Hotel guest experience platform

Guestify

Every Guest Heard, Every Stay Better

Guestify empowers independent hotel managers to collect instant, emoji-based guest feedback—regardless of language—via a playful, mobile app with automatic real-time translation. Managers spot and resolve issues on the spot, boosting guest satisfaction, minimizing negative reviews, and turning diverse feedback into more personalized stays that drive loyal, repeat bookings.

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Guestify

Product Details

Explore this AI-generated product idea in detail. Each aspect has been thoughtfully created to inspire your next venture.

Vision & Mission

Vision
To empower every hotel worldwide to create unforgettable, personalized guest experiences by truly understanding every voice in real time.
Long Term Goal
By 2028, empower 10,000 independent hotels worldwide to increase repeat bookings by 25% by transforming real-time multilingual guest feedback into personalized, unforgettable hospitality experiences.
Impact
Boosts actionable guest feedback submissions by 60% and reduces negative reviews by 30% for independent hotel managers within six months, enabling rapid resolution of guest issues across languages and driving a measurable increase in repeat bookings from diverse international travelers.

Problem & Solution

Problem Statement
Independent hotel managers miss critical guest feedback due to language barriers and slow, text-heavy surveys; existing tools lack real-time translation and accessible formats, resulting in unresolved issues, poor reviews, and lost repeat business from diverse international guests.
Solution Overview
Guestify’s mobile app captures instant, emoji-based feedback from every hotel guest and auto-translates responses in real time, empowering managers to spot issues and resolve complaints quickly—removing language barriers and missed signals that lead to negative reviews and lost repeat bookings.

Details & Audience

Description
Guestify lets hotel managers gather instant, emoji-based feedback from every guest, no matter the language. Independent hoteliers receive real-time, actionable insights to resolve issues and boost guest satisfaction. The playful mobile app’s standout feature—automatic, real-time translation—ensures every voice is understood, helping managers turn diverse feedback into memorable, personalized experiences that drive repeat bookings and better reviews.
Target Audience
Independent hotel managers (30-55) eager to boost guest satisfaction and resolve multilingual feedback instantly.
Inspiration
One rainy afternoon in a cozy Lisbon guesthouse, I watched the owner struggle to decipher a handwritten note from a Japanese guest—her face falling as she realized an unresolved complaint had led to a scathing online review. That single moment of language confusion inspired Guestify: an instant emoji feedback app with real-time translation so no guest voice—and no opportunity to improve—is ever lost again.

User Personas

Detailed profiles of the target users who would benefit most from this product.

A

Agile Anna

- 32-year-old boutique hotel owner-operator - MBA in hospitality management graduate - $150K annual personal income - Urban seaside location, 20-room property

Background

After leading events at a luxury resort, Anna bought a boutique property at 29. Early tech experiments taught her that prompt guest engagement drives repeat stays.

Needs & Pain Points

Needs

1. Instant alerts for guest dissatisfaction signals 2. Clear visual data to adjust services quickly 3. Multilingual support for diverse guest communication

Pain Points

1. Missing silent complaints leads to negative reviews 2. Overloaded dashboards obscure urgent issues 3. Manual translations slow down response time

Psychographics

- Thrill-seeker who embraces rapid feedback loops - Values agility over long-term pondering - Motivated by instant guest delight

Channels

1. Mobile push (instant alerts) 2. WhatsApp group (team chat) 3. Instagram Stories (guest showcase) 4. Email summary (daily insights) 5. LinkedIn articles (industry trends)

S

Social Sam

- 28-year-old marketing coordinator - B.A. in communications - Oversees a 50-room city hotel - $45K annual salary

Background

After boosting an Airbnb’s social presence, Sam was hired by a boutique chain. He learned that genuine guest stories drive higher engagement than stock images.

