged into SentiScan, when they navigate to the Competitive SWOT Analyzer and select competitors, then they should see a clear graphical representation of their sentiment metrics compared to the selected competitors' metrics.

Marketing analysts need to generate a report that summarizes competitive sentiment metrics for an upcoming presentation to stakeholders.

Given the user has selected multiple competitors and set a reporting period, when they generate the report, then the report should include comprehensive sentiment analysis metrics, including visual graphs and a summary of insights, with no data discrepancies.

After conducting a comparative analysis, users want to receive alerts whenever a competitor's sentiment shifts significantly to adjust their marketing strategies accordingly.

Given a user has set up sentiment alerts for selected competitors, when there is a significant sentiment shift, then notifications should automatically be sent to the user's registered email address within 10 minutes of the change.

Brand managers are using SentiScan to identify gaps in their marketing strategies by comparing their metrics against those of key competitors.

Given the user has analyzed competitor metrics, when they look at the benchmarking dashboard, then they should see highlighted areas indicating significant gaps or opportunities for improvement compared to competitor performance.

Users want to understand the time trends of competitor sentiments over the last quarter to inform their decision-making processes in future campaigns.

Given a user selects a date range for the last quarter, when they view the trend analysis in the Competitive SWOT Analyzer, then they should see a detailed timeline graph displaying changes in sentiment for each competitor across the selected period.

Users need to validate the accuracy of the competitive sentiment data provided by SentiScan before making strategic decisions based on this information.

Given a user requests a raw data download for competitor sentiment metrics, when the file is generated, then the data should accurately reflect the displayed metrics in the dashboard with no inconsistencies or errors in value representation.

User Role Access Control

User Story: As an admin, I want to control user access to competitor data so that I can ensure sensitive information remains secure while still allowing collaboration among teammates.
Description: User Role Access Control equips the Competitive SWOT Analyzer with the ability to assign different access levels to users based on their roles within the organization. This requirement is important for ensuring that sensitive competitive analysis data is only accessible to authorized personnel, thereby enhancing data security and management control. By managing user permissions effectively, organizations can ensure appropriate levels of information access while maximizing collaboration among teams.
Acceptance Criteria: As a system administrator, I want to assign specific roles to users so that each user can only access the Competitive SWOT Analyzer features relevant to their job functions.

Given a user role with restricted access, when the user attempts to access the Competitive SWOT Analyzer, then the system should deny access to any features not permitted for the user's role.

As a team leader, I want to review user access levels to ensure that sensitive data is only accessible to authorized users, preventing potential data breaches.

Given a request for the list of user roles, when the team leader retrieves the access logs, then the system should provide an accurate report of all user roles and associated access levels.

As a marketing analyst, I want to be granted access to competitive analysis features based on my role so that I can utilize data without compromising security.

Given a marketing analyst has been assigned the appropriate role, when the analyst logs into the Competitive SWOT Analyzer, then the system should grant access to all features relevant to their role.

As a project manager, I want to change a user's role and access permissions so that they can take on additional responsibilities as needed.

Given a project manager has permission to modify user roles, when the project manager changes a user’s role, then the system should successfully update the user’s access permissions accordingly and reflect these changes in real-time.

As a compliance officer, I want to ensure that user access controls comply with data protection regulations to protect sensitive information.

Given the established data protection regulations, when the compliance officer reviews user role access, then all user roles must align with the compliance requirements and protocols established for data security.

As a system administrator, I want to receive alerts on unauthorized access attempts so that I can mitigate potential threats to sensitive data.

Given that an unauthorized access attempt is detected, when the alert is triggered, then the system should send an immediate notification to the system administrator with the details of the attempt.

Audience Sentiment Mapping

Audience Sentiment Mapping visually breaks down how different consumer segments perceive competitor brands, offering insights into demographic preferences and trends. By understanding sentiment across diverse audience groups, users can tailor marketing strategies to resonate more effectively with their target consumers, enhancing engagement and conversion rates.

Requirements

Real-Time Sentiment Analysis

User Story: As a market analyst, I want to receive real-time sentiment analysis so that I can quickly respond to consumer feedback and adjust my marketing strategies accordingly.
Description: The Real-Time Sentiment Analysis requirement involves developing an algorithm that can process and analyze social media and online platform data to provide instant insights into consumer sentiment. This feature is crucial for SentiScan as it leverages advanced AI and natural language processing to track sentiment fluctuations as they happen. The integration of this requirement will enhance the product's capability to deliver timely information, enabling users to react swiftly to changes in consumer perception and market trends. This analysis will be displayed on dashboards that provide visual representations of sentiment data, allowing users to easily comprehend insights and make strategic decisions based on current consumer attitudes.
Acceptance Criteria: As a marketing analyst, I want to view real-time sentiment data on the SentiScan dashboard so that I can make informed decisions about our marketing strategy in response to consumer sentiment shifts.

Given the algorithm for real-time sentiment analysis is integrated, when I access the SentiScan dashboard, then I should see updated sentiment data displayed within 5 seconds of new data being available.

As a user of SentiScan, I want to filter sentiment data by demographic segments so that I can understand how different groups perceive our competitors' brands.

Given I have selected a specific demographic segment, when I apply the filter on the audience sentiment mapping feature, then the dashboard should display sentiment data only for that chosen demographic with a clear visual representation.

As a product manager, I want to receive alerts when there is a significant shift in consumer sentiment so that I can quickly address any brand-related issues.

Given the sentiment analysis algorithm is tracking data, when a significant sentiment shift is detected (defined as a 20% increase or decrease in positive sentiment), then I should receive an automated alert via email and through the SentiScan notifications.

As a brand strategist, I want to compare our sentiment data against our key competitors in real-time to assess our market position effectively.

Given the real-time sentiment analysis is operational, when I select two competitor brands for comparison on the SentiScan dashboard, then the visual representation should clearly show a side-by-side comparison of sentiment data for both brands over the past 24 hours.

As a user, I want to visualize historical sentiment data to identify trends over time so I can adjust our strategies accordingly.

Given I am on the sentiment analysis dashboard, when I select the historical data view for the past month, then the system should generate a line graph showing sentiment trends over that time period.

As a marketer, I want to ensure the sentiment analysis algorithm accurately categorizes consumer opinions as positive, negative, or neutral so that we can gauge our brand perception correctly.

Given a sample set of social media comments, when I input these comments into the sentiment analysis algorithm, then the output should categorize at least 90% of the comments correctly according to their sentiment.

Segmented Sentiment Visualization

User Story: As a marketing manager, I want to view segmented sentiment visualizations so that I can tailor my campaigns to better meet the preferences of different audience groups.
Description: The Segmented Sentiment Visualization requirement is aimed at creating dynamic visualizations that break down consumer sentiment based on various demographic segments such as age, location, and purchasing behavior. This functionality is vital for users to understand how different groups perceive competitor brands, thus enabling more targeted marketing strategies. By employing data visualization techniques, this requirement will facilitate easier identification of trends and preferences within each segment, ultimately leading to enhanced engagement and conversion rates. Implementing this feature will integrate seamlessly with existing dashboards and reporting tools within SentiScan, providing users with actionable insights.
Acceptance Criteria: User views segmented sentiment visualization for a specific competitor brand across different demographics.

Given a user has selected a competitor brand, when they navigate to the segmented sentiment visualization dashboard, then they should see charts displaying sentiment data categorized by age, location, and purchasing behavior for that brand.

User filters sentiment visualization by demographic criteria.

Given a user is on the segmented sentiment visualization dashboard, when they select a filter option for demographics such as age or location, then the displayed charts should update to reflect only the sentiment data for the selected demographic.

User analyzes sentiment trends over time for targeted groups.

Given a user selects a specific demographic group, when they view the segmented sentiment visualization, then they should see a line graph displaying sentiment trends over the last 12 months for that group.

User interacts with the visualization to obtain detailed insights.

Given a user clicks on a specific segment within the sentiment chart, when they do so, then a pop-up should appear showing detailed statistics such as percentage positive, negative, and neutral sentiment along with sample comments from users in that segment.

User exports segmented sentiment visualization data for further analysis.

Given a user is viewing the segmented sentiment charts, when they click the export button, then a CSV file should be generated containing the segmented sentiment data for the selected competitor brand and demographics.

User receives alerts for significant changes in sentiment within demographics.

Given a user has set up alert preferences for specific demographic segments, when there is a significant change in sentiment for those segments, then an email notification should be sent to the user detailing the changes.

Automated Sentiment Alerts

User Story: As a brand manager, I want to receive automated alerts for significant sentiment changes so that I can act promptly and adjust our branding strategy if needed.
Description: The Automated Sentiment Alerts requirement focuses on setting up notification systems that automatically inform users when significant changes in sentiment are detected. This feature allows marketers and analysts to stay updated on shifts in consumer perceptions without needing to monitor data constantly. Users can configure alerts based on predefined thresholds and select which sentiment changes warrant notifications. This functionality enhances SentiScan's value proposition by ensuring that critical insights are not missed, enabling proactive management of marketing strategies in response to changing consumer attitudes.
Acceptance Criteria: Automated notification for significant sentiment changes

Given that a user has set a threshold for positive sentiment at 70%, when the sentiment for a competitor drops below this threshold, then an alert notification should be sent to the user within 5 minutes.

Customizable alert settings for users

Given that a user accesses the alert configuration settings, when they select specific sentiment trends and set thresholds, then they should be able to save these settings and activate notifications accurately.

Real-time sentiment analysis updates

Given that significant sentiment changes occur, when these changes are detected by the system, then the updates should reflect on the user dashboard within 10 seconds.

User management of notification preferences

Given that a user wants to adjust their notification preferences, when they access the settings, then they should be able to add or remove alert types and modify delivery methods with ease.

Testing alert delivery methods

Given that a user has selected email notifications for alerts, when a sentiment change occurs, then the user should receive an email within 5 minutes outlining the sentiment shift.

Integration with external platforms for alerts

Given that a user wants to receive alerts via a third-party application (e.g., Slack), when a sentiment threshold is breached, then the alert should be sent to the specified channel in real-time.

Historical data tracking of sentiment alerts

Given that the user has received multiple alerts over a month, when they access their alert history, then they should see a detailed log of all alerts with timestamps and sentiment information.

Competitive Benchmarking Dashboard

User Story: As a strategist, I want to access a competitive benchmarking dashboard so that I can evaluate our brand's performance in comparison to competitors and adjust our positioning accordingly.
Description: The Competitive Benchmarking Dashboard requirement involves creating a dedicated section within SentiScan that allows users to compare their brand's sentiment against competitors. This dashboard will integrate various sentiment metrics, providing users with a clear overview of their competitive landscape. Offering insights such as average sentiment scores, trends over time, and sentiment shifts in response to marketing efforts, this feature is essential for strategic planning. By providing comparative data, users can gain a deeper understanding of their market positioning relative to competitors and refine their strategies for better performance.
Acceptance Criteria: User Comparison of Sentiment Metrics for Competitive Brands

Given a user is on the Competitive Benchmarking Dashboard, when they select a competitor brand, then the dashboard displays comparative sentiment metrics such as average sentiment score, sentiment trend graphs, and percentage shift in sentiment over the last month.

Visualization of Sentiment Trends Over Time

Given a user has navigated to the Competitive Benchmarking Dashboard, when they view the sentiment trends section, then the chart visualizes sentiment scores of their brand and competitors over specified time intervals (weekly, monthly, quarterly).

User Alerts for Significant Sentiment Shifts

Given a user has set up alerts within the Competitive Benchmarking Dashboard, when there is a significant change (above a threshold defined by the user) in sentiment scores for either their brand or competitors, then the user receives an immediate notification via email or in-app alert.

Exporting Competitor Sentiment Data

Given a user views competitor sentiment data on the Competitive Benchmarking Dashboard, when they click on the export button, then the selected data is downloaded as a CSV file containing all relevant metrics and trends for further analysis.

User-Friendly Interface for Segment Analysis

Given a user is on the Competitive Benchmarking Dashboard, when they utilize filtering options for demographics (age, location, gender), then the dashboard updates to reflect sentiment metrics specific to the selected audience segment.

Interactive Comparison Tool for Real-Time Data

Given a user is utilizing the Competitive Benchmarking Dashboard, when they select multiple competitor brands for comparison, then an interactive graph is generated that allows the user to visualize and analyze real-time sentiment data side-by-side.

Historical Analysis of Sentiment Data

Given a user is on the Competitive Benchmarking Dashboard, when they access the history section, then the system displays at least six months of historical sentiment data for both their brand and competitors, highlighting key events and their impact on sentiment scores.

Detailed Sentiment Reporting

User Story: As a business analyst, I want to generate detailed sentiment reports so that I can present comprehensive insights to stakeholders and facilitate data-driven decision-making.
Description: The Detailed Sentiment Reporting requirement encompasses generating comprehensive reports on consumer sentiment analysis that can be customized and exported for client presentations and internal reviews. These reports will include in-depth insights into sentiment trends over specified periods, breakdowns by demographic segments, and comparisons with competitors. This feature aims to enhance the professional reporting capabilities of SentiScan, thereby supporting clients in making informed decisions based on extensive data analysis. Customizable templates will allow users to tailor reports to specific needs, thereby increasing the usability and effectiveness of the insights provided by SentiScan.
Acceptance Criteria: User generates a customizable sentiment report for a presentation to stakeholders, including filters for date range and demographic segments.

Given the user selects the 'Generate Report' option, when they specify a date range and demographic segments, then the system generates a report that includes sentiment trends, demographic breakdowns, and competitor comparisons.

User exports the generated sentiment report in various formats for sharing with clients and team members.

Given the user has created a sentiment report, when they choose to export, then the system provides options to export the report in PDF, Excel, and PowerPoint format.

User views the detailed sentiment report on the dashboard to analyze sentiment trends over a specified period.

Given the user accesses the dashboard, when they select a specific report, then the system displays the detailed sentiment trends visually along with key insights for the selected time period.

User customizes the report template to align with the company's branding for client presentations.

Given the user accesses the report template settings, when they modify elements such as logo, colors, and fonts, then those customizations are saved and applied to the exported reports.

User analyzes sentiment trends and demographic breakdowns through interactive visualizations within the reporting feature.

Given the user interacts with the report visualizations, when they hover over data points, then detailed tooltips display specific values and relevant insights for those points.

User compares sentiment ratings of their brand against top competitors in the generated report.

Given the user generates a sentiment report, when they view the competitor comparison section, then the report displays side-by-side sentiment ratings for each competitor over the specified time period.

Competitor Campaign Analyzer

The Competitor Campaign Analyzer assesses the performance of competitors' marketing campaigns, summarizing key metrics such as engagement, reach, and sentiment response. This feature helps users learn from competitor strategies, identifying best practices and potential pitfalls to improve their marketing efforts. By analyzing competitor successes and failures, brands can refine their own tactics for better results.

Requirements

Real-Time Campaign Performance Tracking

User Story: As a marketing analyst, I want to track competitor campaign performance in real-time so that I can quickly identify trends and adjust my strategies accordingly.
Description: This requirement entails the development of a functionality that allows users to monitor the performance of competitors' marketing campaigns in real-time. It will provide insights into various performance indicators such as engagement rates, reach, and consumer sentiment analysis. By integrating this feature within SentiScan, users will be able to make timely and informed decisions based on live data, enhancing their ability to adapt marketing strategies to emerging trends. This functionality is crucial for maintaining a competitive edge in market analysis and will significantly improve user engagement with the software, ensuring they have the most relevant and updated information at their fingertips.
Acceptance Criteria: User initiates the Competitor Campaign Analyzer to monitor a selected competitor's ongoing marketing campaign.

Given a user selects a competitor's campaign in SentiScan, when the user activates the real-time performance tracking, then the system displays live metrics including engagement rates, reach, and sentiment analysis within 5 seconds.

User reviews the real-time metrics for a specific campaign over a defined period.

Given a user views the performance metrics for a selected campaign, when the user specifies a time frame (e.g., last 24 hours), then the system aggregates and displays performance data accurately for that duration.

User receives notifications about significant changes in a competitor's campaign performance.

Given a user has activated alerts for performance indicators, when there is a significant change (e.g., a 20% increase in engagement) in the selected campaign's metrics, then the system sends an immediate notification to the user via email or SMS.

User compares the performance of multiple campaigns from different competitors simultaneously.

Given a user selects multiple competitors’ campaigns, when the user activates the comparison feature, then the system displays a side-by-side comparison of key performance indicators including engagement, reach, and sentiment in a clear, visual format within 10 seconds.

User analyzes sentiment changes over time for a specific campaign.

Given a user selects a campaign to analyze, when the user views the sentiment analysis graph, then the system shows the sentiment trend over the last 30 days with accurate data points for each relevant day.

User exports campaign performance data for offline analysis.

Given a user wishes to export the performance metrics of a selected campaign, when the user clicks on the export button, then the system generates a downloadable CSV file containing all relevant metrics, including engagement and sentiment analysis, within 3 seconds.

User receives a summary report of the competitor’s campaign performance after a defined period.

Given a user has monitored a competitor’s campaign for a week, when the user requests a summary report, then the system generates and displays a comprehensive report including key metrics and insights within 1 hour of request.

Sentiment Analysis Comparison Tool

User Story: As a brand strategist, I want to compare sentiment scores between my brand and competitors so that I can understand our market positioning better and refine our marketing messaging.
Description: This requirement involves creating a tool that allows users to compare sentiment analysis results of multiple competitors' campaigns side-by-side. Users would be able to visualize sentiment trends, fluctuations during campaign timelines, and overall sentiment scores for different campaigns. This feature aids users in understanding how consumers perceive their brand versus competitors in similar contexts. The addition of this feature will provide deeper insights into consumer behavior, allowing brands to adapt their messaging and positioning strategies more effectively based on direct comparisons.
Acceptance Criteria: Comparison of sentiment analysis results between two major competitors is conducted during a live marketing campaign evaluation meeting.

Given that the user has selected two competitor campaigns to compare, When the user initiates the sentiment analysis comparison, Then the tool displays the sentiment scores and trends for both campaigns side-by-side for the selected time frame.

A user wants to analyze how their brand's sentiment shifts compared to a competitor during a specific period.

Given that the user inputs the relevant time period and selects their own brand and a competitor's brand, When the comparison is executed, Then the tool generates a visual representation of sentiment trends for both brands that clearly outlines fluctuations during the selected time frame.

An analyst prepares a report summarizing the sentiment analysis results of multiple campaigns for presentations to stakeholders.

Given that the user has compared three or more campaigns, When the user generates a summary report, Then the report includes key insights such as average sentiment scores, percentage changes, and notable trends in a clear and presentable format.

A user wants to quickly understand the performance of their campaign versus competitors at a glance.

Given that the user accesses the sentiment analysis comparison tool, When the comparison is displayed, Then the tool should highlight the best and worst performing campaigns based on sentiment scores in a visual dashboard format with clear indicators.

A marketing team is conducting a post-campaign analysis and wants to assess the effectiveness of their messaging compared to a competitor.

Given that the user selects specific campaigns for comparison after the campaigns have ended, When the user views the sentiment analysis data, Then the tool provides detailed insights on the impact of campaign messages on consumer sentiment based on comparative analysis.

A user accesses the tool to monitor real-time sentiment changes during the course of a promotional campaign.

Given that the user is actively monitoring a live campaign's sentiment, When the sentiment shifts by more than 10% in a short period, Then the tool alerts the user with a notification detailing the sentiment change and potential reasons.

Engagement Metrics Dashboard

User Story: As a digital marketer, I want an engagement metrics dashboard to visualize key KPIs of competitor campaigns so that I can quickly gauge their effectiveness and learn from them.
Description: The engagement metrics dashboard will serve as a centralized hub where users can view key performance indicators (KPIs) for competitors' campaigns. Users will have access to metrics such as likes, shares, comments, and other forms of engagement, all displayed in an intuitive graphical format. This dashboard not only facilitates quick insights but also allows for filtering based on campaign goals, timelines, and audience demographics. Integration of this dashboard into SentiScan will furnish users with a comprehensive view of engagement trends in a user-friendly manner, enabling more informed decision-making.
Acceptance Criteria: User wants to access the engagement metrics dashboard to evaluate competitors' marketing campaigns.

Given a user is logged into SentiScan, when they navigate to the Competitor Campaign Analyzer section, then they should see the engagement metrics dashboard displaying KPIs including likes, shares, comments, and engagement rates in a graphical format.

User wants to filter engagement metrics based on specific campaign goals.

Given a user is on the engagement metrics dashboard, when they select filtering options for campaign goals, then the dashboard should update to show only the engagement metrics relevant to the selected campaign goals.

User seeks to compare engagement metrics among different competitors' campaigns.

Given a user is on the engagement metrics dashboard, when they select multiple competitors to compare, then the dashboard should display a comparative view of engagement metrics for the selected competitors, allowing side-by-side analysis.

User aims to export engagement metrics from the dashboard for offline analysis.

Given a user is on the engagement metrics dashboard, when they click on the export button, then they should receive a downloadable file (CSV or Excel) containing all displayed engagement metrics.

User wants to view engagement trends over time for a particular campaign.

Given a user is on the engagement metrics dashboard, when they select a specific timeline for a campaign, then the dashboard should display the engagement metrics trend graphically over the selected time period.

User desires to receive notifications for shifts in engagement metrics.

Given a user has set up alerts for engagement metric changes, when there is a significant shift in any metric for a competitor's campaign, then the user should receive a notification via their preferred channel (email or in-app).

Competitor Campaign Alerts

User Story: As a marketing manager, I want to receive alerts on significant changes in competitor campaigns so that I can quickly respond and adjust our strategies to maintain competitiveness.
Description: This requirement looks to implement an alert system that notifies users of significant changes in competitor campaign performance metrics, such as a spike in engagement or dramatic shifts in sentiment. Users will customize their alert preferences based on specific performance indicators they wish to monitor. This proactive approach ensures users can stay ahead of competitors by being immediately informed of significant changes, allowing for agile adjustments to their strategies in real time.
Acceptance Criteria: User sets up alerts for competitor campaigns focusing on engagement metrics.

Given the user is on the alert settings page, when they select 'Engagement' as a performance indicator and save the settings, then the system should confirm that the alert is activated for engagement metrics.

User receives an alert for a significant spike in engagement metrics from a selected competitor.

Given the user has set alerts for significant changes, when a competitor's campaign engagement spikes by more than 20% within 24 hours, then the user should receive a notification via email and in-app alert summarizing the change.

User customizes alert preferences based on performance metrics.

Given the user is on the alert preferences page, when they choose specific metrics like reach and sentiment along with engagement, then the system should allow selecting multiple metrics and save the preferences successfully without errors.

User tests the alert system for dramatic shifts in sentiment response of a competitor's campaign.

Given the user has activated alerts for sentiment responses, when a competitor experiences a drop in sentiment score by 30% in a defined timeframe, then the user should receive a prompt on both mobile and desktop platforms indicating the severity of the sentiment shift.

User views the history of alerts generated for competitor campaigns.

Given the user accesses the alert history page, when they request the last month's alert data, then the system should display a chronological list of alerts with details of performance metrics and timestamps.

User modifies an existing alert preference for competitor campaigns.

Given the user is editing existing alert preferences, when they change the threshold for engagement metrics to 10% and save, then the system should update the alert preference and provide confirmation of the change.

User disables alerts for a specific competitor's campaign.

Given the user is on the alert management section, when they select a competitor and toggle the alert status to 'off,' then the system should confirm that alerts for that competitor are disabled without any discrepancies in other settings.

Best Practices Repository

User Story: As a marketing professional, I want access to a repository of best practices from competitor campaigns so that I can improve our marketing strategies based on proven successful tactics.
Description: This requirement entails the creation of a repository that curates and summarizes best practices derived from competitor campaign analyses. The repository will provide actionable insights and recommendations based on successful strategies identified from the data analysis. Users will benefit from this knowledge base in formulating their own campaign strategies and avoiding common pitfalls. This feature strengthens the value of the Competitor Campaign Analyzer by transforming insights into practical applications, making it easier for users to enact changes based on empirical evidence.
Acceptance Criteria: User Browsing the Best Practices Repository for Campaign Insights

Given the user is logged into the SentiScan platform, when they navigate to the Best Practices Repository, then they should see a list of curated best practices organized by campaign type and performance metrics.

User Accessing Detailed Recommendations from the Repository

Given the user has selected a campaign type from the Best Practices Repository, when they click on a specific best practice, then they should be presented with detailed recommendations, including examples and key performance indicators that contributed to its success.

Users Searching for Best Practices by Competitor

Given the user utilizes the search functionality in the Best Practices Repository, when they enter a competitor's name, then they should be shown relevant best practices attributed to that competitor's successful campaigns.

User Engaging with Visual Data Representations in the Repository

Given the user is browsing a best practice, when they view the recommended strategies, then they should see visual data representations, such as charts or graphs, that illustrate the impact of those practices on campaign performance.

User Bookmarking Best Practices for Future Reference

Given the user is viewing a specific best practice, when they click the bookmark option, then that best practice should be saved to their profile for easy access in the future.

User Providing Feedback on Best Practices Utilization

Given the user has implemented a best practice from the repository in their marketing campaign, when they submit a feedback form detailing their experience, then it should be successfully saved and reflected in a summary report for further analysis.

Quick Poll Creator

Quick Poll Creator allows users to effortlessly design and deploy polls within minutes. With customizable templates and question formats, marketers can quickly capture audience feedback on various topics, and adjust campaigns with real-time insights. This feature streamlines the feedback process, ensuring marketers can stay agile and responsive to audience preferences.

Requirements

Poll Customization Options

User Story: As a marketer, I want to customize my polls to match my brand's style so that my audience feels connected and engaged while providing feedback.
Description: This requirement focuses on providing users with a wide range of customization options for polls created within the Quick Poll Creator feature. Users should be able to select from different question formats (multiple choice, open-ended, rating scale), design aesthetics (colors, fonts, themes), and add multimedia elements (images, videos) to enhance engagement. The aim is to enable marketers to tailor their polls to better align with brand identity and the preferences of their target audience, leading to more effective data collection and insights.
Acceptance Criteria: User selects different question formats while creating a poll in Quick Poll Creator.

Given the user is in the Quick Poll Creator, When they choose to add a question, Then they should see options for multiple choice, open-ended, and rating scale formats.

User customizes the design aesthetics of their poll to match brand identity.

Given the user is designing their poll, When they access the design options, Then they should be able to select colors, fonts, and themes that align with their brand.

User adds multimedia elements to enhance poll engagement.

Given the user is creating a poll, When they opt to include multimedia, Then they should be able to upload images or videos directly into the poll questions.

User previews the poll before finalizing it for deployment.

Given the user has made all necessary customizations, When they click on the preview button, Then the poll should display all selected question formats, design, and multimedia as intended.

User shares their customized poll across social media platforms.

Given the user has finalized their poll, When they select the option to share, Then they should see options to share via major social media platforms with direct links.

User receives real-time feedback analytics after polling is completed.

Given the poll has concluded, When the user accesses the analytics dashboard, Then they should see metrics that reflect audience feedback, including response rates and sentiment analysis.

User saves a draft of the poll for later edits.

Given the user is in the process of creating a poll, When they click on the save draft option, Then the poll should be successfully saved and retrievable in the user's dashboard later.

Real-Time Response Analytics

User Story: As a product manager, I want to see real-time analytics of poll responses so that I can quickly adjust marketing campaigns based on audience feedback.
Description: The requirement involves implementing a system that provides real-time analytics on poll responses. Users should have access to instant updates and visual representations of poll data (graphs, charts) that reflect response trends, demographics, and other key insights. By delivering these analytics in real time, marketers can quickly assess public opinion and adapt their strategies immediately, enhancing their responsiveness to audience preferences and behavior changes.
Acceptance Criteria: User initiates a quick poll using the Quick Poll Creator feature, specifying questions and options, and then monitors the poll responses in real-time.

Given the user has created a poll and made it live, when they access the analytics dashboard, then they should see updated poll results, including response counts and percentages, within 5 seconds of a user voting.

A marketer wants to analyze response trends over time to determine how audience sentiment changes based on different demographics after polling.

Given the poll is live and responses are coming in, when the marketer reviews the analytics dashboard, then they should be able to filter results by demographic categories (age, location, etc.) and view trend graphs for each category.

An admin is interested in the overall performance of active polls to make strategic decisions about future campaigns.

Given multiple polls are running concurrently, when the admin accesses the analytics dashboard, then they should see a summary view displaying key metrics such as total responses, average response rate, and sentiment score for each poll.

A user needs to make an immediate strategic pivot based on an unexpected shift in poll sentiment.

Given the user is viewing the real-time analytics dashboard, when a significant change in sentiment is detected (e.g., more than 20% shift in positive/negative response), then an alert notification should be triggered in the dashboard.

A marketer wants to assess the effectiveness of a poll's question format on response rates.

Given a poll has multiple question formats (multiple choice, open-ended), when the marketer analyzes the analytics, then they should receive comparative data showing response rates and engagement levels for each question type.

A user is conducting a poll on social media and wants to understand how external factors might influence polling results.

Given the user is monitoring the analytics dashboard, when external events (e.g., news, trending topics) occur, then real-time sentiment analysis should reflect any potential impacts on poll responses and trends.

Multi-Platform Distribution

User Story: As a marketer, I want to share my polls across different platforms so that I can reach a broader audience and gather diverse feedback.
Description: This requirement encompasses the ability for users to deploy polls across multiple platforms, such as social media, email, and website embeds. Marketers should be able to seamlessly share their polls and engage audiences on their preferred channels. This capability not only maximizes reach but also allows for a diverse set of responses from varied audience segments, thereby enhancing the quality and breadth of feedback gathered.
Acceptance Criteria: User creates a poll in the Quick Poll Creator and selects multiple platforms for distribution.

Given the user has created a poll, when they select social media, email, and website embed as distribution options, then the poll should be successfully configured for all selected platforms and display a confirmation message indicating successful setup.

User shares a poll via social media and checks for proper functionality.

Given the user has shared a poll on a social media platform, when they navigate to the poll link, then the poll should load correctly, display the questions as designed, and allow users to submit their responses without errors.

User collects responses from a poll distributed across three different platforms and reviews analytics.

Given the poll is active and has collected responses on social media, email, and website embed, when the user accesses the analytics dashboard, then they should see a comprehensive overview of responses segmented by platform, including the total number of responses and individual feedback.

User embeds a poll in their website and tests for compatibility on mobile devices.

Given the user has embedded a poll on their website, when they access the site using a mobile device, then the poll should be responsive, display correctly, and remain fully functional for mobile users.

User schedules a poll distribution to multiple platforms at once.

Given the user has created a poll and specified the distribution date and time for multiple platforms, when the time arrives, then the poll should automatically be activated on all selected channels without requiring further user intervention.

User edits a poll after initial distribution and checks for updated content across platforms.

Given the user has made changes to the poll questions after they have been distributed, when they check each platform where the poll was shared, then the updates should reflect immediately across all platforms with version control in place.

Automated Sentiment Analysis Integration

User Story: As a market analyst, I want automated sentiment analysis on poll responses so that I can swiftly understand the emotional undertones in audience feedback without manual review.
Description: Integrate an automated sentiment analysis tool that evaluates open-ended responses from polls to generate insights into public sentiment regarding surveyed topics. This requirement aims to enhance data analysis by transforming qualitative feedback into quantifiable sentiment metrics, providing marketers with deeper insights into consumer attitudes towards their campaigns or products.
Acceptance Criteria: User creates a poll with open-ended responses and submits it for analysis.

Given a user has created a poll with open-ended questions, when the responses are collected, then the automated sentiment analysis tool should analyze the responses and generate a sentiment report categorizing the feedback into positive, neutral, and negative sentiments.

Marketers view sentiment analysis results on the dashboard after the poll has closed.

Given the poll period has ended, when the marketer accesses the dashboard, then there should be a visual representation of the sentiment analysis results available, showing percentages of each sentiment category and key phrases from the responses.

User receives an alert for significant sentiment shift after poll analysis.

Given that a poll has been conducted with responses analyzed, when there is a significant shift (e.g., over 10% change) in the sentiment metrics, then the user should receive an automated alert notifying them of the shift.

Integration with existing data visualization tools.

Given that the sentiment analysis results are available, when a user attempts to export the results, then the integration with external data visualization tools (e.g., Tableau, Power BI) should work seamlessly, allowing users to create custom visual reports.

Comparison of sentiment across multiple polls.

Given multiple polls have been conducted, when the user accesses the sentiment analysis interface, then there should be functionality to compare sentiment metrics across the selected polls side-by-side for better insights.

User can edit the poll before final submission for sentiment analysis.

Given a user drafts a poll with open-ended responses, when the user opts to make changes to the questions, then they should be able to edit those questions before submitting the poll for analysis, preserving the ability to capture accurate sentiments.

User-Friendly Poll Navigation

User Story: As a new user, I want an easy-to-navigate interface for creating and analyzing polls so that I can effectively use the Quick Poll Creator without confusion or frustration.
Description: Implement a user-friendly interface for navigating through poll creation, distribution, and response analysis. This requirement emphasizes simplifying the user experience by ensuring that all functions are intuitive and accessible, thus reducing the learning curve for new users. Features may include a step-by-step wizard for creating polls, an easily navigable dashboard, and helpful tooltips throughout the process, aiming to enhance user confidence and increase feature adoption.
Acceptance Criteria: User navigates through the Quick Poll Creator interface to create a new poll for a product feedback survey.

Given the user is logged into the SentiScan platform, when they access the Quick Poll Creator, then they see a step-by-step wizard that guides them through creating a poll with easily accessible options for question types and settings.

User distributes the created poll to their target audience via social media channels.

Given the user has completed their poll setup, when they click on the 'Distribute' button, then they should see a confirmation message indicating successful distribution and receive a shareable link for social media platforms.

User analyzes responses collected from the published poll in the Quick Poll Creator dashboard.

Given that responses have been collected from a deployed poll, when the user navigates to the analysis section of the Quick Poll Creator, then they should see a visual representation (charts/graphs) of the responses along with actionable insights.

User seeks assistance while using the Quick Poll Creator to better understand its features.

Given the user is in any section of the Quick Poll Creator, when they hover over an icon or field, then they should see tooltips providing contextual help and guidance about the function.

New user signs up and goes through the poll creation process for the first time.

Given a new user has signed up for the SentiScan platform, when they start the poll creation process, then they should be accompanied by an onboarding tutorial that outlines key features and navigation tips.

User attempts to create a poll with invalid input data to test error handling.

Given the user is on the poll creation screen, when they enter invalid data (such as unsupported question types), then an error message should appear explaining the data issue without preventing them from completing the poll setup process.

User wants to edit an existing poll after responses have started to come in.

Given the user selects an existing poll from their dashboard, when they click on 'Edit', then they should be able to modify the poll questions or settings, with a clear indication of any restrictions on changes post-deployment.

Survey Analytics Dashboard

Survey Analytics Dashboard compiles feedback results into a comprehensive visual interface, providing users with deep insights into responses. This feature highlights key trends, sentiment scores, and demographic breakdowns, allowing marketers to analyze data visually. By offering actionable insights in an intuitive format, users can make informed decisions faster.

Requirements

Dynamic Data Visualization

User Story: As a market researcher, I want to visualize survey results dynamically so that I can quickly identify trends and insights from the data without getting overwhelmed by raw numbers.
Description: The requirement involves creating a dynamic data visualization tool that allows users to interactively explore survey results. This functionality must include customizable charts and graphs that update in real time based on filtered inputs and criteria, ensuring users can easily identify trends and patterns in the data. It will enable users to drill down into specific demographics and sentiment scores, enhancing their ability to analyze and interpret feedback effectively. This integration will reinforce the overall product vision by providing marketers with a versatile way to visualize complex data and make swift, informed decisions.
Acceptance Criteria: User interacts with the Survey Analytics Dashboard to apply filters and view specific demographics.

Given the user has selected a demographic filter, when they apply this filter, the displayed charts and graphs should update in real time to reflect data corresponding to the selected demographic.

User examines the sentiment scores on the Survey Analytics Dashboard across different periods.

Given the user has selected a time range, when they view the sentiment score graph, the graph should accurately depict sentiment scores for each period within the specified timeframe and allow for comparisons.

User wants to export the visualized data from the Survey Analytics Dashboard for reporting purposes.

Given the user is viewing the dashboard, when they select the export option, then the data should be downloaded in a user-friendly format (e.g., CSV, PDF) with all customizations intact.

User reviews trend patterns based on survey responses in the Survey Analytics Dashboard.

Given the user has selected to view trends, when they hover over different sections of the charts, tooltips should display specific data points including percentages and counts of responses.

User customizes the visualization settings in the Survey Analytics Dashboard to suit their analysis needs.

Given the user accesses the settings menu, when they change any visualization options (e.g., chart type, colors, filters), the dashboard should immediately update to reflect these changes accurately and consistently.

User aims to identify potential outliers in survey responses using the Survey Analytics Dashboard.

Given the user is viewing the analysis, when they activate an outlier detection feature, the dashboard should highlight any responses that deviate significantly from the norm along with explanatory metrics.

User wants to understand the overall sentiment trend of customer feedback over time.

Given the user selects a sentiment analysis view, when they explore the trend graph, it should visually represent sentiment changes with clear indicators for positive, negative, and neutral sentiments over time.

Sentiment Analysis Integration

User Story: As a product manager, I want to see sentiment scores alongside survey results so that I can understand not only what customers are saying, but also how they feel about it.
Description: This requirement encompasses the incorporation of sentiment analysis algorithms directly into the Survey Analytics Dashboard. By applying natural language processing (NLP) techniques, the system will analyze open-ended survey responses to derive sentiment scores, which will be displayed alongside quantitative data. This will offer users a comprehensive view of customer feelings toward their products and services, allowing them to address potential issues proactively. This integration is crucial for enhancing analytical capabilities and ensuring that feedback is understood qualitatively, not just quantitatively.
Acceptance Criteria: User reviews sentiment scores alongside quantitative survey results on the Dashboard.

Given a user is on the Survey Analytics Dashboard when they view an open-ended survey response, then they should see corresponding sentiment scores reflecting the qualitative feedback.

Marketer filters survey data by demographic segments and views sentiment analysis results.

Given a marketer applies demographic filters to survey responses when they access the sentiment analysis, then the dashboard should display sentiment scores accurately segmented by the selected demographics.

User receives real-time alerts for significant shifts in sentiment scores after survey completion.

Given a user sets up alert preferences when there is a significant change in sentiment scores (increases or decreases), then the user should receive an immediate notification via email or dashboard alert.

Admin configures sentiment analysis algorithms to evaluate different sentiment models (positive, negative, neutral).

Given an admin is configuring sentiment analysis settings when they save changes, then the system should allow the selection of at least three distinct sentiment evaluation models.

User compares sentiment scores over different survey periods to track changes in customer attitudes.

Given a user selects multiple survey periods when they analyze the dashboard, then the system should visually represent sentiment score changes over time through a comparative graph.

End-user exports survey results and sentiment analysis data for reporting purposes.

Given an end-user requests to export survey results when they choose the export option, then the system should generate a downloadable report that includes both quantitative data and sentiment scores.

Exportable Reports

User Story: As a team leader, I want to export survey analysis reports so that I can share insights with my colleagues in a format that is easy to understand and present.
Description: The requirement outlines the need for a feature that allows users to generate and export detailed reports from the Survey Analytics Dashboard. Users should be able to select various metrics and visualization options to create personalized reports that can be exported in multiple formats, such as PDF and Excel. This feature will greatly enhance usability by allowing users to share insights with stakeholders and create presentations without needing to reformat data manually. It will provide essential tools for documenting findings and disseminating information effectively across teams and departments.
Acceptance Criteria: User generates a report from the Survey Analytics Dashboard to share insights with stakeholders after analyzing survey results.

Given the user is on the Survey Analytics Dashboard, when they select specific metrics and visualization options, then the system should generate a report reflecting these selections in a preview format before export.

User exports a report in PDF format to share with their team members during a presentation.

Given the user has generated the report successfully, when they choose PDF as the export format and click on the export button, then the system should produce a downloadable PDF file of the report within 30 seconds.

User customizes the report by selecting specific demographic breakdowns and sentiment trends before exporting it.

Given the user has access to the customization options, when they apply filters for demographics and trends, then the report generated should only include the filtered selections when exported.

User verifies that the exported Excel report maintains the integrity of the data with the correct formatting.

Given the user exports a report in Excel format, when they open the exported file, then the data should match the original dashboard metrics with proper alignment of columns and rows without loss of information.

User seeks to print the report directly from the Survey Analytics Dashboard interface.

Given that the user is on the report preview page, when they initiate the print command, then the system should provide a print-friendly version of the report displaying all selected metrics and visualizations.