Needs & Pain Points

Needs

1. Quick export of top emoji moments 2. Shareable visuals for social media campaigns 3. Insights into trending guest sentiments

Pain Points

1. Delayed feedback misses peak virality moments 2. Static reports lack engaging visuals 3. Language barriers dilute guest voice

Psychographics

- Seeks authentic stories over polished ads - Obsessed with viral social media trends - Values community engagement and peer validation

Channels

1. Instagram Stories (rapid snapshots) 2. TikTok (viral clips) 3. Twitter threads (guest highlights) 4. Canva templates (visual design) 5. Buffer scheduler (campaign planning)

A

Analytical Arjun

- 38-year-old data analyst - Master’s in hospitality analytics - Manages feedback for 100+ rooms - $80K annual professional salary

Background

Starting as a front-desk clerk, Arjun earned a reputation for spotting service gaps in guest comments. Advanced analytics training led him to quantify feedback for operational improvements.

Needs & Pain Points

Needs

1. Granular time-series emoji sentiment breakdown 2. Customizable dashboards for cross-property comparisons 3. Automated alerts for statistical anomalies

Pain Points

1. Raw data overloads obscure actionable insights 2. Limited timeframe filters hinder trend spotting 3. Inflexible export formats disrupt reporting

Psychographics

- Relentlessly curious about underlying data trends - Believes metrics drive smarter staffing decisions - Prefers structured reports over ad-hoc insights - Values accuracy above flashy visuals

Channels

1. Tableau integration (real-time visuals) 2. Slack alerts (metric notifications) 3. Email CSV exports (raw data) 4. Google Data Studio (report sharing) 5. Microsoft PowerBI (deep analysis)

O

Offsite Olivia

- 45-year-old regional hotel portfolio manager - MBA in international hospitality - Oversees 5 boutique properties - $120K annual corporate salary

Background

Having managed a luxury resort group, Olivia now coordinates remote teams across time zones. Early experience with miscommunication inspired her embrace of instant translation tools.

Needs & Pain Points

Needs

1. Unified dashboard for all property feedback 2. Instant multilingual summaries for remote teams 3. Mobile alerts for on-the-go monitoring

Pain Points

1. Location-specific issues slip through communication cracks 2. Translation delays create resolution bottlenecks 3. Juggling multiple dashboards wastes precious time

Psychographics

- Craves concise insights over lengthy narratives - Prioritizes consistency across diverse locations - Trusts data-driven remote collaboration - Seeks autonomy with oversight capabilities

Channels

1. Mobile app (real-time monitoring) 2. Zoom calls (team alignments) 3. Email digests (end-of-day summaries) 4. Slack channels (instant discussions) 5. Trello boards (task assignments)

E

Eco Ethan

- 35-year-old eco-resort director - Bachelor’s in environmental science - Runs 30-room green-certified lodge - $70K annual net profit allocation

Background

Raised on a family farm, Ethan championed sustainability at resorts early on. He launched composting and solar projects after guest feedback praised eco efforts.

Needs & Pain Points

Needs

1. Feedback stamps on sustainability features 2. Real-time eco-initiative sentiment tracking 3. Benchmarking against eco-lodge standards

Pain Points

1. Microscopic green details get overlooked 2. Hard to correlate feedback with eco efforts 3. Generic reports ignore sustainability specifics

Psychographics

- Passionate about sustainable hospitality practices - Believes guests reward green initiatives - Motivated by environmental impact metrics - Seeks genuine guest eco-insights

Channels

1. Mobile app (eco tags) 2. Email alerts (sustainability feedback) 3. Tripadvisor Green Leaders (reviews) 4. LinkedIn groups (eco hospitality) 5. Industry forums (best practices)

Product Features

Key capabilities that make this product valuable to its target users.

PriorityPulse

Automatically categorizes incoming emoji feedback by sentiment severity, ensuring that urgent issues—like multiple sad or angry emojis—are flagged and delivered first. This helps staff prioritize critical guest concerns and address them before they escalate, boosting satisfaction and preventing negative reviews.

Requirements

Sentiment Analysis Engine Integration
"As a hotel manager, I want Guestify to automatically analyze guest emojis to identify critical negative feedback so that I can address issues promptly before they escalate."
Description

Integrate a machine learning-based sentiment analysis engine capable of interpreting emoji feedback to determine sentiment severity, categorize feedback by emotional tone, and seamlessly integrate with Guestify’s backend for real-time processing.