User collaborates with team members by sharing the exported report via email.

Given the user has exported the report in PDF format, when they attempt to attach the report in an email, then the email should successfully send without attachment size errors and include the document as intended.

Real-Time Collaboration Tools

User Story: As a marketing analyst, I want to collaborate with my teammates in real-time while analyzing survey data so that we can share insights instantly and make decisions faster.
Description: The requirement focuses on introducing real-time collaboration tools within the Survey Analytics Dashboard, enabling multiple users to view and analyze data simultaneously. Features such as comments, annotations, and chat functions will facilitate discussions among team members directly within the reporting interface. Adopting this functionality will greatly enhance teamwork and ensure that insights can be shared and discussed in real time, making the analysis process more efficient and collaborative. This integration aligns with contemporary workflows that often involve remote and cross-departmental collaboration.
Acceptance Criteria: Multiple users are analyzing data on the Survey Analytics Dashboard during a team meeting, discussing insights while simultaneously viewing the same report.

Given multiple users are logged into the Survey Analytics Dashboard, when they access the same report, then each user should see real-time updates and changes made by others within 2 seconds.

A user wants to annotate specific graphs and data points in the Survey Analytics Dashboard for further discussion with team members.

Given a user selects a graph in the Survey Analytics Dashboard, when they add an annotation, then the annotation should be visible to all other users currently viewing the report within 5 seconds.

Team members are engaging in a discussion about survey results directly within the Survey Analytics Dashboard chat feature while analyzing the data.

Given that users are in a chat session within the Survey Analytics Dashboard, when they send messages, then messages should appear instantly for all participants without delay.

A user wants to review previous comments made by team members on specific sections of the survey results.

Given a comment is made on the Survey Analytics Dashboard, when another user accesses the same section, then they should be able to see all previous comments and replies with timestamps.

Team members need to identify sentiment shifts quickly during a collaborative session in the Survey Analytics Dashboard.

Given the Sentiment Analysis feature is enabled, when sentiment scores fluctuate, then alerts should notify all users in real-time within the dashboard interface.

Users want to customize notifications for specific metrics or comments in the Survey Analytics Dashboard to stay informed during collaborative sessions.

Given users are setting notification preferences, when they select specific metrics, then they should receive alerts via email or in-app notifications based on their selections within 1 minute of changes.

Marketers want to export the collaborative discussions and insights from the Survey Analytics Dashboard for later use or sharing with external stakeholders.

Given a user clicks the export button, when they choose to export the comments and annotations, then a downloadable report should be generated within 30 seconds, including all discussions and insights.

Targeted Feedback Filters

Targeted Feedback Filters enable users to segment audience responses based on different demographics or behaviors, ensuring that the feedback collected is relevant and actionable. By tailoring surveys to specific groups, marketers can uncover nuanced insights that drive targeted strategies and campaign adjustments, enhancing overall engagement and effectiveness.

Requirements

Demographic Segmentation

User Story: As a marketer, I want to filter survey responses based on demographics so that I can tailor my campaigns to specific audience segments and improve engagement.
Description: The Demographic Segmentation requirement allows users to filter feedback based on demographic information such as age, gender, location, and income level. This feature enhances the precision of the feedback collection process by enabling marketers to tailor their surveys to specific audience segments. By analyzing this segmented data, users can identify trends and sentiments unique to each demographic, which aids in crafting targeted marketing strategies. The implementation of this requirement will empower marketers to develop insights tailored to distinct groups, ensuring their campaigns resonate effectively with their intended audiences.
Acceptance Criteria: User wants to filter survey responses by age group to analyze feedback from different generations on a marketing campaign.

Given that the user has access to SentiScan, When they select the age demographic filter and specify the age range, Then the system must return responses only from the specified age group without errors.

A marketing analyst is interested in understanding the sentiment of male vs. female respondents regarding a new product launch.

Given that the user applies gender filters to the survey data collection, When they run the analysis, Then the application should display separate sentiment analysis results for male and female respondents.

A marketer needs to gather feedback from users located in specific regions to tailor a localized marketing strategy.

Given that the user selects geographic location filters, When the feedback collection is initiated, Then only responses from the specified regions should be included in the data set retrieved for analysis.

A user is analyzing income level segments to determine how marketing messages resonate with different income brackets.

Given that the user sets income level filters, When they request the feedback report, Then the report must include only the insights derived from the selected income brackets and should clearly indicate the ranges applied.

The team wants to compare sentiment trends across multiple demographic segments over time.

Given that the user has access to historical survey data, When they apply demographic filters for comparison, Then the system should accurately display trend visuals for each selected demographic segment, allowing for side-by-side analysis.

Behavioral Insights Integration

User Story: As a product manager, I want to segment feedback based on user behaviors so that I can adapt my product offerings and marketing messages to align with how different segments engage with my brand.
Description: The Behavioral Insights Integration requirement focuses on enabling marketers to segment audience feedback based on user behavior, including purchasing habits, product usage frequency, and engagement levels. This functionality allows users to correlate sentiments with specific behaviors, providing deeper insights into customer needs and preferences. By understanding how different segments behave, users can refine their marketing strategies, ensuring that their messaging aligns with customer interactions. This requirement will be crucial in enhancing the overall effectiveness of marketing efforts and improving conversion rates.
Acceptance Criteria: Marketer uses Behavioral Insights Integration to segment audience feedback during a campaign analysis meeting.

Given the marketer has access to audience feedback data, when they apply the behavioral filters for purchasing habits, Then the system should display segmented insights related to purchase frequency for the selected demographic.

A marketer applies filters to a survey designed for product usage frequency, aiming to gather specific behavioral insights.

Given the survey is created with behavioral targeting filters, when the survey is sent out to users based on their product usage frequency, Then the collected responses should reflect insights specific to high, medium, and low usage categories.

Analyzing sentiment data during a quarterly review, marketers wish to correlate sentiment with customer engagement levels.

Given the sentiment data is available, when the marketer selects the engagement level filter, Then the system should provide a report showing how different engagement levels correspond with positive or negative sentiments.

Marketer attempts to optimize a marketing strategy based on behavioral insights from customer feedback.

Given that the behavioral insights have been generated, when the marketer reviews the insights report, Then they should identify at least three suggested changes to the marketing strategy based on the displayed audience behavior correlations.

During a product launch, the marketing team uses behavioral insights to fine-tune their messaging.

Given the messaging is drafted, when the team applies behavioral insights filters for demographics, Then the messaging adjustments should reflect the interests and needs of the targeted segments, as recommended by the insights.

A user wants to export segmented audience insights for a stakeholder presentation.

Given the user has completed the segmentation, when they select the export option, Then the exported document should include accurate and detailed segmented insights based on behavioral patterns, formatted for presentation.

Real-time Feedback Alerts

User Story: As a marketer, I want to receive real-time alerts on sentiment changes so that I can quickly adapt my strategies and optimize engagement with my target audience.
Description: The Real-time Feedback Alerts requirement facilitates the immediate notification of users when significant sentiment shifts occur within targeted groups or demographics. This functionality will enable users to react promptly to changes in audience sentiment, allowing for agile adjustments in marketing strategies and communication efforts. By providing these alerts, the system ensures that marketers are always aware of emerging trends and can capitalize on positive sentiment while addressing negative feedback swiftly. Implementing this requirement enhances overall responsiveness and adaptability to market dynamics.
Acceptance Criteria: Real-time alerts for sentiment shift in a targeted demographic segment during a product launch campaign.

Given a significant sentiment shift occurs in a targeted demographic, When the alert system triggers an alert, Then the user receives an immediate notification via the alert system.

Monitoring emotional changes in consumer feedback after a marketing campaign adjustment.

Given the marketing team adjusts their campaign strategy, When the emotional sentiment in consumer feedback changes beyond a set threshold, Then the system generates an alert to notify the marketing team.

Receiving notifications for positive sentiment spikes during a promotional event.

Given there is a spike in positive sentiment from a specific group during a promotional event, When this spike occurs, Then the user receives a real-time alert detailing the increase in positive sentiment.

Evaluating feedback trends over a two-week period to assess ongoing sentiment.

Given feedback has been gathered over two weeks, When a significant trend in negative sentiment is detected, Then the system alerts the user with a summary of the trend along with actionable insights.

Daily summary of sentiment shifts in key demographic segments for the marketing team.

Given the end of the day, When the report generation process runs, Then the marketing team receives a daily summary report highlighting any significant sentiment shifts within key demographics.

Real-time feedback on product feature reception from beta users.

Given the beta testing period for a new feature, When users provide feedback that indicates a sentiment shift, Then the product team receives immediate notifications regarding the feedback sentiment.

Integration of sentiment alerts with team collaboration tools.

Given a significant sentiment shift occurs, When the alert is triggered, Then a notification is sent to the team’s collaboration tool, ensuring all members are informed instantly.

Actionable Insights Dashboard

User Story: As a data analyst, I want an interactive dashboard that displays segmented feedback data visually so that I can quickly understand the insights and make informed decisions.
Description: The Actionable Insights Dashboard requirement aims to create an intuitive visual representation of segmented feedback data, allowing users to easily interpret and act on insights derived from the feedback. This dashboard will showcase key metrics, trends, and comparisons among different segments, enabling users to make informed decisions at a glance. By streamlining the data visualization process, this feature will enhance users' ability to derive actionable strategies from complex data sets, ultimately improving decision-making and strategic planning.
Acceptance Criteria: User accesses the Actionable Insights Dashboard to review segmented feedback from a recent marketing campaign targeting millennials vs. Gen Z.

Given that the user has logged into SentiScan and navigated to the Actionable Insights Dashboard, when they select the feedback segment for millennials, then the dashboard should display metrics such as response rates, sentiment scores, and engagement levels associated with that demographic.

Marketer wants to compare sentiment scores from two different campaigns directed at different audience segments in the Actionable Insights Dashboard.

Given that the user selects two distinct campaigns within the dashboard, when the user initiates a comparison, then the dashboard should visually present side-by-side sentiment scores, including a clear indication of which campaign performed better for each segment.

User aims to analyze trends in feedback over the past month using the Actionable Insights Dashboard.

Given that the user selects a one-month timeframe and a specific audience segment, when the user clicks 'Apply,' then the dashboard should display an accurate graphical representation of trends, including at least three key metrics like average sentiment score, volume of feedback, and percentage of positive responses over that period.

Analyst examines feedback data in the Actionable Insights Dashboard to identify areas for improvement based on user sentiment.

Given that the user is viewing the feedback data, when they hover over key metrics, then the dashboard should display contextual tooltips that offer deeper insights and suggested actions based on the sentiment analysis performed.

User wants to filter feedback based on demographic attributes in the Actionable Insights Dashboard to gather targeted insights.

Given that the user has applied demographic filters (e.g., age, location), when the user views the segmented results, then the dashboard should only display feedback data that matches the applied filters, ensuring relevance and actionable insights.

User intends to set up alerts for significant shifts in sentiment as shown in the Actionable Insights Dashboard.

Given that the user is on the dashboard, when they configure an alert threshold for sentiment shifts, then the system should notify the user via email or in-app notification whenever those thresholds are exceeded in real-time.

Custom Survey Templates

User Story: As a marketer, I want to create and save custom survey templates so that I can collect more relevant feedback from specific audience segments and enhance my research effectiveness.
Description: The Custom Survey Templates requirement allows users to create and save tailored survey templates that align with specific demographic or behavioral segments. By providing users with the ability to customize their surveys, this feature ensures that the feedback collected is not only relevant but also contextually rich. Users can design surveys that resonate with distinct audience characteristics, leading to higher response rates and more meaningful insights. This requirement plays an essential role in maximizing the value of the feedback collected through SentiScan.
Acceptance Criteria: Creating a New Survey Template for a Specific Demographic

Given a user is logged into SentiScan, when they navigate to the survey creation section and select 'Create New Template', then they can customize survey questions based on chosen demographics such as age, gender, and location, ensuring that the template can be saved for future use.

Saving Customized Survey Templates

Given a user has created a survey template, when they click the 'Save Template' button, then a confirmation message should appear indicating that the template has been successfully saved and should be retrievable from the 'My Templates' section.

Editing Existing Survey Templates

Given a user is in the 'My Templates' section, when they select an existing template and click 'Edit', then they can modify the survey questions and demographic selections, and upon saving, the updates should reflect in the template list.

Deleting Unused Survey Templates

Given a user is viewing their saved survey templates, when they select a template and choose the 'Delete' option, then a confirmation prompt should appear, and upon confirming, the template should be removed from the list without any errors.

Sharing Survey Templates with Team Members

Given a user has created a survey template, when they select the 'Share Template' option and enter an email address, then the intended recipient should receive a notification with a link to access the shared template.

Previewing Survey Templates Before Launching

Given a user has created a survey template, when they click on 'Preview', then they should see how the survey will appear to respondents, including all questions and demographic filters, without any layout issues.

Analytics and Insights for Customized Surveys

Given a user has deployed a customized survey, when they view the performance analytics, then they should see response rates and sentiment analysis segmented by the demographics defined in the survey setup.

Real-Time Feedback Notifications

Real-Time Feedback Notifications alert users immediately when new responses come in through polls and surveys. This feature ensures that marketers are always informed of audience sentiment as it develops, allowing for rapid response to any emerging issues and making data-driven adjustments to campaigns promptly.

Requirements

Instant Notification System

User Story: As a marketing manager, I want to receive immediate notifications when new survey responses are submitted so that I can quickly adapt my campaign based on real-time audience feedback.
Description: The Instant Notification System is designed to send real-time alerts to users as soon as new responses are received from polls and surveys. This feature integrates smoothly with the existing platform, using push notifications and webhooks to ensure that marketers and analysts are immediately aware of changes in audience sentiment. The primary benefit is that it allows for rapid awareness of emerging issues or trends, enabling timely data-driven decisions and adjustments to marketing campaigns. The system ensures that all responses are captured and communicated efficiently, reinforcing the product’s capability to provide actionable insights and enhance user engagement.
Acceptance Criteria: User receives a push notification on their mobile device when new survey responses are submitted, while they are actively logged into the SentiScan platform.

Given a user is logged into the SentiScan platform, when a new response is received from a survey, then the user should receive a push notification within 5 seconds of the response being recorded.

User views the dashboard and notices an alert indicating new poll responses, enabling them to analyze the sentiment immediately.

Given a user is on the SentiScan dashboard, when a new poll response comes in, then an alert should be displayed on the dashboard that highlights the number of new responses and their sentiment trends within 10 seconds.

Marketer receives an email alert summarizing the latest feedback from polls and surveys on a daily basis to monitor ongoing campaigns.

Given it is the end of the day, when the daily summary of responses is generated, then the marketer should receive an email containing the total number of responses, key sentiment insights, and any significant trends identified.

User sets up a webhook to trigger a third-party application whenever a new positive sentiment response is received, facilitating immediate action.

Given a user has configured a webhook for positive sentiment alerts, when a new positive sentiment response arrives, then the webhook should trigger the third-party application with the relevant data within 5 seconds.

User wishes to customize the type of notifications they receive (e.g., only significant changes in sentiment or all responses), making adjustments in the settings.

Given a user is on the notification settings page, when they select their preferences and save changes, then only the specified types of notifications should be sent to the user, effective immediately.

The system experiences a temporary downtime and subsequently restores functionality for sending notifications.

Given the notification system was down for maintenance, when it is restored, then all missed notifications should be sent to users within 5 minutes of being back online.

User utilizes a feedback filter option to receive notifications based on specific keywords related to survey responses.

Given a user has set keyword filters, when a new response containing those keywords is submitted, then the user should receive an immediate notification about that response.

Customizable Alert Settings

User Story: As a data analyst, I want to customize my alert settings so that I only receive notifications for the most relevant feedback, allowing me to focus on critical insights without being overwhelmed by information.
Description: The Customizable Alert Settings provide users with the ability to tailor their notification preferences based on the type of feedback and urgency. Users can select which surveys or polls generate alerts, the frequency of notifications, and the medium through which alerts are received (e.g., email, SMS, in-app). This feature enhances user experience by allowing individuals to prioritize what is most relevant to their campaigns, thus reducing notification fatigue while ensuring they remain engaged with significant changes in sentiment. This not only contributes to a more efficient workflow but also ensures that vital information is not overlooked, empowering users to make informed decisions promptly.
Acceptance Criteria: User customizes alert settings to receive notifications for specific polls and sets preferences for frequency and medium.

Given the user has access to the alert settings, when they select specific surveys and configure the notification frequency and medium, then those preferences should be saved and trigger alerts as per the user's selections.

User receives an alert in the chosen medium when feedback is submitted for a poll they configured.

Given that a user has set up alerts for a specific poll and has selected email as the notification medium, when a new response is received for that poll, then the user should receive an email alert promptly upon submission.

User adjusts their alert settings to reduce the frequency of notifications and validates changes.

Given a user is currently receiving frequent alerts for polls, when they change their notification frequency to 'weekly', then they should confirm that the changes are applied and receive alerts only once a week thereafter.

User checks alert history to confirm they received notifications as configured.

Given the user has previously customized their alert settings, when they access the alert history section, then they should see a log of their received alerts that aligns with their configured preferences (type, frequency, and medium).

Multiple users set different alert preferences for a shared poll and validate simultaneous notification delivery.

Given that multiple users have access to a shared poll and have set individual alert preferences, when a new response is submitted, then all relevant users should receive notifications according to their specific settings without delays.

User opts out of specific alerts and validates successful removal from the notification system.

Given the user wishes to stop receiving alerts for a particular survey, when they opt out and save their settings, then they should no longer receive notifications for that survey henceforth, confirmed through system acknowledgment and alert history.

Sentiment Trend Analysis

User Story: As a market researcher, I want to visualize sentiment trends over time so that I can identify patterns and the effectiveness of my marketing campaigns, leading to strategic improvements.
Description: The Sentiment Trend Analysis feature offers users insights into how customer sentiment is evolving over time by graphically displaying trends derived from recent feedback. Integrated with SentiScan’s data visualization tools, this functionality allows users to track the impact of different campaigns over periods and recognize any shifts in consumer attitudes. By visualizing sentiment data, users can identify long-term patterns, correlations with marketing efforts, and areas needing improvement. This feature is crucial for enabling informed strategic adjustments and fostering a deeper understanding of audience behavior, further enhancing the overall analytics capability of the product.
Acceptance Criteria: Users can view real-time sentiment trends after implementing a new marketing campaign, allowing them to compare sentiments pre- and post-campaign.

Given that a marketing campaign has been launched, when users access the Sentiment Trend Analysis feature, then they should see a graphical representation of sentiment data before and after the campaign showing at least 3 distinct data points for comparison.

Marketers want to monitor shifts in consumer sentiment over a defined period to evaluate the effectiveness of their recent ads and promotions.

Given that sentiment data spans over a timeline, when users select a date range in the Sentiment Trend Analysis dashboard, then the displayed trend graph should accurately reflect sentiment changes within that specified period and provide clear labels for the emotional sentiment detected.

Analysts need to view correlations between specific marketing actions and shifts in consumer sentiment to make data-driven decisions for future campaigns.

Given a set of marketing actions and their corresponding sentiment data, when users analyze the Sentiment Trend Analysis, then they should be able to filter sentiment data by specific campaigns and see visual indicators of correlation, including at least 5 data highlights to support their analysis.

Marketing teams require a clear understanding of long-term consumer sentiment patterns to inform strategic adjustments and improve engagement strategies.

Given a minimum of two weeks' worth of sentiment data collected, when users generate a trend analysis report, then the report should include at least three long-term patterns with predicted sentiment trends and actionable insights provided in an easy-to-understand format.

Users expect to receive immediate alerts when significant shifts in sentiment occur, impacting ongoing campaigns.

Given that users have set up their alert preferences, when a sentiment shift occurs that meets or exceeds the predefined thresholds, then the system should notify the users via their chosen method (e.g., email, SMS), with details of the sentiment change and its percentage.

New users need guidance on how to effectively utilize the Sentiment Trend Analysis feature to gain the most valuable insights.

Given that a user accesses the Sentiment Trend Analysis for the first time, when they request help or tutorials, then the system should provide detailed, step-by-step guidance, along with example dashboards and common use cases to facilitate understanding and ease of use.

Automatic Feedback Summarization

User Story: As a product manager, I want to receive automatic summaries of consumer feedback so that I can quickly understand the overall sentiment without having to review each individual response, which saves me time and increases my focus on strategic planning.
Description: The Automatic Feedback Summarization feature leverages AI to distill incoming responses into coherent summaries, helping users quickly grasp the sentiment landscape without sifting through numerous individual replies. By aggregating data Points and highlighting key sentiments, this feature enhances user efficiency and comprehension. Users can receive daily or weekly summaries that highlight emerging topics, common sentiments, and overall satisfaction ratings. This capability is essential for busy marketers who need concise insights at their fingertips, thereby improving decision-making speed and clarity.
Acceptance Criteria: Automatic Feedback Summarization for Daily Summaries

Given that the user has opted for daily summaries, when new feedback responses are received, then the system should automatically generate a summary report that includes emerging topics, common sentiments, and overall satisfaction ratings by 9 AM every day.

Automatic Feedback Summarization for Weekly Summaries

Given that the user has chosen weekly summaries, when feedback responses accumulate over the week, then the system should generate a clear summary that highlights key sentiments and trends observed throughout the week before Monday noon.

Real-Time Response Aggregation

Given that responses are coming in from polls or surveys, when new responses are submitted, then the summarization feature should update the existing summary within 5 minutes to reflect the latest sentiments and data points.

Error Handling in Summarization

Given that there may be instances of system errors or data inconsistencies, when the summarization algorithm encounters an issue, then the system will alert the user within one minute and log the error for review.

Sentiment Analysis Accuracy

Given that the feedback contains varied responses, when the summarization feature processes the data, then at least 85% of the sentiment classifications should be accurate compared to manual annotations during testing.

User Customization of Summaries

Given that users may want specific metrics in their summaries, when setting up their preferences, then users should have the option to choose which key topics or metrics they want highlighted in their summaries.

User-Friendly Summary Format

Given that users are busy marketers, when they receive a summary, then the summary should be presented in a clear, concise format that is easy to read, featuring bullet points and visuals where applicable.

Improved Dashboard Integration

User Story: As a user, I want to see real-time notifications integrated into my dashboard so that I can monitor feedback at a glance and respond swiftly to changes in audience sentiment without navigating away from my main workspace.
Description: The Improved Dashboard Integration requirement focuses on enhancing the user interface of SentiScan’s dashboard to incorporate real-time feedback notifications seamlessly. This will include visual indicators for new responses and sentiment changes, ensuring users have immediate insights visible at a glance. This integration aims to provide a centralized view where users can track all key performance indicators related to consumer sentiment, allowing for a more efficient decision-making process. The goal of this requirement is to amplify user engagement by dynamically updating the dashboard according to incoming data, making the information more actionable and accessible.
Acceptance Criteria: User receives immediate notifications on the dashboard when new survey responses are submitted during a live campaign.

Given that a user is logged into the SentiScan dashboard, when new survey responses are submitted, then the dashboard should display a visual notification within 5 seconds.

Users can see visual indicators on the dashboard that reflect changes in sentiment from survey responses.

Given that there are new responses in the survey, when the sentiment changes based on the incoming data, then the sentiment indicator on the dashboard should update within 2 seconds.

The dashboard allows users to filter responses by date, sentiment, and type of survey for better analysis.

Given that a user selects filtering options on the dashboard, when the user applies the filters, then the displayed responses should match the selected filter criteria accurately.

The system reliably logs and retains all new feedback notifications for future access.

Given that new feedback notifications are received, when the user checks the notification log, then all notifications should be listed accurately with timestamps.

Users can customize the types of feedback alerts they want to receive based on specific metrics.

Given that a user accesses the preferences section of the dashboard, when they select the desired feedback notification settings, then only the chosen metrics should trigger notifications.

Dashboard refresh rates ensure that users always have access to the latest data without manual intervention.

Given that a user is on the dashboard, when they remain on the page for a set period, then the system should automatically refresh data every 10 seconds without losing user inputs or filters.

Users are able to receive alerts via email or SMS for critical sentiment shifts identified in real-time.

Given that a user has opted in for email/SMS notifications, when there is a significant change in sentiment, then the user should receive an alert within 5 minutes of the change being detected.

Interactive Feedback Reports

Interactive Feedback Reports transform raw survey data into engaging presentations that can be easily shared with teams and stakeholders. This feature includes visual elements like graphs and charts, making it easier for users to communicate insights and recommendations derived from feedback in a compelling narrative format.

Requirements

Dynamic Graph Generation

User Story: As a market analyst, I want to automatically generate graphs and charts from survey data so that I can present insights in a more engaging and understandable format to my team and stakeholders.
Description: The Dynamic Graph Generation requirement focuses on the ability to automatically create and update various types of graphs and charts based on the raw survey feedback data. This feature enhances the presentation of insights by employing visual representations that can be manipulated in real-time, allowing users to select different data filters and parameters. It is crucial for converting complex datasets into straightforward, easy-to-read visuals that communicate key insights effectively and engage stakeholders. The implementation will include a user-friendly interface for customization of graphs, ensuring that users can tailor the visuals to fit their narrative and audience needs. The expected outcome is a significant improvement in how insights are visualized and shared, leading to better data-driven decision-making.
Acceptance Criteria: User initiates a report generation after completing a survey analysis.

Given the user has completed a survey analysis, when they select the 'Generate Report' button, then a dynamic report with graphs reflecting the survey results should be produced in under 3 seconds.

User applies different filters to visualize specific subsets of data within the graphs.

Given the user is viewing the generated graphs, when they apply a filter (e.g., date range, demographic), then the graphs should update in real-time to reflect the filtered data without any delay greater than 1 second.

User customizes the appearance of the graphs to match their presentation style.

Given the user is in the customization interface, when they modify the graph styles (e.g., color scheme, chart type), then the graphs should visually update to reflect these changes correctly and instantly without needing to refresh the page.

User shares the interactive feedback report with team members via email.

Given the user has completed customization of the report, when they click the 'Share Report' button, then an email containing a link to the interactive report should be sent to the specified recipients, confirmed by the presence of a success message.

User exports the report data as a downloadable file.

Given the user has finalized their report, when they select the 'Export' feature, then a downloadable file (e.g., PDF or Excel) containing all graphs and underlying data should be created and made available for download within 10 seconds.

User provides feedback on the usability of the Dynamic Graph Generation feature.

Given the user has completed using the Dynamic Graph Generation feature, when they submit their feedback through the provided form, then the feedback should be recorded and stored in the feedback database for future analysis and improvements.

User views historical data trends through the generated graphs.

Given the user is exploring their data, when they select the option to view historical trends, then the graphs should display accurate trends over selected time periods, with clear labels and legends for interpretation.

Customizable Presentation Templates

User Story: As a marketing manager, I want to use customizable templates for my reports so that my presentations look consistent and professional across different stakeholders.
Description: The Customizable Presentation Templates requirement involves the creation of template designs that users can customize to present their survey data insights. This feature will offer a variety of styles and layouts that users can select and adapt according to their presentation needs. The templates will streamline the report generation process, ensuring consistency in branding and messaging across different reports and internal reviews. Users will have the ability to upload their logos, adjust color schemes, and rearrange content blocks, making it easier for professionals to create stunning presentations quickly. The outcome will be enhanced professionalism in reporting and a more efficient presentation workflow.
Acceptance Criteria: User selects a customizable template to generate a presentation from survey insights.

Given the user has access to the presentation templates, when the user selects a template, then the template should load with placeholder content that can be edited.

User uploads a logo to a selected presentation template.

Given the user is on the template editing interface, when the user uploads a logo, then the logo should be displayed in the designated area of the template and maintain its aspect ratio.

User customizes the color scheme of a presentation template.

Given the user is editing the template, when the user selects a new color scheme, then all template elements should update to reflect the new colors in real-time.

User rearranges content blocks within a presentation template.

Given the user is in the template editing mode, when the user drags and drops a content block, then the content block should move to the new position without compromising the layout integrity.

User saves a customized presentation template for future use.

Given the user is satisfied with the customizations made, when the user clicks the save button, then the customized template should be saved and available in the user's list of templates.

User generates a presentation from a customized template and shares it.

Given the user has completed the presentation, when the user clicks the share button, then the presentation should be exported in a shareable format (PDF or link) without errors.

Real-time Collaboration Features

User Story: As a team lead, I want to collaborate in real-time with my colleagues on feedback reports so that we can contribute our insights and finalize the reports more efficiently together.
Description: The Real-time Collaboration Features requirement enhances the existing report-building toolset by allowing multiple users to work on the same feedback report simultaneously. This feature will support live editing, chat, and comment functionalities to facilitate teamwork among different departments or groups. It is essential for fostering collaborative efforts in analyzing feedback and toggling insights and will empower users to harness collective knowledge quickly. The expected outcome is improved teamwork efficiency, reduced report delivery timelines, and better integrated insights from diverse perspectives.
Acceptance Criteria: Multiple users collaborate on an Interactive Feedback Report simultaneously, with each user editing different sections and receiving real-time updates on changes made by others.

Given multiple users are editing a report, when one user makes a change, then all other users should see the change reflected in real-time without needing to refresh the page.

Users utilize the chat functionality to discuss insights about survey results while working on the report.

Given users are collaborating on a report, when a user sends a message in the chat, then all users should receive the message instantly within the report interface.

Users can leave comments on specific sections of the report to provide feedback or ask questions regarding the displayed data.

Given a user is reading a report, when they add a comment to a section, then the comment should be visible to all collaborators and indicate which user left the comment.

Users can view a history of edits made to the report to track changes and revisions over time.

Given that users have edited a report, when they access the edit history feature, then they should see a log of all changes made, including timestamps and user information.

The system alerts users when someone else is editing a section they are currently viewing, preventing conflicting edits.

Given multiple users are working on the same report, when one user is editing a section, then other users should receive a notification indicating that the section is currently being edited by another user.

Users can invite new collaborators to the report at any time during the editing process.

Given a user wants to collaborate on a report, when they enter the email address of the new user and send an invite, then the new user should receive an email invitation to join the report editing session.

Automated Insights Generation

User Story: As a data analyst, I want the software to automatically generate insights from survey data so that I can quickly access key findings and focus on developing strategic recommendations.
Description: The Automated Insights Generation requirement involves the implementation of an AI-powered feature that analyzes survey data and produces summary insights automatically. This feature will utilize Natural Language Processing (NLP) to identify key trends, sentiments, and actionable recommendations without manual effort. Its integration within the Interactive Feedback Reports will enhance efficiency by providing quick access to pertinent insights and will free up analysts to focus more on strategy rather than data interpretation. The expected outcome will be faster report generation and more actionable intelligence derived from survey data.
Acceptance Criteria: Automated generation of insights from survey data collected after a marketing campaign review.

Given a dataset of survey responses from the marketing campaign, when the Automated Insights Generation feature processes the data, then it must produce a summary report highlighting key trends, sentiments, and actionable recommendations within 5 minutes of submission.

Sharing the automatically generated insights report with team members and stakeholders.

Given the generated insights report, when a user selects the share option, then the report must be successfully shared via email or a collaboration platform, with all visual elements intact and accessible to the recipients.

Validating the accuracy of the insights produced by the automated system.

Given a set of hand-analyzed survey data as a control, when the Automated Insights Generation feature generates insights, then the accuracy of the automated insights compared to the control should show an alignment of at least 90% on key trends and sentiments.

User interface for reviewing the automated insights before sharing.

Given that insights are generated, when a user accesses the Interactive Feedback Reports, then they should see an intuitive user interface allowing them to view, edit, or adjust insights and visual elements before final sharing.

Feedback loop for improving the automated insights generated over time.

Given user experiences and insights reports generated, when users provide feedback through the system, then the feedback mechanism must document and categorize user suggestions for enhancing the AI model and report features.

Integration of the automated insights with the live dashboard for real-time changes.

Given that sentiment shifts occur in the data, when these shifts are identified by the system, then the dashboard must automatically update to reflect the latest insights without manual input, ensuring information is real-time and relevant.

Training the AI model based on user feedback and survey outcomes.

Given that the automated insights feature is used, when users submit feedback regarding the relevance and accuracy of insights, then the system must utilize this feedback to retrain the AI model at regular intervals, ensuring continual improvement of the insights generated.

Export to Multiple Formats

User Story: As a project manager, I want to export reports in different formats so that I can share insights with stakeholders using their preferred formats for easier dissemination and use.
Description: The Export to Multiple Formats requirement allows users to export their completed Interactive Feedback Reports into various file formats such as PDF, PPT, and CSV. This feature is critical for ensuring that reports can be easily shared and utilized across different platforms and for various stakeholder needs. Users will be able to select the desired output format and ensure that all visual elements and data are maintained in the export, thus simplifying the distribution process. The outcome will facilitate wider sharing of insights and encourage utilization of reports in different contexts, from meetings to email communications.
Acceptance Criteria: User needs to export an Interactive Feedback Report as a PDF for a presentation to stakeholders.

Given that the user has completed an Interactive Feedback Report, when they select the option to export as PDF, then the system should generate a PDF file that preserves all visual elements and data accurately.

A user wants to share survey results with their team via email in CSV format for data analysis.

Given that the user has selected the CSV export option, when they initiate the export, then the system should create a CSV file that correctly formats all the survey data and is downloadable without errors.

Marketers need to present survey findings in a team meeting using a PowerPoint presentation.

Given that the user has completed an Interactive Feedback Report, when they choose to export it as a PPT, then the exported presentation must contain all relevant graphs, charts, and commentary in a user-friendly layout.

A user needs to verify the accuracy of exported reports across different formats post-export.

Given that the user has exported the report in various formats, when they open each of these files, then all key visual elements and data should be intact and accurate across PDF, PPT, and CSV formats.

A project manager requires a quick overview of survey results for an upcoming client meeting.

Given that the project manager selects the PDF export option, when they export the report, then the PDF should include a summary page highlighting key findings and insights for quick reference.

After exporting a report in CSV format, a user wants to ensure compatibility with Excel for data manipulation.

Given that the user has exported the report as a CSV, when they open the file in Excel, then all data should be correctly aligned in columns and rows without any loss of information.

User Access Management

User Story: As an admin, I want to set user roles and permissions so that I can control access to sensitive feedback reports and ensure that only authorized personnel can view or edit them.
Description: The User Access Management requirement focuses on providing role-based access controls to the Interactive Feedback Reports feature. This means users will have different levels of access depending on their roles within the organization, ensuring that sensitive data is protected while allowing collaboration among team members. This feature is crucial for maintaining data security and integrity while enabling functionality for collaboration. With the appropriate access levels set, users can confidently share insights without the risk of misusing or mishandling sensitive information. The expected outcome is to streamline collaboration while safeguarding data, fostering a secure environment for report generation.
Acceptance Criteria: Role-based access controls for Interactive Feedback Reports for Admin users.

Given an Admin user, when they log into the system, then they should have full access to create, edit, and delete Interactive Feedback Reports.

Role-based access for Team Lead users viewing Interactive Feedback Reports.

Given a Team Lead user, when they access the Interactive Feedback Reports, then they should be able to view and edit the reports but not delete them.

Role-based access restrictions for Analyst users accessing sensitive feedback data.

Given an Analyst user, when they attempt to access the Interactive Feedback Reports that contain sensitive data, then they should receive an access denied message if their role does not permit such access.

Auditing access to Interactive Feedback Reports for compliance purposes.

Given multiple users accessing the Interactive Feedback Reports, when a report is accessed, then an audit log should be created capturing the user ID, timestamp, and action performed.

Notification system for role changes within User Access Management.

Given a change in user roles within the system, when the role is updated, then an automated notification should be sent to the user informing them of their new access rights.

Testing the performance of role-based access controls under load.

Given a scenario where multiple users of different roles are attempting to access Interactive Feedback Reports simultaneously, then the system should maintain performance and not experience any access delays or failures.

User interface to manage access roles for Interactive Feedback Reports.

Given an Admin user, when they navigate to the User Access Management interface, then they should have the ability to assign and update roles for other users without errors.

Sentiment Trend Analysis

User Story: As a marketing strategist, I want to analyze sentiment trends over time so that I can assess the impact of our marketing campaigns and adjust our strategies accordingly.
Description: The Sentiment Trend Analysis requirement enables users to visualize sentiment over time based on the feedback data collected. This feature will allow users to generate graphs that showcase how consumer sentiments have shifted throughout specified periods. By integrating this analysis within the Interactive Feedback Reports, users will obtain deeper insights into the effectiveness of marketing strategies and can pinpoint specific campaigns or events that triggered shifts in consumer sentiment. The expected outcome is to provide users with actionable insights on engagement effectiveness and areas for improvement.
Acceptance Criteria: As a marketing analyst, I want to generate a sentiment trend analysis report after conducting a survey, so that I can visualize the shifting consumer sentiments over the past quarter in response to our marketing campaigns.

Given that I have collected survey data, when I generate the sentiment trend analysis report, then the report should display a line graph indicating sentiment changes over time with indicators for specific campaigns and events.

As a product manager, I need to present the findings from our sentiment analysis report during a team meeting, to illustrate how consumer perceptions have changed over time based upon our recent advertisements.

Given the sentiment trend analysis data, when I view the interactive feedback report, then I should be able to see at least three visualizations (graphs or charts) that effectively present the sentiment data for different time periods and marketing strategies.

As a stakeholder, I want to easily share sentiment trend analysis insights with my team, facilitating collaborative decision-making based on the feedback data.

Given an interactive feedback report that includes sentiment trend analysis, when I export the report, then it should retain all visual elements and be easily shareable in PDF or PPT format without losing data integrity.

As a data analyst, I want to filter sentiment trend analysis data by specific demographics (age, location, etc.), so that I can better understand how different consumer segments perceive our brand over time.

Given the sentiment trend analysis feature, when I apply demographic filters and generate the report, then the resulting data visualizations should accurately reflect the selected demographic segments and their sentiment changes.

As an insights manager, I want to receive alerts on significant shifts in sentiment trends, so that I can take timely actions based on customer feedback.

Given the sentiment trend analysis integration, when there is a significant positive or negative shift in sentiment detected, then an alert notification should be sent to my dashboard and via email to inform me of the change.

As a user, I want to navigate through the sentiment trend analysis reports efficiently, so that I can quickly find relevant insights during my analysis sessions.

Given an interactive feedback report, when I utilize the search and filter functionalities, then I should be able to access specific sections of the sentiment analysis report within three clicks, ensuring ease of use and efficient navigation.

As a senior marketer, I want to compare sentiment trends against our competitors to assess our market position, so that I can make strategic decisions based on consumer sentiment insights.

Given the sentiment trend analysis tool, when I select the competitor comparison feature, then the report should generate visual graphs that illustrate sentiment trends for both our brand and the identified competitors side by side for the same time periods.

Poll Engagement Incentives

Poll Engagement Incentives provide users with the option to offer rewards for participating in surveys, such as discounts or exclusive content. This feature boosts participation rates, allowing marketers to gather a larger range of insights and make more data-driven decisions while also enhancing the consumer experience.

Requirements

Reward Structure Configuration

User Story: As a marketer, I want to configure various reward structures for survey participants so that I can incentivize higher engagement and gather more meaningful insights into consumer sentiment.
Description: This requirement involves enabling users to create and customize reward structures for survey participation, including options such as discounts, cashback, or exclusive content access. It enhances user engagement by allowing marketers to tailor incentives based on their target audience's preferences, thereby maximizing participation rates in surveys. This functionality integrates seamlessly with existing survey creation tools within SentiScan, providing marketers with the flexibility to design effective campaigns that encourage consumer input. Implementation will include a user-friendly interface for setting up rewards, tracking redemption rates, and analyzing the impact on survey participation over time.
Acceptance Criteria: Configuration of a Reward Structure for a Survey Campaign

Given a user is logged in to SentiScan, when they navigate to the survey creation tool and select the option to configure rewards, then they must be able to define a reward structure that includes at least one type of reward (discount, cashback, exclusive content).

Tracking Redemption Rates for Survey Rewards

Given the user has configured a reward structure for their survey, when participants redeem their rewards, then the system should track and display the cumulative redemption rate in real-time on the user dashboard.

Analyzing Participation Impact Post-Rewards Implementation

Given a survey has been conducted with a reward structure in place, when the survey period has ended, then the user should be able to generate a report that compares participation rates before and after the implementation of the reward structure.

User Interface for Reward Configuration

Given a user is in the reward configuration interface, when they attempt to add multiple reward options, then they should be able to do so without system errors and with clear visual feedback on the rewards added.

Displaying Reward Options to Survey Participants

Given a survey with rewards configured, when participants are presented with the survey, then they should see a clear and compelling description of the reward options available for their participation.