Acceptance Criteria
Real-time Sentiment Classification
Given a guest submits a single emoji feedback (e.g., 😊), when the sentiment engine processes the feedback, then the system must return the correct sentiment label “Positive” within 200ms.
Severity Flagging for Multiple Negative Emojis
Given a guest submits feedback containing three or more sad or angry emojis (e.g., 😢😠😢), when the sentiment engine analyzes the feedback, then the feedback must be flagged as “High Severity” and routed to the urgent issues queue.
Accurate Emoji Interpretation Across Languages
Given a guest uses emojis and text in any language, when the sentiment engine processes the feedback, then it must correctly translate and categorize the overall sentiment with at least 90% accuracy compared to a human-annotated benchmark.
Backend Integration for Prioritization
Given a sentiment label and severity are produced by the engine, when the system calls the backend API, then the feedback record must be updated with the sentiment data and priority flag, and the API response must return a 2xx status code without errors.
Performance Under High Load
Given 500 simultaneous feedback submissions, when processed by the sentiment engine, then the average processing time per feedback must remain below 300ms and zero feedback processing failures occur.
Emoji Severity Scoring
"As a Guestify system user, I want each emoji in guest feedback to be scored by severity so that urgent concerns like multiple sad or angry emojis are escalated first."
Description

Develop an algorithm that assigns severity scores to individual emojis based on their sentiment weight, allowing the system to quantify feedback intensity and prioritize messages with high-severity scores.

Acceptance Criteria
Single Emoji Severity Assignment
Given a single emoji from the guest feedback when processed by the algorithm then it must assign a severity score that matches the sentiment weight defined in the approved emoji-sentiment mapping table.
Multiple Emojis Combined Severity Calculation
Given a feedback message containing multiple emojis when processed then the algorithm must calculate a combined severity score using the defined aggregation method (e.g., average or maximum) and ensure the result falls within the expected range of 0–100.
Threshold-Based Alert Trigger
Given an incoming feedback with a computed severity score when the score equals or exceeds the critical threshold (e.g., 80) then the system must flag the feedback as “urgent” and generate an alert for staff prioritization within 1 second.
Real-time Feedback Prioritization
Given a stream of incoming feedback items when the severity scores are computed then the system must sort and display the feedback in descending order of severity in the staff dashboard, updating the order within 2 seconds of receiving new input.
Edge Case: Unrecognized Emoji Handling
Given an input that includes an unrecognized or unsupported emoji when processed then the algorithm must assign a default neutral severity score (e.g., 50), log the unrecognized emoji event, and continue processing without errors.
Real-Time Priority Queue
"As a front desk staff member, I want a live queue that lists the most severe feedback at the top so that I can address the worst issues first."
Description

Create a real-time queue management system that orders incoming feedback based on severity scores, ensuring that high-priority items are surfaced immediately to staff dashboards and notification systems.

Acceptance Criteria
High-Severity Feedback Surfacing
Given a guest submits feedback containing three or more sad or angry emojis, When the system processes the feedback, Then it assigns the highest severity score and places the feedback item at the top of the real-time queue on the staff dashboard within 2 seconds of receipt.
Mixed-Sentiment Feedback Ordering
Given multiple feedback items with different severity scores arriving within a one-minute window, When the system orders the queue, Then it sorts items in descending order of severity and, for items with equal scores, by most recent timestamp first.
Live Dashboard Update
Given the real-time queue is displayed on the staff dashboard, When a new feedback item with higher severity is received, Then the dashboard automatically refreshes within 5 seconds without manual intervention to reflect the updated queue order.
Priority Notification Delivery
Given a feedback item reaches a predefined critical severity threshold, When it becomes the top item in the queue, Then the system sends a push notification to all assigned staff devices within 3 seconds, including feedback details and priority level.
Queue State Persistence and Recovery
Given the queue management system restarts or experiences downtime, When the system comes back online, Then it restores the full queue with all existing feedback items and their correct priority order within 60 seconds, without any data loss.
Staff Notification Alerts
"As a support staff member, I want to receive instant alerts for high-severity feedback so that I can respond swiftly and improve guest satisfaction."
Description

Implement a notification module that sends instant alerts (push notifications or emails) to designated staff members when feedback crosses a defined severity threshold, enabling immediate response to critical guest concerns.