Customizing Rewards Based on Target Audience

Given a user is creating a reward structure, when they select demographic filters for their target audience, then the system should allow or suggest rewards that are tailored to those demographics based on prior engagements.

Incentive Tracking System

User Story: As a data analyst, I want to track the redemption and effectiveness of survey incentives so that I can analyze the ROI and improve future marketing campaigns based on consumer behavior.
Description: The Incentive Tracking System requirement focuses on developing a backend mechanism that tracks the issuance and redemption of rewards associated with survey participation. This system will allow marketers to monitor which incentives are most effective, track user engagement levels, and assess the return on investment (ROI) of incentive strategies. Integrating this tracking system with analytics dashboards will enable users to visualize data trends and make informed adjustments to their incentive offerings. The functionality is crucial for optimizing marketing campaigns and ensuring that rewards are leading to actual insights.
Acceptance Criteria: Incentive Monitoring for Survey Engagement

Given a user has launched a survey with incentives, when an incentive is issued, then the system should log the issuance details including user ID, incentive type, and timestamp.

Incentive Redemption Tracking

Given a user has redeemed an incentive, when they complete the redemption process, then the system should update the user’s profile to reflect the redemption and deduct the corresponding incentive from the available balance.

Effectiveness Analysis of Incentives

Given multiple surveys with different incentives, when the survey period ends, then the system should generate a report showing the participation rates correlated with each incentive type.

User Engagement Level Assessment

Given a set of surveys conducted over a specific period, when analyzed, then the system should provide metrics on user engagement levels based on participation and incentive redemption.

Dashboard Integration of Incentive Data

Given the user accesses the analytics dashboard, when viewing incentive-related data, then the dashboard must display real-time statistics for issued and redeemed incentives in an easy-to-read format.

ROI Calculation of Incentive Strategies

Given a set of survey results and associated incentives, when the user requests ROI analysis, then the system should calculate and present the ROI for each incentive strategy based on user engagement outcomes and costs.

Automated Notification System

User Story: As a survey participant, I want to receive notifications about rewards I have earned so that I am aware of my incentives and can redeem them easily for added value.
Description: The Automated Notification System requirement entails creating a feature that sends notifications to users when they qualify for a reward after participating in a survey. This system will enhance user experience by ensuring participants are promptly informed about their incentives, thereby increasing satisfaction and perceived value. It will work in conjunction with the reward structure configuration, allowing marketers to customize notification content based on different reward types. Implementing a user-friendly opt-in/out preference will ensure compliance with privacy regulations while fostering direct communication with participants.
Acceptance Criteria: User receives a notification after completing a survey and qualifying for a reward.

Given a user has completed a survey, when they qualify for a reward, then they should receive a notification via their preferred communication channel (email or in-app).

Notification content is customized based on reward type.

Given the reward structure is configured with different types of incentives, when a user qualifies for a reward, then the notification content should reflect the specific reward type they are receiving.

User opts in to receive reward notifications.

Given a user is accessing their account settings, when they choose to opt-in for reward notifications, then their preference should be saved successfully and reflected in their notification settings.

User opts out of receiving reward notifications.

Given a user is accessing their account settings, when they choose to opt-out of reward notifications, then the system should remove them from the notification list successfully and confirm the change.

Notification is sent within a specific time frame after survey completion.

Given a user has completed a survey and qualifies for a reward, when the notification system triggers, then the user should receive their notification within 10 minutes after survey completion.

Notification system complies with privacy regulations.

Given a user has opted in to receive notifications, when the notification is triggered, then it must adhere to relevant privacy regulations, ensuring data protection and user consent is upheld.

Survey Participation Dashboard

User Story: As a marketer, I want to access a dashboard that shows my survey participation metrics so that I can analyze the success of my incentive strategies and optimize my campaigns effectively.
Description: This requirement centers on designing an interactive dashboard specifically for marketers that consolidates survey participation metrics and incentive performance data. By visualizing data such as participation rates, reward redemptions, and overall engagement, marketers can quickly assess the effectiveness of their incentive strategies and make data-driven decisions. The dashboard will integrate with existing analytics tools within SentiScan, providing a comprehensive view of survey performance that aligns with marketers' goals for engagement and sentiment analysis. It is a critical element in empowering users to refine their campaigns in real-time.
Acceptance Criteria: Survey Participation Dashboard Visualization and Metrics Tracking

Given a marketer accesses the Survey Participation Dashboard, When they view the dashboard, Then they should see visual representations of participation rates, reward redemptions, and engagement metrics over time.

Integration with Existing Analytics Tools

Given that the Survey Participation Dashboard is developed, When it is integrated with existing analytics tools within SentiScan, Then marketers should be able to pull data seamlessly without errors or data discrepancies.

Real-Time Data Updates for Engagement Strategies

Given a marketer is utilizing the Survey Participation Dashboard, When new survey participation data is collected, Then the dashboard should refresh and reflect the latest metrics within 5 seconds.

User Access and Role Permissions Management

Given that the Survey Participation Dashboard is live, When marketers log in with different roles, Then they should only see permissive data relevant to their access level (e.g., admin vs. user) without data leakage.

User Training and Documentation for Dashboard Use

Given the completion of the Survey Participation Dashboard, When users access the training materials, Then they should be able to understand how to navigate and utilize the dashboard features effectively within 30 minutes.

Feedback Mechanism for Continuous Improvement

Given the active use of the Survey Participation Dashboard, When marketers provide feedback on functionality, Then a feedback collection mechanism should be in place, allowing users to submit suggestions easily.

Performance Benchmarking Against Industry Standards

Given the functionality of the Survey Participation Dashboard, When the metrics are reviewed, Then they should include performance benchmarks that allow comparison against industry standards for survey engagement.

Feedback Mechanism

User Story: As a survey participant, I want to provide feedback on the rewards I receive so that my opinions can help influence future survey incentives and improve the overall experience.
Description: This requirement includes the development of a feedback mechanism that allows survey participants to provide insights on the rewards they receive. This feature is designed to capture qualitative data on participant satisfaction and incentive effectiveness. Providing a feedback tool not only enhances user engagement but also helps marketers understand consumer preferences better and refine their strategies. The integration of feedback mechanisms into the overall survey process will ensure that insights about participant experiences are actionable and directly inform future incentive offerings.
Acceptance Criteria: Survey participant provides feedback on received reward after completing a poll.

Given a participant completes a survey and receives a reward, when the participant accesses the feedback mechanism, then they should be able to submit qualitative feedback about their satisfaction with the reward.

Marketing team reviews feedback data from participants regarding incentive effectiveness.

Given multiple survey participants have provided feedback on their rewards, when the marketing team views the aggregated feedback report, then they should be able to see average satisfaction ratings and common themes in qualitative feedback within a defined time frame.

System notifies participants about the completion of their feedback submission.

Given a participant submits their feedback on the reward, when the feedback submission is successful, then the participant should receive a notification confirming their feedback has been recorded.

Feedback mechanism is easily accessible to participants during the survey.

Given the participant is taking the survey, when they finish, then the feedback mechanism should be prominently displayed with clear instructions on how to provide feedback.

Incentives offered in the survey influence participants' willingness to provide feedback.

Given that survey participants receive varying types of incentives, when analyzing feedback submission rates, then the data should indicate an increase in submissions correlating with more attractive rewards.

Feedback mechanism accurately captures participant input for further analysis.

Given a participant provides feedback, when they submit their responses, then the system should store the feedback accurately without data loss and categorize it correctly for future analysis.

Feedback Integration Hub

Feedback Integration Hub allows users to consolidate survey responses with existing sentiment analysis data. By providing a comprehensive view of feedback alongside market trends, this feature enables marketers to correlate audience sentiment with product performance, optimizing strategies based on holistic insights.

Requirements

Unified Data Dashboard

User Story: As a market analyst, I want to view survey responses alongside sentiment analysis data so that I can identify correlations and make informed decisions on marketing strategies.
Description: The Unified Data Dashboard requirement entails the creation of a central visual interface that integrates survey responses and sentiment analysis data. This dashboard will allow users to visualize trends, track changes in sentiment over time, and easily navigate through various metrics. With intuitive graphics and customization options, it enhances data accessibility, enabling users to quickly derive insights from a comprehensive view of feedback and market trends. This integration ensures marketers can efficiently correlate audience sentiment with product performance, facilitating data-driven decision-making. The expected outcome is an improved understanding of consumer attitudes in relation to product offerings, ultimately optimizing marketing strategies.
Acceptance Criteria: User accesses the Unified Data Dashboard to view consolidated survey responses and sentiment analysis data for a specific product over the last quarter.

Given the user has logged into the SentiScan platform, When they select a product and the last quarter's data range, Then the Unified Data Dashboard should display a visual representation of both survey responses and sentiment analysis metrics in an integrated format.

Marketing analyst customizes the dashboard to focus on specific sentiment trends related to product performance.

Given the analyst is on the Unified Data Dashboard, When they apply filters for specific sentiment trends and product performance metrics, Then the dashboard should update in real-time to reflect the changes and display relevant data visualizations.

User wants to export the data from the Unified Data Dashboard for further analysis.

Given the user is viewing the data on the Unified Data Dashboard, When they choose to export the data, Then the system should allow them to download the data in multiple formats (CSV, PDF), ensuring all displayed information is included.

User navigates the dashboard to compare sentiment trends between two different products.

Given the user selects two products on the dashboard, When they initiate a comparison, Then the dashboard should present a side-by-side analysis of the sentiment trends and survey responses for both products in an easily interpretable format.

User receives a notification alerting them about a significant decrease in positive sentiment for their product.

Given the user has enabled alert features in the SentiScan platform, When a significant drop in positive sentiment is detected, Then the system should send an instant notification to the user detailing the change and the relevant time frame.

User explores historical sentiment data to identify long-term trends in consumer attitudes.

Given the user selects the historical view option on the Unified Data Dashboard, When they set a desired date range, Then the dashboard should accurately display historical sentiment data trends alongside survey responses for that period, complete with relevant visual graphics.

User seeks to understand the impact of a marketing campaign on sentiment and survey data post-launch.

Given the user looks at the Unified Data Dashboard post-campaign launch, When they filter data to include the campaign period, Then the dashboard should show clear correlations between sentiment shifts and survey responses during that time frame, with visual indicators of changes.

Automated Survey Import

User Story: As a marketing manager, I want to automatically import survey data from external platforms so that I can save time and reduce errors in my analysis.
Description: The Automated Survey Import requirement focuses on the seamless integration of various survey tools into the SentiScan platform. This feature should allow users to automatically pull in responses from commonly used survey platforms, reducing the manual effort required for data entry. The automation component of this requirement ensures real-time data updates and consistency across datasets. Users will benefit from having their survey responses automatically aggregated with sentiment data, which provides a dynamic understanding of consumer sentiment that reflects current trends. The desired outcome is an efficient process that enhances the accuracy and timeliness of insights derived from combined feedback.
Acceptance Criteria: Automated Survey Import from a popular survey tool like SurveyMonkey during a new product launch campaign.

Given the user has connected the SentiScan platform to SurveyMonkey, when a survey is conducted, then responses should be automatically aggregated into the sentiment analysis dashboard without any manual intervention.

Users need to monitor sentiment shifts after importing survey data from a feedback platform.

Given survey responses have been imported, when the user accesses the sentiment analysis report, then the combined metrics of survey feedback and sentiment scores should be displayed clearly and accurately in the dashboard.

The system processes survey responses every hour to ensure real-time insights are available to marketers.

Given the survey tools are integrated, when survey responses are received, then they should be reflected in the SentiScan system within one hour of submission, ensuring timely access to insights.

A user wishes to validate the accuracy of imported survey data in comparison to historical sentiment trends.

Given the user has initiated data import, when the survey data is compared to past sentiment metrics, then discrepancies should be limited to a predefined threshold of 5% to ensure data integrity.

Multiple users wanting to connect different surveys simultaneously without data conflict.

Given multiple users are connected to different survey platforms, when surveys are imported simultaneously, then the system should handle each import independently without data loss or conflicts in the database.

Users want to customize the integration settings for different surveys based on their priorities and needs.

Given the user has access to integration settings, when they modify the integration parameters (like frequency of imports or specific survey selections), then those settings should be saved and respected in future imports without reverting to defaults.

Sentiment Shift Alerts

User Story: As a brand manager, I want to receive alerts for significant shifts in audience sentiment so that I can quickly adjust my marketing strategy and respond to market changes.
Description: The Sentiment Shift Alerts requirement involves establishing a system that monitors changes in sentiment levels and alerts users to significant deviations. This feature will utilize threshold settings that users can customize based on their needs and preferences. The alerts will facilitate timely responses to shifts in audience sentiment, enabling marketers to adapt their strategies promptly. By integrating this functionality into the SentiScan platform, users will gain proactive notification capabilities, leading to enhanced responsiveness in their marketing approaches. The expected outcome is an agile marketing strategy that aligns with real-time consumer attitudes, ultimately fostering improved engagement and brand loyalty.
Acceptance Criteria: User sets up custom sentiment shift alert thresholds for their specific marketing needs in the Feedback Integration Hub.

Given a user with administrative access, when they navigate to the Sentiment Shift Alerts settings and input threshold values indicating their desired sensitivity, then the system should save these settings and apply them accurately to monitor sentiment changes.

System generates and sends an alert notification when sentiment levels deviate significantly from the established thresholds.

Given the user has set a threshold for sentiment change, when a significant deviation occurs based on real-time sentiment analysis, then an alert notification should be triggered and sent to the user's designated communication channel (email, SMS, etc.).

User receives alerts and views an updated sentiment dashboard reflecting recent changes after an alert is triggered.

Given an alert has been triggered due to sentiment shift, when the user clicks on the notification, then they should be redirected to the updated sentiment dashboard showing the current sentiment analysis, historical data, and specific details of the shift.

User can adjust sentiment shift alert thresholds after receiving initial alerts based on further analysis of data.

Given a user has received a sentiment shift alert, when they review the dashboard and decide to adjust their threshold settings for the alerts, then they should be able to modify and save these new settings successfully.

User can opt-in or opt-out of receiving sentiment shift alerts based on their preferences in their account settings.

Given a user is in their account settings, when they toggle the option for receiving sentiment shift alerts, then their preference should be saved, and they should either continue receiving alerts or stop based on their selection.

The system logs all triggered sentiment shift alerts for compliance and analytical purposes.

Given that a sentiment shift alert has been triggered, when the alert is generated, then the system should log the event, including timestamp, sentiment levels before and after the shift, and the user's notification preference settings in a secure log for future reference.

Correlation Analysis Tool

User Story: As a data analyst, I want to perform correlation analysis between sentiment data and survey results so that I can identify key factors affecting customer perceptions.
Description: The Correlation Analysis Tool requirement focuses on developing a feature that provides users with the ability to conduct in-depth analyses between survey feedback and sentiment metrics. This tool should offer various analytical methods, including regression analysis and correlation coefficients, to help users better understand the relationships between different data points. By providing insights into how audience sentiment influences product performance, the tool will empower marketers to refine their strategies based on data-driven evidence. The outcome is a powerful analytical capability that enhances strategic decision-making.
Acceptance Criteria: Users should be able to upload survey data from various formats such as CSV or Excel to the Correlation Analysis Tool.

Given the user has survey data in CSV or Excel format, when they upload the data to the tool, then the tool successfully imports the data without errors and displays a confirmation message.

The tool shall allow users to select sentiment metrics and survey feedback for analysis.

Given the user has imported their survey data, when they choose sentiment metrics and survey feedback options, then the tool should correctly display the selected data for correlation analysis.

Users need to perform regression analysis on selected data points to understand trends and relationships.

Given the user has selected appropriate sentiment metrics and survey feedback, when they initiate a regression analysis, then the tool conducts the analysis and presents visual output along with regression coefficients and p-values.

The Correlation Analysis Tool must display a clear correlation coefficient between selected data sets.

Given the user has selected two data sets for analysis, when they run the correlation analysis, then the tool displays the correlation coefficient value and categorizes its strength (e.g., strong, moderate, weak) in the output.

Users should have the ability to export analysis results into a report format for sharing.

Given the user has completed their correlation analysis, when they choose the export option, then the tool generates a downloadable report that includes graphs, statistical outputs, and key findings in PDF or DOC format.

The tool should provide an interactive dashboard summarizing correlation analysis results.

Given the user has conducted multiple analyses, when they access the dashboard, then they should see a summary of all analyses with key insights, trends, and visual representations of the data.

Custom Reporting Feature

User Story: As a marketing director, I want to create custom reports that highlight specific insights from analysis so that I can inform and persuade stakeholders with relevant data.
Description: The Custom Reporting Feature requirement is dedicated to allowing users to generate tailored reports that focus on specific metrics relevant to their business needs. Users should be able to select data ranges, types of analysis, and preferred visual formats for their reports. This flexibility will enable marketers and analysts to convey insights in a manner that is most meaningful for their stakeholders. By integrating this reporting capability, SentiScan enhances its usability and value for users who need to present data in different contexts. The expected outcome is an increased ability to communicate insights effectively and drive strategic decisions based on comprehensive reports.
Acceptance Criteria: User generates a custom report focusing on product performance metrics over the last quarter.

Given the user is logged in with appropriate permissions, when they select 'Custom Reporting' and choose a data range of the last quarter, then they should be able to generate a report that accurately reflects the selected metrics in the preferred visual format.

User selects multiple data types for the custom report, including sentiment analysis and survey responses.

Given the user is in the 'Custom Reporting' section, when they choose both sentiment analysis and survey response data types, then the generated report should integrate and display these data types coherently and visually represent the correlations between them.

User saves a custom report for future reference and sharing.

Given the user has generated a custom report, when they click 'Save Report' and provide a report title, then the report should be saved and retrievable for future access or sharing with stakeholders.

User customizes the visual format of the report to match their branding guidelines.

Given the user has access to the visual formatting options, when they customize the report layout, colors, and fonts according to their branding, then the final report should reflect these customizations accurately.

User receives an alert for significant changes in sentiment metrics after generating a report.

Given the user has generated a report, when a significant change in sentiment analysis is detected based on pre-defined thresholds, then the user should receive an alert notification with relevant details about the change.

User exports the custom report to a PDF format for presentation purposes.

Given the user has a custom report open, when they choose the 'Export' option and select PDF as the format, then the report should be successfully exported and downloadable without data loss.

Crisis Mitigator

Crisis Mitigator proactively identifies and alerts users about potential sentiment crises before they escalate. By using advanced sentiment analysis algorithms, it assesses patterns and trends to project the likelihood of negative sentiment surges, allowing for timely interventions. This feature empowers marketers to safeguard their brand reputation and respond effectively to issues, minimizing damage and maintaining consumer trust.

Requirements

Real-Time Sentiment Monitoring

User Story: As a marketing manager, I want to monitor real-time sentiment across social media so that I can quickly respond to any adverse reactions from consumers.
Description: The Real-Time Sentiment Monitoring requirement involves implementing a continuous sentiment analysis functionality that allows users to receive live updates on public sentiment related to their brand or product. This feature is crucial for quickly identifying changes in sentiment on social media and other platforms, enabling users to react promptly to emerging trends. It should integrate seamlessly within the existing SentiScan infrastructure and allow users to customize alerts based on specific keywords or sentiment thresholds, facilitating a proactive approach to market engagement and brand management.
Acceptance Criteria: User receives live updates on sentiment changes for their brand during a product launch event.

Given that the user has set up monitoring for their brand keywords, when a significant negative sentiment surge is detected, then an alert is triggered and sent to the user's dashboard and email.

A user customizes their alert preferences for sentiment thresholds and keywords.

Given that the user is on the alert settings page, when they select specific keywords and set sentiment thresholds, then these preferences are saved successfully and take effect immediately for future updates.

A marketing analyst reviews sentiment data over a specific period.

Given that the user selects a date range for sentiment analysis, when they view the results, then the data reflects accurate sentiment scores and trends for the selected period based on real-time analysis.

A brand manager is alerted about a negative sentiment trend escalating over a week.

Given that the sentiment monitoring is active, when the system detects a 30% increase in negative sentiment over a week, then a notification is generated and sent to the brand manager’s device.

Users interact with the dashboard to view sentiment details and trends.

Given that the user accesses the sentiment dashboard, when they click on a specific date in the trend graph, then detailed sentiment information for that date is displayed accurately, including sentiment breakdowns and related alerts.

The system identifies and logs instances of sentiment crises for future reference.

Given that a sentiment crisis is identified, when the crisis occurs, then the system logs the incident with all relevant details, including date, time, sentiment scores, and keywords for review and reporting purposes.

Alert notifications are sent to users through multiple channels.

Given that a user has multiple notification methods (email, SMS, app notifications) set up, when a significant sentiment change occurs, then the alert is successfully sent to all designated channels without delay.

Sentiment Shift Prediction

User Story: As a brand strategist, I want to predict sentiment shifts before they occur so that I can implement strategies to mitigate potential negative impacts.
Description: The Sentiment Shift Prediction requirement focuses on developing algorithms that analyze historical sentiment data to predict potential fluctuations in sentiment over time. Utilizing machine learning techniques, this feature will assess factors such as current events or promotional campaigns to forecast whether there could be a significant sentiment shift. The outputs of this feature will enable users to prepare for potential issues before they arise, ensuring they can maintain brand reputation and customer engagement effectively. The prediction model should be constantly updated with the latest sentiment data to enhance accuracy and reliability.
Acceptance Criteria: As a marketing analyst, I need to receive alerts about potential sentiment crises based on trending sentiment analysis data, so that I can act quickly to address and mitigate any negative perceptions before they escalate.

Given that the sentiment analysis algorithm is running, when a significant upward trend in negative sentiment is detected within a 24-hour period, then an alert should be sent to the user within 10 minutes.

As a brand manager, I want to review historical sentiment data to better understand patterns that lead to sentiment shifts, which helps in strategic planning and proactive communication.

Given that the historical sentiment data is accurately stored, when I access the historical sentiment report, then I should be able to view data segmented by day, week, and month and be able to isolate periods of significant change.

As a product marketing lead, I need recommendations based on sentiment predictions to prepare for possible negative sentiment during product launches, so our communications can be timely and effective.

Given that the sentiment shift prediction model has processed historical data and current events, when I check the prediction results, then I should receive clear recommendations on how to address anticipated sentiment changes before product launch.

As a customer experience manager, I would like to see how promotional campaigns correlate with shifts in sentiment, allowing for quick adjustments to marketing strategies if negative trends are detected.

Given that the sentiment shift data is linked to promotional campaign data, when a new campaign is launched, then I should see a correlation report generated within 30 minutes that highlights sentiment fluctuations during and after the campaign rollout.

As a data scientist, I want to ensure that the sentiment prediction algorithms are updated regularly with new data to maintain their accuracy and relevance in forecasting sentiment changes.

Given that new sentiment data is available, when the sentiment shift prediction model is executed, then it should incorporate the most recent data and display an accuracy report reflecting potential changes every week.

As a chief marketing officer, I need dashboards that provide real-time visualizations of sentiment trends and predictions to quickly assess brand health and reaction strategies.

Given that the sentiment shift prediction algorithms are functional, when I access the dashboard, then I should see real-time updates of sentiment scores, trend lines, and predictive analytics for the last 30 days at a glance.

Custom Alert System

User Story: As a social media analyst, I want to set up custom alerts for sentiment changes so that I can be immediately notified and act quickly if a crisis is emerging.
Description: The Custom Alert System requirement involves creating a configurable alert feature that allows users to set criteria for receiving notifications about potential sentiment crises. Users should be able to specify thresholds for positive or negative sentiment changes, as well as define relevant keywords that trigger alerts. This feature will empower users to stay informed about critical developments affecting their brand without needing to manually monitor sentiment data. By automating alert notifications, marketers can dedicate their time to crafting responsive strategies rather than monitoring data, ultimately enhancing the efficiency and effectiveness of their crisis management efforts.
Acceptance Criteria: User defines a threshold for negative sentiment alerts in their Custom Alert System settings.

Given the user has accessed the Custom Alert System settings, When the user sets a threshold for negative sentiment at -20%, Then the system should generate an alert if the sentiment score drops below -20%.

User sets relevant keywords that should trigger sentiment alerts.

Given the user is in the Custom Alert System settings, When the user adds keywords 'crisis', 'problem', and 'issue' to the alert configuration, Then an alert should be triggered if any of these keywords appear in the sentiment analysis results.

User configures the alert system to notify them through email.

Given the user has entered their email address in the notification settings, When a sentiment alert is triggered, Then the system should send an email to the user's specified email address containing details of the alert.

User expects to view a history log of triggered alerts.

Given the user accesses the alert history section, When the user views the recent alerts, Then the system should display a list of previously triggered alerts with timestamps and relevant sentiment data.

User tests the alert functionality with sample data.

Given the user has configured a test alert for negative sentiment changes, When the sentiment data for testing reflects a drop below the configured threshold, Then the system should immediately notify the user as per their notification settings.

User wants to modify existing alert criteria.

Given the user is in the Custom Alert System settings, When the user updates the keyword list and sentiment threshold, Then the system should save the changes and apply them to future sentiment analysis results.

Dashboard Integration

User Story: As a product manager, I want to see crisis mitigation tools integrated into my dashboard so that I can easily access all relevant information and make informed decisions quickly.
Description: The Dashboard Integration requirement entails embedding the Crisis Mitigator and its functionalities directly into SentiScan's user interface dashboard. This will allow users to visualize sentiment trends and predictions alongside other analytics they are monitoring, creating a unified view of their market landscape. The integration should prioritize user experience, ensuring that the presentation of data is intuitive and easily comprehensible. This enhancement will deliver significant value as it enables users to track their brand’s performance and sentiment in one cohesive space, facilitating quicker decision-making and strategy adjustments.
Acceptance Criteria: User accesses the SentiScan dashboard to analyze sentiment trends from different social media channels while preparing a weekly report for the marketing team.

Given the user is on the SentiScan dashboard, when they navigate to the Crisis Mitigator section, then the user should see real-time visualizations of sentiment trends and prediction alerts, displayed in an intuitive format.

A marketer receives a notification about a potential sentiment crisis due to sudden negative sentiment surge detected by the Crisis Mitigator integrated in the SentiScan dashboard.

Given a negative sentiment surge is detected, when the system identifies the issue, then an alert should be triggered and presented to the user on the dashboard in a clear and recognizable manner.

A user is reviewing the dashboard and wants to customize the layout to prioritize the Crisis Mitigator information based on personal preferences.

Given the user is on the SentiScan dashboard, when they select customization options for data presentation, then they should be able to rearrange, resize, and prioritize the Crisis Mitigator widget within the dashboard.

While analyzing sentiment data, a user wants to filter trends specifically related to their brand's recent advertising campaign.

Given the user is on the SentiScan dashboard, when they apply filters specific to their advertising campaign, then the Crisis Mitigator should update the visualizations to reflect only relevant sentiment data.

A user wants to download the sentiment analysis report generated from the Crisis Mitigator section for sharing with stakeholders.

Given the user is in the Crisis Mitigator section of the SentiScan dashboard, when they click the download button, then a report containing the relevant sentiment data should be generated and saved in a standard file format.

The marketing team conducts a review meeting where they assess the sentiment trends displayed on the SentiScan dashboard integrated with Crisis Mitigator.

Given the marketing team is in a review meeting, when they analyze the data presented in the Crisis Mitigator section, then the information should provide easy-to-interpret insights for strategic discussions with visual aids such as graphs and alerts.

User Training Module

User Story: As a customer success manager, I want to offer training sessions for users of the Crisis Mitigator so that they feel empowered to utilize the tool effectively and respond to challenges proactively.
Description: The User Training Module requirement focuses on creating educational resources to help users make the most out of the Crisis Mitigator feature. This module should provide tutorials and best practices for effectively using the alert systems, interpreting sentiment data, and responding to crises. It is crucial for ensuring users can fully leverage the functionality of the tool and understand its application in real-world scenarios. Providing comprehensive training will increase user confidence, promote better usage of features, and ultimately lead to more effective management of brand sentiment across channels.
Acceptance Criteria: User Training Module provides on-demand access to video tutorials and documentation for using the Crisis Mitigator feature.

Given a user accesses the User Training Module, When the user selects the Crisis Mitigator tutorials, Then the user should be able to view and interact with at least three tutorial videos and associated documentation that clearly explain the features and settings of the Crisis Mitigator.

User Training Module includes a section on best practices for interpreting sentiment data from the Crisis Mitigator.

Given a user is in the User Training Module, When the user navigates to the best practices section, Then the user should have access to clearly written guidelines that outline how to interpret various sentiment metrics with at least five examples of real-world applications.

User Training Module features a quiz to test users' knowledge on utilizing the Crisis Mitigator effectively.

Given a user has completed the training materials, When the user takes the assessment quiz, Then the user should pass with a score of at least 80% to demonstrate understanding of the material covered in the training module.

User Training Module enables users to provide feedback on the training resources and their usefulness.

Given a user completes the training module, When the user fills out the feedback form, Then the input should capture the user's satisfaction level and suggestions, with at least a 70% response rate for useful and relevant content.

User Training Module provides a live Q&A session with experts for users of the Crisis Mitigator feature.

Given a scheduled live Q&A session, When users attend the session, Then they should have the opportunity to ask questions and receive answers in real-time, with at least 80% of attendees reporting satisfaction with the resolution of their inquiries.

User Training Module includes a guide on how to respond to sentiment crises identified by the Crisis Mitigator.

Given a user reviews the crisis response guide, When the user implements the suggested actions during a sentiment crisis, Then the user should be able to mitigate negative sentiment effectively, as measured by a decrease in negative mentions within 24 hours post-intervention.

Opportunity Notifier

Opportunity Notifier detects positive swings in sentiment and instantly alerts users to capitalize on favorable public opinions. By monitoring real-time sentiment changes, this feature highlights specific times to engage with the audience, driving targeted marketing efforts. This proactive approach enhances strategic marketing, enabling brands to leverage positive sentiment for increased engagement and conversion opportunities.

Requirements

Real-Time Sentiment Monitoring

User Story: As a marketer, I want to receive real-time alerts of sentiment shifts so that I can engage with my audience promptly and leverage positive trends.
Description: This requirement involves implementing a robust system that continuously monitors social media and online platforms for sentiment analysis. It will leverage advanced AI algorithms to extract and analyze user-generated content, enabling SentiScan to provide real-time insights into consumer attitudes. This feature is crucial for identifying trends and shifts in sentiment, providing users with up-to-date information to make quick, informed decisions. By integrating this monitoring capability, users will be able to respond proactively to changes in public opinion.
Acceptance Criteria: Real-time Sentiment Monitoring during a product launch campaign

Given a marketing team is launching a new product, when they enable the Real-Time Sentiment Monitoring feature, then the system should provide updates on sentiment changes every minute and send alerts for any positive sentiment spikes above a predefined threshold.

Adjusting marketing strategies based on sentiment analysis following a major event

Given a major public event occurs, when the real-time sentiment analysis detects a significant sentiment shift related to the event, then users should receive an immediate notification and an analysis report within 3 minutes for strategic adjustment.

Identifying trends over a week for a specific brand

Given a user selects a specific brand to monitor, when they access the trend analysis feature, then the system should display sentiment trends for the past 7 days, highlighting notable sentiment changes with visual indicators for easy interpretation.

Competitor analysis using sentiment trends

Given a user wants to compare sentiment trends between two competing brands, when they initiate the competitor analysis feature, then the system should provide a side-by-side comparison of sentiment changes over the last month including alert notifications for significant shifts.

Integrating sentiment data with marketing campaigns

Given a marketing campaign aimed at engaging consumers, when the sentiment monitoring detects increased positive sentiment, then the system should recommend optimized engagement strategies based on the identified sentiment patterns.

Custom Alert System

User Story: As a user, I want to customize my alert settings so that I only receive notifications on sentiment shifts that are most relevant to my campaigns.
Description: Develop a customizable alert system that allows users to set specific parameters for sentiment changes that trigger notifications. This feature will enable users to personalize their experience by defining what kinds of sentiment shifts they wish to be notified about, such as positive or negative thresholds in specific keywords or topics. The ability to tailor alerts improves user efficiency, as they can focus on the most relevant data that impacts their marketing strategies.
Acceptance Criteria: User sets a personalized alert for a specific keyword related to their brand and monitors the results for several days, looking for sentiment changes that trigger notifications.

Given the user has logged into SentiScan and navigated to the alert settings, when they input a specific keyword and define positive sentiment thresholds, then an alert should be triggered once the sentiment data reflects a positive change meeting the user-defined criteria.

A marketing analyst wants to be notified of negative sentiment regarding a competitor's product. They configure the alert system accordingly and observe its functionality.

Given the user has configured an alert for negative sentiment regarding a competitor's product, when the sentiment drops below the set threshold, then the user receives a real-time notification through the SentiScan platform and their registered email account.

A user operates the alert system over a week while monitoring customer sentiment on social media around new product releases and wants assurance that alerts are timely and relevant.

Given the user has set multiple alerts across different keywords and sentiment thresholds, when a sentiment shift occurs, then all relevant alerts should be sent within 5 minutes of the change being detected by the system.

After setting a range of different alert parameters, a user reviews their alert history to evaluate the effectiveness of the alert system in capturing sentiment changes relevant to their products.

Given that the user has access to their alert history, when they review the notifications received, then they should find that 90% of the alerts correspond accurately to significant sentiment changes defined in their criteria.

A user seeks to modify the parameters of existing alerts to better fit evolving marketing strategies and assess the flexibility of the alert system.

Given the user has selected an existing alert to modify, when they change its parameters—such as keywords and sentiment thresholds—then the system should allow the changes to take effect immediately without errors.

A user tests the alert system with a variety of different sentiment parameters over an extended period to check for reliability and consistency.

Given the user has set alerts for multiple keywords with various thresholds, when they run a testing phase over a month, then at least 95% of the alerts should accurately reflect the user-defined conditions without false positives or missed notifications.

In a team environment, multiple users need to receive notifications from the customizable alert system to improve collaborative marketing strategies.

Given that multiple users have been added to an alert distribution list, when a sentiment change occurs that meets any user's criteria, then every user in the distribution list receives a notification simultaneously through their preferred communication channels.

Sentiment Analysis Dashboard Integration

User Story: As a data analyst, I want a centralized dashboard that displays real-time sentiment data so that I can easily analyze market trends and improve my reporting accuracy.
Description: Create an integrated dashboard that visually showcases real-time sentiment analysis alongside the Opportunity Notifier feature. This dashboard will present data in an intuitive format, allowing users to see patterns and trends at a glance. By having a centralized interface that combines insights and alerts, users can quickly assess the current market sentiment and make data-driven decisions. This integration is vital for providing users with actionable intelligence in one convenient location.
Acceptance Criteria: User views the sentiment analysis dashboard integrated with the Opportunity Notifier feature to assess real-time sentiment changes during a marketing campaign launch.

Given that the user is logged into SentiScan, when the user navigates to the sentiment analysis dashboard, then the dashboard displays real-time sentiment data as well as alerts from the Opportunity Notifier, allowing the user to make informed decisions.

User receives a notification from the Opportunity Notifier about a significant increase in positive sentiment for a specific product.

Given that the sentiment analysis data shows a 15% increase in positive sentiment, when the Opportunity Notifier detects this change, then it sends an immediate alert to the user via email and in-app notification.

User analyzes historical sentiment trends alongside the current sentiment data presented in the dashboard to find correlations and make future marketing decisions.

Given that the user accesses the sentiment analysis dashboard, when the user selects a date range for historical sentiment data, then the dashboard updates to show both historical trends and real-time sentiment in a comparative format.

User examines the dashboard to identify specific times of day when positive sentiment peaks occur over a week.

Given that the sentiment analysis dashboard presents data for a specific week, when the user views the sentiment graph, then the dashboard highlights peak sentiment times with an easily identifiable color or marker.

User interacts with the dashboard to filter sentiment data by product category to assess market dynamics accurately.

Given that the user utilizes the filtering options available on the sentiment analysis dashboard, when the user selects a specific product category, then the dashboard updates to exclusively show sentiment data for that category, maintaining the integrated Opportunity Notifier alerts.

User Feedback Loop

User Story: As a product manager, I want to gather user feedback on the Opportunity Notifier feature so that I can continuously improve the functionality based on user needs.
Description: Implement a user feedback loop that collects insights and reactions from users about the Opportunity Notifier feature. This would involve surveys or feedback options built into the platform, allowing users to share their experiences and suggest improvements. This requirement addresses the need for continuous improvement based on user input, ensuring that the feature evolves to meet user needs effectively over time.
Acceptance Criteria: User initiates a feedback survey via the Opportunity Notifier after receiving an alert about a positive sentiment shift.

Given a user receives an alert from the Opportunity Notifier, when they click on the feedback option, then they should be presented with a survey that captures their sentiment about the latest notification.

A user submits their feedback through the survey about the Opportunity Notifier's usefulness after interacting with it.

Given a user completes the feedback survey, when they submit their responses, then their feedback should be successfully saved in the system without any errors.

The platform aggregates feedback received from users regarding the Opportunity Notifier's effectiveness over a month.

Given the feedback collection is ongoing for a month, when an admin reviews the aggregated data, then it should show an overall satisfaction score and specific suggestions from users.

Users receive a confirmation message after submitting their feedback on the Opportunity Notifier.

Given a user submits their feedback, when the submission is successful, then they should receive a confirmation message indicating the feedback was received.

The system provides analytics on feedback received about the Opportunity Notifier feature.

Given a data analytics report is generated, when an admin reviews the report, then it should include metrics such as total feedback submissions, average rating, and common user suggestions.

The feedback loop is integrated into the Opportunity Notifier feature in the user dashboard.

Given a user accesses the Opportunity Notifier section of the dashboard, when they look for feedback options, then they should see a clear and accessible option to provide their feedback on the feature.

Historical Sentiment Data Access

User Story: As a strategic planner, I want to access historical sentiment data so that I can analyze trends over time and inform my marketing strategies accordingly.
Description: Enable access to historical sentiment data for users to analyze past trends alongside current sentiment shifts. This feature is essential for understanding the context of sentiment changes and for providing users with insights into how sentiments have evolved over time. Users will be better equipped to make strategic decisions based on a more comprehensive understanding of consumer behavior patterns.
Acceptance Criteria: User accesses historical sentiment data to analyze trends for a specific product campaign.

Given the user has selected a specific product campaign, when they request to view historical sentiment data, then the system displays sentiment trends for the chosen campaign over the past year.

A marketer evaluates how sentiment has changed over time for a brand after a major product launch.

Given the user is examining sentiment shifts post-product launch, when they filter data for the last six months, then the system shows sentiment scores and trends for that timeframe clearly on the dashboard.

An analyst compares current sentiment data to historical data during a quarterly review presentation.

Given the analyst has selected both current and historical sentiment data sets, when they generate a report, then the system creates a comparative analysis chart that visualizes changes in sentiment with key dates highlighted.

A user sets custom alerts for significant sentiment changes based on historical data patterns.

Given the user has defined specific thresholds for sentiment changes, when these thresholds are met, then the system sends an immediate alert to the user through the designated communication channel.

A marketing team reviews the impact of historical sentiment data on recent marketing strategies.

Given the marketing team has access to both current and historical sentiment data, when they analyze this data, then they can identify at least three actionable insights related to past and present strategies.

The user explores data from different geographical regions to see historical sentiment variations.

Given the user selects a geographical region, when they view the historical sentiment data, then the system provides segmented data for that region over the selected timeframe, allowing for easy comparison with other regions.

Sentiment Severity Scale

Sentiment Severity Scale categorizes alerts based on the urgency and significance of sentiment changes. Users receive tailored notifications reflecting the intensity of the sentiment shifts, allowing for prioritized responses. This granular approach helps marketers focus their efforts on the most pressing issues or opportunities, optimizing their reaction time and resource allocation.

Requirements

Alert Categorization Engine

User Story: As a marketing analyst, I want to receive categorized alerts based on sentiment severity so that I can prioritize my responses to the most significant sentiment shifts and manage my resources effectively.
Description: The Alert Categorization Engine is a vital component that processes and analyzes sentiment data to classify alerts based on their severity. This includes developing algorithms that automatically assign a severity level to sentiment shifts, enabling users to quickly assess which issues require immediate attention. The functionality will integrate smoothly with existing alert systems, ensuring that users receive timely and relevant notifications tailored to the urgency of sentiment changes. Greater granularity in alerts will empower users to prioritize responses effectively, enhancing strategic decision-making and resource allocation.
Acceptance Criteria: User receives an alert notification for a significant sentiment shift on a product's social media page.

Given the sentiment categorization algorithm is fully integrated, When there is a sentiment change classified as 'High Severity', Then the user should receive an immediate alert notification via email and the dashboard indicating the urgency and nature of the sentiment shift.

Marketers assess alerts for various sentiment shifts over a defined time period, such as a week.

Given the user accesses the Sentiment Severity Scale, When the user filters alerts by 'Last 7 Days', Then the system should display all alerts categorized by severity level with timestamps and sentiment analysis summaries for each alert.

A user prioritizes alerts to determine which issues to address first based on severity.

Given the user views the categorized alerts, When the user sorts the alerts by 'Severity Level', Then the alerts should be re-ordered in descending order from 'Critical' to 'Low', allowing the user to focus on the most significant issues first.

An analyst wants to customize notification preferences based on severity levels.

Given the user sets notification preferences in the settings, When the user selects which severity levels they want to receive alerts for, Then the system should only send notifications for the selected severity levels moving forward.

The system needs to test its performance under high alert volume conditions to ensure timely notifications are dispatched.

Given a simulated load with a high volume of sentiment alerts, When the system processes these alerts, Then it should categorize and send notifications to users within 2 minutes of the sentiment shift being detected.

Users need a historical view of alerts to analyze trends over time.

Given the user accesses the historical alerts report, When the user selects a specific date range, Then the system should generate a report summarizing the number and types of alerts categorized by severity over that period.

Real-time Notification System

User Story: As a user, I want to receive real-time notifications about sentiment severity changes so that I can react quickly to shifts in consumer attitudes and adjust my marketing strategies accordingly.
Description: The Real-time Notification System ensures that users are promptly informed about significant changes in sentiment through various communication channels. This system will deliver immediate alerts regarding sentiment shifts categorized by severity levels, allowing marketers to act swiftly in response to consumer attitudes. The functionality could include push notifications, in-app alerts, and email updates, providing users with flexibility in terms of how they receive critical information. This timely communication is essential for maintaining responsive marketing strategies and optimizing customer engagement.
Acceptance Criteria: User receives a real-time notification on their mobile device when there is a significant surge in negative sentiment regarding their brand on social media.

Given a user has opted in for mobile notifications, when the sentiment severity scale detects a surge in negative sentiment, then the user should receive a push notification within 5 minutes of the sentiment change.

Marketers receive an in-app alert when the sentiment analysis shows a shift from neutral to positive sentiment for a specific campaign.

Given a marketer is logged into the app, when the sentiment analysis indicates a positive shift, then an in-app alert should be displayed immediately with details about the sentiment change.

Users need to receive timely email updates about sentiment changes for key metrics they are tracking.

Given a user has subscribed to email notifications, when there is a change in sentiment categorized as high severity, then an email should be sent with the details of the shift within 10 minutes.

A marketing team leader wants to ensure all team members are informed about significant sentiment changes before strategic meetings.

Given team members have access to the notification system, when a sentiment change is categorized as medium or high severity, then all team members should receive an email alert before the next scheduled team meeting.

A user wants to filter notifications based on sentiment severity levels to focus only on critical alerts.

Given a user is accessing the notification settings, when the user selects to receive only high severity alerts, then the user should not receive notifications for medium or low severity changes.

A data analyst needs a historical log of sent notifications regarding sentiment shifts for performance review.

Given a user accesses the notification history feature, when the user requests to view past notifications, then the system should display a comprehensive log of notifications for the last 30 days, categorized by severity level.

A marketer is monitoring sentiment shifts in real-time and requires instant updates at a glance.

Given a user is monitoring a dashboard, when a sentiment severity alert is triggered, then the dashboard should update to highlight the severity level immediately and display a summary of the change.

Intuitive Dashboard Integration

User Story: As a marketer, I want to see sentiment severity trends on my dashboard so that I can easily monitor shifts and make informed decisions based on clear visual data representations.
Description: The Intuitive Dashboard Integration enhances the existing user interface by incorporating a visual representation of sentiment severity trends and alert histories. This feature will allow users to intuitively track and analyze sentiment shifts over time, view categorized alerts, and filter information based on varying criteria. The dashboard will be customizable, enabling users to prioritize the data that matters most to them. By simplifying data interaction, users can make informed decisions faster and improve their strategic planning efforts.
Acceptance Criteria: Visual Representation of Sentiment Severity Trends Displayed on the Dashboard

Given the user accesses the dashboard, when they select the Sentiment Severity Scale feature, then they should see a graphical representation of sentiment trends categorized by severity over the selected time period.

Categorized Alerts Filtering Functionality

Given the user is on the dashboard, when they filter alerts based on severity levels (low, medium, high), then only the relevant alerts should be displayed according to the selected filter criteria.

Customizable Dashboard for User Preferences

Given the user has logged into SentiScan, when they access the customization options for the dashboard, then they should be able to select and prioritize the displayed metrics and alerts according to their preferences.

Notification Alert System for Sentiment Shifts

Given an existing alert has been triggered based on sentiment shift, when the severity changes, then the user should receive a notification reflecting the updated severity level.

Historical Data Review for Sentiment Analysis

Given the user is on the dashboard, when they select a historical date range for sentiment analysis, then they should see trend data and categorized alerts for that specific time frame displayed accurately.

User Engagement Analytics Integration with Sentiment Tracking

Given the user wants to analyze engagement metrics, when they correlate with sentiment shifts displayed on the dashboard, then the analytics should showcase a relationship or trend between engagement and sentiment over time.

User Configuration Options

User Story: As a user, I want to configure my alert settings so that I can receive notifications that fit my specific needs and avoid information overload.
Description: User Configuration Options will provide users the ability to customize their alert settings for sentiment notifications. This functionality will include preferences for notification types, severity thresholds for alerts, and frequency of updates. By allowing users to tailor these options, SentiScan ensures that each user can align notifications with their unique workflow and priorities, enhancing the overall user experience and ensuring that important information is not overlooked.
Acceptance Criteria: User Customizes Alert Settings for Sentiment Notifications.

Given a user is logged into the SentiScan dashboard, when they navigate to the 'User Configuration Options' section, then they should be able to set preferences for notification types, severity thresholds for alerts, and frequency of updates, and save these settings without error.

User Receives Tailored Notifications Based on Severity Thresholds.

Given a user has configured their alert settings with specific severity thresholds, when a sentiment shift occurs that meets or exceeds these thresholds, then the user should receive a notification reflecting the severity level of the sentiment change.

User Adjusts Frequency of Sentiment Notifications.

Given a user is on the 'User Configuration Options' page, when they change the frequency of updates to receive alerts, then the system should save this setting, and the user should receive notifications only at the specified intervals moving forward.

User Tests Notification Preferences.

Given a user has set up custom notification preferences, when they simulate a sentiment change within the system, then they should receive the correct notifications according to their configured settings, without delay.

User Views Alerts History to Confirm Alert Settings Functionality.

Given a user has received various sentiment alerts, when they access the 'Alerts History' section, then they should see a log of all notifications sent to them, including the severity levels and timestamps, confirming their configuration is functioning as intended.

User Updates Custom Configuration Options Successfully.

Given a user is on the 'User Configuration Options' page, when they modify any of their alert settings and click 'Update', then the changes should be saved, and the system should confirm the update was successful without errors.

Notifications Are Sent via User-Preferred Channels.

Given a user has set preferences for notification channels (e.g., email, SMS), when a sentiment change occurs, then the notification should be sent through the selected channels as per the user's configuration.

Sentiment Analysis Reporting

User Story: As a marketing executive, I want to generate reports on sentiment severity changes so that I can analyze trends and adjust our marketing strategies based on consumer feedback over time.
Description: The Sentiment Analysis Reporting feature will enable users to generate reports summarizing sentiment severity changes over specified time frames. These reports will provide insights into trends, high-priority alerts, and user-defined parameters. By offering both graphical visualizations and detailed analytics, users can better understand the shifts in consumer sentiment and evaluate their impact on marketing strategies. This capability promotes data-driven decision-making and enhances the strategic value of SentiScan.
Acceptance Criteria: User generates a sentiment analysis report focusing on the last 30 days of data to assess the effectiveness of a recent marketing campaign.

Given the user has selected the last 30 days as the time frame, when they click on 'Generate Report', then the system should create a report displaying sentiment severity changes with trends and alerts clearly highlighted.

Marketers want to visualize sentiment changes over the past week to address negative shifts rapidly.

Given the user chooses a 7-day time frame and applies filters for sentiment severity, when they view the generated report, then the graphical visualizations should accurately reflect sentiment changes categorized by severity levels.

A user wants to receive notifications for high-priority sentiment shifts during business hours.

Given the user has set their alert preferences to include high-severity categories, when a significant sentiment shift occurs, then the user should receive an immediate notification detailing the nature and urgency of the sentiment change.

The marketing team needs to evaluate positive sentiment trends monthly to plan future strategies.

Given it is the end of the month, when the user generates the monthly sentiment report, then it should include a summary of positive sentiment trends with percentage growth and corresponding graphical representations for easy understanding.

An analyst needs to customize the report parameters to include specific keywords for in-depth analysis.

Given the user enters specific keywords in the report parameters, when they generate the report, then the report should only reflect sentiment changes related to those keywords with detailed analytics provided.

A product manager requires a dashboard that shows the correlation between sentiment severity and sales performance.

Given the sentiment analysis report includes sales data for the same period, when the report is generated, then it should contain a visual correlation graph highlighting the relationship between sentiment severity and sales changes over time.

Users want to be able to export their sentiment analysis reports in multiple file formats for sharing with stakeholders.

Given the report has been successfully generated, when the user selects the export option, then the system should allow exporting the report in at least three different formats (PDF, Excel, CSV).

User-Defined Thresholds

User-Defined Thresholds let users customize the parameters for receiving alerts based on their specific needs and brand goals. By allowing tailored sensitivity levels to sentiment changes, this feature ensures users receive only the most relevant notifications, reducing noise and enhancing the focus on impactful shifts. This customization aligns alerts with business objectives, promoting effective decision-making.

Requirements

Custom Alert Configuration

User Story: As a marketing manager, I want to set customized thresholds for alerts so that I receive notifications only when there are significant sentiment changes that align with my brand goals.
Description: The Custom Alert Configuration requirement enables users to define and customize their own sensitivity levels for receiving alerts. This feature is essential for ensuring that users are alerted only to sentiment changes that matter to them, thus filtering out less relevant notifications and providing a streamlined experience. By integrating this capability into SentiScan's dashboard, users can align the alerts with their unique business objectives, leading to more effective monitoring and decision-making. This customization is fundamental for businesses that require precision in their market research efforts and wish to focus on critical shifts in consumer sentiment.
Acceptance Criteria: User successfully defines a custom alert threshold for sentiment changes based on specific keywords related to their brand.

Given the user is on the SentiScan dashboard, when they access the Custom Alert Configuration section and define a threshold for a specific keyword, then the system must save the threshold and display it as an active alert configuration.

User receives an alert when sentiment shifts exceed their defined threshold for specified brands or keywords.

Given the user has set a custom threshold for sentiment alerts, when a sentiment shift occurs that exceeds this threshold, then the user must receive an immediate notification through their selected communication channel (e.g., email, SMS, in-app alert).

User wants to edit their existing custom alert configuration for more relevant notifications.

Given the user navigates to the Custom Alert Configuration section, when they edit an existing alert's parameters (like threshold level or keyword focus), then the system must successfully update the alert configuration and confirm the changes to the user.

User attempts to set a threshold that is too sensitive, leading to excessive alerts.

Given the user tries to define a custom alert threshold that includes setting a very low sensitivity level, when they save the configuration, then the system must prompt a warning message advising that this setting may produce too many alerts.

User deletes a previously defined custom alert configuration.

Given the user is in the Custom Alert Configuration section, when they choose to delete an existing alert configuration, then the alert must be removed from their active alerts, and the user should receive a confirmation of the deletion.

User checks their current custom alert configurations to ensure they align with their business goals.

Given the user accesses the Custom Alert Configuration view, when they review their list of active alerts, then all configurations must be displayed accurately with corresponding sensitivity levels and keywords, allowing the user to verify alignment with audience monitoring objectives.

Visual Threshold Indicators

User Story: As a data analyst, I want to see visual indicators for my defined thresholds so that I can quickly assess sentiment changes and whether they warrant immediate attention.
Description: The Visual Threshold Indicators requirement aims to provide users with clear visual representations of their defined thresholds within the SentiScan platform. This feature enhances user experience by allowing immediate comprehension of where their thresholds lie in relation to real-time sentiment data. By utilizing color-coding and graphic indicators, users will be able to quickly identify whether sentiment changes have crossed their customized thresholds, making it easier to assess potential areas of action. The indicators not only enhance clarity but also promote quicker decision-making, as users won't need to sift through raw data to understand the significance of sentiment shifts.
Acceptance Criteria: User views their customized dashboard in SentiScan to monitor real-time sentiment data and identify threshold indicators.

Given the user has set specific sentiment thresholds, when they access the dashboard, then they should see visual indicators (color-coded and graphic) representing these thresholds against the sentiment data.

User receives an alert notification when sentiment shifts cross their defined thresholds.

Given the user has defined thresholds for sentiment changes, when a sentiment shift occurs that crosses these thresholds, then the user should receive a relevant alert notification clearly indicating the threshold that was exceeded.

User customizes their threshold settings to align with business objectives through the settings panel.

Given the user accesses the threshold settings, when they input and save their desired threshold levels, then the visual indicator on the dashboard should update accordingly to reflect the new thresholds immediately.

User evaluates sentiment data over a specified period and visually identifies trends and threshold breaches.

Given the user analyzes sentiment data on the dashboard for a specified time frame, when sentiment changes occur that breach the established thresholds, then these instances should be visually highlighted on the dashboard for easy identification.

User seeks assistance in understanding how to utilize the Visual Threshold Indicators feature effectively within SentiScan.

Given the user is accessing the help section, when they query about Visual Threshold Indicators, then they should receive clear instructional content explaining how the feature works and its importance in monitoring sentiment data.

User wishes to customize their alert settings based on different time periods of sentiment analysis.

Given the user is in the alert settings page, when they set different threshold levels for various time periods, then the system should allow saving of these settings and display the updated thresholds on the dashboard accordingly.

Threshold Adjustment Notifications

User Story: As a product manager, I want to receive notifications when I adjust my alert thresholds so that I can stay informed about my customization changes and ensure I am monitoring the right sentiment data.
Description: The Threshold Adjustment Notifications requirement specifies that users will receive system notifications when their customized threshold settings are successfully updated or modified. This is crucial for maintaining user awareness and ensuring operational continuity. Users will benefit by being informed of any changes they make to their alert settings, reducing the risk of missing alerts if they have forgotten previous configurations. Such notifications will also help in tracking changes over time, fostering improved management of sentiment alerts in relation to evolving marketing strategies and goals.
Acceptance Criteria: Users are able to update their threshold settings for sentiment alerts through the SentiScan dashboard and require confirmation of the successful change.

Given the user has modified their threshold settings, when they press the 'Save' button, then a notification should appear confirming the successful update of their threshold settings.

Users want to track changes made to their alert thresholds over time to analyze their decision-making process.

Given the user has successfully updated their threshold settings, when they navigate to the 'Settings History' section, then they should see a log of all previous threshold adjustments made with timestamps and details of the changes.

Users are alerted of any changes made to their threshold settings, regardless of whether they made them or they were made by an admin.

Given an admin updates a user's threshold settings, when the user logs into the SentiScan application, then they should receive a notification detailing the adjustments made to their alert thresholds.

In cases where threshold settings fail to save, users need to be notified through the system.

Given the user attempts to change their threshold settings but the system encounters an error, when the user presses the 'Save' button, then an error notification should appear explaining that the update has failed and prompt them to try again.

Users expect to customize their notification preferences for threshold changes for different alert types.

Given the user has multiple types of sentiment alerts, when they update their threshold settings, then the system should provide an option to customize notification preferences for each alert type, and a confirmation notification post-update should reflect these customized preferences.

In order to reduce alert fatigue, users need a summary of significant threshold changes at a set frequency.

Given the user has configured their threshold settings, when the threshold changes exceed a predefined sensitivity, then a summary notification should be generated and sent to the user on their selected schedule (e.g., daily, weekly).

User Training Resources

User Story: As a new user, I want access to training resources on how to set and adjust my alert thresholds so that I can effectively monitor sentiment changes relevant to my brand.
Description: The User Training Resources requirement encompasses the development of comprehensive training materials and resources for users to effectively utilize the User-Defined Thresholds feature. This could include video tutorials, user manuals, and live webinars. The training resources are critical for maximizing user adoption and proficiency, ensuring that all users can leverage the full potential of customized alerts. By providing structured learning resources, SentiScan can empower its users to create effective and relevant alert settings, significantly enhancing the overall effectiveness of the sentiment analysis process.
Acceptance Criteria: User accesses the training resources section of the SentiScan platform to learn how to set user-defined thresholds effectively.

Given the user is on the training resources page, when they click on the video tutorial link, then the video should load successfully without errors and have knowledgeable content on setting thresholds.

User attends a live webinar to understand the User-Defined Thresholds feature better.

Given the user registers for the webinar, when the webinar starts, then the user should be able to join without any technical issues and receive a follow-up email with a recording of the session.

User refers to the user manual to configure alerts based on user-defined thresholds during peak social media hours.

Given the user accesses the user manual, when they search for 'setting alerts', then they should find clear, step-by-step instructions on how to set and customize alerts effectively.

User interacts with a FAQ section to troubleshoot common issues related to User-Defined Thresholds settings.

Given the user visits the FAQ section, when they click on 'common issues with setting thresholds', then they should see a list of at least five common problems and solutions available.

User completes all training modules and receives feedback on their understanding of the User-Defined Thresholds feature.

Given the user has completed the modules, when they submit their answers to the module quiz, then they should receive a certificate of completion if their score is above the passing grade.

User analyzes the effectiveness of the training materials after implementing the learned techniques.

Given the user has implemented the training techniques, when they assess the accuracy of their alerts over a month, then they should report an improvement of at least 20% in relevant alert notifications.

Threshold Impact Analysis

User Story: As a business analyst, I want to analyze the impact of my threshold settings on sentiment reporting so that I can optimize my alert configurations accordingly.
Description: The Threshold Impact Analysis requirement introduces an analytical feature that allows users to review the impact of their customized alert thresholds on sentiment reporting and business decisions over time. This functionality will help users understand how their settings have influenced their response strategies and business outcomes. By analyzing historical data in correlation with defined thresholds, users can refine their settings and improve future alert responses. This analytical capability is vital for fostering a data-driven decision environment and for enabling users to optimize their marketing efforts based on actual performance metrics.
Acceptance Criteria: User reviews historical sentiment data to analyze the effectiveness of their customized alert thresholds in driving business decisions.

Given the user navigates to the Threshold Impact Analysis feature, when they select a specific time period and alert threshold, then they should see a report detailing the correlation between the threshold settings and sentiment reporting outcomes over that period.

Administrator configures the system to calculate the impact of different user-defined thresholds on past sentiment data.

Given the system is configured with multiple user-defined thresholds, when an administrator runs an impact analysis, then the system should generate comparative results showing the impact of each threshold on user engagement and decision-making metrics.

A user examines the historical performance of their alerts based on customized thresholds to refine future settings.

Given the user accesses the Threshold Impact Analysis dashboard, when they apply different threshold settings to historical data, then they should be able to visualize and understand the resultant changes in sentiment reporting and adjust their future thresholds accordingly.

Marketers review the historical trends of sentiment analysis aligned with threshold changes to optimize future marketing strategies.

Given the user selects a marketing campaign and associated thresholds, when they generate a report, then the report should indicate how changes in thresholds affected sentiment trends and campaign outcomes over time.

A user receives notification alerts based on their defined thresholds and analyzes their effectiveness post-campaign.

Given the user has customized alert thresholds and completed a marketing campaign, when they view the Threshold Impact Analysis, then they should see a detailed breakdown of the alerts triggered and their correlation with key performance indicators.

The application allows users to simulate different threshold settings and view potential impacts on sentiment analysis.

Given the user is on the simulation interface, when they adjust the sensitivity levels of previous thresholds, then they should see projected sentiment reporting outcomes reflecting those changes in real-time.

Sentiment Trend Analytics

Sentiment Trend Analytics complements Sentiment Alerts by providing users with historical context and trend analysis related to recent alerts. This feature allows users to visualize the evolution of sentiment over time, giving them insights into the factors driving changes. By understanding trends, marketers can craft strategic responses that not only address immediate concerns but also anticipate future consumer behavior.

Requirements

Historical Sentiment Analysis

User Story: As a marketing analyst, I want to analyze historical sentiment data so that I can understand long-term trends and make informed strategic decisions.
Description: The Historical Sentiment Analysis requirement involves the development and implementation of a feature that allows users to access and analyze sentiment data over various past timeframes. It includes the aggregation of sentiment scores, categorization by themes, and integration with visualization tools to showcase changes in consumer sentiment over time. This feature is crucial as it provides a deeper understanding of long-term trends and patterns in consumer attitudes, enabling marketers to make more informed decisions based on historical context. The expected outcome is to equip users with the ability to correlate past sentiment trends with marketing campaigns, product launches, and external events, thereby enhancing strategic planning.
Acceptance Criteria: Historical sentiment analysis for a marketing campaign evaluation

Given that a user has initiated an analysis on the sentiment related to a past marketing campaign, when they select the campaign's timeframe and apply relevant filters, then the system should display a visual graph of sentiment trends over the selected period that includes aggregated sentiment scores and categorization by themes.

Accessing historical sentiment data for thematic exploration

Given that a user is interested in analyzing sentiment themes over time, when they access the historical sentiment analysis feature and select specific themes, then the system should provide a detailed timeline visualization that shows how sentiment towards those themes has evolved across different periods.

Integration of historical sentiment data with real-time alerts

Given that a user receives a sentiment alert for a specific topic, when they access the historical sentiment analysis, then the system should correlate past sentiment scores and trends to the recent alert, providing insights into how sentiments have shifted in relation to the alert.

Generating reports on historical sentiment analysis for stakeholder review

Given that a user wants to create a report on historical sentiment trends, when they select the desired timeframes and themes and generate the report, then the system should produce a comprehensive and visually appealing report that can be exported in multiple formats (PDF, Excel) with all relevant data and trend visualizations included.

User feedback on the historical sentiment analysis interface

Given that a user is interacting with the historical sentiment analysis feature, when they complete their analysis and provide feedback through the built-in feedback mechanism, then the system should record the feedback and display a confirmation message indicating successful submission.

User authentication for accessing historical sentiment analysis

Given that a user is not logged into the SentiScan application, when they attempt to access historical sentiment analysis, then the system should prompt them to log in to ensure secured access to sensitive data.

Timeframe selection for intensive analysis of sentiment data

Given that a user is using the historical sentiment analysis feature, when they choose a custom date range for the analysis, then the system should accurately reflect the sentiment trends only for the selected period and not for other timeframes.

Real-Time Sentiment Dashboard

User Story: As a brand manager, I want a real-time sentiment dashboard so that I can monitor live changes in consumer attitudes and react swiftly to any arising issues.
Description: The Real-Time Sentiment Dashboard requirement focuses on creating an intuitive visual interface that continuously updates to reflect the current sentiment analysis from various social media and online platforms. This dashboard will display key sentiment metrics, such as sentiment score, volume of positive and negative mentions, and trend indicators. The dashboard will be customizable, allowing users to view specific metrics or compare different time frames. The benefit of this feature is its ability to provide users with immediate insights that drive agile marketing responses and facilitate timely decision-making. The expected outcome is that users will have a clear, instant visual representation of sentiment data, enhancing their ability to react quickly to changes in consumer sentiment.
Acceptance Criteria: User accesses the Real-Time Sentiment Dashboard to view current consumer sentiment across multiple social media platforms during a product launch event.

Given the user is logged into SentiScan, when they open the Real-Time Sentiment Dashboard, then the dashboard should display sentiment scores updated within the last minute, including metrics for positive, negative, and neutral mentions across selected platforms.

A marketer wants to compare sentiment trends over the last week to identify shifts before an upcoming marketing campaign.

Given the user selects a date range for the past week on the dashboard, when they apply the filter, then the dashboard should accurately reflect the sentiment trend visualizations and key metrics for that period without latency.

The marketing team needs to set alerts for significant sentiment changes during a public relations crisis.

Given the user configures a sentiment alert threshold in the settings, when sentiment scores trigger a defined threshold, then the user should receive an immediate notification through the selected communication channel (email or in-app alert).

A user customizes their dashboard to focus on specific metrics relevant to their brand's audience.

Given the user has access to the customization features, when they select specific metrics to display on the dashboard, then the dashboard should reflect the user's choices accurately and save these preferences for future sessions.

The business intelligence team is reviewing historical sentiment data to prepare a report on consumer sentiment changes related to brand loyalty.

Given the user navigates to the historical trend analysis section, when they select a defined time frame, then the dashboard should present accurate historical data and allow for exporting this data as a report in a preferred format (CSV, PDF).

An analyst needs to quickly identify spikes in sentiment data during promotional events to evaluate campaign effectiveness.

Given the real-time data is being analyzed, when there is a spike in positive sentiment during a promotional event, then the dashboard should visually highlight this spike and provide insights into potential causes.

A user is training a new team member on how to utilize the Real-Time Sentiment Dashboard effectively.

Given the user accesses the help section, when they load the dashboard, then they should see tooltips and guided walkthroughs on key features and functionalities to support new users.

Sentiment Trigger Alerts

User Story: As a social media manager, I want to receive sentiment trigger alerts so that I can quickly address potential brand issues and leverage positive feedback.
Description: The Sentiment Trigger Alerts requirement involves the implementation of an alert system that notifies users when sentiment metrics exceed predefined thresholds or experience significant shifts. This could include spikes in negative sentiment or drops in positive feedback. Alerts can be sent via email or through app notifications and will provide context such as the subject of the sentiment, the volume of mentions, and potential implications for the brand. This feature is essential for ensuring that marketing teams can quickly address any emerging issues or capitalize on positive sentiment trends. The expected outcome is a proactive approach to sentiment management, where users can swiftly act on changes in sentiment before they escalate.
Acceptance Criteria: User receives an alert via email when the sentiment score for a brand drops below the predefined threshold set in the application.

Given the user has set a threshold for negative sentiment, when the sentiment score drops below that threshold, then an email alert should be sent to the user with the details of the sentiment drop.

The application sends a push notification to users when there is a spike in positive sentiment regarding a newly launched product.

Given a new product has been launched and the sentiment score is monitored, when the sentiment score shows a spike above a specified level, then a push notification should be triggered to inform users of the positive sentiment.

Users can view the historical data related to sentiment changes that triggered alerts in the last month.

Given the user accesses the Sentiment Trend Analytics dashboard, when the user selects the 'Last Month' filter, then the system must display the historical sentiment data reflecting all alerts triggered in that timeframe.

The system categorizes the alerts based on the type of sentiment (positive, negative, neutral) for easier analysis by users.

Given multiple alerts have been triggered, when the user views the alerts dashboard, then all alerts must be categorized and labeled according to their sentiment type (positive, negative, neutral).

Users receive a summary of potential implications for their brand associated with each sentiment alert.

Given the user receives a sentiment alert, when looking at the alert details, then a summary of potential brand implications must be included within the alert message.

Alerts can be configured by users to be sent at specific times or under specific conditions based on their needs.

Given the user accesses the alert settings, when setting conditions for alerts, then the user must be able to specify the frequency and situations in which alerts will be sent.

Comparative Sentiment Benchmarking

User Story: As a market strategist, I want to perform comparative sentiment benchmarking so that I can analyze our brand’s position against competitors and identify improvement opportunities.
Description: The Comparative Sentiment Benchmarking requirement focuses on developing a feature that enables users to compare their brand’s sentiment metrics against competitors within the same industry. This will include the visualization of comparative data, analysis of sentiment changes over time, and identifying areas where the brand is performing well or could improve. This feature is vital for marketing teams to understand their standing in the market and make competitive strategizing decisions based on sentiment data. The expected outcome is for brands to benchmark their performance effectively, enabling targeted marketing efforts that enhance competitiveness.
Acceptance Criteria: Comparative sentiment benchmarking for a brand’s performance against top three competitors in the footwear industry during a promotion period.

Given that a marketing analyst is in the Comparative Sentiment Benchmarking dashboard, When they select a competitor's brand and a specific promotion period, Then the system should display a comparative sentiment analysis chart showing sentiment scores for the selected competitor and the user's brand over the chosen duration.

Analyzing sentiment shifts in response to recent marketing campaigns compared to competitors’ campaigns within the electronics sector.

Given that a user has access to the sentiment benchmarking feature, When they input the dates for their recent marketing campaign, Then the tool should identify and display sentiment shifts over time for their brand and competitors during the campaign period, highlighting key events that influenced changes in sentiment.

Visualizing comparative sentiment metrics on user-defined timelines to assess brand perception against industry benchmarks.

Given that a user wants to evaluate their brand's sentiment over the last six months, When they set a custom date range and select industry benchmarks, Then the system should generate a visual representation (graph/table) comparing their brand’s mean sentiment score against the mean scores of selected competitors across the same period.

Identifying strengths and weaknesses by comparing sentiment metrics with leading brands in the food and beverage industry.

Given a user is analyzing their brand's performance, When they view the sentiment benchmarking report, Then the system should categorize areas of strength (positive sentiment) and weakness (negative sentiment) in relation to leading competitors with actionable insights and recommendations for improvement.

Monitoring sentiment changes over time during crisis events affecting the brand and competitors in the fashion industry.

Given a historical crisis event affecting the fashion sector, When the user selects the specific event timeline, Then the system should present a detailed comparative sentiment graph showing the user brand's performance against competitors' sentiment trends during the crisis period.

Utilizing sentiment analysis data to inform strategic marketing decisions in real-time analysis for competitive positioning.

Given a user is analyzing current sentiment data, When they apply filters for specific metrics (e.g., positivity, negativity), Then the system should provide real-time insights on how their brand is performing relative to the identified competitors across selected metrics.

Sentiment Segmentation Analysis

User Story: As a digital marketer, I want to perform sentiment segmentation analysis so that I can tailor my campaigns to specific audiences based on their sentiment responses.
Description: The Sentiment Segmentation Analysis requirement involves the capability to dissect sentiment data into various segments, such as demographics, geographic locations, or product categories. This feature would enable users to understand which audience segments are driving specific sentiment trends, allowing for tailored marketing strategies that resonate with distinct consumer groups. The importance of this requirement lies in its ability to help marketers craft personalized campaigns based on segment performance, leading to more effective engagement. The expected outcome is a detailed understanding of consumer segments, which guides targeted marketing efforts and enhances overall campaign effectiveness.
Acceptance Criteria: User is analyzing sentiment data for a specific demographic group during a campaign evaluation meeting.

Given the user selects a demographic segment, When they request a sentiment segmentation report, Then the system displays a detailed breakdown of sentiment scores by sub-segments within that demographic.

A marketer wants to visualize sentiment trends over time for a particular product category before launching a new campaign.

Given the user accesses the Sentiment Trend Analytics dashboard, When they filter the data by product category, Then they can view a graph displaying sentiment score changes over the last six months, with key events annotated.

During a follow-up meeting, users need to discuss the impact of a recent marketing strategy on consumer sentiment across different geographic regions.

Given the user selects multiple geographic regions, When they generate a sentiment analysis report, Then the report must include comparative insights on sentiment changes across selected regions along with recommendations for future strategies.

A product manager is looking to target communication based on sentiment trends associated with various customer segments in an upcoming strategy session.

Given the user requests a segmented analysis of sentiment data, When they specify the target segments, Then the system must deliver clear insights indicating which segments have the highest positive and negative sentiment, with actionable recommendations.

An analyst is preparing a presentation on consumer sentiment shifts related to a recent social media campaign.

Given the user has access to the sentiment data, When they compile a report on the campaign's impact, Then the report must contain visualizations that effectively highlight significant sentiment fluctuations over the campaign period across multiple segments.

As part of user training, a marketer is demonstrating how to use the sentiment segmentation feature to tailor marketing strategies.

Given the user engages the segmentation feature, When they apply segmentation filters, Then the system should accurately segment and display examples of past successful marketing strategies based on the analyzed sentiment data.

Actionable Response Suggestions

Actionable Response Suggestions accompany Sentiment Alerts with tailored recommendations for immediate action based on sentiment changes. Using AI to analyze similar past incidents and responses, this feature equips users with concrete steps to take in reaction to sentiment shifts, ensuring that their responses are logical, timely, and effective in mitigating negative effects or amplifying positive sentiment.

Requirements

AI-Driven Recommendations

User Story: As a marketer, I want AI-driven response recommendations so that I can effectively respond to sentiment changes in real-time and improve audience engagement.
Description: This requirement entails the development of an AI-based engine that analyzes historical sentiment data and current events to generate tailored response suggestions for users upon receiving Sentiment Alerts. These recommendations will be designed to help users react in ways that are both logical and effective. By harnessing previous incident data and correlating it with current sentiment trends, this feature will enhance decision-making capabilities, streamline responses, and ultimately boost user confidence in handling sentiment shifts. This functionality ensures that marketers and analysts can address sentiment changes with agility and precision, fostering engagement and optimizing strategies.
Acceptance Criteria: User receives a sentiment alert indicating a significant shift towards negative sentiment for a product launch campaign on social media.

Given a sentiment alert has been triggered, when the user accesses the actionable response suggestions, then the system should provide at least three specific recommendations tailored to addressing the negative sentiment detected.

A marketing analyst wants to compare the AI-driven suggestions provided for a recent negative sentiment alert with past responses to similar sentiments.

Given the user requests to view historical incident data, when the user selects a specific incident, then the system should display past responses along with their outcomes for at least five similar incidents.

A user receives a sentiment alert indicating a positive sentiment increase for a product, following a recent advertising campaign.

Given a sentiment alert has been triggered for positive sentiment, when the user reviews the actionable response suggestions, then the system should recommend at least two strategies to amplify the positive sentiment and include potential channels for their execution.

An analyst is monitoring sentiment trends in real-time and receives an alert for a sudden shift in sentiment related to a competitor's product.

Given the analyst receives a sentiment alert for a competitor's product, when the user requests additional data, then the system should provide a comparative analysis of the competitor's sentiment trend and suggest at least two competitive responses.

A user has just implemented one of the actionable response suggestions from the system and wants to evaluate its effectiveness.

Given the user implemented a suggested response, when the sentiment data is updated, then the system should show the change in sentiment and provide a performance metric indicating whether the sentiment improved, remained neutral, or worsened as a result of the action taken.

A marketing team is preparing for a quarterly review and wants to analyze how the AI-driven recommendations affected past sentiment shifts.

Given the marketing team is reviewing quarterly data, when they access the reports, then the system should present a summary of actionable recommendations given during sentiment shifts and their impact on engagement metrics over the past quarter.

Sentiment Shift Alerts

User Story: As a market analyst, I want to receive real-time alerts for sentiment shifts so that I can respond quickly and mitigate any potential negative impacts.
Description: This requirement focuses on the development of a robust alert system that notifies users of significant shifts in sentiment across monitored channels in real time. The alerts will utilize AI algorithms to detect abrupt changes and categorize them based on urgency and potential impact. This feature is crucial as it allows users to stay informed and proactive, enabling prompt responses to negative sentiments or opportunities to amplify positive feedback. Integration with the existing dashboard and notification system will ensure that users receive alerts seamlessly. This enhancement is pivotal for timely decision-making and maintaining a favorable brand reputation.
Acceptance Criteria: Sentiment Shift Alerts for Negative Sentiment Monitoring

Given a user is monitoring brand sentiment, when a significant negative shift is detected in real-time, then an alert is triggered, categorized as high urgency, and displayed on the user's dashboard.

Sentiment Shift Alerts for Positive Sentiment Amplification

Given a user is monitoring social media sentiment, when a significant positive shift is detected, then an alert is triggered, categorized as medium urgency, and includes a suggestion to amplify this sentiment through targeted marketing actions.

Real-time Delivery of Sentiment Alerts

Given the AI algorithms are operating, when a sentiment shift occurs, then the alert is delivered to the user's notification system within 5 seconds of detection.

Categorization of Alerts Based on Impact

Given an alert is triggered, when a shift is categorized, then the alert must include a severity rating (high, medium, low) based on the potential impact of the sentiment shift.

Integration with Dashboard for User Notifications

Given an alert is triggered, when the user accesses their dashboard, then all recent sentiment alerts must be displayed prominently, with clear indications of urgency and recommended actions.

User Feedback Mechanism for Alert Effectiveness

Given users receive sentiment shift alerts, when users provide feedback on the usefulness of these alerts, then at least 80% of user feedback must indicate that the alerts helped them make informed decisions.

Historical Data Analysis for Pattern Recognition

Given past sentiment alerts, when the AI analyzes trends, then at least 90% accuracy must be achieved in predicting future sentiment shifts based on historical data.

Dashboard Integration

User Story: As a user of SentiScan, I want to see actionable response suggestions directly on my dashboard so that I can easily access recommendations and take prompt actions without disruptions.
Description: This requirement involves the integration of actionable response suggestions directly into the user dashboard of SentiScan, enabling users to access recommendations without navigating away from their primary work interface. Users will benefit from a streamlined experience where sentiment alerts and corresponding action suggestions appear in a unified view, enhancing usability and decision-making efficiency. This integration is essential for reducing cognitive load and promoting timely actions based on sentiment analysis. Ensuring that the interface is intuitive and incorporates visual indicators for different sentiment recommendations will also be a key aspect of this requirement.
Acceptance Criteria: Integration of Actionable Response Suggestions into User Dashboard

Given a user is logged into SentiScan, when they receive a sentiment alert, then actionable response suggestions should be displayed directly on the dashboard without any additional navigation steps.

Visual Indicators for Sentiment Recommendations

Given actionable response suggestions are shown on the dashboard, then they must include visual indicators (such as color coding) to differentiate between positive, neutral, and negative sentiment recommendations.

Consistency in Response Suggestions

Given a sentiment alert is triggered, when a user views actionable response suggestions, then the suggestions must be consistent with similar past incidents in both format and relevance to ensure clarity for the user.

Timeliness of Suggestions

Given a user receives a sentiment alert, when they view the actionable response suggestions, then the suggestions must load within 2 seconds to ensure timely access for decision-making.

User Interaction with Suggestions

Given actionable response suggestions are displayed, when a user clicks on a suggestion, then the system should provide additional details and next steps related to that suggestion promptly.

Usability Testing of Dashboard Integration

Given multiple users interact with the new dashboard integration, when a usability test is conducted, then at least 80% of users should indicate that the actionable response suggestions are easy to understand and useful.

User Feedback Collection

Given that actionable response suggestions are implemented, when a feedback mechanism is provided, then at least 50% of users should actively provide feedback on the usefulness of the suggestions within the first month of use.

Historical Data Analysis

User Story: As a strategist, I want to analyze historical sentiment data alongside current alerts so that I can better understand trends and improve my response strategies.
Description: This requirement covers the functionality enabling users to analyze historical sentiment data alongside current sentiment alerts and recommendations. The feature will allow users to draw correlations between past incidents and their outcomes, facilitating a deeper understanding of sentiment trends and the effectiveness of previous responses. This capability will be advantageous for users in refining their engagement strategies and making informed predictions about potential future sentiment changes. Offering visual analytics tools and comparative metrics will enhance the user’s ability to leverage historical insights effectively.
Acceptance Criteria: Analyzing Historical Sentiment Data to Understand Trends

Given a user logs into SentiScan, when they navigate to the Historical Data Analysis section, then they should be able to access and visualize sentiment data for the past year, including key metrics such as sentiment score and sentiment volume.

Drawing Correlations Between Past Incidents and Outcomes

Given a user accesses the Historical Data Analysis feature, when they select a specific incident from the past, then the system should display corresponding outcomes, along with visualizations comparing the sentiment before and after the incident.

Utilizing Visual Analytics Tools for Insights

Given that sentiment alerts have been received, when a user reviews the historical sentiment trends, then they should be able to utilize available visual analytics tools (charts, graphs) to discern patterns and make data-driven decisions.

Comparative Metrics to Benchmark Current Sentiment Against Historical Data

Given a user wants to compare current sentiment metrics, when they select the appropriate filters in the Historical Data Analysis, then they should see comparative metrics such as percentage change and historical averages prominently displayed.

Improving Engagement Strategies Based on Historical Insights

Given a user has analyzed historical sentiment data, when they review the suggested actions for recent sentiment alerts, then they should see tailored recommendations that consider the effectiveness of past responses in similar situations.

Timely Alerts for Significant Sentiment Changes

Given that historical sentiment data is integrated with current alerts, when a significant change in sentiment occurs, then the user should receive a real-time notification with context from historical data.

Ease of Access to Historical Data Analytics

Given a user interacts with the SentiScan dashboard, when they navigate to Historical Data Analysis, then the user should find it intuitive and require no more than three clicks to access detailed historical sentiment analytics.