Acceptance Criteria
Critical Feedback Trigger
Given a feedback submission with severity classified as critical (three or more sad/angry emojis) When the feedback is submitted Then a push notification is sent to all designated staff members within 30 seconds
Email Alert Fallback
Given a staff member has disabled push notifications When critical feedback is received Then an email alert is sent to the staff member within one minute
Custom Threshold Configuration
Given the hotel manager updates the severity threshold to a custom value When new feedback meets or exceeds the configured threshold Then notifications are sent according to the custom threshold settings
Notification Acknowledgement
Given staff receive a notification When a staff member acknowledges the alert Then the system logs the acknowledgement timestamp and suppresses further alerts for that feedback ID
Multiple Staff Routing
Given multiple staff roles are designated for alerts When a critical feedback event occurs Then notifications are sent only to staff members with the specified roles and to no others
Dashboard Severity Filters
"As a hotel manager, I want to filter feedback on my dashboard by severity so that I can focus on the most pressing guest concerns."
Description

Enhance the feedback dashboard with filters and views that allow staff to sort and view feedback by severity level, date, and status, improving visibility into critical issues and overall feedback trends.

Acceptance Criteria
Filter by Severity Level
Given the staff member is on the feedback dashboard When they select the severity filter and choose 'Critical' Then only feedback entries labeled with 'Critical' severity are displayed
Filter by Date Range
Given the staff member is on the feedback dashboard When they set a start date of 2025-07-01 and an end date of 2025-07-30 Then only feedback entries submitted between these dates are displayed
Filter by Feedback Status
Given the staff member is on the feedback dashboard When they select the feedback status filter and choose 'Pending' Then only feedback entries marked as 'Pending' are displayed
Combined Filters Application
Given the staff member is on the feedback dashboard When they apply the severity filter set to 'High' and the date range filter set to last 7 days Then only feedback entries with 'High' severity from the last 7 days are displayed
Persistent Filter Settings Across Sessions
Given the staff member applies filters on the feedback dashboard and logs out When they log back in within 24 hours on the same device Then the previously applied filters are automatically re-applied
Feedback Resolution Tracking
"As a hotel operations manager, I want to track the lifecycle of critical feedback from alert to resolution so that I can measure response effectiveness and accountability."
Description

Introduce functionality to track the resolution status of flagged feedback items, including timestamps for when issues were flagged, assigned, and resolved, providing a complete audit trail and performance metrics.

Acceptance Criteria
Flagging Feedback Item Timeline Recording
Given a guest feedback item is flagged by a manager, when the flag action is completed, then the system shall store a timestamp and user ID for the flag event in the feedback record.
Assigning Feedback Items to Staff
Given a flagged feedback item, when a manager or supervisor assigns the item to a staff member, then the system shall record the assignment timestamp and assignee details.
Resolving Feedback Items
Given an assigned feedback item, when a staff member marks the item as resolved, then the system shall capture a resolution timestamp and update the status to “Resolved.”
Audit Trail Data Accuracy
Given any feedback item, when viewing its history, then the system shall display flagging, assignment, and resolution events in chronological order with accurate timestamps and user details.
Performance Metrics Reporting
Given resolved feedback items over a selectable time period, when generating performance reports, then the system shall calculate and display average time from flagging to resolution and total number of resolved items.

TaskRouter

Intelligently assigns feedback alerts to the most relevant team member based on role, shift, and location. By ensuring that the right person receives the notification, hotels can guarantee swift, specialized responses and reduce resolution times.