Multi-Channel Integration Alerts

Multi-Channel Integration Alerts notify users of sentiment changes occurring across various digital platforms in real-time. This feature provides a cohesive view of how sentiment varies by channel such as social media, reviews, and news articles, ensuring that users maintain a comprehensive understanding of their brand reputation. By promoting adaptive strategies across channels, this feature enhances overall marketing effectiveness.

Requirements

Real-Time Sentiment Monitoring

User Story: As a marketing analyst, I want to receive real-time alerts about sentiment changes across various digital platforms so that I can promptly adjust our marketing strategies according to public perception.
Description: The Real-Time Sentiment Monitoring requirement enables the SentiScan platform to continuously track and analyze sentiment changes across multiple digital channels including social media, online reviews, and news articles. It provides users with instantaneous alerts when significant fluctuations in sentiment are detected, allowing for prompt action to be taken. This functionality enhances user decision-making and response strategies, increasing the overall marketing effectiveness. The integration of this monitoring capability ensures that users are always informed of their brand's public perception, facilitating timely adjustments to their marketing strategies and messaging based on real-time data.
Acceptance Criteria: User receives an alert when there is a significant positive shift in sentiment regarding their brand on social media within 5 minutes of the change occurring.

Given the SentiScan system is actively monitoring social media channels, When there is a notable positive sentiment shift exceeding a predefined threshold, Then the user should receive a real-time alert within 5 minutes of the change.

User is notified of a significant negative sentiment change from online reviews for a specific product.

Given the SentiScan is tracking online reviews, When a significant negative sentiment shift occurs, Then the user should receive an alert with detailed metrics illustrating the sentiment change within 5 minutes.

User accesses the multi-channel dashboard and views sentiment metrics across different platforms after receiving an alert.

Given the user is on the multi-channel dashboard, When they receive a sentiment alert, Then they should be able to view real-time sentiment metrics specifically showing the changes by channel (social media, reviews, news).

User sets a custom alert threshold for sentiment changes and tests its functionality.

Given the user is in the settings page of the alert system, When they set a threshold for sentiment changes and significant fluctuations occur, Then the alert should trigger according to the user-defined parameters tested in a controlled environment.

User receives an aggregated report of sentiment change statistics over the last week following alerts received.

Given the alert system has been active for a week, When the user requests an aggregated report, Then they should receive a comprehensive report detailing the alerts and corresponding sentiment changes categorized by platform for that week.

User experiences a delayed notification of a sentiment change exceeding a set threshold.

Given the SentiScan is monitoring sentiment changes, When a significant shift occurs and the notification is delayed beyond a set time limit, Then a warning should be generated for the user highlighting the delay and the reason.

User integrates SentiScan with third-party analytics tools to analyze sentiment data.

Given the user has configured API access for third-party tools, When sentiment data is sent to these tools, Then the data should be accurately reflected and accessible in real-time in the third-party analytics platforms.

Channel-Specific Sentiment Insights

User Story: As a digital marketer, I want to analyze sentiment trends for specific channels so that I can optimize my campaigns based on where our messaging resonates best.
Description: The Channel-Specific Sentiment Insights requirement focuses on providing users with detailed analysis of sentiment variations tailored to individual channels such as Facebook, Twitter, Instagram, and others. Each channel will have its own dashboard that highlights sentiment trends over time, enabling marketers to identify which platforms are most effective for engagement. This feature promotes better resource allocation by allowing users to fine-tune their strategies according to channel performance, ultimately optimizing overall marketing effectiveness and audience engagement.
Acceptance Criteria: User accesses the Channel-Specific Sentiment Insights dashboard for Twitter, aiming to analyze sentiment trends over the past month.

Given the user selects the Twitter channel, When they request sentiment insights, Then the dashboard displays a graph illustrating sentiment trends for the past month with metrics on positive, negative, and neutral sentiments.

User sets up alerts for significant sentiment shifts on Facebook to monitor their brand reputation.

Given the user configures alert settings for the Facebook channel, When the sentiment changes by more than 10% in either direction, Then the user receives an immediate notification via email and in-app alert.

User wants to compare sentiment trends between Instagram and Twitter over a specific period to determine which platform is more effective for engagement.

Given the user selects both Instagram and Twitter for comparison, When they generate the report for the specified period, Then the report includes side-by-side graphs for sentiment trends, allowing for direct analysis.

User analyzes sentiment data from online reviews to refine marketing strategies and improve customer engagement.

Given the user navigates to the online reviews channel, When they view the sentiment insights, Then the dashboard displays a summary of sentiment variations, including key themes derived from the sentiment data.

Marketing manager reviews the sentiment insights for all channels during a strategy meeting to allocate resources effectively.

Given the user accesses the comprehensive view of sentiment insights across all channels, When the user filters by sentiment positive and negative trends, Then the interface shows aggregated results and a breakdown by channel.

Sentiment Benchmarking Reports

User Story: As a product manager, I want to access sentiment benchmarking reports so that we can understand our performance relative to competitors and improve our market positioning.
Description: The Sentiment Benchmarking Reports requirement allows users to compare their sentiment metrics against industry benchmarks and competitor performance. This feature provides users with a deeper understanding of where their brand stands in relation to others in the market, highlighting strengths and weaknesses. By offering contextual reports, this feature enhances strategic planning and helps marketers identify opportunities for improvement and competitive advantages that could be leveraged in their campaigns.
Acceptance Criteria: Comparing sentiment metrics against established industry benchmarks to evaluate brand performance.

Given the user accesses the Sentiment Benchmarking Reports feature, when they select specific industry benchmarks, then the system displays comparative sentiment metrics alongside identified strengths and weaknesses for their brand.

Generating a comprehensive report that highlights sentiment performance trends over a defined period.

Given the user specifies a time range for analysis, when they request a Sentiment Benchmarking Report, then the report generates with visual charts and actionable insights based on comparative data.

Providing users with actionable recommendations based on the sentiment analysis and benchmarking results.

Given the user has viewed their Sentiment Benchmarking Report, when they seek guidance, then the system presents relevant recommendations tailored to improve their brand's positioning and performance against competitors.

Allowing users to customize the metrics and industries used for benchmarking within the reports.

Given the user navigates to the report settings, when they select custom metrics and industries, then the Sentiment Benchmarking Report updates to reflect the selected options accordingly.

Enabling users to export the benchmarking reports into various formats for presentation and analysis.

Given the user views the generated Sentiment Benchmarking Report, when they select the export option, then the system allows them to download the report in formats such as PDF, Excel, and CSV.

Offering real-time notifications for significant changes in sentiment compared to benchmarks.

Given the user subscribes to sentiment alerts, when the system detects a significant deviation from benchmark metrics, then an immediate notification is sent to the user.

Allowing users to share benchmarking reports directly through the software with team members.

Given the user has generated a Sentiment Benchmarking Report, when they choose the share option, then the system enables sharing the report via email or integrated collaboration tools.

Customizable Alert Triggers

User Story: As a brand manager, I want to adjust my alert criteria so that I can focus on the most relevant sentiment changes while avoiding information overload.
Description: The Customizable Alert Triggers requirement enables users to set specific parameters for when they would like to receive alerts regarding sentiment changes. Users can customize their alert settings based on sentiment thresholds, specific keywords, or trends, allowing them to focus on the most relevant and impactful information. This enhances user control over their monitoring and response processes, ensuring they can react to sentiment changes that matter most to their strategies.
Acceptance Criteria: User sets up a customizable alert for sentiment changes regarding a specific keyword across multiple digital platforms.

Given the user accesses the alert configuration page, when the user inputs a specific keyword and sets a sentiment threshold (positive, neutral, negative), then an alert should be triggered when the sentiment changes exceed the set threshold for that keyword.

User receives alerts based on predefined thresholds for sentiment changes on different platforms.

Given a sentiment threshold is set for a particular channel (e.g., social media), when the sentiment changes and crosses the threshold, then a notification should be sent to the user via their preferred communication method (email, SMS, app notification).

User wants to monitor sentiment trends over time and receive alerts for significant shifts.

Given the user selects a trend monitoring option, when there is a significant deviation (e.g., a 20% increase or decrease in sentiment) over a specified period, then the user should receive an alert detailing the trend change and its context.

User modifies existing alert settings to include additional keywords and adjust thresholds.

Given the user edits an existing alert setup, when the user adds more keywords and updates the threshold values, then the system should save the changes and reflect the updated alert parameters in the user's alert summary.

User tests the alert functionality to ensure alerts are triggered correctly.

Given the user is in a testing phase, when the user simulates sentiment changes that meet the alert criteria, then the user should receive the corresponding alert within 5 minutes of the simulated change.

User accesses a dashboard to review active alerts and their statuses in real-time.

Given the user navigates to the alerts dashboard, when the dashboard loads, then it should display current active alerts, sentiment statuses, and details regarding the configuration of each alert.

User receives feedback on the alert configurations to optimize future monitoring.

Given the user opts to receive suggestions, when the user's alert configurations are analyzed, then the system should provide actionable recommendations on adjusting thresholds and keywords to enhance alert effectiveness.

Mobile Optimization for Alerts

User Story: As a marketing executive, I want to receive real-time alerts on my mobile device so that I can stay informed about sentiment changes even when I'm away from my desk.
Description: The Mobile Optimization for Alerts requirement ensures that the alert system is fully optimized for mobile devices, allowing users to receive notifications and access insights on the go. This feature significantly improves user accessibility, enabling marketing professionals to stay updated with sentiment changes wherever they are. The mobile-friendly interface bolsters user engagement by providing a seamless experience across devices, ensuring users can act swiftly and effectively regardless of their location.
Acceptance Criteria: User receives a mobile notification for sentiment change in real-time while attending a marketing conference.

Given the user is at a marketing conference with no access to a desktop, when a sentiment change occurs on any integrated platform, then the user should instantly receive a mobile notification with details about the sentiment shift.

User logs into the mobile app to view recent sentiment alerts and insights after a busy day.

Given the user has received multiple notifications throughout the day, when they access the mobile application, then they should see a chronological list of all alerts with the latest sentiment analysis at the top.

User customizes their notification settings within the mobile app.

Given the user navigates to the notification settings, when they toggle the preferences for alert types and channels, then the application should update their settings accordingly and reflect changes immediately in the received notifications.

User seeks to filter alerts and insights by channel within the mobile application.

Given the user accesses the alerts section in the mobile app, when they apply filters for specific channels (e.g., social media, reviews), then the alerts displayed should only include those from the selected channels, ensuring a tailored experience.

User experiences a slow internet connection while trying to access notifications.

Given the user is in an area with limited connectivity, when they open the mobile app, then it should load the last accessed notifications and insights without requiring an internet connection, allowing offline access to critical information.

User interacts with the alert notification and wishes to view more details about a sentiment change.

Given the user receives a notification about a sentiment shift, when they tap on the notification, then they should be directed to a detailed screen showing the source of the sentiment change and additional insights.

User seeks to adjust the frequency of the notifications received for sentiment changes.

Given the user is on the notification settings page, when they set the frequency to receive alerts (e.g., immediate, hourly, daily), then this setting should be saved and reflected in the notifications they receive going forward.

Insight Dashboard Customizer

This feature enables users to tailor their dashboard layout and data display based on their specific interests and preferences. By allowing users to select the metrics and insights that matter most to them, the Insight Dashboard Customizer enhances user engagement and ensures that critical information is always front and center. This personalization promotes efficient data analysis and decision-making.

Requirements

Widget Selection Tool

User Story: As a data analyst, I want to select different visualization types for my metrics so that I can better understand trends and present my findings in a clearer way.
Description: The Widget Selection Tool allows users to choose from a variety of data visualization options such as graphs, charts, and tables to display their selected metrics. This requirement is essential for enabling users to represent the data in formats that are most meaningful to them, enhancing clarity and understanding. The implementation of this tool will increase user engagement by facilitating better transformation of raw data into visually appealing and easily interpretable visuals. Consequently, users will be more equipped to analyze trends and make timely, informed decisions based on the insights presented in their customized formats.
Acceptance Criteria: User selects multiple visualization options for the data they want to display on their customized dashboard.

Given a user is on the dashboard customizer, when they select at least three different visualization types from the widget options, then the dashboard should update to display all selected visualization types correctly and simultaneously.

User saves their customized dashboard with selected widgets, ensuring preferences are retained across sessions.

Given a user has customized their dashboard, when they click 'Save Dashboard', then their configuration should be stored and retrievable upon next login without data loss.

User removes a selected widget from the dashboard layout that is no longer needed.

Given a user has selected widgets on their dashboard, when they choose to remove a widget and confirm the action, then the widget should be removed from the dashboard layout immediately without affecting other widgets.

User is able to adjust the size and position of each visualization widget on the dashboard.

Given a user is viewing their dashboard, when they click and drag to resize or reposition a widget, then the widget should respond accordingly and maintain its new dimensions or position without errors.

User can preview their dashboard configuration before finalizing changes.

Given a user is customizing their dashboard, when they select 'Preview', then the dashboard should display a temporary view of the current configuration including all widgets selected for display.

User receives visual feedback when adding or removing widgets to/from their dashboard.

Given a user interacts with the widget selection tool, when they add or remove a widget, then the action should trigger a visual feedback indicating success of the operation (e.g., a brief animation or color change).

Real-time Metric Updates

User Story: As a marketing manager, I want my dashboard to update in real-time so that I can react immediately to shifts in consumer sentiment and adjust my strategies accordingly.
Description: The Real-time Metric Updates requirement ensures that the data displayed on user dashboards refreshes automatically and in real-time. This feature is crucial for providing users with the latest insights, allowing them to respond quickly to changes in sentiment or market conditions. By implementing this functionality, SentiScan will enhance its capability to deliver timely information, significantly improving decision-making processes. This requirement involves integrating live data feeds and presenting updates seamlessly within the dashboard, promoting a more dynamic and responsive analytics experience.
Acceptance Criteria: Real-time Updates During Live Analysis

Given the user is monitoring sentiment data on the dashboard, when a new data point is received, then the relevant metric on the dashboard should refresh automatically within 5 seconds without requiring a manual refresh.

Alert System for Significant Changes

Given the user has set thresholds for specific metrics, when the metric exceeds or drops below that threshold, then the user should receive an alert notification within 1 minute of the change.

User Experience During Metric Updates

Given the user is engaged with the dashboard, when a metric is updated in real-time, then the update should not disrupt the user's current interactions or cause any visual glitches.

Data Consistency Across Multiple Devices

Given the user accesses the dashboard from different devices, when a metric update occurs, then the data displayed on all devices must show the same updated values within 5 seconds.

Integration with External Data Sources

Given the user integrates SentiScan with external social media platforms, when a change occurs in the external data, then the dashboard should reflect that change in real-time with an appropriate lag time not exceeding 7 seconds.

Customizable Alert System

User Story: As a brand strategist, I want to set alerts for specific metric changes so that I can be notified instantly and take necessary action to address any shifts in consumer sentiment.
Description: The Customizable Alert System allows users to set specific thresholds or triggers for metrics they are monitoring. When these thresholds are exceeded, users receive instant notifications via their preferred communication channels, ensuring they never miss critical changes in sentiment. This requirement focuses on enhancing user responsiveness and promoting proactive decision-making. By effectively integrating the alert system with user preferences, SentiScan empowers users to take immediate action based on key insights, thus improving overall effectiveness in market analysis.
Acceptance Criteria: User sets up a new alert for a specific sentiment metric, choosing the threshold and the preferred communication channels (email, SMS, etc.).

Given the user is on the alert setup page, when they select a metric, specify a threshold, and choose a communication channel, then they should receive a confirmation message indicating that the alert has been successfully created.

An alert is triggered when the sentiment metric exceeds the set threshold, and the user receives a notification.

Given the user has set an alert and the metric exceeds the threshold, when the threshold is exceeded, then the user should receive an instant notification via the preferred communication channel chosen during alert setup.

The user wants to edit an existing alert to modify the threshold or communication settings.

Given the user has logged in and accessed their alert settings, when they select an existing alert and change either the threshold or the communication settings, then the changes should be saved and a success message displayed.

The user wishes to delete an existing alert.

Given the user is viewing their alerts, when they select an alert to delete, then the alert should be removed from the alert list, and a confirmation message should be shown.

A user attempts to set an alert with an invalid threshold value (e.g., negative number).

Given the user is on the alert setup page, when they enter an invalid threshold value and attempt to save the alert, then an error message should be displayed indicating the threshold must be a positive number.

User reviews the alert history to check past alerts triggered.

Given the user navigates to the alert history section, when they view the history, then they should see a list of all past alerts with timestamps and details on whether the alert was triggered or not.

Multi-Metric Comparison Feature

User Story: As a market researcher, I want to compare different metrics at once so that I can analyze the relationships between them and find actionable insights.
Description: The Multi-Metric Comparison Feature enables users to select and compare multiple metrics side by side on their dashboards. This requirement is vital for users who need to analyze relationships between different data points and understand how various factors affect sentiment simultaneously. By supporting comprehensive analyses through comparative insights, users can make more informed decisions based on the interplay of different metrics. This functionality underlines the importance of nuanced decision-making in a dynamic market environment.
Acceptance Criteria: User customizes their dashboard to compare sales growth and customer sentiment metrics side by side during a quarterly review meeting.

Given the user is on the Insight Dashboard Customizer, when they select the 'Sales Growth' and 'Customer Sentiment' metrics, then both metrics should be displayed side by side on the dashboard in a clear and visually appealing manner.

User attempts to add more metrics to their dashboard while maintaining a user-friendly interface for analysis.

Given the user has selected two metrics to compare, when they add a third metric, then the dashboard should rearrange dynamically, ensuring all selected metrics are visible without cluttering the interface.

User wants to export their customized dashboard data after comparing multiple metrics for a stakeholder presentation.

Given the user has completed setting up their multi-metric comparison, when they choose to export the dashboard, then the exported file should include all selected metrics and their current values in a clear format suitable for presentations.

User would like to receive alerts when a selected metric deviates significantly from historical data while using the Insight Dashboard.

Given the user has configured alerts for specific metrics, when a significant deviation occurs, then the user should receive a notification on their dashboard and via email if they choose that option.

User customizes their dashboard for quick access to the metrics important for evaluating marketing campaign performance.

Given the user has saved their customized dashboard layout, when they log in again, then the dashboard should display exactly as they left it with all metrics retained and arranged accordingly.

User needs to ensure that comparative metrics maintain accuracy during real-time updates from the data source.

Given the user is viewing the multi-metric comparison dashboard, when the underlying data source receives an update, then the metrics displayed should refresh automatically without requiring a manual reload, ensuring users see the latest data.

User wants to filter metrics based on date ranges to compare historical versus current sentiments effectively.

Given the user has selected specified date ranges for comparison, when they apply the filter, then the metrics should only display data relevant to those chosen date ranges on the dashboard.

User Permission Settings

User Story: As an account administrator, I want to set different permission levels for users so that I can control who has access to sensitive data and functionalities within the dashboard.
Description: The User Permission Settings requirement allows account administrators to define different access levels and permissions for various users within SentiScan. This functionality is essential for maintaining data integrity and security, ensuring that sensitive information is only accessible to authorized personnel. By implementing granular permission settings, SentiScan promotes a secure environment for collaborative analysis and protects user data, which is vital in a multi-user platform.
Acceptance Criteria: Admin assigns specific access levels to a new user based on their role in the organization.

Given an admin user, when they select a new user and define access levels, then the new user should receive the correct permissions as per the admin's input.

User attempts to access a feature they do not have permission for and receives appropriate feedback.

Given a regular user, when they try to access a feature restricted to admin users, then they should see an error message indicating insufficient permissions.

Admin modifies the permissions of an existing user and the changes take effect immediately.

Given an admin user, when they change the permission settings for an existing user, then those changes should be reflected in the user's access within 5 minutes.

Users with various permissions log in and see a dashboard tailored to their access level.

Given different user roles, when they log into SentiScan, then each user should only see the features and data that their permissions allow.

Admin generates a report of user access levels and verifies it for accuracy.

Given an admin user, when they request a report on user permissions, then the report should accurately reflect the permission settings assigned to each user.

New features are implemented and user permissions are updated accordingly.

Given the introduction of a new feature, when the admin configures permissions for this feature, then all users should only access this feature based on their defined permissions.

External audit of user permissions to ensure compliance isn't flagged for issues.

Given an audit scenario, when an external auditor reviews user permissions, then all access logs and settings should demonstrate compliance with data security regulations.

Smart Reporting Templates

Smart Reporting Templates provide users with customizable templates that adapt to their reporting needs based on historical engagement data and user preferences. By utilizing machine learning to suggest the most relevant visual formats and metrics, this feature simplifies the reporting process, saving time and increasing the effectiveness of presentations to stakeholders.

Requirements

Dynamic Template Customization

User Story: As a marketing analyst, I want to customize reporting templates in real-time so that I can present the most relevant data to my stakeholders and facilitate better decision-making during meetings.
Description: Dynamic Template Customization allows users to modify reporting templates in real-time, enabling them to tailor metrics, visual formats, and layouts based on their specific audience and engagement objectives. This requirement leverages user input and historical data to optimize presentation effectiveness, ensuring that stakeholders receive insights that matter to them. The implementation of this feature will require a backend system capable of storing user preferences and a front-end interface that allows for easy drag-and-drop edits and adjustments. As a result, users will enhance their reporting outcomes and foster more impactful discussions with stakeholders by delivering tailored and relevant insights through their presentations.
Acceptance Criteria: Real-time customization of a reporting template for a quarterly marketing review meeting with stakeholders.

Given that a user opens a reporting template for a quarterly marketing review, when they adjust metrics and visual formats using the drag-and-drop interface, then the template should update to reflect those changes in real-time without any lag.

Utilizing historical engagement data to automatically suggest metrics for a new marketing campaign report.

Given that a user selects a reporting template specifically for a new marketing campaign, when they access the machine learning suggestions, then the system should propose at least three relevant metrics based on past engagement data, which the user can manually select or deselect.

Saving user-customized report templates for future use.

Given that a user has customized a reporting template, when they click the 'Save Template' button, then the system should store the template and allow the user to access it from a 'My Templates' section in future sessions.

Sharing customized reporting templates with team members during collaboration.

Given that a user has created a customized reporting template, when they select the 'Share' option, then the system should allow for email invitations to be sent to specific team members and grant them access to view or edit the report.

Adjusting template layout based on specific audience preferences.

Given that a user is customizing a reporting template for a specific audience, when they select audience preferences, then the layout of the template should adapt accordingly, such as changing font size or visual elements to match audience needs.

Ensuring the reporting templates are mobile responsive.

Given that a user views a customized reporting template on a mobile device, when they open the template, then the layout should automatically adjust to maintain readability and usability across different screen sizes.

Generating reports based on selected templates accurately reflecting updated inputs and metrics.

Given that a user finalizes their customized reporting template and inputs data, when they click the 'Generate Report' button, then the system should produce a report that accurately reflects all selected metrics and visual formats in the chosen layout.

Machine Learning Metrics Suggestions

User Story: As a data analyst, I want to receive intelligent metric suggestions based on historical data so that I can create impactful reports that resonate with my audience and drive actionable insights.
Description: Machine Learning Metrics Suggestions will enhance the Smart Reporting Templates by analyzing historical engagement data and patterns to recommend the most effective metrics for inclusion in each report. By understanding what has resonated in the past, this requirement will enable users to leverage intelligent suggestions that align with stakeholder interests and reporting goals. Implementation includes the integration of machine learning algorithms that assess past report performances, transforming them into actionable suggestions for current reporting sessions. This feature aims to streamline the reporting process and ensure users always focus on impactful metrics, ultimately leading to improved stakeholder engagement and insights derived from reports.
Acceptance Criteria: User Analysis of Suggested Metrics for New Reports

Given a user is creating a new report, when they access the Smart Reporting Templates feature, then they will see a list of suggested metrics based on historical engagement data from previous reports with similar content and audience.

Validation of Machine Learning Algorithm Performance

Given the machine learning algorithm is implemented, when a user reviews suggested metrics for their report, then at least 80% of suggested metrics must align with user-defined reporting goals and stakeholder interests.

User Customization of Metric Suggestions

Given a user is presented with suggested metrics, when they customize their report by adding or removing metrics, then the Smart Reporting Templates must update to reflect these changes in real-time without requiring a page refresh.

Effectiveness of Metrics Suggestions on Stakeholder Engagement

Given the user has delivered a report utilizing the suggested metrics, when stakeholder feedback is collected after the presentation, then at least 70% of stakeholders should express that the metrics provided valuable insights for their decision-making process.

Historical Data Insights on Suggested Metrics

Given the machine learning metrics suggestions feature is operational, when the user activates the feature, then the system should provide insights into the historical performance of each suggested metric within the past reports.

Visual Format Optimization Engine

User Story: As a report creator, I want an optimization engine that suggests the best visual formats for my data so that I can communicate my findings clearly and effectively to my stakeholders.
Description: The Visual Format Optimization Engine will automatically curate the most effective visual representation for the data included in the reports. By analyzing the types of data selected and the context in which it will be presented, this requirement ensures that users can effortlessly generate visuals that enhance clarity and engagement. The engine will consider the data's characteristics and dynamically suggest appropriate charts, graphs, and infographics. In doing so, the implementation of this requirement will allow users to save time and ensure that complex data sets are displayed in a digestible manner, cultivating greater understanding and conversation among stakeholders.
Acceptance Criteria: User initiates a reporting session and selects multiple data sets for analysis.

Given the user has selected data sets from multiple sources, When the Visual Format Optimization Engine processes these data sets, Then it should suggest at least three relevant visual formats for each selected data set based on best practices in data visualization.

User requests a report and chooses a specific audience segment to analyze.

Given the user has selected a specific audience segment, When the Visual Format Optimization Engine analyzes the characteristics of the data, Then it should recommend visual formats that are proven to engage this specific segment more effectively, optimizing for user engagement.

User customizes the reporting template by adjusting specific metrics and visual preferences.

Given the user has customized the reporting template, When the Visual Format Optimization Engine evaluates the adjustments made by the user, Then it should dynamically update its suggestions to reflect the user's customizations without losing relevance or clarity.

User views the final report generated with optimized visuals before presenting to stakeholders.

Given the user has generated the report with optimized visuals, When the user previews the report, Then all suggested visuals must be displayed correctly and must align with the context of the data provided, ensuring clarity and usability.

User receives feedback from stakeholders regarding the effectiveness of the visuals in a reported presentation.

Given the user has presented the report to stakeholders, When feedback is gathered, Then at least 80% of stakeholders should report that the visuals effectively conveyed the data insights as intended, indicating successful optimization.

User attempts to generate a report with a unique data set not previously used.

Given the user selects a unique data set, When the Visual Format Optimization Engine processes this unfamiliar data, Then it should still successfully generate at least two appropriate visual formats that best represent the data characteristics.

Version Control for Templates

User Story: As a team lead, I want version control for our reporting templates so that our team can collaborate effectively and preserve the integrity of our reports over time.
Description: Version Control for Templates will allow users to track changes and revisions made to the reporting templates over time. Through an intuitive interface, users can easily revert to previous versions, compare changes, and understand the evolution of their reporting styles. This requirement is critical for maintaining consistency and quality in reporting, especially when multiple users contribute to shared templates. Implementation involves creating a version history log and user permissions that ensure template integrity while promoting collaborative efforts. The outcome is a more cohesive reporting practice, where users can sustain and improve their strategies based on iterative feedback.
Acceptance Criteria: User Accessing Version History of a Template

Given a user with the appropriate permissions, when the user selects a reporting template and clicks on the 'Version History' option, then the system should display a timeline of changes made to that template, including dates, authors, and a summary of changes for each version.

Reverting to a Previous Template Version

Given a user views the version history of a reporting template, when the user selects a previous version and clicks 'Revert', then the system should restore that version as the current template and confirm the action to the user.

Comparing Changes Between Versions

Given a user is on the version history screen for a reporting template, when the user selects two different versions to compare, then the system should display a side-by-side comparison of the differences, highlighting added, removed, and modified content.

Displaying User Permissions for Template Actions

Given an administrator is managing user access, when they view the permissions for a reporting template, then the system should clearly display which users can view, edit, and revert the template versions, with the ability to modify these permissions.

Notification System for Template Updates

Given a user subscribes to changes in reporting templates, when a template is updated or a new version is added, then the system should send a notification to the user, detailing the changes and encouraging them to review the updated template.

User Training on Version Control Features

Given a new user starts using the version control feature, when they open the help documentation, then the system should provide a detailed guide, including step-by-step instructions and FAQs about utilizing version control effectively.

Audit Log for Template Changes

Given an administrative user accesses the audit log, when they review the changes made to any reporting template, then the system should provide a comprehensive log of all actions taken, including timestamps, user IDs, and specific changes made.

Real-Time Collaboration Features

User Story: As a project manager, I want to collaborate with my team in real-time on reporting templates so that we can generate high-quality reports efficiently and avoid delays from back-and-forth revisions.
Description: Real-Time Collaboration Features will enable multiple users to work simultaneously on the same reporting template, fostering a more collaborative environment for creating and refining reports. This requirement ensures that teams can effectively communicate ideas and make immediate edits, reducing bottlenecks associated with sequential work. Implementing this will require integrated chat functionalities, simultaneous editing capabilities, and auto-saving features to ensure all changes are captured effortlessly. Ultimately, this feature aims to enhance teamwork and streamline permissions and access control for different team members while working on shared reporting documents.
Acceptance Criteria: User A and User B collaborate on a reporting template simultaneously during a strategy meeting.

Given that User A has shared a reporting template with User B, when both users access the template, then they should be able to see each other's edits in real-time without any delays.

A team member uses the integrated chat function to discuss changes on a reporting template while working on it.

Given that the integrated chat function is active, when a team member sends a message in the chat, then all participants currently editing the template should receive the message instantly.

The system saves the reporting template automatically while multiple users are editing it.

Given that multiple users are working on a reporting template, when a user makes an edit, then the system should auto-save the changes within 5 seconds to ensure no data is lost.

User C wants to change permissions on the shared report template to restrict access to certain team members.

Given that User C has appropriate permissions, when they attempt to change access controls, then they should be able to modify permissions for each team member effectively, with a confirmation of the changes.

A team encounters a connectivity issue while collaborating on the reporting template.

Given that a team member loses internet connectivity, when they reconnect, then the system should automatically synchronize their changes made prior to the disconnection with the current state of the reporting template.

A reporting template is opened for editing by multiple users across different devices and platforms.

Given that the reporting template is being accessed by different users on different devices, when alterations are made simultaneously, then the system should maintain the integrity of the data and display updates without corruption or loss.

User-Friendly Onboarding for Templates

User Story: As a new user, I want a guided onboarding experience for using Smart Reporting Templates so that I can learn how to effectively create and customize reports without feeling overwhelmed.
Description: User-Friendly Onboarding for Templates will provide new users with a guided experience to understand how to utilize the Smart Reporting Templates effectively. This requirement includes the creation of interactive tutorials, video guides, and practical examples that will help users navigate platform features and draw the most value from their reporting capabilities. The implementation process entails developing an educational framework alongside the templates to enhance user confidence and skill development. By addressing user onboarding effectively, this feature is expected to reduce the learning curve and enable users to swiftly adopt the tool, thereby maximizing their efficiency in reporting tasks.
Acceptance Criteria: User initiates the onboarding process for Smart Reporting Templates for the first time.

Given the user is on the onboarding tutorial page, when they click 'Start', then an interactive tutorial should open guiding them through the template features step-by-step.

User completes the interactive tutorials for Smart Reporting Templates.

Given the user has completed all steps of the interactive tutorial, when they finish, then a completion message should appear alongside a feedback survey to assess their understanding.

User accesses video guides for Smart Reporting Templates after completing the initial tutorial.

Given the user has completed the interactive tutorial, when they navigate to the video guide section, then they should be able to view and select from a list of relevant video guides based on their reported interests.

User interacts with practical examples of Smart Reporting Templates.

Given the user is viewing template examples, when they click on an example template, then the system should display the template in a preview mode with options to customize.

User provides feedback on the onboarding experience for Smart Reporting Templates.

Given the user has completed the onboarding process, when they fill out the feedback survey, then the system should log their responses and provide suggestions for improvement based on collected data.

User attempts to navigate away from the onboarding tutorials.

Given the user is in the middle of an onboarding session, when they attempt to leave the page, then a pop-up warning should appear asking if they want to continue or stay and finish the onboarding.

User measures their confidence level before and after the onboarding process.

Given the user has self-reported their confidence level in using templates before and after the onboarding, then there should be a measurable increase in their confidence as recorded in the system.

Behavioral Insights Feed

The Behavioral Insights Feed offers a dynamic stream of insights powered by user behavior analysis. This feature delivers timely notifications about trends, anomalies, or opportunities specifically tailored to each user's focus areas. It keeps users informed about critical developments, enabling them to act swiftly and strategically.

Requirements

Real-time Notification System

User Story: As a market analyst, I want to receive real-time notifications about shifts in consumer sentiment so that I can quickly adjust my marketing strategies and capitalize on emerging trends.
Description: The Real-time Notification System provides users with instant alerts and notifications about significant behavioral shifts, trends, and anomalies detected in customer sentiment data. This feature is essential for empowering users to respond swiftly to changes in consumer attitudes, ensuring they can capitalize on emerging trends or address issues proactively. Notifications can be customized based on user-defined parameters, ensuring relevance and utility in their decision-making processes. By integrating seamlessly with the Behavioral Insights Feed, this system enhances user engagement and drives timely action.
Acceptance Criteria: User receives a notification about a significant positive shift in customer sentiment after a marketing campaign.

Given that a marketing campaign has begun, when a positive shift in customer sentiment data is detected, then the user should receive a real-time notification via their chosen communication channel (email, SMS, or in-app alert).

User customizes notification settings to receive alerts pertaining only to specific product categories.

Given that the user is in the notification settings menu, when the user selects specific product categories for alerts and saves the settings, then the user will only receive notifications relevant to the chosen categories moving forward.

User receives an alert about an anomaly in customer sentiment data indicating potential dissatisfaction.

Given that customer sentiment data has been analyzed, when an anomaly indicating dissatisfaction is detected, then the user should receive an immediate alert detailing the issue, including relevant metrics and timeframes.

User checks the Behavioral Insights Feed for recent trends and notifications after two days of inactivity.

Given that the user returns to the Behavioral Insights Feed after two days, when they log in, then the feed should display all missed notifications and summarize key trends that occurred during that period.

User receives a notification for a trend that indicates an increase in positive sentiment towards a competitor's product.

Given that competitor analysis is part of the user's preferences, when a significant trend indicating increased positive sentiment towards a competitor's product is detected, then the user should receive an alert highlighting this trend and its potential impact.

User reviews historical notifications to assess past trends and responses to shifts in sentiment.

Given that the user accesses the historical notifications section, when they request to view notifications from the past 30 days, then the system should present a chronological list of notifications with corresponding sentiment analysis data for each entry.

User Behavior Analytics Dashboard

User Story: As a product manager, I want to access an analytics dashboard that visualizes consumer behavior patterns so that I can identify trends and adjust our marketing tactics accordingly.
Description: The User Behavior Analytics Dashboard is a comprehensive interface that allows users to visualize and analyze consumer behavior patterns over time. This dashboard will incorporate various data visualization tools, including graphs, heat maps, and trend lines, to present crucial insights and trends derived from user behavior. It aims to provide an at-a-glance overview of sentiment metrics, enabling users to identify significant changes and make data-backed decisions efficiently. The dashboard will integrate with the Behavioral Insights Feed, presenting insights in a cohesive and informative manner.
Acceptance Criteria: User views the User Behavior Analytics Dashboard for the first time after logging into SentiScan.

Given the user is authenticated, when they access the User Behavior Analytics Dashboard, then the dashboard should load within 3 seconds and display an overview of sentiment metrics, including graphs and heat maps.

User selects specific time frames to analyze behavior patterns within the User Behavior Analytics Dashboard.

Given the user selects a date range from the filter options, when they apply the filters, then the dashboard should refresh to display updated insights and trends relevant to the specified time frame.

User receives notifications from the Behavioral Insights Feed while analyzing data on the User Behavior Analytics Dashboard.

Given the user is actively analyzing data, when a new relevant insight is triggered by the Behavioral Insights Feed, then the user should receive a notification pop-up that displays the new insight without obstructing their view of the dashboard.

User interacts with the visualization tools on the User Behavior Analytics Dashboard to generate a targeted report.

Given the user interacts with a graph to zoom in on specific data points, when they complete the action, then the graph should dynamically update to reflect the selected data points and provide tooltips with detailed information for each point.

User identifies a significant trend change through the User Behavior Analytics Dashboard.

Given the dashboard displays sentiment metrics, when the user identifies a significant uptick in a specific sentiment, then the dashboard should highlight the trend in a distinct color and provide context about possible triggers for the change.

Data from the Behavioral Insights Feed integrates smoothly into the User Behavior Analytics Dashboard.

Given new insights from the Behavioral Insights Feed, when the user checks the dashboard, then the insights should be seamlessly integrated and clearly categorized under the relevant sections in the dashboard.

Customizable Insight Filters

User Story: As a marketing strategist, I want to filter behavioral insights based on specific criteria so that I can focus on the most relevant data for my campaigns.
Description: The Customizable Insight Filters allow users to tailor the types of behavioral insights they receive based on specific criteria such as demographic segments, topic relevance, or sentiment scoring. Users will have the ability to set preferences and refine their insight streams to receive the most pertinent information directly related to their focus areas. This customization ensures that users are not overwhelmed with irrelevant data, enhancing their ability to focus on actionable insights and improve decision-making processes regarding market strategies.
Acceptance Criteria: User sets up personalized filters for behavioral insights based on specific demographic segments including age, gender, and location preferences.

Given the user accesses the customizable insight filters, when they select demographic segments, then the system should display insights relevant only to the chosen demographics, and no irrelevant data should appear.

User configures filters to receive insights related to specific topics such as health trends, technology, or consumer behavior.

Given the user selects specific topics in the filter settings, when they save the preferences, then the Behavioral Insights Feed should only show insights that pertain to the selected topics, with all other topics excluded.

User adjusts sentiment scoring thresholds to prioritize insights that meet specific positive or negative sentiment criteria.

Given the user sets a sentiment threshold, when insights are delivered, then only those meeting the defined sentiment score should be presented in the feed, with a log of discarded insights for transparency.

User receives real-time alerts when significant anomalies in consumer behavior occur within their selected interest areas.

Given the user defines specific thresholds for anomalies, when an insight crosses that threshold, then the user should receive an immediate notification, ensuring prompt awareness of critical developments.

User tests the filter settings to ensure only selected insights are shown within the Behavioral Insights Feed.

Given the user activates the filters, when they review the Behavioral Insights Feed, then only insights corresponding to the selected filter settings should be visible, validating the effectiveness of the customization.

User wants to deactivate certain filters temporarily while maintaining other active preferences.

Given the user accesses their filter settings, when they deactivate a specific filter, then the Behavioral Insights Feed should continue to reflect all other active filters and cease to show insights from the deactivated filter.

User updates their filter preferences to refine the type of insights received after evaluating relevance over time.

Given the user modifies their filter preferences, when they save these changes, then the Behavioral Insights Feed should immediately reflect the updated filters, demonstrating real-time adaptability of the feature.

Anomaly Detection Algorithm

User Story: As an analyst, I want to leverage an anomaly detection algorithm to identify unusual consumer behavior so that I can proactively address potential issues or seize market opportunities.
Description: The Anomaly Detection Algorithm will be an advanced analytical tool that identifies unusual patterns or deviations in sentiment data that could indicate significant market shifts or emerging trends. By employing machine learning techniques, this algorithm will analyze historical data, recognize typical patterns, and flag anomalies for users’ attention. This feature not only aids in uncovering hidden opportunities but also helps in risk mitigation by drawing attention to potential pitfalls early. Integration with the Behavioral Insights Feed will ensure users receive prompt alerts regarding any detected anomalies.
Acceptance Criteria: User receives a notification for a detected anomaly in sentiment data that indicates a significant market shift.

Given that the Anomaly Detection Algorithm is operational, when the algorithm detects a deviation from typical sentiment patterns, then the user should receive a timely notification in the Behavioral Insights Feed.

Users can view and analyze anomalies detected by the algorithm in the dashboard interface.

Given that the Anomaly Detection Algorithm has flagged anomalies, when the user accesses the dashboard, then all detected anomalies should be displayed with relevant historical data and context for analysis.

Users can customize the types of anomalies they want to be alerted about.

Given that the user has access to the settings, when they select specific criteria for anomaly detection, then the system should only notify them about anomalies that match their selected criteria.

The algorithm appropriately learns from historical data to improve its detection capabilities over time.

Given that the algorithm has been trained on the initial dataset, when new historical data is introduced, then the algorithm should adapt its anomaly detection thresholds based on the updated patterns in the data.

The system provides users with insights explaining the reasons behind each detected anomaly.

Given that an anomaly is detected, when the user views the detailed analysis in the Behavioral Insights Feed, then they should see an explanation outlining potential causes or influences related to the anomaly.

Users can compare detected anomalies with previous trends to assess significance.

Given a detected anomaly, when the user requests a historical comparison, then the system should provide a visual representation of the anomaly compared to previous sentiment trends, highlighting the differences.

Competitive Benchmarking Tool

User Story: As a business analyst, I want to benchmark our sentiment data against competitors so that I can identify our strengths and weaknesses in the market.
Description: The Competitive Benchmarking Tool will enable users to compare their user behavior and sentiment insights against those of competitors within the same industry. This feature provides crucial context, allowing users to understand market positioning and make informed strategic decisions. By offering visual reports and data analysis related to competitor sentiment, this tool enhances the overall capabilities of the Behavioral Insights Feed, ensuring that users remain competitive in their market strategies.
Acceptance Criteria: User wants to compare their sentiment analysis results with a competitor in the same industry for the past month to evaluate their market positioning.

Given a user selects a competitor and a time frame from the Competitive Benchmarking Tool, When the user clicks on 'Generate Report', Then a visual report comparing user sentiment insights between the user and the selected competitor should be displayed, accurately reflecting the sentiments over the specified time frame.

User receives a notification about a significant increase in competitor sentiment after launching a new product.

Given that the Competitive Benchmarking Tool is integrated with the Behavioral Insights Feed, When the competitor's sentiment shifts significantly, Then the user should receive an immediate notification highlighting the change and suggesting actions to consider.

User wants to analyze trends in user behavior against multiple competitors over the last quarter to strategize their marketing efforts accordingly.

Given a user selects multiple competitors and a quarterly timeframe in the Competitive Benchmarking Tool, When the user initiates the comparative analysis, Then the system should produce a comprehensive report that includes key metrics and visual representations of behavioral trends throughout the selected period.

User is looking to evaluate the effectiveness of their recent marketing campaign by comparing sentiment before and after the campaign against competitors.

Given the user inputs the campaign dates and selects relevant competitors in the Competitive Benchmarking Tool, When the comparative report is generated, Then the insights should clearly indicate sentiment shifts pre- and post-campaign for both the user and competitors, allowing for strategic evaluation.

User wants to filter competitive sentiment data to focus on specific demographics relevant to their marketing strategy.

Given that the user has access to demographic filtering options in the Competitive Benchmarking Tool, When the user applies demographic filters and runs the analysis, Then the system should display results that highlight sentiment trends across the selected demographics, ensuring relevance to the user's strategy.

User desires to bookmark and revisit previously generated competitive reports for future reference or strategy meetings.

Given that the user generates a report in the Competitive Benchmarking Tool, When the user selects 'Bookmark Report', Then the report should be saved to the user's dashboard for easy access, with the ability to view or share in future sessions.

Sentiment Shift Alerts

User Story: As a brand manager, I want to receive alerts for significant sentiment shifts so that I can quickly address any potential brand issues or leverage opportunities for marketing.
Description: Sentiment Shift Alerts will notify users when significant changes in consumer sentiment occur, based on user-defined thresholds. This feature ensures that users can respond instantly to major sentiment shifts that could impact their products or brand reputation. By setting tailored alerts that factor in various sentiment metrics, users can take proactive measures to address concerns or leverage positive developments. Integration with the Behavioral Insights Feed will ensure that alerts are delivered promptly and directly to users, keeping them informed at all times.
Acceptance Criteria: User receives an alert when consumer sentiment falls below a user-defined negative threshold for a specific product.

Given the user has set a negative sentiment threshold of -0.5, when the sentiment score for the product falls to -0.6, then the user should receive an alert notification.

User receives an alert when consumer sentiment rises above a user-defined positive threshold for a particular brand.

Given the user has set a positive sentiment threshold of 0.7, when the sentiment score for the brand rises to 0.8, then the user should receive an alert notification.

Users can customize their sentiment alert settings based on various metrics like product types or demographic segments.

Given the user is setting up their alert preferences, when they choose demographic segments and product types, then the system should allow these specific customizations to be saved and applied for future alerts.

Alerts are integrated with the Behavioral Insights Feed to ensure timely delivery of sentiment shift notifications.

Given the user has subscribed to the Behavioral Insights Feed, when a significant sentiment shift occurs, then the user will receive the alert within 5 minutes through the Behavior Insights Feed notification system.

Users can see a historical log of sentiment alerts received over time for analysis.

Given the user accesses the sentiment alerts history feature, when they view the logs, then they should see a detailed list of all previous alerts received, including timestamps and sentiment scores.

Users can test and validate their alert settings before finalizing them.

Given the user is configuring their sentiment alert settings, when they click the 'Test Alert' button, then they should receive a simulated alert as per their current settings to ensure proper functionality.

Users can disable and enable sentiment alerts quickly based on ongoing marketing campaigns or strategies.

Given the user is in the settings menu for sentiment alerts, when they toggle the 'Enable/Disable Alerts' option, then the system should update the alert status immediately and reflect this change accurately in the user profile.

Automated Insights Generator

The Automated Insights Generator leverages AI to produce tailored insights reports based on user engagement patterns and preferences. Users receive personalized summaries highlighting key trends and actionable insights effortlessly, significantly enhancing their ability to make data-driven decisions without the need for extensive manual analysis.

Requirements

User Engagement Pattern Detection

User Story: As a marketer, I want to identify patterns in user engagement so that I can tailor my strategies to better meet audience preferences and improve engagement rates.
Description: This requirement entails the development of algorithms that can analyze user engagement data to identify patterns and preferences in real-time. The insights generated will be integrated into the Automated Insights Generator, allowing users to understand their audience better and make informed decisions based on engagement trends. This is crucial for ensuring that the insights provided are relevant and tailored to user behavior, leading to more effective marketing strategies and improved audience engagement. The implementation will focus on using AI and machine learning to enhance the accuracy of the detection process, thus delivering high-quality insights that align with user needs.
Acceptance Criteria: User Engagement Pattern Detection for Social Media Posts

Given a dataset of social media posts, when the algorithm analyzes engagement metrics such as likes, shares, and comments, then it should successfully identify at least three distinct user engagement patterns.

Real-time Pattern Detection During Marketing Campaigns

Given a live marketing campaign, when users interact with the content, then the system should provide real-time updates on user engagement patterns at least every five minutes.

Integration of Detected Patterns into Insights Reports

Given detected user engagement patterns, when generating insights reports, then the Automated Insights Generator should include at least five actionable items based on these patterns in the summary report.

Accuracy of Pattern Detection Algorithm

Given historical user engagement data, when the algorithm runs its analysis, then it should achieve an accuracy rate of at least 85% in identifying engagement patterns compared to manual analysis.

User Interface for Viewing Engagement Patterns

Given the user dashboard, when a user selects the 'Engagement Patterns' option, then the system should display visual representations of at least three identified patterns in an intuitive format.

Feedback Loop for Continuous Improvement

Given user interactions with insights reports, when users provide feedback on the relevance of the insights, then the system should incorporate this feedback into future detection algorithms to enhance accuracy.

Alerts for Significant Engagement Trends

Given ongoing user engagement monitoring, when a significant trend is detected (e.g., a sudden spike in engagement), then the system should send an alert to the user within 10 minutes of the detection.

Customizable Insights Summary

User Story: As a data analyst, I want to customize the insights summary I receive so that I can focus on metrics that are most relevant to my reporting needs.
Description: This requirement involves enabling users to customize the types of insights they receive in the Automated Insights Generator. Users will have the ability to select specific metrics, trends, and data points they wish to focus on for their tailored reports. This feature enhances the user experience by allowing marketers and analysts to prioritize information that is most relevant to their needs, thereby streamlining their decision-making process. It also promotes greater user satisfaction and retention by offering a personalized interaction with the software.
Acceptance Criteria: User selects specific metrics and trends for their insights report in the Automated Insights Generator feature.

Given that the user is logged into SentiScan, when they navigate to the Automated Insights Generator, then they should be able to select from a list of available metrics and trends to customize their insights summary.

User generates a customizable insights summary based on selected metrics and trends.

Given that the user has selected their preferred metrics and trends, when they click on the 'Generate Report' button, then a tailored insights summary should be generated that reflects only the selected data points.

User views and analyzes the generated insights summary to ensure relevant data is included.

Given that the insights summary has been generated, when the user views the report, then they should see only the metrics and trends they selected, displayed in a clear and understandable format.

User modifies their selection of metrics and trends post-report generation.

Given that the user has an existing insights summary open, when they choose to modify their metric selections, then the report should be updated accordingly to reflect the new selections.

User saves their customized insights summary for future reference.

Given that the user has generated a tailored insights summary, when they select the option to save the report, then the summary should be saved successfully in their account for future access.

User receives notifications regarding changes in selected metrics and trends over time.

Given that the user has saved preferences for metrics and trends, when there are significant changes in those metrics, then the user should receive an automatic alert or notification within the platform.

Real-time Alert System for Insights

User Story: As a marketer, I want to receive real-time alerts for significant sentiment shifts so that I can respond quickly to changes in consumer attitudes and adjust my strategies accordingly.
Description: This requirement focuses on creating a real-time alert system that notifies users of significant changes or trends in the data that warrant immediate attention. By implementing this feature, users will be able to react swiftly to shifts in consumer sentiment, ensuring they are always informed about emerging trends. The alert system will be integrated with the dashboard, providing notifications directly to users without disrupting their workflow. This capability is vital for maintaining agility and responsiveness in a fast-paced market environment.
Acceptance Criteria: User receives an alert when there is a significant shift in sentiment based on real-time consumer sentiment analysis.

Given a user is logged into their SentiScan dashboard, when a significant sentiment shift occurs in the monitored data, then the user receives a real-time alert notification on their dashboard within 1 minute of the data change.

The alert system allows users to customize the types of trends they want to be notified about.

Given a user accesses their notification settings, when they select specific sentiment trends and save their preferences, then the real-time alert system only notifies them about the selected trends based on the defined thresholds.

Users can view and manage past alerts to track sentiment changes over time.

Given a user views their alert history, when they access the past alerts section, then the system displays a chronological list of all past alerts with timestamps and sentiment details, allowing users to review and analyze trends.

The alert system integrates seamlessly with other dashboard functionalities without causing interruptions.

Given a user is interacting with the dashboard features, when a real-time alert is triggered, then the alert appears as a non-intrusive notification that can be reviewed or dismissed without interrupting the user’s workflow.

Users are able to receive alerts via multiple channels (e.g., email, mobile app notifications).

Given a user sets their alert preferences, when a significant sentiment shift occurs, then the user receives alerts through all selected channels (dashboard, email, mobile) within 1 minute of the event.

The alert system provides users with actionable insights alongside the notification.

Given a user receives a real-time alert, when they click on the alert, then the system presents detailed insights related to the sentiment shift, including possible reasons and recommended actions.

AI-Driven Recommendations Engine

User Story: As a marketing strategist, I want AI-driven recommendations based on my insights so that I can implement effective strategies quickly and efficiently.
Description: This requirement covers the development of an AI-driven recommendations engine that suggests actions or strategies based on the insights generated by the Automated Insights Generator. The engine will analyze the insights along with market data and user preferences to provide actionable recommendations. This feature will enable users to not only receive insights but also understand the potential next steps they can take, driving more effective decision-making. Implementing this capability will add significant value to the user experience, fostering deeper engagement with the software.
Acceptance Criteria: User receives a tailored insights report generated by the Automated Insights Generator after interacting with SentiScan.

Given a user has engaged with SentiScan and the Automated Insights Generator has processed their data, When the user accesses the report, Then the report should present personalized summaries of insights based on their interaction patterns.

The AI-Driven Recommendations Engine provides actionable strategies based on the latest insights report.

Given a user has viewed their tailored insights report, When the user requests recommendations, Then the system should analyze the report and generate at least three actionable strategies for user engagement.

The user reviews recommendations from the AI-Driven Recommendations Engine and provides feedback on their relevance and usefulness.

Given the user has received recommendations from the AI-Driven Recommendations Engine, When the user rates the recommendations, Then the system should record the feedback and update the recommendation algorithm accordingly.

The recommendations engine successfully aligns its suggestions with real-time market data and trends.

Given the recommendations engine is operational, When new market data is available, Then the recommendations should reflect the latest trends and data insights.

The user can easily access the AI-Driven Recommendations Engine from the dashboard without complications.

Given the user is logged into SentiScan, When they navigate to the dashboard, Then they should see a clearly labeled link to access the AI-Driven Recommendations Engine.

Users can customize the types of recommendations they want to receive based on their specific needs

Given a user is in the settings menu of the SentiScan application, When they select preferences for recommendations, Then they should be able to choose from multiple categories (e.g., Marketing, Content Strategy, Audience Engagement) to tailor the engine's output.

The system logs all decision data made based on the recommendations for future analysis and improvement.

Given a user implements a strategy suggested by the AI-Driven Recommendations Engine, When the strategy is executed, Then the system should log the action taken and the relevant context for future reference and analysis.

Integration with Third-party Platforms

User Story: As a product manager, I want to integrate SentiScan with my existing tools so that I can consolidate my data and gain more comprehensive insights from various platforms.
Description: This requirement involves enabling integration with popular third-party platforms (such as CRM systems, social media management tools, and analytics software) to enhance the functionality of the Automated Insights Generator. Users will benefit from streamlined access to data and insights from multiple sources, allowing for a more comprehensive analysis of consumer sentiment and engagement trends. This feature is essential for maximizing the software's usability and ensuring that users can leverage a holistic view of their market intelligence efforts.
Acceptance Criteria: User integrates the Automated Insights Generator with a popular CRM system to analyze customer engagement data.

Given the user has valid API credentials for the CRM system, when they initiate the integration process, then the Automated Insights Generator should successfully connect and pull in customer engagement data without errors.

User utilizes the insights generated by the Automated Insights Generator after integrating with a social media management tool.

Given that the integration with the social media management tool is active, when the user requests a report, then the report should include insights derived from the latest social media engagement data.

User examines the performance of insights generated from multiple third-party platforms.

Given the user has integrated at least three third-party platforms, when they generate a comprehensive insights report, then the report should present a comparative analysis of data from all integrated sources, ensuring data accuracy and consistency.

User sets up alerts for sentiment shifts after integrating the Automated Insights Generator with analytics software.

Given the user has configured sentiment shift parameters in the settings, when the sentiment shifts occur based on data from the analytics software, then the user should receive real-time alerts via their preferred notification method.

User evaluates the seamlessness of data transfer between the Automated Insights Generator and third-party platforms.

Given the user has initiated data sync from any integrated third-party platform, when they check the data status in the Automated Insights Generator, then the latest data should be reflected accurately within 5 minutes of the sync initiation.

User reviews the documentation provided for third-party integrations with the Automated Insights Generator.

Given the documentation is available, when the user accesses the documentation, then they should find clear, step-by-step instructions for integrating each supported third-party platform.

User Preference Learning

User Preference Learning continuously adapts to individual user interactions and feedback, refining the personalization process over time. By understanding user choices and behaviors, this feature ensures that the insights and notifications delivered remain relevant and aligned with each user's evolving interests, thereby fostering a more meaningful and engaging experience.

Requirements

Dynamic User Feedback Integration

User Story: As a SentiScan user, I want the system to learn from my interactions so that it can provide me with more relevant insights and notifications over time, enhancing my engagement with the tool.
Description: The Dynamic User Feedback Integration requirement facilitates the continuous gathering and analysis of user interactions and feedback within the SentiScan platform. This integration will enable the system to adjust and refine the learning algorithms based on real-time user preferences, thereby improving the accuracy of sentiment analysis and the relevance of insights delivered. Users will gain a more tailored experience, as their individualized preferences shape the information and alerts they receive, fostering enhanced user engagement and satisfaction with the software. The seamless integration of user feedback into the algorithm will also promote ongoing improvements in personalization, ensuring that users can stay ahead of market trends based on their interests and needs.
Acceptance Criteria: User Interaction Adjusts Personalized Insights in Real-Time

Given a user interacts with SentiScan by providing feedback on their preferences, when the feedback is processed by the learning algorithm, then the personalized insights and notifications should reflect the updated preferences within one minute of the interaction.

Feedback Mechanism for Reporting User Experience Quality

Given a user reports their satisfaction level with the suggestions provided by SentiScan, when the report is submitted, then the feedback should influence future insight deliveries to better align with user expectations, with observable changes within three user sessions.

Algorithm Adjustments Based on User Sentiment Feedback

Given a user provides sentiment feedback on the insights received, when this feedback is incorporated into the algorithms, then the accuracy of the sentiment analysis results for that user should improve by at least 20% as measured by user satisfaction ratings.

Onboarding Process with Adaptive Learning Integration

Given a new user completes the onboarding process, when they select their interests and preferences, then the system should demonstrate an ability to suggest relevant insights on their first dashboard visit, achieving a relevance score of at least 80% based on user feedback.

Historical Data Analysis for User Preferences

Given a user interacts with SentiScan over time, when their historical interaction data is analyzed, then the system should identify at least three distinct evolving preferences that can guide future content delivery, with a success rate of 90% in correctly anticipating user interests.

Real-Time Sentiment Alerts Based on User Changes

Given a user has previously defined alert criteria for sentiment changes, when a relevant change is detected in real time, then the system should notify the user immediately via their preferred communication channel without delay and ensure the user can provide feedback on the alert within the same session.

Personalized Insights Dashboard

User Story: As a market analyst, I want my dashboard to show personalized insights based on my past interactions so that I can make quicker and more informed decisions that reflect my interests.
Description: The Personalized Insights Dashboard requirement calls for the development of a user-centric dashboard that dynamically adjusts to display insights based on individual user preferences and historical interactions. This dashboard will allow users to visualize data in a way that is most meaningful to them, with customizable widgets and filters to tailor the information displayed. By effectively showcasing the most relevant sentiment analysis results, trends, and alerts, this dashboard will enhance decision-making capabilities, ensuring that users can quickly access the data they need to make informed marketing choices. The user will have greater control over their experience, and insights will be more aligned with their specific needs, ultimately driving user engagement and productivity within SentiScan.
Acceptance Criteria: The user navigates to the Personalized Insights Dashboard where they have previously set up their preferred data filters and metrics. They expect the dashboard to load with their personalized settings every time they access it.

Given a registered user with saved preferences, when the user accesses the dashboard, then the dashboard should automatically display the insights according to the user’s saved filters and metrics.

A user wants to customize the widget layout on their Personalized Insights Dashboard. They will drag and drop widgets to rearrange the layout according to their preferences.

Given the user is on the dashboard page, when the user drags and drops widgets to rearrange them, then the dashboard should save this new arrangement and reflect it the next time the user logs in.

Upon receiving notifications about significant sentiment shifts for brands they follow, the user needs to adjust which notifications are shown on their dashboard to ensure relevance.

Given a user has access to notifications settings, when the user updates their notification preferences, then the dashboard should reflect the changes in real-time during the user session.

A user analyzes the sentiment trends for the past month using the Personalized Insights Dashboard to make a marketing strategy decision.

Given a user selects a one-month time frame from the dashboard filters, when the user applies the changes, then the system should show relevant sentiment analysis results for that time period with graphical representation.

A returning user expects the dashboard to reflect the latest data update. They want to see if any new trends have emerged since their last login.

Given the dashboard is loaded, when the user accesses the platform, then the dashboard should show the most recent sentiment data and updates without delays.

The user accesses the dashboard for the first time and is taken through a guided setup to establish their preferences for insights they would like to see.

Given the user is logging into the dashboard for the first time, when the guided setup is completed, then the dashboard should display insights tailored to the preferences inputted by the user during the setup process.

Adaptive Notification System

User Story: As a user, I want to receive notifications that are tailored to my interests so that I can stay informed about the most relevant sentiment changes without feeling overwhelmed.
Description: The Adaptive Notification System requirement involves creating a robust system for delivering alerts and notifications that adapt based on user behavior, preferences, and feedback. This capability will allow users to receive timely updates on significant changes in sentiment analysis that align with their interests and preferences, minimizing information overload while maximizing the relevance of notifications. By employing smart algorithms capable of analyzing user patterns, this system will enhance user engagement and ensure that critical insights are not missed. The notifications will be customizable, allowing users to select the type and frequency of alerts they wish to receive, which fosters a more tailored user experience within SentiScan.
Acceptance Criteria: User receives a notification for a significant sentiment shift related to their defined interests in the SentiScan dashboard.

Given the user has set preferences for 'brand mentions' and 'product reviews', when there is a 20% increase in negative sentiment towards a product they follow, then the user receives a notification within 5 minutes of the event.

User customizes notification settings for types of alerts they wish to receive.

Given the user is in the notification settings menu, when they select 'daily summary notifications' and save their preferences, then the system must store this choice and send a daily summary the following day at the specified time without errors.

User interacts with a notification alert regarding a positive trend in sentiment.

Given the user receives a notification about a 15% increase in positive sentiment for a brand they follow, when they click on the notification, then they should be redirected to the analytics dashboard displaying insights relevant to that trend within 2 seconds.

The system adapts notification frequency based on user engagement with previous notifications.

Given the user has ignored the last three notifications, when the system assesses user interaction, then the notification frequency should automatically decrease by 50% until the user engages with notifications again.

User receives a notification regarding sentiment changes beyond a threshold set in their preferences.

Given the user has set a threshold of 30% for any sentiment changes, when a sentiment shift occurs that exceeds this threshold, then the system must trigger a notification immediately reflecting the nature of the change.

User provides feedback on the relevancy of incoming notifications.

Given the user receives a notification and marks it as irrelevant, when the system processes this feedback, then the user should receive a prompt asking for reasons for the feedback and the system should adjust future notifications accordingly.

User accesses a history of their received notifications.

Given the user navigates to the notifications history section, when they access this section, then they should see a list of all past notifications organized by date, including summaries and engagement metrics (opened, ignored).

Contextual Learning Enhancement

User Story: As a business strategist, I want the system to understand the context of my market so that I can access insights that are relevant to my specific industry and location.
Description: The Contextual Learning Enhancement requirement seeks to deepen the AI's understanding of user context through the investigation of factors such as industry trends, geographical influences, and user-specific parameters. By integrating contextual data into the learning algorithms, this enhancement will improve the personalization process, allowing the system to deliver insights that are not only based on user interactions but also relevant to the broader market context. This capability will provide users with richer, more comprehensive sentiment analysis, enabling them to make better-informed decisions. In turn, users can leverage this advanced contextual understanding to respond proactively to market dynamics, ultimately leading to improved strategic outcomes with SentiScan.
Acceptance Criteria: User leverages contextual learning to receive tailored insights regarding emerging market trends in their industry based on recent interactions.

Given a user with past interaction data, When the system integrates industry trends and geographical factors, Then the user should receive personalized insights that reflect the most relevant market changes.

User receives notifications of significant sentiment shifts that affect their industry in real-time.

Given that the user has set up alerts for sentiment shifts, When a shift occurs in the relevant geographical area or market context, Then the user should receive an immediate notification about the significant change.

User tests the feature by analyzing different user parameters and preferences to see if the recommendations evolve accordingly.

Given a user with specific parameters set, When the user interacts with the platform over time, Then the system should adapt the recommendations based on the collected data and feedback for ongoing personalization.

User evaluates the impact of contextual insights on their decision-making process for marketing strategies.

Given a user who has access to contextual insights, When the user implements changes based on the insights provided, Then the user should be able to track improvements in engagement metrics post-implementation.

User inputs preferences that will shape the contextual data analysis they receive from the software.

Given a user profile with defined preferences, When the user updates their preferences, Then the system should immediately incorporate those changes into its contextual analysis and insight generation.

User interacts with the dashboard to visualize sentiment analysis data overlaid with contextual insights.

Given a user using the dashboard, When the user selects the contextual learning feature, Then the dashboard should display insights that clearly integrate contextual parameters with sentiment data.

The system analyzes user feedback to enhance the contextual learning models effectively.

Given ongoing user interactions with the features, When the platform collects feedback from users, Then the system should update its contextual analysis algorithm based on the aggregated feedback to improve relevance and accuracy.

Ad Hoc Insight Queries

Ad Hoc Insight Queries allow users to create customizable queries to retrieve specific data points or insights on demand. This feature enhances the flexibility of data exploration, enabling users to ask directed questions and receive tailored responses that reflect their immediate needs, thus improving the overall analysis experience.

Requirements

Dynamic Query Builder

User Story: As a market analyst, I want to create and save custom queries so that I can quickly retrieve tailored insights whenever I need them for my reports and presentations.
Description: The Dynamic Query Builder allows users to create, modify, and save custom queries easily. By utilizing a user-friendly interface, users can select various parameters, filters, and insights relevant to their specific questions. This feature integrates seamlessly with the existing SentiScan data architecture, providing instant feedback on data retrieval and ensuring users can effectively extract tailored insights on demand. The ability to adjust queries in real-time fosters a more exploratory analysis process, significantly enhancing the decision-making speed and accuracy. Furthermore, saved queries can serve as templates for future usage, promoting efficiency for recurrent analysis tasks.
Acceptance Criteria: User creates a custom query to analyze sentiment trends for a specific product over the last six months.

Given the user has access to the Dynamic Query Builder, when they select parameters for product name and date range, then the system should display the sentiment trends accurately for the specified period.

User modifies an existing saved query to include new filters for demographic data.

Given the user has a saved query, when they add demographic filters and save the changes, then the modified query should retain the new filters and show updated results based on the new parameters.

User attempts to save a query without any selected parameters or filters.

Given the user tries to save a query with no parameters selected, when they click the save button, then an error message should be displayed indicating that at least one parameter must be selected before saving.

User retrieves insights using a saved query to analyze competitor sentiment.

Given the user selects a saved query for competitor sentiment analysis, when they execute the query, then the results should reflect the latest sentiment data for the specified competitor.

User uses the Dynamic Query Builder to generate a report and wants to export the results.

Given the user has run a custom query in the Dynamic Query Builder, when they select the export option, then the system should generate a downloadable report in CSV format containing the query results.

User accesses the Dynamic Query Builder to explore data in real-time for immediate decision-making.

Given the user is in the Dynamic Query Builder interface, when they adjust any parameter and apply changes, then the system should showcase real-time updates to the insights displayed without lag.

Real-time Data Updates

User Story: As a marketing strategist, I want real-time updates on sentiment analysis so that I can make informed, timely decisions and adapt my strategies based on the latest consumer perceptions.
Description: Real-time Data Updates ensure that users receive the latest insights without delay. This requirement encompasses the automatic refresh of sentiment data at specified intervals, allowing analysts to access the most current information on consumer attitudes and market trends. By integrating real-time data updates, SentiScan empowers users to respond swiftly to changes in public sentiment, thereby enhancing their strategic decision-making processes. This feature ultimately leads to more proactive marketing and competitive strategies, enabling marketers to stay ahead in the dynamic market landscape.
Acceptance Criteria: Retrieve real-time sentiment data for a specific product during a product launch event.

Given a product launch event is occurring, when the user accesses the Ad Hoc Insight Queries tool and submits a sentiment analysis query, then the system should display the latest sentiment data within 5 seconds.

Analyze sentiment shifts following a major social media campaign launch.

Given a major social media campaign is live, when the user checks the sentiment data via the dashboard, then the data should reflect real-time changes with no delay and show the updated sentiment analysis every minute.

Receive notifications for significant sentiment changes in consumer attitudes toward a brand.

Given the sentiment threshold is set by the user, when a significant shift in sentiment occurs, then the user should receive an automated alert within 2 minutes of the data refresh.

Generate a report outlining the sentiment trends over the last week.

Given the user selects the option to generate a report, when the report is generated, then it should include data collected in real-time, covering the previous 7 days, and display sentiment trends accurately.

Validate user access to real-time data during peak usage hours.

Given the system is experiencing high traffic, when a user attempts to retrieve sentiment data, then the system should still provide insights within 10 seconds without performance degradation.

Test the integration of real-time data updates with third-party analytics tools.

Given a successful integration setup, when real-time sentiment data is updated, then the third-party tool should reflect these updates within 3 seconds.

Collect user feedback on the usefulness of real-time data updates.

Given a user survey is implemented, when users are prompted for feedback, then the responses should indicate at least 80% satisfaction with the real-time data update feature.

Sentiment Trend Visualization

User Story: As a product manager, I want to visualize sentiment trends over time so that I can identify changes in consumer attitudes and make data-driven decisions for future product development.
Description: The Sentiment Trend Visualization feature provides graphical representations of sentiment data over time, allowing users to identify patterns, spikes, and shifts in consumer feelings towards brands or products. This requirement involves integrating advanced charting capabilities within SentiScan’s dashboards, enabling users to visualize complex data easily. By making sense of large datasets, this feature enhances analytical capabilities, supports more effective presentations, and facilitates strategic discussions based on visual insights. Clear visualizations will assist users in recognizing trends that may require swift action or deeper analysis.
Acceptance Criteria: Sentiment Trend Visualization displays real-time sentiment data for a specific product during a daily marketing meeting, allowing marketers to make quick decisions based on the latest trends.

Given the user accesses the Sentiment Trend Visualization, when they select a specific product and time frame, then the visualization displays accurate and updated sentiment data over that period.

A user wants to compare sentiment trends across multiple brands over the past month to identify competitors' strengths and weaknesses.

Given the user selects multiple brands, when they visualize the sentiment trend for the last month, then the dashboard shows a clear comparison of sentiment scores between brands with distinguishable charts.

During a quarterly analysis meeting, analysts need to present visual insights on sentiment shifts regarding a major marketing campaign with clear graphical representations.

Given the user generates a sentiment trend visualization for a specific marketing campaign, when they present it during the analysis meeting, then the visualization must effectively highlight key spikes, dips, and overall trends that align with campaign timelines.

A marketer receives an alert about a sudden positive sentiment spike regarding their brand and wants to visualize this trend over the past week.

Given the alert of a sentiment spike, when the user accesses the Sentiment Trend Visualization for the past week, then the visualization should indicate a clear spike, including percentage changes and timeline details for easy understanding.

Users need to filter sentiment data by geographical location to see if consumer attitudes differ across regions.

Given the user applies a geographical filter on the Sentiment Trend Visualization, when they view the results, then the visualization must accurately reflect sentiment trends specific to the selected regions without data discrepancies.

User Access Control System

User Story: As an administrator, I want to define user access roles so that I can ensure sensitive data is only accessible to authorized personnel and maintain data security within the application.
Description: The User Access Control System strengthens data security by allowing administrators to set permissions based on user roles within the SentiScan application. This requirement entails developing a tiered access framework that restricts data visibility and editing capabilities according to user roles (e.g., analyst, manager, admin). Implementing this feature will ensure that sensitive data remains protected while empowering users to access only the information they need for their respective tasks. This not only promotes data integrity but also aligns with compliance regulations on data privacy.
Acceptance Criteria: User Role-Based Permissions Setup

Given an admin user, when they access the User Access Control System, then they should be able to create, modify, and delete user roles and permissions with immediate effect on access levels.

Data Visibility Restrictions by Role

Given a user assigned the 'analyst' role, when they log into SentiScan, then they should only be able to view data that is relevant to their role, while data restricted to 'manager' and 'admin' roles should not be visible.

Edit Permissions Based on User Role

Given a user assigned the 'manager' role, when they attempt to edit a data insight, then they should be able to do so only if the data is within their permission scope, and denied access to edit sensitive data reserved for 'admin' role.

Audit Log of User Access Changes

Given an admin user modifies a user role or permission, when they complete the modification, then a detailed entry should be created in the audit log capturing the changes made, including timestamps and user details.

Immediate Effect of Permission Changes

Given an admin has changed the permission of a user, when the user next logs in, then they should only have access to the functionalities corresponding to their updated role without requiring a system restart or additional authentication.

Compliance with Data Privacy Regulations

Given the User Access Control System has been configured, when a compliance officer audits the system, then they should confirm that user roles and access permissions meet established data privacy regulations and best practices.

Automated Reporting Schedules

User Story: As a busy analyst, I want to automate my reporting schedules so that I receive timely updates on key metrics without having to manually generate reports every time.
Description: The Automated Reporting Schedules feature allows users to set up and automate routine reports based on specific criteria, which can then be delivered via email or dashboard notifications. This requirement aims to enhance user efficiency by minimizing the manual effort needed to generate insights regularly. Users can customize the frequency and content of reports according to their needs, ensuring they remain informed without needing to log in frequently. The automatic delivery of pertinent information fosters a proactive analysis culture, enabling teams to act swiftly on insights.
Acceptance Criteria: User sets up a daily report to receive insights on sentiment trends in social media towards their brand.

Given a user has access to the reporting feature, when they configure a daily report with specific criteria, then they should receive the report via email at the designated time each day containing the relevant insights.

User customizes the content of the automated report to include specific metrics such as engagement rate and sentiment score.

Given a user selects the metrics they want to include in the report, when they save the report configuration, then the report should reflect these selected metrics when generated and sent out.

User modifies the frequency of the automated report from weekly to bi-weekly.

Given a user has an existing automated report, when they change the frequency setting to bi-weekly and save the changes, then the report should automatically adjust its delivery schedule accordingly.

User receives a notification when a generated report is ready for review.

Given a user has set up an automated report, when the report is generated, then the user should receive a dashboard notification indicating that the report is ready for viewing.

User tests the automated reporting feature by creating a report and reviewing its contents for accuracy.

Given a user has set up an automated report, when they request to view the report, then the report displayed should contain accurate information as per the defined criteria set by the user.

User deletes an existing automated report that is no longer needed.

Given a user has an automated report set up, when they select the delete option, then the report should be removed from their dashboard and no further reports should be sent.

User sets up an automated report with multiple recipients.

Given a user is configuring an automated report, when they add multiple email addresses for report delivery, then the report should successfully send to all specified recipients at the scheduled time.

Insight Sharing Platform

The Insight Sharing Platform facilitates seamless sharing of personalized insights with team members or stakeholders. Users can share selected reports or dashboards directly within the platform, fostering collaboration and ensuring that everyone involved has access to the most relevant information for decision-making.

Requirements

Personalized Insight Sharing

User Story: As a marketing analyst, I want to share specific insights from reports with my team members directly in SentiScan so that we can collaboratively discuss our findings and make informed decisions based on the most recent data.
Description: The Personalized Insight Sharing requirement allows users to select specific reports or dashboards to share with team members or stakeholders directly within SentiScan. This feature enhances collaboration by ensuring all involved parties have real-time access to relevant insights, aiding in collective decision-making. The ability to share tailored insights not only streamlines communication but also boosts efficiency by reducing the need for external tools or processes to disseminate findings, making it easier for users to stay aligned with organizational goals and strategies.
Acceptance Criteria: User successfully shares a selected dashboard with a team member via the Insight Sharing Platform.

Given a user is logged into SentiScan and has selected a dashboard, when the user clicks the 'Share' button and enters the email of the team member, then the dashboard should be sent to the specified email with a unique link for access.

User receives a notification upon successful sharing of a dashboard or report.

Given a user has shared a dashboard or report, when the sharing action is completed, then the user should receive a confirmation notification on the platform confirming that the share was successful.

User can select multiple reports for sharing at once via the Insight Sharing Platform.

Given a user is logged into SentiScan and has selected multiple reports, when the user clicks the 'Share' button, then all selected reports should be sent to the specified team member(s) in a single action without errors.

User is able to access shared reports immediately after sharing.

Given a user has successfully shared a report with another team member, when the team member clicks the link in the email to access the report, then they should be able to view the report in SentiScan without any additional login required.

Notifications are displayed correctly on the Insight Sharing Platform after sharing.

Given a user shares a dashboard, when the dashboard is successfully shared, then a notification should appear on the user's dashboard indicating the successful sharing of the dashboard, including the recipient's name.

User can edit or revoke access to shared reports or dashboards.

Given a user has shared a report, when the user chooses to revoke access, then the team member should receive a notification stating that their access has been revoked, and the report should no longer be accessible to them.

User can see a history of shared reports and dashboards within the Insight Sharing Platform.

Given a user is logged into SentiScan, when they navigate to the 'Shared Insights' section, then they should see a list of all reports and dashboards they have shared along with the dates and recipients.

Dashboard Access Permissions

User Story: As a project manager, I want to set permissions for dashboard access within SentiScan so that only team members with appropriate roles can view or edit sensitive information, enhancing data security and compliance.
Description: The Dashboard Access Permissions requirement provides functionality for users to manage who can view or edit specific dashboards within the Insight Sharing Platform. By implementing role-based access controls, this feature ensures sensitive data is shared only with authorized personnel, enhancing data security and governance. Additionally, it facilitates better management of information flow, allowing users to tailor access based on the roles and needs of team members, promoting more effective collaboration while safeguarding confidential insights.
Acceptance Criteria: As a team leader, I want to grant editing access to specific dashboards for my team members based on their roles so that they can contribute to the analysis and updates.

Given the team leader is logged into the Insight Sharing Platform, when they select a dashboard and choose team members to edit, then those members should receive editing permissions immediately after selection.

As a platform administrator, I need to remove access for a former employee from all dashboards to ensure sensitive information is not accessible to unauthorized users.

Given the platform administrator has identified a former employee, when they revoke that employee's access, then they should no longer be able to view or edit any dashboards, and confirmation of removal should be logged.

As a marketing analyst, I want to view specific dashboards shared with me to gain insights for my project.

Given that a dashboard is shared with the marketing analyst, when they log into the Insight Sharing Platform, then they should be able to see the shared dashboard in their dashboard list.

As a project manager, I want to ensure that only senior staff can view sensitive data dashboards to protect company secrets.

Given a dashboard contains sensitive data, when the project manager sets access permissions, then only users with 'senior staff' roles should have viewing rights for that dashboard.

As a team member, I want to request access to a dashboard that I need for my work, ensuring that access requests are documented and reviewed appropriately.

Given a team member lacks access to a required dashboard, when they submit a request for access, then the request should be logged for review by the team leader or administrator.

As a compliance officer, I need to generate a report of all users who have access to sensitive dashboards to review compliance with data security policies.

Given the compliance officer has access to the permission management section, when they request a report of users with access to sensitive dashboards, then a comprehensive report should be generated including user roles and access levels.

Instant Notification for Shared Insights

User Story: As a team member, I want to receive instant notifications when a colleague shares a new dashboard or report with me so that I can access and analyze the insights immediately to contribute effectively to our strategy discussions.
Description: The Instant Notification for Shared Insights requirement enables users to receive real-time alerts when a report or dashboard is shared with them. This feature ensures that stakeholders are promptly informed of new insights, fostering timely discussions and actions based on the shared data. By providing immediate notifications, users can stay updated and engaged, leading to quicker decision-making and more agile responses to market changes or consumer sentiment shifts.
Acceptance Criteria: User receives a notification when a report is shared with them in real-time.

Given that the user is logged into the Insight Sharing Platform, when a report or dashboard is shared with them, then an instant notification should be sent to their designated notification preferences.

User can customize their notification settings for shared insights.

Given that the user accesses their settings, when they choose their notification preferences for sharing, then their selections should be saved and respected for future shared insights.

User receives notifications for both reports and dashboards shared with them.

Given that the user is part of a team collaboration, when either a report or dashboard is shared, then they should receive distinct notifications indicating the type of content shared.

User receives notifications even if they are not currently logged into the platform.

Given that the user has enabled notifications, when a report is shared while they are logged out, then a notification should be sent to their registered email or mobile device for later reference.

User can access a history log of notifications related to shared insights.

Given that the user navigates to the notifications tab, when they check their history, then they should see a chronological list of all notifications regarding shared insights, including timestamps and type of content.

User is able to mark notifications as read or unread for better management.

Given that the user views their notification list, when they select a notification, then they should have the option to mark it as read or unread, updating its status accordingly.

Collaborative Annotation Tools

User Story: As a data analyst, I want to annotate shared dashboards with my observations and thoughts so that I can easily share insights and collaborate with my teammates on the interpretation of the data.
Description: The Collaborative Annotation Tools requirement introduces features allowing users to add comments, tags, or highlights on shared reports and dashboards. This functionality enhances collaborative efforts by enabling team members to communicate directly on specific insights, facilitating better discussions and clarifying thought processes. By allowing annotations, users can ensure that all points of view are captured and considered during decision-making processes, leading to a more comprehensive understanding of the data being analyzed.
Acceptance Criteria: User A wants to collaborate with User B on a sentiment analysis report by adding annotations that highlight key data points and provide additional context.

Given User A has opened a shared report, when they add a comment on a specific data point, then User B should receive a notification of the new annotation.

User C is reviewing a shared dashboard and wants to tag specific insights for their team members to focus on during an upcoming meeting.