Requirements

Role and Shift Configuration
"As a product administrator, I want to configure team member roles, shifts, and locations so that feedback alerts are routed only to the appropriate and available staff."
Description

Allow administrators to define and manage team member profiles with associated roles (e.g., front desk, maintenance, housekeeping), working shifts (start and end times), and location or zone assignments within the hotel. This integrates with the existing employee scheduling system, supports creation, editing, and deactivation of user profiles, and ensures TaskRouter has accurate availability and qualification data for routing decisions.

Acceptance Criteria
Create Team Member Profile
Given an administrator is on the Role and Shift Configuration page When the administrator enters a unique name, selects a valid role, defines shift start and end times within operational hours, assigns at least one location or zone, and clicks Save Then a new team member profile is created, displayed in the profile list with all entered details, and an acknowledgment message is shown
Edit Team Member Role and Shift
Given an existing team member profile is listed When the administrator updates the role, modifies shift start and end times without overlapping existing shifts, and clicks Save Then the profile reflects the updated role and shift times, and a confirmation message is displayed
Deactivate Team Member Profile
Given an active team member profile When the administrator selects Deactivate and confirms the action Then the profile status changes to inactive, the profile is marked accordingly in the UI, and the user is excluded from TaskRouter assignments
Assign Location Zone to User
Given an administrator is configuring a team member profile When the administrator selects multiple zones or locations from the list and saves the profile Then the assigned locations are displayed in the profile details and used by TaskRouter for accurate alert assignment
Sync with Employee Scheduling System
Given the scheduling system integration is configured When a profile is created or updated Then the changes are sent to the external scheduling API in real time, with a success response logged and no errors reported
Rule-Based Routing Engine
"As a hotel manager, I want feedback alerts automatically routed based on staff availability, role, and location so that each issue is handled swiftly by the right team member."
Description

Implement a dynamic routing engine that evaluates feedback alerts against configurable rules—such as staff role, current shift, location proximity, and alert priority—to determine the best recipient. Include fallback mechanisms if no direct match is found, round-robin distribution for equally qualified staff, and escalation paths for high-priority alerts to ensure timely resolution.

Acceptance Criteria
Direct Match Routing to Eligible Staff
Given a feedback alert with metadata matching a staff member’s role, current shift, and location proximity, when the alert is received, then the system routes the alert to that staff member within 2 seconds.
Fallback Assignment When No Direct Match
Given a feedback alert with no staff matching role, shift, and location rules, when the engine executes routing, then it assigns the alert to a predefined fallback user group.
Round-Robin Distribution Among Equally Qualified Staff
Given multiple staff that equally satisfy routing rules, when a new alert arrives, then the alert is assigned to the next staff member in the round-robin sequence.
High-Priority Alert Escalation
Given a feedback alert flagged as high priority, when no staff member acknowledges within 1 minute, then the system escalates the alert to the duty manager and sends notifications via SMS and email.
Rule Configuration Updates Reflection
Given an administrator updates routing rules in the configuration, when the changes are saved, then subsequent alerts are routed according to the updated rules without requiring a system restart.
Real-Time Notification Delivery
"As a frontline staff member, I want to receive immediate notifications on my device when a new task is assigned so that I can respond to guest feedback without delay."
Description

Provide instant delivery of assignment notifications via push notifications in the mobile app, SMS, and email. Ensure reliable delivery with retries, delivery confirmation tracking, and offline handling—queuing messages until devices reconnect—to guarantee staff are alerted immediately when a feedback alert is assigned.

Acceptance Criteria
Push Notification on Assignment
Given a feedback alert is assigned to a staff member When the assignment occurs Then a push notification is delivered to the mobile app within 5 seconds and a delivery log entry is created
SMS Notification with Retry
Given the staff member’s phone number is valid When the initial SMS notification fails Then the system retries delivery up to 3 times at 1-minute intervals and records each attempt’s outcome
Email Notification Confirmation
Given an assignment notification is sent via email When the mail server acknowledges receipt Then the system records a delivery confirmation within 10 minutes
Offline Notification Queuing
Given the mobile device is offline When a push notification is triggered Then the notification is queued on the server and delivered within 30 seconds of the device reconnecting
Multi-Channel Delivery Consistency
Given push, SMS, and email channels are enabled for notifications When an assignment occurs Then each channel sends the notification and logs delivery status within 60 seconds
Staff Availability and Load Balancing
"As an operations manager, I want tasks evenly distributed among available staff and automatically reassigned when unacknowledged so that no alerts go unaddressed and workloads remain balanced."
Description

Continuously monitor staff responses, current workload, and acknowledgment times to balance task distribution. Automatically reassign tasks if a staff member does not acknowledge within a configured SLA window, and redistribute new alerts to ensure even workload and prevent task backlog or staff overload.

Acceptance Criteria
Real-Time Workload Monitoring
Given staff workloads are tracked continuously When the system calculates response times and current task counts Then the workload dashboard updates in real time and flags imbalances exceeding 20% of average workload
SLA-Based Task Reassignment
Given a task is assigned to a staff member When the staff member fails to acknowledge the task within the configured SLA window Then the task is automatically reassigned to the next available staff member with the lowest current workload
Even Distribution of New Alerts
Given multiple new feedback alerts arrive simultaneously When the system assigns these new alerts Then each staff member receives no more than one task above the team’s average task count and tasks are balanced within a 10% variance
Manual Override After Overload Detection
Given a staff member’s assigned task count exceeds the predefined maximum When the system detects the overload condition Then the system prompts the shift manager with a recommendation for task redistribution and allows manual reassignment
Escalation Notification for Unassigned Tasks
Given tasks remain unassigned or unacknowledged after the SLA expiry and no staff are available When the system cannot reassign tasks automatically Then an escalation notification is sent to the hotel administrator and logged for audit purposes
Assignment Dashboard and Analytics
"As a hotel manager, I want to view assignment statistics and performance metrics in a dashboard so that I can identify trends, optimize staff allocation, and improve response times."
Description

Offer a real-time dashboard that displays current task assignments, response and resolution times, SLA compliance rates, and assignment counts per staff member. Include visual analytics—such as heatmaps of high-feedback areas and trend charts—to help managers identify bottlenecks, measure performance, and optimize staffing and routing rules over time.

Acceptance Criteria
Viewing Real-Time Task Assignment Overview
Given the manager is logged into the Assignment Dashboard, When they navigate to 'Real-Time Assignments', Then the dashboard displays a list of all active feedback tasks with assigned staff member, location, and assignment timestamp, and it refreshes automatically every 30 seconds.
Monitoring Response and Resolution Times
Given the manager selects a date range filter, When the filter is applied, Then the dashboard displays the average response time and average resolution time for feedback tasks within the selected period, updating in real time and allowing export as CSV.
SLA Compliance Rate Reporting
Given an SLA threshold is configured, When the manager views the SLA Compliance section, Then the dashboard shows the percentage of tasks meeting the SLA for today, this week, and this month, and highlights any violations in red.
Heatmap Visualization of High-Feedback Areas
Given feedback tasks are geo-tagged by location, When the manager toggles the 'Heatmap' view, Then the dashboard overlays a color-coded heatmap on the hotel floor plan indicating high, medium, and low feedback density areas.
Trend Chart Analysis for Assignment Counts
Given the manager selects a staff member or 'All Staff' and a time interval (daily, weekly, monthly), When the selection is made, Then the dashboard displays a trend chart showing the number of task assignments over the chosen period, with tooltips showing exact counts per interval.

PulseDigest

Generates a customizable end-of-shift summary report of all emoji alerts, highlighting trends, resolved tickets, and pending issues. This concise digest empowers managers to review daily performance, allocate resources efficiently, and identify training opportunities.

Requirements

Digest Generation Engine
"As a hotel manager, I want the system to automatically compile all emoji alerts into a single end-of-shift report so that I can quickly review performance without manual data aggregation."
Description

The system shall aggregate all emoji-based alerts recorded during a manager’s shift and compile them into a concise summary report at the end of the shift. The report will include totals of each emoji type, timestamps, source locations, and key performance metrics presented in a visually coherent format. This automated engine eliminates manual compilation, ensures consistency, and delivers immediate insights into guest feedback.