Given User C is on a shared dashboard, when they tag an insight with '@UserD', then User D should be able to see the tagged insight in their notifications and directly access it.

User E is finalizing a report that includes multiple annotations by different team members and needs to ensure all comments are visible and accessible for decision-making.

Given the report contains multiple annotations, when User E views the report, then all comments and highlights should be displayed clearly alongside the corresponding data points.

User F wants to edit an annotation they previously made on a shared dashboard to update their feedback based on new data.

Given User F has previously made an annotation, when they edit that annotation, then the updated comment should be reflected in real-time for all other users viewing the dashboard.

Users G and H are working on a report and want to resolve a disagreement on a specific insight through commenting on the relevant annotation.

Given the annotation has comments from both User G and User H, when User G replies to User H’s comment, then the conversation thread should be updated with their response and maintain its visibility.

User I wants to disable the annotation feature temporarily while they prepare a presentation using the shared dashboard.

Given that User I is the owner of the dashboard, when they disable annotations, then all other users should be prevented from adding new comments or tags until the feature is re-enabled.

User J wants to review all annotations made on a report to ensure that all comments are relevant and constructive for the upcoming strategy session.

Given User J is in the shared report, when they click on the 'View All Annotations' option, then a modal should display a comprehensive list of all annotations made along with the corresponding user names and timestamps.

Optimal Timing Advisor

Optimal Timing Advisor analyzes historical engagement patterns to suggest the best times for posting content. By leveraging data on when audience interactions peak, this feature allows marketers to schedule their posts with precision. This ensures that content reaches audiences at times when they are most active, maximizing visibility and engagement.

Requirements

Peak Engagement Analytics

User Story: As a social media manager, I want to understand the best times to post content based on past engagement patterns, so that I can maximize visibility and interaction with my audience.
Description: The Peak Engagement Analytics requirement focuses on analyzing historical user engagement data to identify specific times when audience interactions are at their highest. This feature will utilize AI algorithms to process data across various platforms, providing insights on optimal posting times based on user activity. By implementing this requirement, SentiScan will enhance its Optimal Timing Advisor by enabling marketers to make data-driven decisions on when to post their content, ensuring maximum visibility and engagement. This capability is vital for improving audience reach and fostering better user interactions, ultimately driving higher engagement rates and increasing the effectiveness of marketing campaigns.
Acceptance Criteria: As a marketer, I want to access Peak Engagement Analytics to determine the optimal times to post content, based on historical engagement data, so that I can improve the reach of my marketing campaigns.

Given the Peak Engagement Analytics feature is implemented, when I input specific content types and target demographics, then I should receive a list of optimal posting times with corresponding engagement metrics.

As a user of the SentiScan platform, I need the Peak Engagement Analytics to be integrated seamlessly with the Optimal Timing Advisor feature, ensuring a smooth user experience as I shift from one feature to the other.

Given that I am using the Optimal Timing Advisor, when I access Peak Engagement Analytics, then the interface should allow me to toggle between both features without any disruptions or delays.

As a data analyst, I need to verify that the AI algorithms used for Peak Engagement Analytics accurately process historical engagement data to deliver reliable results that I can trust for decision-making.

Given the AI algorithms for Peak Engagement Analytics are running, when I compare the engagement predictions made by the system with actual historical data, then the predictions should have at least an 80% accuracy rate.

As a marketer, I want to receive alerts for significant shifts in engagement patterns so that I can quickly adjust my posting strategy according to real-time insights.

Given the alert system for sentiment shifts is in place, when there is a notable change in user engagement metrics, then I should receive an instant notification via email and SMS to inform me of the required action.

As a product manager, I want to see a comprehensive report generated from Peak Engagement Analytics that summarizes the engagement insights over the past month, which I can share with stakeholders.

Given that the Peak Engagement Analytics feature has been used for one month, when I request a performance report, then I should receive a downloadable document that includes key metrics such as peak engagement times, audience demographics, and interaction types.

As a social media manager, I want to ensure that the suggested optimal posting times consider various time zones relevant to my target audience to ensure maximum reach and engagement worldwide.

Given I input target audience locations, when the Peak Engagement Analytics generates optimal posting times, then the suggested times should be adjusted according to the respective time zones of the audience demographics.

Customizable Notification Alerts

User Story: As a marketer, I want to set up custom alerts for changes in sentiment and engagement metrics, so that I can react quickly to trends that affect my marketing strategies.
Description: The Customizable Notification Alerts requirement allows users to set personalized alerts for significant changes in sentiment analysis data or engagement metrics. Users will be able to define the parameters for these alerts based on their specific needs, such as thresholds for engagement rates or sentiment score changes. This feature will enhance user experience by providing timely notifications that enable marketers to respond proactively to shifts in consumer sentiment or engagement trends, thereby improving decision-making and strategy adjustment processes.
Acceptance Criteria: Setting up personalized notification alerts for sentiment analysis changes.

Given a user is on the Customizable Notification Alerts setup page, when they define thresholds for engagement rates and sentiment score changes, then the alerts should be saved successfully and reflect the specified parameters in the user's notification settings.

Receiving alerts when engagement rates fall below the specified threshold.

Given a user has set an engagement rate threshold for notifications, when the system detects that the engagement rate falls below this threshold, then the user should receive a real-time alert via the chosen notification method (email, SMS, in-app notification).

Updating existing notification settings to adjust sentiment score thresholds.

Given a user navigates to the Notification Settings page, when they modify the sentiment score threshold and save changes, then the updated threshold should be accurately reflected in the settings and functional in triggering alerts.

Testing the notification system for reliable alert delivery.

Given a user has set various alerts for both engagement and sentiment changes, when significant changes occur in the metrics, then the user should receive all relevant alerts within 5 minutes of the change, with no delays or missed notifications.

Viewing the history of notification alerts sent to the user.

Given a user accesses the Notification History page, when they view the alerts received in the past month, then the history should display accurate timestamps, alert types, and content of the alerts sent.

Customizing the notification delivery method for alerts.

Given a user is on the Notification Settings page, when they select their preferred method of delivery for alerts (e.g., email, SMS, in-app), then the system should save this preference and deliver all future alerts according to the chosen method.

Enabling and disabling specific notifications based on user needs.

Given a user is on the Customizable Notification Alerts page, when they choose to enable or disable certain notifications, then the changes should be processed immediately, and the user should see the updated status of these notifications in their settings.

User-Friendly Dashboard

User Story: As a user, I want an intuitive dashboard that displays my analytics clearly, so that I can quickly understand and analyze engagement data without confusion.
Description: The User-Friendly Dashboard requirement aims to create a dynamic and intuitive interface for users to visualize their engagement analytics and insights generated by the Optimal Timing Advisor. This dashboard will provide customizable widgets that allow users to choose the metrics most relevant to their strategies, such as engagement rates, post timings, and sentiment trends. By implementing this feature, SentiScan will enhance its usability, making it easier for marketers and analysts to interpret data at a glance and make informed decisions based on real-time insights.
Acceptance Criteria: User wants to create a personalized dashboard to visualize engagement analytics from the Optimal Timing Advisor, selecting the metrics that matter most to their posting strategy.

Given the user accesses the User-Friendly Dashboard, When the user customizes their dashboard with specific widgets for engagement rates, post timings, and sentiment trends, Then the widgets should display the selected metrics accurately and dynamically update with real-time data.

User interacts with the dashboard to analyze audience engagement trends over different time periods to determine optimal posting times.

Given the user has selected a specific time frame in the User-Friendly Dashboard, When the user views the engagement trends, Then the dashboard should accurately reflect the engagement data for the selected period, highlighting peak interaction times.

User wants to save their customized dashboard settings for future analysis without needing to reconfigure after each login.

Given the user customizes their dashboard, When the user chooses to save their dashboard layout, Then the settings should be saved and automatically loaded the next time the user accesses the dashboard.

User needs to share their customized dashboard analytics with team members for collaborative decision-making.

Given the user has configured their dashboard, When the user selects the share option, Then the dashboard link should be generated and allow access for selected team members without compromising data security.

User encounters an error while trying to retrieve engagement data from the dashboard.

Given the user experiences an error while accessing the dashboard, When the error occurs, Then a user-friendly error message should be displayed providing guidance on how to resolve the issue or contact support.

User wants the ability to reset their dashboard to default settings as needed for a fresh start.

Given the user has made several customizations to their dashboard, When the user selects the reset option, Then all widgets should revert to default settings without retaining previous customizations.

User wishes to receive notifications about significant changes in engagement trends through the dashboard.

Given the user has opted in for notifications, When a significant change in engagement trends is detected, Then the user should receive an alert through the dashboard interface or via email.

Cross-Platform Data Integration

User Story: As a social media strategist, I want to pull engagement data from all my social media platforms into one tool, so that I can analyze audience behavior comprehensively.
Description: The Cross-Platform Data Integration requirement enables the Optimal Timing Advisor to gather and analyze engagement data from various social media platforms, ensuring a comprehensive understanding of audience behavior across channels. This capability is essential for understanding how different platforms influence audience interaction and will allow users to make more informed scheduling decisions. By providing insights from multiple sources, SentiScan will enhance its value proposition, allowing marketers to tailor their content strategies across multiple platforms effectively.
Acceptance Criteria: Integration of Data from Social Media Platforms

Given the user has connected their social media accounts, when the user accesses the Optimal Timing Advisor, then the system displays engagement data from all selected platforms within a single dashboard.

Historical Engagement Pattern Analysis

Given the system has access to the historical engagement data, when the user selects a particular social media platform, then the system analyzes and displays peak engagement times based on the last three months of data.

Real-Time Data Updates

Given that the user is logged into SentiScan, when new engagement data is available from connected social media platforms, then the system updates the Optimal Timing Advisor insights in real-time without requiring a manual refresh.

Visualization of Engagement Patterns

Given that the historical engagement data is accessible, when the user views the Optimal Timing Advisor, then the system presents the data in an intuitive graph format showing peaks and troughs in user engagement over time.

Content Scheduling Recommendations

Given the user has analyzed engagement patterns, when the user requests scheduling recommendations, then the system provides a list of optimal posting times for the next week based on projected engagement.

User Notifications for Insights

Given that significant engagement patterns change, when the system detects a shift, then the user receives a notification alerting them to the new optimal posting times via email and within the platform.

Automated Suggestion Engine

User Story: As a digital marketer, I want automated suggestions for the best posting times, so that I can save time and ensure my content reaches my audience when they are most active.
Description: The Automated Suggestion Engine requirement aims to develop an AI-driven tool that provides users with automated posting time suggestions based on ongoing engagement patterns and historical data analysis. This feature will continuously learn and adapt, providing periodic updates and suggestions that reflect real-time analysis of audience behavior. This innovation will significantly enhance the functionality of the Optimal Timing Advisor, ensuring that marketers are equipped with the most current and relevant insights for optimizing their posting strategies and improving engagement outcomes.
Acceptance Criteria: When a user accesses the Optimal Timing Advisor, they want to receive automated posting time suggestions based on real-time engagement data.

Given the user has logged into SentiScan, When they navigate to the Optimal Timing Advisor, Then the system displays automated posting time suggestions based on the latest engagement patterns.

A marketer needs to understand how the Automated Suggestion Engine adapts to changing audience behavior over time.

Given the Automated Suggestion Engine has been operational for at least one week, When the user requests a new posting time suggestion, Then the system provides suggestions that reflect the most recent engagement data from the past week.

An analyst wants to compare suggested posting times with actual audience engagement metrics to evaluate the accuracy of the suggestions.

Given the user accesses the historical analytics dashboard, When they review engagement metrics from posts scheduled using suggested times, Then the metrics reflect at least a 20% increase in engagement compared to times outside the suggestions.

Users need to receive notifications if the engagement patterns shift significantly, affecting the posting time suggestions.

Given the system monitors engagement patterns continuously, When there is a significant shift in audience interaction times, Then the user receives an alert notifying them of the change in optimal posting times.

A user wants to ensure that the suggestions provided by the Automated Suggestion Engine are based on diverse data sources.

Given the user requests posting time suggestions, When the system generates these suggestions, Then the suggestions incorporate data from at least three different social media platforms and historical engagement analysis.

Marketers require a user-friendly interface for reviewing and adjusting the proposed posting times based on personal strategies.

Given the user reviews the suggested posting times, When they interact with the interface, Then they can easily edit and save their preferred posting times without any technical difficulties.

Content Type Recommender

Content Type Recommender provides tailored suggestions on the types of content (e.g., video, images, polls) that are most likely to resonate with specific audience segments. By analyzing past performance metrics across different formats, this feature empowers marketers to create highly engaging content that aligns with audience preferences, enhancing interaction and driving conversions.

Requirements

Personalized Content Suggestions

User Story: As a marketer, I want personalized content recommendations so that I can create engaging materials that are tailored to my audience’s preferences and drive higher conversion rates.
Description: This requirement entails developing an algorithm that analyzes user behavior and historical content performance to deliver personalized recommendations for content types that will resonate with specific audience segments. The algorithm will leverage machine learning techniques to continuously improve and refine suggestions based on ongoing feedback and engagement metrics. Integration with SentiScan's existing sentiment analysis capabilities allows for real-time adjustments to recommendations, ensuring marketing strategies align with evolving consumer preferences. The expected outcome is an increase in content engagement and conversion rates, providing a significant competitive advantage for users.
Acceptance Criteria: Algorithm Delivers Personalized Recommendations Based on Analyzed User Behavior

Given an audience segment with historical engagement data, when the Content Type Recommender is executed, then it returns at least three personalized content type suggestions that have a higher predicted engagement than the average historical performance.

Real-time Adjustment of Recommendations Based on Sentiment Analysis

Given updated sentiment data from SentiScan, when the Content Type Recommender processes the new information, then it updates at least 50% of previously suggested content types within 24 hours to align with current consumer sentiment.

Improvement in Engagement Metrics Post-Implementation

Given the implementation of personalized content suggestions, when marketers use these recommendations, then there is a measurable increase of at least 15% in content engagement rates as compared to the previous quarter.

User Feedback Loop Integration for Continuous Improvement

Given the feedback collected from users on the content suggestions, when this feedback is analyzed by the algorithm, then the algorithm updates its learning model to improve suggestion accuracy by at least 20% in the next iteration.

Competitive Benchmarking Using Recommended Content Types

Given the competitive analysis metrics, when the Content Type Recommender suggests content types, then the selected types outperform the average industry engagement rate by at least 10% within the same time frame.

User Interface for Content Type Recommender

Given the user interface of SentiScan, when the user accesses the Content Type Recommender, then the interface displays the personalized recommendations clearly with supporting performance metrics for each suggestion, ensuring usability standards are met.

Feedback Collection Mechanism for Suggested Content Types

Given the implementation of the Content Type Recommender, when users interact with the suggested content types, then a feedback collection mechanism is triggered, allowing users to rate the effectiveness of each suggestion on a scale from 1 to 5.

Performance Metrics Dashboard

User Story: As a marketer, I want a performance metrics dashboard so that I can easily assess how different content types are performing and make data-driven decisions for future campaigns.
Description: This requirement involves the creation of a comprehensive dashboard that displays key performance metrics for content engagement across different types (video, images, polls, etc.). The dashboard will pull data from various analytics sources, presenting a visual representation of how each content format performs with different audience segments. Users will have the ability to customize their views and filter data based on timeframes, demographics, and engagement metrics. This centralized data visualization will assist marketers in identifying trends, optimizing content strategy, and assessing the effectiveness of their campaigns over time.
Acceptance Criteria: Performance Metrics Visualization for All Content Types

Given a user is logged into SentiScan, when they access the Performance Metrics Dashboard, then the dashboard displays performance metrics for video, image, and poll content types with accurate engagement data.

Customizable Dashboard Filters

Given a user selects specific timeframes and demographic filters on the dashboard, when they apply these filters, then the dashboard updates to show performance metrics exclusively for the selected criteria.

Real-time Data Updates

Given a user is viewing the dashboard, when new performance metrics are available from the analytics sources, then the dashboard automatically refreshes to display the latest data without manual input.

User Engagement Trends Identification

Given a user reviews the performance metrics, when they analyze the data, then they should clearly identify trends in audience engagement for each content type over selected timeframes.

Exporting Performance Reports

Given a user has accessed the Performance Metrics Dashboard, when they select to export a report, then they receive a downloadable file in their chosen format (PDF, CSV) containing the displayed metrics.

Benchmarking Against Competitors

Given a user accesses the Performance Metrics Dashboard, when they use the benchmarking feature, then they should see how their content performance compares against industry standards and competitors.

Automated Content Type Analysis

User Story: As a content creator, I want an automated content type analysis tool so that I can quickly understand which formats work best for my audience and save time on research.
Description: This requirement is focused on building an automated analysis tool that evaluates the effectiveness of various content types used by marketers. By harnessing natural language processing and machine learning, the tool will survey social media and online platform engagements, providing insights into which content formats lead to the highest levels of audience interaction. This functionality allows marketers to make informed decisions about content strategy, ultimately leading to improved audience engagement and marketing efficiency. The automation aspect will significantly reduce the time marketers spend on manual analysis, freeing them to focus on creative content development.
Acceptance Criteria: Automated Content Type Analysis for Engagement Metrics Reporting

Given a set of historical content engagement data, when the analysis tool is activated, then it should process the data and identify the top three content types that maximized audience interaction, providing a detailed report.

Real-time Recommendations Based on Current Trends

Given real-time social media engagement data, when a marketer queries the system for content type suggestions, then the system should return a list of recommended content types based on the latest engagement trends that resonates with the target audience.

User Interface for Viewing Content Performance Insights

Given that the automated analysis tool has processed the data, when a user accesses the analytics dashboard, then they should see clear visual representations (charts/graphs) of performance metrics for various content types over selected timeframes.

Integration with Social Media Platforms

Given that the marketing team wants to analyze content performance across different platforms, when the analysis tool is integrated with platforms like Facebook and Twitter, then it should successfully fetch engagement metrics without errors from each connected account.

Feedback Mechanism for Content Strategy Adjustments

Given the insights provided by the analysis tool, when a user inputs feedback on new content strategies based on the findings, then the system should store these inputs and suggest additional content types based on user preferences and past performance.

Audience Segmentation Enhancement

User Story: As a marketer, I want enhanced audience segmentation features so that I can create targeted campaigns that speak directly to the unique preferences of different segments.
Description: This requirement focuses on enhancing the current audience segmentation features to allow for deeper insights into consumer behavior and preferences. By incorporating advanced segmentation techniques, marketers will be able to categorize audiences based on more precise indicators, such as sentiment scores, interaction history, and demographic data. This enhancement aims to provide a clearer understanding of diverse audience needs, enabling marketers to tailor their content recommendations more effectively to each segment. Ultimately, this will lead to improved marketing strategies and higher engagement rates for varied audience groups.
Acceptance Criteria: Audience Segmentation by Sentiment Scores

Given a dataset of users with associated sentiment scores, when the marketer applies the enhanced audience segmentation feature, then the system should accurately categorize users into distinct segments based on specified sentiment score ranges, allowing for targeted content recommendations.

Audience Segmentation by Interaction History

Given historical interaction data of users with various content types, when the marketer runs the audience segmentation enhancement tool, then the system should segment users based on their past engagement metrics, such as likes, shares, and comment frequency, ensuring content recommendations reflect their interaction patterns.

Demographic-Based Audience Segmentation

Given the demographic data of users, when the enhanced segmentation feature is utilized, then the system should allow the marketer to filter and segment audiences according to demographic indicators (age, gender, location), providing tailored recommendations that resonate with each demographic group.

Real-time Updates to Audience Segments

Given ongoing user interactions and sentiment changes, when the audience segmentation is applied, then the system should dynamically update audience segments in real-time based on the latest data, ensuring marketers have access to the most relevant segments for content targeting.

Cross-Analysis of Segment Performance

Given multiple audience segments and their corresponding content performance metrics, when the marketer analyzes segment performance, then the system should provide insights that compare engagement rates across segments, informing future content strategy adaptations based on segment-specific trends.

Usability of Segmentation Dashboard

Given a marketer using the segmentation enhancement feature, when they navigate to the audience segmentation dashboard, then the UI should be intuitive, allowing users to easily create, edit, and analyze segments without requiring extensive training.

Integration with Content Type Recommender

Given enhanced audience segments, when the marketer utilizes the Content Type Recommender tool, then the system should incorporate the new audience segments to generate content type suggestions tailored to the preferences of each segment, enhancing overall content strategy effectiveness.

Sentiment-Driven Alerts

User Story: As a marketer, I want sentiment-driven alerts so that I can quickly react to shifts in consumer sentiment and adjust my strategies accordingly.
Description: This requirement involves implementing an alert system that notifies users of significant changes in sentiment related to their specified audience segments or topical interests. By utilizing SentiScan's existing sentiment analysis tools, users can set criteria for receiving alerts when sentiment shifts occur, allowing them to respond proactively to consumer sentiment changes. The alerts will be delivered through various channels (email, SMS, in-app notifications), providing marketers with timely insights to adjust their strategies. This functionality aims to enhance responsiveness and agility in marketing decision-making based on real-time data.
Acceptance Criteria: User is a marketer who wants to monitor sentiment changes for a specific product campaign. They set up criteria to receive alerts related to sentiment shifts in the target audience identified for the campaign.

Given the user sets up a sentiment alert for a specific product campaign, when a significant sentiment shift occurs in the target audience, then the user receives an alert via their chosen channel (email, SMS, in-app notification).

A user is tracking multiple audience segments and wants to ensure they receive timely alerts for each segment. They configure separate settings for each audience segment within the SentiScan platform.

Given the user has configured multiple sentiment alerts for different audience segments, when a significant sentiment shift occurs for any of those segments, then the user receives an individual alert for that specific segment through their selected delivery channel.

The user is interested in the data accuracy of the sentiment-driven alerts. They want assurance that alerts are based on real-time data analysis and are relevant to their defined parameters.

Given that the user has defined specific criteria for sentiment-driven alerts, when an alert is generated, then it must be backed by real-time sentiment analysis data that matches the user’s predefined parameters for accuracy and relevance.

A marketer receives an alert about a significant upward sentiment shift for an audience segment. They want to access detailed insights on why the sentiment has changed to make informed decisions.

Given that a significant sentiment shift alert has been triggered, when the user clicks on the alert notification, then they should be directed to detailed insights that include analysis of the relevant data and sentiment trend information.

The user configures the alert settings to ensure that they do not receive excessive notifications. They need to establish thresholds for when an alert is triggered based on sentiment changes.

Given the user has set thresholds for sentiment changes, when the sentiment shift is below the threshold level, then no alert is generated, ensuring the user receives only meaningful notifications.

A user wants to test the functionality of the alert system before full implementation. They will simulate changes in sentiment to verify the alerts are received as expected.

Given that the user simulates a sentiment shift within the system, when the simulation occurs, then the alert should be generated and delivered through the configured channels in real-time for validation of functionality.

The user is reviewing the alert history to assess the effectiveness of their sentiment-driven alerts over time. They want to understand trends in alerts received.

Given the user accesses the alert history section, when they review the history of received alerts, then they should see a detailed log of alerts that includes timestamps, sentiment changes, and audience segments for analysis.

Engagement Rate Forecasting

Engagement Rate Forecasting leverages advanced AI algorithms to project potential engagement rates for upcoming campaigns based on historical performance data. This feature helps marketers to set realistic expectations and benchmarks for their content, improving strategic planning and resource allocation. By understanding predicted engagement levels, users can refine their campaigns for better outcomes.

Requirements

AI-Powered Data Analysis

User Story: As a market analyst, I want AI algorithms to analyze sentiment data from social media so that I can swiftly identify market trends and consumer attitudes to fine-tune our engagement strategies accordingly.
Description: The AI-Powered Data Analysis requirement is designed to enhance SentiScan's capability to analyze large volumes of unstructured data from various platforms using advanced machine learning algorithms. This feature will automatically categorize sentiments, trends, and consumer patterns in real-time, providing users with immediate insights into market sentiment. The functionality of this requirement will significantly improve the accuracy of sentiment analysis, allowing businesses to adapt their strategies swiftly. Integrating seamlessly with SentiScan’s dashboard, it will provide visual representations of the analyzed data, enabling marketers to make data-driven decisions with enhanced confidence. The expected outcome is a more informed understanding of consumer attitudes that will enhance engagement strategies and improve campaign effectiveness.
Acceptance Criteria: Real-time sentiment analysis during a marketing campaign.

Given a live marketing campaign, when the AI analyzes social media mentions, then it should categorize at least 95% of sentiments correctly within 30 seconds.

Displaying visual representations of analyzed data on the SentiScan dashboard.

Given that the AI has processed unstructured data, when a user accesses the dashboard, then it should display sentiment categories, trends, and consumer patterns in visual formats (charts/graphs) that update in real-time.

Generating alerts for significant shifts in consumer sentiment.

Given a predefined threshold for sentiment changes, when the AI detects a shift that exceeds the threshold, then it should send an alert notification to users within 1 minute of detection.

Historical performance data analysis for engagement rate forecasting.

Given historical campaign data, when the AI is applied to forecast engagement rates, then it should generate forecasts that are within 10% accuracy of the actual engagement rates for previous campaigns.

Seamless integration of sentiment analysis with engagement strategies.

Given the results of the sentiment analysis, when users generate insights, then the system should recommend at least three engagement strategy adjustments that align with the analyzed sentiment.

User feedback collection on the effectiveness of sentiment analysis.

Given that users have accessed sentiment analysis reports, when they complete a feedback survey, then at least 80% of users should rate the insights as 'useful' or higher.

Performance testing of AI algorithms under high data loads.

Given large volumes of unstructured data, when the AI processes this data, then it should maintain response time under 2 seconds for 95% of the requests during peak usage.

Customizable Reporting Dashboard

User Story: As a marketing manager, I want a customizable reporting dashboard so that I can tailor my reports to focus on the metrics that are most relevant to my campaigns, enabling better insights and informed decision-making.
Description: The Customizable Reporting Dashboard requirement focuses on providing users with the ability to create personalized reports based on their specific needs and preferences. Users will be able to select metrics, adjust layouts, and integrate various data sources to produce tailored reports that reflect their unique objectives. The functionality will allow for the automation of report generation, where users can schedule the dashboard to generate reports at specified intervals. This feature enhances user experience and efficiency by empowering users to focus on the data that matters most to them, rather than navigating through pre-defined reports. The expected outcome is increased user satisfaction and improved decision-making capabilities for clients by allowing them to visualize data in ways that align with their business needs.
Acceptance Criteria: User creates a personalized report for a specific marketing campaign.

Given a logged-in user on the Customizable Reporting Dashboard, when they select metrics for their campaign, adjust layout preferences, and click 'Generate Report', then the report should reflect the selected metrics and layout accurately.

User automates report generation on a scheduled basis.

Given a user has configured the report settings and scheduled a report to run weekly, when the scheduled time arrives, then a new report should be generated and emailed to the user without manual intervention.

User integrates data from multiple sources into their report.

Given a user has access to multiple data sources, when they choose to include data from these sources in their report, then the report should display data aggregated correctly from all selected sources.

User adjusts report layout and sees changes applied.

Given a user has made layout adjustments to their report, when they apply these changes and regenerate the report, then the changes should be reflected in the final report output with no discrepancies.

User accesses pre-saved report templates for quick reporting.

Given the user has saved report templates for future use, when they select a template from the dashboard, then the report should be generated based on the selected template with all metrics and layouts pre-defined.

User receives alerts for changes in important metrics.

Given a user has set up alerts based on specific metric thresholds, when the thresholds are crossed, then the user should receive a notification through their preferred communication method (email, SMS, etc.) promptly.

User shares their custom report with team members.

Given a user has created a custom report, when they choose to share it with team members, then the selected members should receive access to the report and be able to view it in real-time.

Real-time Alerts for Sentiment Changes

User Story: As a brand manager, I want real-time alerts for sentiment changes so that I can promptly address any negative feedback and capitalize on positive trends, maintaining our brand's reputation effectively.
Description: The Real-time Alerts for Sentiment Changes requirement aims to provide users with instant notifications regarding significant shifts in consumer sentiment related to their brand or products. This feature will utilize machine learning algorithms to monitor sentiment data continuously and trigger alerts when pre-defined thresholds are crossed. By integrating these alerts into SentiScan’s existing notification system, users will receive timely updates via email or direct message, enabling them to respond rapidly to emerging trends before they escalate. The implementation of this feature will help users maintain a proactive approach to reputation management and enhance their responsiveness to market dynamics. The expected outcome is a quicker reaction time to changes in public sentiment, leading to better stakeholder communication and damage control.
Acceptance Criteria: User receives a real-time alert via email when the sentiment of their brand mentions drops below a predetermined threshold within 10 minutes of the change.

Given that a user has set a sentiment threshold for alerts, when sentiment drops below this threshold, then the user should receive an email notification within 10 minutes.

A user is able to customize the threshold levels for receiving alerts on sentiment changes in the SentiScan platform.

Given a user is in the settings of the alert system, when they adjust the sentiment threshold sliders and save the changes, then those new thresholds should be reflected in their alert preferences.

The system logs all sentiment change alerts generated for a user over the past 30 days for analytical review.

Given the user accesses the alert history section, when they view the past 30 days of alerts, then all relevant sentiment changes should be displayed with timestamps and sentiment data.

Users should have the option to receive alerts via direct messaging on a connected messaging platform in addition to email.

Given a user has linked their messaging platform account, when a significant sentiment change occurs, then the user should receive a notification on both their email and connected messaging app.

The system accurately classifies sentiment as positive, neutral, or negative before sending alerts to users.

Given real-time sentiment data is being processed, when a shift in sentiment occurs, then the system should classify that shift correctly and trigger an alert only if it is categorized appropriately based on user thresholds.

Alerts should be sent only during business hours defined by the user to avoid unnecessary notifications during off-hours.

Given the user has set their business hours in the application settings, when a sentiment change occurs outside these hours, then alerts should be delayed until the start of business hours the following day.

Users should be able to disable specific alert types while keeping others active for personalized settings.

Given a user is in their alert preferences, when they toggle off specific types of sentiment change alerts, then those alerts should no longer trigger notifications while others remain active based on their selections.

Benchmarking Competition

User Story: As a strategist, I want to benchmark our engagement metrics against competitors so that I can identify areas for improvement and better position our marketing strategies.
Description: The Benchmarking Competition requirement enables users to compare their engagement metrics against competitors in their industry. This feature will aggregate publicly available data from various sources to provide insights into how brands perform relative to each other. By integrating this functionality into SentiScan’s analytical capabilities, marketers can understand their positioning in the competitive landscape and identify opportunities for improvement. This benchmarking tool will assist in strategic planning and allow for more informed decision-making based on competitive insights. The expected outcome will be a clearer perspective on market positioning and enhanced abilities to adjust marketing strategies to stay ahead of competitors.
Acceptance Criteria: User accesses the Benchmarking Competition tool within the SentiScan platform to analyze their brand's engagement metrics against a selected competitor's metrics for the past quarter.

Given the user is logged into SentiScan and has selected a competitor, when they request benchmarking data, then the system should display a comparative report of engagement metrics, including likes, shares, and comments for both brands.

Marketer wants to view trends over the last six months to help identify patterns in the competitor's engagement metrics and compare them to their own metrics.

Given the user selects the six-month timeframe for benchmarking comparison, when the data is retrieved, then the system should show a trend line graph of engagement metrics for both their brand and the competitor's brand, highlighting key insights.

A user assesses how their engagement metrics rank within the industry after inputting relevant benchmarking data.

Given the user has completed the benchmarking analysis, when viewing the results, then it should include a summary section that clearly states their brand's ranking against competitors, with specific percentages demonstrating performance differences.

A marketing analyst receives alerts when significant changes in competitor engagement metrics occur that could impact strategic planning.

Given the user has set up alerts for competitor engagement metrics, when a significant metric change occurs (e.g., a 20% increase in engagement), then the system should trigger an alert notification to the user via email or in-app notification.

User wishes to generate a report summarizing competitive engagement insights for presentations to stakeholders.

Given the user has accessed the Benchmarking Competition tool, when they select to export a report, then the system should generate a downloadable PDF report that includes graphs, comparisons, and key findings of the engagement metrics against competitors.

Audience Sentiment Analyzer

Audience Sentiment Analyzer provides insights into the emotional tone of audience interactions, helping marketers understand how sentiment shifts might impact engagement. This feature allows users to assess the potential reactions to their content before launch, enabling them to craft messaging that resonates positively with their audience, thus increasing overall engagement.

Requirements

Real-time Sentiment Analysis

User Story: As a marketing analyst, I want to receive real-time insights into audience sentiment so that I can make immediate adjustments to my marketing strategies and improve engagement with my content.
Description: The Real-time Sentiment Analysis requirement enables the Audience Sentiment Analyzer to assess and interpret audience sentiment instantly as new interactions occur across various platforms. This functionality is crucial for marketers, as it provides immediate insights that drive decision-making, allowing for timely adjustments in campaigns. The implementation of this requirement will involve creating efficient algorithms that can process streaming data and generate sentiment scores on-the-fly, integrating seamlessly with the existing framework of SentiScan. The expected outcome is an up-to-date understanding of consumer sentiment, ensuring that marketers can respond promptly to audience sentiments and optimize engagement strategies accordingly.
Acceptance Criteria: Real-time sentiment tracking during a product launch campaign.

Given a marketing campaign is launching on social media, When the Audience Sentiment Analyzer processes new interactions in real-time, Then it should display sentiment scores with less than a 5-second delay.

Monitoring audience sentiment changes during a promotional event.

Given a promotional event is ongoing, When new comments are posted on social media platforms, Then the system should update sentiment scores dynamically, reflecting changes within a minute.

Comparing sentiment scores before and after a content adjustment.

Given initial sentiment scores are recorded prior to a content modification, When the content is launched and interactions begin, Then the sentiment scores should show a measurable improvement of at least 10% within 30 minutes of content release.

Integration of sentiment scores with marketing dashboards.

Given real-time sentiment data is generated, When the data is pushed to the marketing dashboard, Then the dashboard should accurately reflect the latest sentiment scores with no discrepancies.

Alert system for significant sentiment shifts.

Given that sentiment scores fluctuate above or below a designated threshold, When a significant change occurs, Then an alert should be triggered and sent to marketing teams within 2 minutes of detection.

Assessing sentiment across multiple social media channels.

Given that the Audience Sentiment Analyzer is processing data from different social media platforms, When interactions are received, Then it should be able to aggregate and display sentiment scores for each platform within a single report.

User feedback loop for sentiment score validation.

Given a sample set of audience feedback on content, When the Audience Sentiment Analyzer generates sentiment scores, Then at least 80% of users should agree with the sentiment assessment in a follow-up survey.

Sentiment Trend Visualization

User Story: As a marketer, I want to visualize sentiment trends over time so that I can identify patterns and adjust my strategies based on long-term sentiment analysis.
Description: The Sentiment Trend Visualization requirement involves creating interactive graphical representations of sentiment changes over time. This feature will allow users to visually analyze patterns in the data, helping them to identify long-term sentiments versus short-term reactions. This integration is essential because visualizations enhance understanding and facilitate presentations, making data-driven decisions more accessible to stakeholders. The implementation will require the development of dashboard components and data mapping techniques that align sentiment data with timeline features, ultimately allowing users to draw actionable insights from trends effectively.
Acceptance Criteria: Interactive Graph Display of Sentiment Trends Over Time

Given a user accesses the Sentiment Trend Visualization interface, When the user selects a specific date range for analysis, Then the system displays an interactive graph showcasing sentiment trend data for that period, accurately reflecting the changes in sentiment.

Comparison of Long-Term vs. Short-Term Sentiments

Given a user selects both long-term and short-term sentiment options, When the user generates the sentiment trend report, Then the system displays both data sets side by side for clear comparison analysis of long-term versus short-term sentiment trends.

Visualization Updates on Real-Time Sentiment Changes

Given that there are new sentiment data updates, When the user refreshes the dashboard, Then the system automatically updates the sentiment trend graph in real-time without requiring a full page reload or manual intervention.

Data Filtering Options for Targeted Analysis

Given a user is on the Sentiment Trend Visualization page, When the user selects specific parameters such as demographics or marketing campaigns, Then the system filters the sentiment data displayed in the graph accordingly, ensuring that the visual representation aligns with the selected criteria.

Export Capability for Sentiment Reports

Given a user has generated a sentiment trend report, When the user selects the export option, Then the system successfully exports the sentiment data and visual representations into a specified format (e.g., CSV, PDF) for offline use or presentation.

Mobile Responsiveness of the Sentiment Trend Visualization

Given a user accesses the Sentiment Trend Visualization on a mobile device, When the interface loads, Then the system adapts the layout and functionality to ensure optimal usability and readability for mobile users, maintaining all graphical representations and filtering options.

Content Sentiment Prediction

User Story: As a content creator, I want to predict how my audience will respond to new content so that I can tailor it to ensure a positive reaction and increase engagement.
Description: The Content Sentiment Prediction requirement enables the Audience Sentiment Analyzer to forecast how new content will likely be perceived by the audience before its launch. By utilizing machine learning models trained on historical data, this feature will estimate the potential audience sentiment associated with various types of content. Implementing this requirement will help marketers to create content that resonates positively with their audience, effectively increasing engagement and reducing the risk of negative backlash. It requires advanced predictive analytics and integration with the content creation workflow within SentiScan.
Acceptance Criteria: Content Sentiment Prediction Overview

Given a piece of new content to be analyzed, when the Audience Sentiment Analyzer is used, then it should return a sentiment score within the range of -1 to 1, where scores closer to 1 indicate positive sentiment and scores closer to -1 indicate negative sentiment.

Integration with Content Creation Workflow

Given that an editor is using SentiScan to create new content, when the editor opts to analyze the content for sentiment, then the tool should seamlessly integrate with the content creation workflow, allowing for the prediction to be generated within 5 seconds.

Historical Data Utilization

Given that the Content Sentiment Prediction feature is trained on historical data, when predicting sentiment for a new piece of content, then the prediction accuracy should be at least 85% based on historical results from similar content types.

User Accessibility Options

Given that a user accesses the Audience Sentiment Analyzer, when they view the sentiment analysis results, then the tool should provide options for viewing the results in both graphical and numerical formats for enhanced accessibility.

Feedback Loop for Continuous Improvement

Given that the marketer launches content based on sentiment predictions, when audience feedback is collected post-launch, then this data should be used to improve future predictions automatically through a feedback loop mechanism.

Real-Time Updates on Sentiment Changes

Given that the Audience Sentiment Analyzer is live, when there are significant changes in audience sentiment on social media platforms, then the system should generate real-time alerts for the marketer within 30 minutes.

Reporting Capabilities

Given the results of the sentiment analysis, when the user requests a report, then the system should generate a detailed report that includes sentiment scores, potential market reactions, and suggested content adjustments within 10 minutes.

Sentiment Change Alerts

User Story: As a marketing manager, I want to receive alerts when audience sentiment changes significantly so that I can react quickly and adjust my strategies accordingly.
Description: The Sentiment Change Alerts requirement provides users with real-time notifications when significant shifts in audience sentiment occur. This functionality is important for enabling rapid responses to changing audience attitudes, ensuring that marketing efforts can be adjusted quickly to address potential concerns or capitalize on positive sentiment. The implementation involves creating an alert system that monitors sentiment analysis results and triggers notifications based on user-defined thresholds or significant deviations from the norm. This feature is critical for proactive marketing strategies that rely on timely information.
Acceptance Criteria: Real-time Sentiment Changes Notification for a Marketing Campaign

Given a marketing campaign is launched, when there is a significant sentiment shift (increase or decrease of 20% or more) in audience interactions within a specified time frame, then the user receives a real-time notification via the dashboard.

User Defined Threshold Alerts for Sentiment Shifts

Given the user sets a custom threshold for sentiment change notifications, when audience sentiment changes by the defined threshold, then the user receives a notification through their preferred communication channel (email, SMS, app alert).

Dashboard Display of Sentiment Trends and Alerts

Given the Sentiment Change Alerts system is active, when significant sentiment shifts occur, then the user's dashboard updates to show the sentiment trend graphs along with a list of triggered alerts for the last 30 days.

Response Time to Sentiment Alerts

Given a significant sentiment change alert is triggered, when the user accesses the Sentiment Change Alert, then they should be able to respond to the sentiment shift (e.g., adjusting marketing strategies) within 5 minutes of receiving the alert.

Integration of Sentiment Alerts with External Tools

Given an integration setup is completed, when a sentiment change alert is triggered, then the alert is sent to the integrated external tools (e.g., Slack, CRM systems) within 2 minutes.

Historical Data Review of Sentiment Changes

Given past sentiment changes are requested, when users access the historical data, then they should see a record of all significant sentiment changes and associated alerts for at least the last 6 months.

Competitive Sentiment Benchmarking

User Story: As a market strategist, I want to benchmark my brand's sentiment against competitors so that I can identify strengths and weaknesses in our market position.
Description: The Competitive Sentiment Benchmarking requirement allows users to compare audience sentiment towards their brand against competitors. This feature is vital as it provides strategic insights that help businesses understand their market position and identify areas for improvement. The implementation involves gathering and analyzing sentiment data from multiple sources regarding competitors, integrating this analysis into the SentiScan system, and presenting it in a user-friendly format. The expected outcome is enhanced strategic planning capabilities by understanding both relative performance and audience perception in the competitive landscape.
Acceptance Criteria: User accesses the Competitive Sentiment Benchmarking feature to compare brand sentiment against competitors before launching a new marketing campaign.

Given that the user has sufficient data available for their brand and competitors, when they initiate a sentiment comparison, then the system should present a graph comparing sentiment scores across all competitors within 5 seconds.

Marketers want to view historical sentiment data over time for their brand and competitors to analyze trends.

Given that the user selects a date range for the historical data, when the user submits the request, then the system should display sentiment trend charts that accurately reflect the selected time frame within 10 seconds.

A user attempts to generate a report on competitive sentiment insights for a presentation.

Given that the user is logged into the SentiScan system and has access to the Competitive Sentiment Benchmarking feature, when they select the report option, then the system should generate a downloadable PDF report with all relevant sentiment data and charts within 3 minutes.

Users want to receive alerts when sentiment shifts significantly for their brand or competitors.

Given that the user has set up alert preferences for sentiment changes, when a competitor's sentiment score changes by more than 10% over a 24-hour period, then the system should send a notification to the user via email and in-app alert within 15 minutes of the change.

Users employ Competitive Sentiment Benchmarking to guide content strategy by identifying areas of improvement based on competitor analysis.

Given that the user analyzes sentiment data, when they identify a competitor with a significantly higher positive sentiment, then the system should provide actionable insights and suggestions to refine their content strategy based on that analysis.

A marketing team conducts a quarterly review of brand sentiment against competitors.

Given that the marketing team has scheduled a quarterly review, when they access the Competitive Sentiment Benchmarking feature, then they should be able to view a comparison summary of sentiment analysis over the past quarter with key highlights and notable trends.

A user seeks to customize the comparison metrics of sentiment analysis to focus on specific criteria relevant to their goals.

Given that the user accesses the customization options within the Competitive Sentiment Benchmarking feature, when they select specific metrics to compare, then the system should allow them to save this configuration and update the comparison results accordingly within 30 seconds.

Multi-Channel Engagement Dashboard

Multi-Channel Engagement Dashboard allows users to view engagement predictions seamlessly across all their social media platforms. This centralized visualization ensures marketers can compare performance metrics and optimal posting strategies in one place, streamlining decision-making and maximizing cross-channel effectiveness.

Requirements

Real-Time Engagement Metrics

User Story: As a marketer, I want real-time engagement metrics so that I can quickly adjust my strategies to maximize audience interaction and optimize my campaign effectiveness.
Description: The Real-Time Engagement Metrics requirement ensures that the Multi-Channel Engagement Dashboard provides up-to-the-minute data on user interactions across all social media platforms. This feature will enable marketers to assess engagement levels promptly and make data-driven decisions. By integrating real-time analytics, users can instantly determine which posts and strategies are performing well or poorly, allowing them to adjust their campaigns dynamically. This requirement is crucial for maximizing campaign effectiveness and improving overall audience engagement through timely insights into social media performance.
Acceptance Criteria: User accesses the Multi-Channel Engagement Dashboard to review current engagement metrics for their latest social media posts during a campaign launch event

Given the user is logged into SentiScan and has access to the Multi-Channel Engagement Dashboard, when the user selects the 'Real-Time Engagement Metrics' option, then the dashboard should display engagement data from all connected social media platforms within the last 5 minutes.

Marketer analyzes the effectiveness of posts made within the last hour to adjust their posting strategy accordingly

Given the user is on the Multi-Channel Engagement Dashboard, when the user filters the posts to show only those made in the last hour, then the displayed metrics should update to reflect real-time engagement, showing likes, shares, and comments for each post.

User receives an alert when engagement metrics of a specific post drop below a predefined threshold during a live product launch

Given that the user has configured alert preferences, when the engagement level for a post drops below the configured threshold, then the system should trigger an alert notification to the user via their preferred communication channel (email or in-app notification).

Analyst compares performance metrics of posts across different social media platforms to identify the most effective channel

Given that the user is on the Multi-Channel Engagement Dashboard, when the user selects two or more social media platforms for comparison, then the dashboard should present a side-by-side comparison of engagement metrics, including impressions, clicks, and conversion rates.

User wants to generate a report summarizing engagement metrics over the past week for campaign performance review

Given the user is on the Multi-Channel Engagement Dashboard, when the user selects the report generation feature and specifies the date range for the last week, then a downloadable report should be generated, containing summarized engagement metrics, trends, and insights.

Cross-Platform Comparison Tool

User Story: As a marketer, I want a cross-platform comparison tool so that I can identify which social media channels are performing best and optimize my content strategy accordingly.
Description: The Cross-Platform Comparison Tool requirement enables users to compare engagement metrics across different social media platforms within the Multi-Channel Engagement Dashboard. This feature will provide visual representations, such as graphs and charts, that highlight the effectiveness of various platforms. By allowing marketers to see which channels are delivering the highest engagement rates, this tool helps in refining their marketing strategies and allocating resources efficiently. The integration of this comparison functionality is essential for marketers looking to enhance their cross-channel performance and improve campaign outcomes.
Acceptance Criteria: User compares engagement rates for Facebook, Twitter, and Instagram on the Multi-Channel Engagement Dashboard to determine which platform has the highest user interaction during a specific campaign period.

Given the user has selected a campaign period, when they access the Cross-Platform Comparison Tool, then the dashboard should display a comparative bar graph showing engagement metrics for Facebook, Twitter, and Instagram side by side.

A marketer wants to identify trends in engagement rates over the past month across multiple social media platforms using the Cross-Platform Comparison Tool.

Given the user has selected a date range of the last month, when they view the engagement metrics, then the dashboard should show a line graph illustrating the trend of engagement rates for each selected social media platform during that period.

A user is testing the responsiveness of the Cross-Platform Comparison Tool on different devices to ensure it performs well on mobile and desktop.

Given the user navigates to the Multi-Channel Engagement Dashboard on a mobile device, when they access the Cross-Platform Comparison Tool, then the dashboard should maintain usability and visual integrity, ensuring data is clearly readable and interaction elements are accessible.

After analyzing platforms, a marketer utilizes the insights from the Cross-Platform Comparison Tool to adjust their posting strategy based on the performance of each channel.

Given the user has identified the platform with the highest engagement from the comparison data, when they implement a revised posting strategy, then the tool should allow the user to save these insights and modifications in a separate strategy document for future reference.

A team of marketers is tracking campaign performance and wishes to generate a report based on the engagement metrics displayed by the Cross-Platform Comparison Tool.

Given the user selects the option to generate a report, when they click the 'Export' button, then the dashboard should create a downloadable report that includes all visual comparisons and engagement metrics for the selected social media platforms for the specified timeframe.

Customizable Dashboard Layout

User Story: As a user, I want to customize my dashboard layout so that I can prioritize the metrics that matter most to me and improve my workflow.
Description: The Customizable Dashboard Layout requirement allows users to personalize their Multi-Channel Engagement Dashboard according to their individual needs and preferences. This feature empowers users to drag and drop widgets, select what metrics to display, and arrange their dashboard layout in a way that makes the most sense for them. By providing the ability to customize the dashboard, SentiScan enhances user experience, ensuring that critical data is easily accessible and visible. This requirement is fundamental for fostering user ownership of their data analysis process, ultimately leading to more effective engagement tracking.
Acceptance Criteria: User customizes their Multi-Channel Engagement Dashboard for the first time, dragging and dropping various widgets around the screen to create a layout that suits their data analysis needs.

Given a user accesses the Customizable Dashboard Layout for the first time, when they drag and drop at least three widgets into different positions on the dashboard, then the dashboard should save the new layout and retain it upon refreshing the page.

A marketing analyst wants to display only specific metrics related to engagement predictions on their dashboard, focusing solely on metrics for Facebook and Twitter.

Given a user selects specific metrics to display, when the user initiates the customization mode and deselects metrics not related to Facebook and Twitter, then only the selected metrics should be visible on the dashboard.

Users need to revert their dashboard layout back to the default settings after experimenting with multiple custom layouts.

Given a user has customized their dashboard layout, when they choose the option to revert to the default layout, then the dashboard should revert to its original state with all default metrics and widget placements.

Multiple users are collaborating on the same dashboard and need to ensure that their individual customizations do not overwrite each other.

Given multiple users have access to the same Multi-Channel Engagement Dashboard, when one user customizes their layout and saves it, then the other users’ customizations should remain unchanged and saved independently.

A user wants to quickly assess the impact of their layout changes on the overall performance metrics shown in their dashboard.

Given a user customizes their dashboard layout, when they switch between different layouts, then the displayed metrics should update in real-time to reflect the latest performance data associated with the selected configuration.

User wants to ensure that their saved dashboard layout is accessible across different devices, such as mobile and desktop.

Given a user customizes their dashboard layout on a desktop, when they log into the same account on a mobile device, then the customized layout should appear exactly as saved on the desktop device.

Sentiment Analysis Integration

User Story: As a marketer, I want sentiment analysis integrated into my dashboard so that I can gain deeper insights into how my audience feels about my content and adjust my strategies accordingly.
Description: The Sentiment Analysis Integration requirement will connect the Multi-Channel Engagement Dashboard with SentiScan's advanced sentiment analysis tools. This strategic integration will allow users to gain insights not only into engagement metrics but also into the emotional tone and sentiment surrounding their social media content. By incorporating sentiment analysis, marketers can understand not just how many people are engaging with their content, but how they feel about it, providing a comprehensive view of audience perception. This feature is essential for refining messaging and enhancing emotional resonance in marketing campaigns.
Acceptance Criteria: User accesses the Multi-Channel Engagement Dashboard to view sentiment analysis data alongside their engagement metrics for a specific campaign.

Given the user has valid access to the Multi-Channel Engagement Dashboard, when they select a specific campaign, then they should see sentiment analysis data integrated within the dashboard that reflects the emotional tone of engagement.

Marketers need to set up alerts for significant shifts in sentiment around their social media campaigns.

Given the user is on the settings page for the Multi-Channel Engagement Dashboard, when they configure alerts for sentiment changes, then they should receive notifications via email or in-app when sentiment shifts exceed predefined thresholds.

Users want to compare sentiment scores from different social media platforms within the Multi-Channel Engagement Dashboard to inform their strategy.

Given the user has selected multiple social media platforms, when they view the dashboard, then sentiment scores from each platform should be displayed side-by-side for easy comparison and analysis.

A user is analyzing the overall sentiment trends over the last 30 days for their social media content.

Given the user navigates to the sentiment analysis report on the Multi-Channel Engagement Dashboard, when they specify a 30-day range, then the report should generate visual trends showing sentiment changes in that timeframe.

Users need to filter sentiment analysis based on specific topics or keywords related to their campaigns.

Given the user is on the sentiment analysis section of the dashboard, when they apply filters for specific topics or keywords, then the displayed sentiment data should update to reflect only the relevant information pertaining to those filters.

Marketers need to export sentiment data for their marketing reports.

Given the user has accessed the sentiment analysis data, when they choose to export the data, then the system should generate and download a report in CSV format containing all relevant sentiment metrics.

Automated Reporting System

User Story: As a marketer, I want an automated reporting system so that I can regularly receive comprehensive insights on my engagement performance without manual intervention.
Description: The Automated Reporting System requirement will enable users to generate and schedule comprehensive reports on their engagement metrics automatically. This feature allows users to set parameters for the reports they want and receive them in their preferred format via email or within the dashboard. By streamlining the reporting process, marketers save time and improve their efficiency in analyzing engagement trends, leading to more informed decision-making. This requirement is pivotal for organizations that rely on regular performance insights to adjust their marketing strategies and stakeholders engaged.
Acceptance Criteria: Scheduled Report Generation for Weekly Engagement Metrics

Given the user has configured the report parameters and scheduling settings, when the scheduled time arrives, then the system generates and delivers the report to the user's email and dashboard successfully without errors.

Customization of Report Parameters by User

Given the user accesses the reporting settings, when the user modifies any parameter (e.g., date range, engagement metrics), then the changes are saved successfully and reflected in the generated reports according to the new parameters.

Successful Delivery of Reports in Preferred Formats

Given the user has selected their preferred report format (PDF, Excel), when the report is generated, then the report is formatted correctly and sent in the chosen format without corruption or data loss.

Real-Time Notification of Report Completeness

Given the system generates a report, when the generation is complete, then a real-time notification is sent to the user informing them that their report is available for review.

Multi-User Access to Reports

Given multiple users are assigned the same report parameters, when any user accesses the report, then all designated users can view the most recent version of the report concurrently without access issues.

Historical Trends Analysis in Reports

Given the user has specified historical data parameters, when the report is generated, then the report includes a comparative analysis of historical engagement metrics over the specified timeframe.

Adaptive Engagement Strategy

Adaptive Engagement Strategy uses real-time data to adjust engagement predictions based on changing audience behaviors and trends. By continuously learning from new data points, this feature ensures that marketers can pivot their strategies promptly, optimizing content performance in response to emerging insights.

Requirements

Dynamic Data Monitoring

User Story: As a marketing analyst, I want to continuously monitor real-time data from social media so that I can swiftly adapt my engagement strategies according to shifting audience sentiments.
Description: The Dynamic Data Monitoring requirement involves implementing a system that continuously collects and analyzes real-time data from various online platforms and social media channels. This system will employ advanced algorithms to track audience behavior, sentiment changes, and emerging trends. By integrating this feature with SentiScan’s existing analytics tools, users will gain valuable insights that enable them to quickly adapt their marketing strategies. The benefits include timely updates on audience sentiments, allowing marketers to respond proactively and effectively, thus improving engagement and overall campaign success.
Acceptance Criteria: Real-time audience sentiment analysis and reporting for a marketing campaign.

Given the Dynamic Data Monitoring system is operational, when marketers access the sentiment dashboard, then they should receive real-time sentiment updates for their audience with a latency of no more than 5 seconds.

Automated alerts for significant changes in audience engagement metrics.

Given the Dynamic Data Monitoring system tracks audience behavior, when there is a shift of more than 15% in engagement metrics, then an alert should be generated and sent to the designated marketing team members immediately.

Integration with existing SentiScan analytics tools.

Given the Dynamic Data Monitoring feature is implemented, when users access the analytics tools, then they should be able to view and analyze real-time data alongside historical data without any discrepancies.

User feedback collection on the effectiveness of engagement predictions.

Given the Adaptive Engagement Strategy feature is in use, when marketing teams collect feedback from campaign results, then at least 80% of users should report improved engagement following real-time strategy adjustments based on Dynamic Data Monitoring.

Historical comparison of sentiment trends over time for strategic planning.

Given the Dynamic Data Monitoring feature is gathering data, when users generate a historical report, then they should be able to visualize sentiment trends for the past 30 days with accurate data representation at least 95% of the time.

Automated Insights Generation

User Story: As a marketer, I want to receive automated insights from audience data so that I can make quick decisions on my engagement strategies without manual analysis.
Description: The Automated Insights Generation requirement aims to utilize AI-driven analysis to automatically generate actionable insights from the collected data. This functionality will analyze sentiment shifts, identify key themes in audience feedback, and present these findings in an easily digestible format. By providing instant insights, this feature will enable marketers to make informed decisions more quickly and effectively, enhancing the overall performance of their campaigns and strategies. Integration with visual reporting dashboards will facilitate better understanding and strategic planning based on real-time data.
Acceptance Criteria: Automated insights are generated based on social media data collected over a week to analyze changes in consumer sentiment during a product launch campaign.

Given the data collected from social media platforms, when the analysis is performed, then the system should generate insights that highlight the sentiment shift, key themes, and trends observed during the week.

Marketing professionals access the visual reporting dashboard to view the generated insights following an analysis of user feedback from recent campaigns.

Given that the automated insights have been generated, when the user accesses the dashboard, then the insights should be displayed in a clear and easily digestible format, including visual elements such as charts or graphs.

Real-time adjustments for engagement strategies are made based on newly generated insights post-analysis of audience feedback.

Given the newly generated insights from automated analysis, when the marketer reviews the data, then the system should suggest specific engagement adjustments based on identified themes and sentiment shifts.

The automated insights feature is tested for accuracy against a predefined dataset representing historical audience feedback and sentiment analysis.

Given a set of predefined historical data, when the automated insights generation is executed, then the results should match expected insights within a 90% accuracy threshold.

Marketers receive alerts when significant sentiment shifts are detected in the automated insights generated from ongoing data analysis.

Given that sentiment shifts are analyzed, when there is a significant change in sentiment, then the system should automatically trigger an alert to the marketers detailing the nature of the shift.

Integration with existing visual reporting dashboards to ensure seamless display of automated insights for users.

Given that the automated insights have been generated, when accessed through the integrated dashboards, then the data should refresh in real-time without any lag, maintaining data integrity.

Predictive Engagement Modeling

User Story: As a brand manager, I want to predict audience engagement trends so that I can tailor my marketing strategies to align with anticipated audience reactions.
Description: The Predictive Engagement Modeling requirement focuses on developing models that forecast audience engagement trends based on historical and current data. By using machine learning techniques, this feature will help marketers anticipate how different segments of audiences might respond to various content types and strategies. The predictive analytics will enhance campaign planning and execution, allowing for more personalized marketing efforts that resonate with audiences. This capability is crucial for optimizing return on marketing investment and improving overall engagement with the brand.
Acceptance Criteria: Predictive engagement model generates forecasts for a new marketing campaign targeting a specific demographic segment within 24 hours of data ingestion.

Given that the historical engagement data has been ingested, when the predictive model runs, then it should provide engagement forecasts for the specific demographic segment with at least 80% accuracy.

Marketers access the predictive engagement model's dashboard to view real-time analytics of predicted engagement metrics.

Given the predictive model has been activated, when marketers access the dashboard, then they should see real-time predicted engagement metrics for different content types updated every hour.

The predictive engagement model adjusts its forecasts based on newly ingested data signals.

Given that new engagement data is available, when the model processes this data, then it should update forecasts immediately and reflect changes in predicted engagement trends.

The model provides recommendations for content strategy adjustments based on predicted audience responses.

Given that the predictive engagement data is available, when the model analyzes it, then it should provide at least three actionable recommendations for adjusting content strategies relevant to the target audience.

Campaign planners receive alerts on significant shifts in predicted engagement trends that may impact their content strategy.

Given that the predictive model detects significant changes in engagement forecasts, when this occurs, then the system should automatically alert campaign planners within 5 minutes via email.

The predictive engagement model is integrated with existing marketing automation tools to enhance personalized outreach.

Given the model is connected to the marketing automation tools, when a campaign is launched, then it should apply the predictive engagement insights to tailor messages for at least 90% of the target segments.

Real-Time Sentiment Alerts

User Story: As a marketing manager, I want to receive alerts when major sentiment changes occur so that I can quickly respond and adjust our marketing strategies accordingly.
Description: The Real-Time Sentiment Alerts requirement involves creating a notification system that triggers alerts based on significant changes in audience sentiment. These alerts will help marketers stay informed of shifts in consumer attitudes toward their brand or products, thus enabling rapid response and adjustment of marketing strategies. The feature will integrate seamlessly with SentiScan’s existing tools, ensuring that users receive timely and relevant updates that can significantly mitigate potential negative impacts from sudden sentiment shifts.
Acceptance Criteria: Notification triggers when there is a 20% increase or decrease in sentiment score within a 1-hour period.

Given that a sentiment score is tracked continuously, when the sentiment score fluctuates by 20% within an hour, then an alert notification is sent to the user through the SentiScan dashboard and via email.

Users can customize the thresholds for triggering alerts based on product category relevance.

Given that a user is in the settings menu, when they set custom thresholds for specific product categories, then those thresholds are saved and applied for monitoring alerts associated with those categories.

Alerts are triggered for both positive and negative sentiment shifts to provide a holistic view of audience sentiment.

Given that the system is monitoring sentiment, when there is a significant positive or negative shift beyond the defined threshold, then the user receives a notification detailing the nature of the change.

Users receive a summary report of sentiment shifts along with alert notifications.

Given that an alert notification is triggered, when the user accesses the notification, then they receive a summary report outlining the sentiment changes, potential impacts, and recommended actions.

Alert notifications are tested for real-time delivery to ensure timely responses.

Given that an alert is triggered, when tested, then the alert notification is received by the user within 5 minutes of the sentiment change occurring.

Integration of the alert system with existing dashboards to ensure seamless user experience.

Given that the alert system is implemented, when a user accesses the dashboard, then they can easily view recent alert notifications alongside other relevant metrics without navigation issues.

Customizable Engagement Dashboards

User Story: As a user, I want to customize my engagement dashboard to display the metrics that are most important to my marketing efforts so that I can focus on my key performance indicators and improve strategic outcomes.
Description: The Customizable Engagement Dashboards requirement aims to provide users with the ability to create tailored dashboards that reflect their specific engagement metrics and KPIs. This feature will allow marketers to select relevant data points, visualize trends, and assess the effectiveness of their strategies through user-friendly interfaces. By customizing their dashboards, users can focus on the metrics that matter most to them, leading to more strategic insights and enhanced decision-making processes within their teams.
Acceptance Criteria: User creates a customizable engagement dashboard to monitor their selected KPIs and metrics for their marketing campaigns in real-time.

Given the user is logged into SentiScan, when they navigate to the dashboard creation page and select at least three engagement metrics, then a customizable dashboard reflecting those metrics should be generated successfully.

User modifies an existing dashboard to include new metrics based on changing marketing strategy.

Given the user has an existing dashboard, when they select additional metrics and save the dashboard, then the changes should be applied, and the dashboard should reflect the new metrics without any errors.

User removes an engagement metric from their dashboard that is no longer relevant to their strategy.

Given the user is viewing their engagement dashboard, when they remove a selected metric and confirm the action, then the metric should no longer display on the dashboard, and the overall engagement view should update accordingly.

User shares their customized engagement dashboard with team members for collaborative analysis.

Given the user has created a dashboard, when they choose to share the dashboard with specific team members, then those members should receive an invitation to view the dashboard with correct permissions and access.

User accesses the engagement dashboard on a mobile device to check on campaign performance.

Given the user is on a mobile device, when they log into SentiScan and access their customized dashboard, then the dashboard should load quickly and display all selected metrics in an optimized mobile view.

User reviews engagement trends over time using the customizable dashboard's time filter feature.

Given the user is on the dashboard view, when they apply a time filter to view metrics over the last 30 days, then the displayed data should accurately reflect the selected time period without discrepancies.

Seasonal Engagement Insights

Seasonal Engagement Insights provide analysis of historical engagement trends specific to different seasons or holidays. This feature equips marketers with knowledge of optimal times to promote time-sensitive content or campaigns, ensuring they capitalize on seasonal opportunities to drive higher engagement rates.

Requirements

Historical Engagement Analytics

User Story: As a marketer, I want to access an analysis of historical engagement trends related to different seasons so that I can plan my campaigns more effectively and maximize audience engagement during peak times.
Description: The Historical Engagement Analytics requirement focuses on the collection and analysis of historical engagement data related to various seasonal times and holidays. This feature will provide users with a comprehensive view of past performance metrics, including likes, shares, comments, and other relevant engagement statistics during specific periods. By synthesizing this data, marketers can recognize patterns and trends that inform future marketing strategies. It is crucial for identifying peak engagement seasons, allowing businesses to time their campaigns effectively. The integration with SentiScan’s existing AI-driven analytics engine will ensure that marketers gain insights that are both actionable and relevant, improving overall campaign effectiveness and return on investment.
Acceptance Criteria: As a marketer, I want to access seasonal engagement data for the last three years so that I can identify patterns in consumer behavior during major holidays.

Given the user selects a specific holiday from the seasonal engagement dashboard, when they view the historical engagement analytics, then the system should display engagement data metrics such as likes, shares, and comments for that holiday over the past three years.

As a marketing analyst, I need to analyze engagement trends over multiple seasons to determine which times of year yield the highest consumer interaction.

Given the user accesses the seasonal engagement insights, when they generate a report for multiple seasons, then the report should provide a comparative analysis showing peak engagement times for each selected season based on historical data.

As a product manager, I want to evaluate the effectiveness of seasonal marketing campaigns by comparing current engagement data with historical performance metrics.

Given the user inputs current engagement metrics for a seasonal campaign, when the system compares these metrics against historical averages from past campaigns, then the user should receive a report indicating whether the current campaign is performing above or below the historical average.

As a user trying to optimize a marketing campaign, I want to be alerted when engagement metrics for an upcoming holiday show a significant shift compared to historical data.

Given the user has set up alerts for specific holidays, when the system detects a significant change in engagement metrics for those holidays compared to historical averages, then the user should receive a notification alerting them to this shift.

As a data scientist, I want to visualize historical engagement data on an interactive timeline to easily spot trends over the years.

Given the user accesses the historical engagement analysis tool, when they select the interactive timeline feature, then the system should display an interactive graph that plots engagement metrics over time for selected seasons, allowing for easy visualization of trends.

As a marketer, I need to export historical engagement data in a CSV format for further offline analysis.

Given the user is viewing the historical engagement data, when they select the export option, then the system should generate and download a CSV file containing all relevant engagement metrics for the selected seasonal period.

Seasonal Trend Notifications

User Story: As a user, I want to receive notifications when there are significant shifts in seasonal engagement trends so that I can quickly pivot my marketing strategies and take advantage of these opportunities.
Description: The Seasonal Trend Notifications requirement involves the implementation of an alert system that notifies users about significant seasonal trends in consumer engagement. By leveraging AI algorithms that analyze real-time data, the system will automatically detect noteworthy shifts in sentiment or engagement around specific holidays or seasonal events. Users will receive customizable notifications via email or in-app alerts. This feature is essential for enabling marketers to respond promptly to emerging opportunities, ensuring that they capitalize on current trends and modify their strategies to enhance customer engagement.
Acceptance Criteria: User receives a notification when a significant increase in positive sentiment is detected during the Christmas holiday season.

Given the user has defined a threshold for engagement sentiment, when a sentiment score exceeds this threshold for Christmas, then the user should receive an email notification about the trend.

Marketers want to customize their notification settings to only receive alerts for specific holidays.

Given the user is in the notification settings menu, when they select specific holidays (e.g., Thanksgiving, Halloween) and save, then they should only receive alerts related to those selected holidays.

The alert system detects a significant drop in consumer engagement during the summer season.

Given the AI algorithms have analyzed the engagement data, when a drop of engagement exceeds a predefined percentage for the summer season, then an in-app notification should be triggered to all relevant users.

A user updates their preferences to include text message alerts for significant seasonal trends.

Given the user is in the settings menu, when they select the option to receive text message alerts and provide a valid phone number, then they should receive text notifications for significant trends.

The alert system notifies users of emerging trends specific to Valentine's Day.

Given the system has identified a noteworthy increase in engagement related to Valentine's Day, when the trend is detected, then an email notification should be dispatched to all users subscribed to Valentine's Day alerts.

Users want to review past notifications to monitor trends over time.

Given the user accesses the notifications history section, when they review past notifications, then they should see a chronological list of all alerts received, including details about the corresponding trends.

Marketers need to ensure that notifications are timely and reach all intended users.

Given the alert is triggered, when the notification is sent, then all users who opted in should receive it within 5 minutes via their chosen notification method (email or in-app).

Competitive Seasonal Comparison

User Story: As a product analyst, I want to compare my seasonal engagement metrics against my competitors to understand my market positioning and refine my marketing strategies accordingly.
Description: The Competitive Seasonal Comparison requirement will allow users to benchmark their engagement performance against competitors during various seasonal periods. This feature will aggregate data from multiple sources to provide insights into how competitors perform in terms of engagement, sentiment, and overall campaign effectiveness. Users will be able to visualize these comparisons through intuitive dashboards, which will highlight strengths and weaknesses concerning seasonal engagement strategies. This capability is critical for marketers to adapt and recalibrate their own strategies based on proven successful approaches in the market.
Acceptance Criteria: User Benchmarking during Holiday Campaigns

Given that the user has selected a holiday period, when they access the Competitive Seasonal Comparison dashboard, then they should see engagement performance metrics of selected competitors clearly displayed for that period.

Visualized Data Comparisons

Given that the user has accessed the Competitive Seasonal Comparison feature, when they view the insights, then they should be able to visualize competitive engagement metrics through graphical representations like bar charts or line graphs.

Sentiment Analysis Over Specific Seasons

Given that the user has requested seasonal sentiment data, when they initiate the comparison, then the system should return sentiment scores overlaid with engagement metrics for the selected competitors.

Campaign Effectiveness Metrics

Given that the user is analyzing engagement data, when they select different seasonal campaigns, then they should be able to compare the effectiveness metrics such as click-through rates and conversion rates of their campaigns against competitors.

Alerts for Seasonal Strategy Adaptation

Given that the user has defined their competitive set, when there are significant shifts in engagement metrics during a season, then the user should receive alerts to evaluate their strategies accordingly.

Multi-Source Data Integration

Given that the competitive seasonal comparison feature is used, when users view the insights, then the data presented should aggregate information from various social media and marketing platforms, providing a comprehensive analysis.

User Customization of Metrics Displayed

Given that the user is on the Competitive Seasonal Comparison dashboard, when they choose their preferred metrics to display, then the dashboard should update in real-time to reflect the selected metrics.

Custom Seasonal Reporting

User Story: As a marketer, I want to generate customized reports that focus on seasonal engagement metrics so I can present data relevant to my specific campaign goals during different times of the year.
Description: The Custom Seasonal Reporting requirement enables users to create tailored reports focusing on engagement metrics associated with specific seasons or holidays. Users will have the option to select date ranges, metrics, and visual formats for their reports, which will be generated dynamically. This flexibility will allow marketers to generate insights relevant to their unique campaigns and objectives, improving strategic decision-making. By integrating with existing dashboard functionalities, users will be able to share these reports easily with stakeholders, enhancing collaboration and visibility.
Acceptance Criteria: User selects a specific seasonal promotion period and generates a report to analyze engagement metrics for that time frame.

Given the user selects the date range for a seasonal campaign, when the user requests a custom report, then the system should generate a report displaying engagement metrics related to the selected dates and season.

User wants to visualize engagement trends over time around a specific holiday (e.g., Christmas) using various visualization options.

Given the user selects a specific holiday and chooses a visual format (chart, graph, etc.), when the user generates the report, then the system should display the engagement metrics in the selected format, providing clear insights.

User needs to analyze the effectiveness of seasonal campaigns by comparing multiple engagement metrics across different time frames.

Given the user selects multiple metrics (likes, shares, comments) and two seasonal periods for comparison, when the report is generated, then the system should show a side-by-side comparison of the selected metrics for the two periods.

User intends to share the generated custom seasonal report with stakeholders.

Given the user has successfully generated a custom seasonal report, when the user selects the share option, then the system should allow the user to send the report via email or generate a shareable link.

User wants to ensure that the report generation process is completed within a specific time frame.

Given the user initiates the custom report generation, when the report request is processed, then the system should complete the report generation within 10 seconds.

User needs to save configurations for future use in generating seasonal reports.

Given the user sets desired date ranges and metrics for a report, when the user saves the configuration, then the system should store these settings for the user to access and reuse in the future.

Press Articles

SentiScan Launches Enhanced Features to Revolutionize Market Sentiment Analysis: FOR IMMEDIATE RELEASE
Date: 2025-01-26

SentiScan, the premier sentiment analysis solution for market research, is thrilled to announce a comprehensive upgrade to its platform, introducing innovative features designed to empower marketers and analysts with real-time insights into consumer attitudes across social media and online platforms. By leveraging cutting-edge AI and natural language processing, SentiScan continues to set the standard for actionable intelligence that enhances audience engagement and optimizes marketing strategies.

The new features include the highly anticipated InsightPulse, which provides predictive analytics on emerging trends based on historical sentiment data. This functionality enables businesses to proactively engage with their audiences before significant shifts occur, enhancing strategic capabilities in a competitive landscape.

"The landscape of market research is evolving rapidly, and we aim to stay ahead of the curve by offering tools that not only provide insights but also anticipate future trends," said Dr. Emily Grant, Chief Technology Officer at SentiScan. "InsightPulse is a game-changer for our users, allowing them to harness the power of predictive analytics to make informed decisions and drive engagement effectively."

In conjunction with InsightPulse, the platform will also introduce the Competitor Radar module, equipping users with the ability to monitor competitor sentiment and activity in real-time. By tracking brand mentions and analyzing sentiments related to competitor products, SentiScan facilitates a deeper understanding of the competitive landscape, thus allowing brands to adjust their strategies effectively.

Another significant enhancement—a visual feature called Sentiment360—aggregates sentiment data across multiple channels into a unified dashboard. This provides users with a comprehensive view of brand sentiment evolution across platforms, allowing for a more collaborative approach to marketing and strategy development.

"With SentiScan, we are not just providing data; we are transforming the way our users interact with that data," added James Lewis, CEO of SentiScan. "The enhancements we've made will allow our users to make faster, more effective decisions, ultimately driving growth and improving customer satisfaction."

Additionally, SentiScan is proud to introduce an interactive feedback feature, Feedback Loop, which enables users to generate real-time polls and surveys directly from the software. This tool promotes immediate audience engagement, allowing brands to adapt quickly to consumer feedback and enhance campaign effectiveness.

The full suite of enhanced features will be available to all current and new SentiScan users starting February 15, 2025. By integrating advanced insights and streamlining strategic planning, SentiScan is committed to helping marketers boost their campaigns and achieve measurable results.

For more information about SentiScan and the latest features, please visit www.sentiscan.com or contact:

Jessica Parker
Public Relations Manager
SentiScan
Email: press@sentiscan.com
Phone: (555) 123-4567

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About SentiScan:
SentiScan is a cutting-edge market research software leading the way in sentiment analysis. With a unique combination of AI technology and intuitive design, SentiScan provides invaluable insights that allow businesses to thrive in an ever-changing market environment.

SentiScan Expands Product Capabilities with Real-Time Sentiment Tracking: FOR IMMEDIATE RELEASE
Date: 2025-01-26

SentiScan, the leading sentiment analysis platform, is excited to announce a major expansion of its product capabilities, featuring real-time tracking of consumer sentiment with enhanced analytics. This update will enable marketers and analysts to stay more connected with their audience while making well-informed decisions based on precise data.

Designed specifically for market research analysts, digital marketers, and brand managers, the new enhancements will provide tools that accurately track and analyze consumer sentiment across social media platforms and online channels. With these refined capabilities, businesses can identify trends, analyze competition, and strengthen their market strategies continuously.

"We believe that actionable insights drive actionable strategies, and that’s why we’ve incorporated advanced analytics and real-time tracking into our arsenal," stated Maria Thompson, Head of Product Development at SentiScan. "These upgrades will allow users to not only observe sentiment changes but also understand the underlying reasons behind those shifts, facilitating deeper engagement with their target audience."

Among the standout features is the introduction of Sentiment Drift Analysis, which monitors fluctuations in consumer sentiment over time, allowing users to detect subtle shifts that may indicate emerging trends, issues, or new opportunities.

Alongside the new analytics features, SentiScan is launching an upgraded user interface that improves the overall user experience, providing a clear and engaging journey through the platform. This UI update will simplify navigation, making it easier to access essential tools and insights quickly.

"Our goal is to ensure that our users can access the insights they need readily and with ease," remarked Sam Green, Customer Experience Officer at SentiScan. "We are committed to creating a platform that is friendly to use while delivering powerful analytics that significantly enhance marketing efforts."

These new features will be available for all existing and new customers starting March 1, 2025, as part of SentiScan's commitment to continuous development and excellence in market intelligence.

For additional information about the new advancements in SentiScan, please check www.sentiscan.com or reach out to:

Leah Morgan
Marketing Communications Director
SentiScan
Email: media@sentiscan.com
Phone: (555) 987-6543

END

About SentiScan:
SentiScan is an innovative market research solution that leverages advanced technology to provide real-time insights into consumer sentiment. Powered by artificial intelligence and natural language processing, SentiScan helps businesses navigate the complexities of market intelligence and stay competitive in a fast-paced digital world.

SentiScan Introduces AI-Powered Features to Enhance User Engagement: FOR IMMEDIATE RELEASE
Date: 2025-01-26

SentiScan is proud to unveil a suite of AI-powered features designed to revolutionize how marketers engage with consumers. These groundbreaking enhancements are focused on delivering personalized insights, adaptive strategies, and real-time feedback, ensuring that users are equipped with the tools needed to succeed in today's competitive landscape.

Among the key AI-driven features is the Actionable Insight Recommendations tool, which analyzes market trends and consumer behavior to provide tailor-made suggestions for users. This innovative functionality empowers marketers to implement data-driven campaigns that resonate more effectively with their target audience.

"Our new AI features address a critical need in the market for personalized, actionable insights that can be swiftly implemented into marketing strategies," said Dr. Alan Cheng, Chief Data Scientist at SentiScan. "We are combining sophisticated algorithms with user-friendly interfaces, resulting in a platform that helps brands achieve higher engagement and better outcomes."

In addition, SentiScan will introduce Audience Sentiment Analysis and Audience Segmentation Tools, allowing marketers to gain deeper insights into how different consumer segments respond to various campaigns. By understanding sentiment on a granular level, brands can craft messages that spark interest and convert engagement into sales.

These enhancements will be launched on April 10, 2025, following extensive testing and user feedback. Each feature is being developed with an emphasis on user experience, ensuring that businesses can access valuable insights quickly and leverage them effectively.

“For us, understanding the voice of the consumer has never been so vital,” commented Rebecca Hall, Head of Marketing at SentiScan. “With these new capabilities, businesses can not only understand their audience better but also respond in ways that build loyalty and drive growth.”

To learn more about these AI features and how they can benefit your business, visit www.sentiscan.com or contact:

Michael Adams
Media Relations Officer
SentiScan
Email: inquiries@sentiscan.com
Phone: (555) 654-3210

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About SentiScan:
SentiScan specializes in providing advanced sentiment analysis solutions tailored for the evolving needs of businesses. This cutting-edge platform equips organizations with real-time insights to leverage consumer sentiment and optimize marketing strategies for improved engagement and success.

Create products with ease

Product Details

Personas

Insightful Ivy

Strategic Sam

Innovative Isla

Product Ideas

Product Features

Trend Forecaster

Requirements

Real-time Data Processing

Sentiment Trend Prediction

Intuitive Dashboard Visualization

Alerts for Sentiment Shifts

Competitor Benchmarking

Sentiment Shift Alerts

Requirements

Real-time Notification System

Customizable Alert Settings

Sentiment Analysis Dashboard

Predictive Sentiment Metrics

Integration with Third-Party Tools

Scenario Simulator

Requirements

Dynamic Variable Adjustment

Scenario Visualization Dashboard

Custom Scenario Save and Load

Integrated Alerts for Sentiment Changes

Comparative Benchmarking Tool

Historical Insight Comparisons

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Side-by-Side Trend Analysis

Dynamic Filtering Options

Automated Insight Alerts

Exportable Comparison Reports

Interactive Data Visualization Tools

User Role Customization

Consumer Sentiment Heatmaps

Requirements

Interactive Heatmap Visualization

Sentiment Change Alerts

Demographic Segmentation Filters

Comparative Analysis Tool

Exportable Reports

Actionable Insight Recommendations

Requirements

Real-time Sentiment Analysis

Predictive Analytics Integration

User-friendly Dashboard

Actionable Insights Alerts

Competitive Benchmarking Features

Competitive Trend Benchmarking

Requirements

Real-time Competitive Sentiment Analysis

Historical Trend Comparison

Automated Reporting Alerts

Competitor Sentiment Comparison Tool

Sentiment Insights Dashboard

Channel Performance Insights

Requirements

Sentiment Trend Analysis

Channel Comparison Dashboard

Automated Alerts for Sentiment Changes

Platform-Specific Reporting

Sentiment Visualization Tools

Customizable Reporting

Requirements

Dynamic Metric Selection

Drag-and-Drop Report Builder

Variety of Visualization Options

Automated Report Scheduling

Customizable Report Templates

Sentiment Drift Analysis

Requirements

Real-time Sentiment Monitoring

Historical Sentiment Trends Visualization

Sentiment Drift Alert System

Competitive Sentiment Benchmarking

Sentiment Anomaly Detection