Acceptance Criteria
End-of-Shift Digest Initialization
Given a manager's shift has ended or the manager manually requests a digest report, when the system receives the trigger, then the digest generation engine starts compiling data within 30 seconds.
Emoji Alert Aggregation Accuracy
Given multiple emoji-based guest alerts recorded during a shift, when the digest generation engine processes the data, then it aggregates alerts by emoji type, providing correct total counts for each emoji.
Inclusion of Timestamps and Source Locations
Given aggregated emoji alerts, when the digest is compiled, then the report lists the earliest and latest timestamps along with the respective hotel location for each alert type.
Key Performance Metrics Presentation
Given the compiled digest, when the report is displayed, then it includes calculated key performance metrics (e.g., average response time, resolution rate) formatted in charts or tables following the UI guidelines.
Digest Report Delivery and Accessibility
Given the generated report, when the digest is complete, then the system sends a notification to the manager's mobile app and makes the report available in the PulseDigest dashboard, accessible within 1 minute of generation.
Customizable Report Template
"As a hotel manager, I want to customize the layout and content of my end-of-shift digest so that the report aligns with my property's reporting standards and priorities."
Description

The application shall allow managers to define and customize the structure and content of their end-of-shift digest. Options will include selecting which metrics to display, customizing section order, adding property branding elements, and choosing visualization styles such as bar charts or pie charts. This customization ensures that each manager receives a report tailored to their operational standards and preferences.

Acceptance Criteria
Selecting Metrics for the Digest
Given a manager is on the Report Template customization page, When they select one or more metrics from the metrics list, Then those metrics appear in the real-time preview and are included in the final end-of-shift digest in the correct order.
Reordering Report Sections
Given a manager has at least two sections in their template, When they drag and drop a section to a new position, Then the section order updates immediately in the preview and saves in the template configuration.
Adding Property Branding Elements
Given a manager uploads a logo and selects brand colors, When they apply these elements to the template, Then the preview displays the logo at the header and charts/text use the selected colors in the final report.
Choosing Visualization Styles
Given a manager is customizing data visualization, When they select a style (bar chart or pie chart) for a metric, Then the preview updates to show that metric with the chosen chart type and maintains readability.
Saving and Applying Custom Templates
Given a manager has configured metrics, order, branding, and visualizations, When they click 'Save Template', Then the template is stored under their account and can be selected as the default for future end-of-shift digests.
Trend Analysis Module
"As a hotel manager, I want to see trend analyses of guest feedback to identify recurring issues or positive patterns so that I can make informed resource allocation decisions."
Description

The system shall analyze collected emoji alert data over the shift period to detect patterns and trends. It will highlight recurring issues, positive feedback clusters, and sentiment shifts, presenting these insights through charts and summary indicators. This analytical module enables managers to identify operational hotspots and evolving guest satisfaction trends for proactive decision-making.

Acceptance Criteria
Recurring Issue Detection
Given a dataset of emoji alerts for an entire shift containing at least three identical negative emoji types, when the trend analysis runs, then the system highlights this issue as recurring in the summary report.
Positive Feedback Cluster Identification
Given multiple positive emoji alerts across different service categories, when the analysis is complete, then the system clusters these feedback types and displays the top three positive categories with their respective percentages.
Sentiment Shift Tracking
Given sentiment distribution data at the start and end of a shift, when the trend module processes the data, then any sentiment shift greater than 10% is flagged and displayed in the summary indicators.
Trend Chart Visualization
Given processed trend data, when rendering charts in the end-of-shift digest, then the charts display accurate labels, data points, and adapt layout correctly for both desktop and mobile views.
Data Filtering by Time Interval
Given full-shift emoji data, when a manager applies a time interval filter (e.g., specific hour range), then the trend analysis updates to reflect only the alerts within that interval.
Ticket Resolution Tracking
"As a hotel manager, I want the digest to indicate which alerts have been resolved and which are still pending so that I can follow up on unresolved issues promptly."
Description

The digest must clearly indicate which emoji alerts have been resolved during the shift and which remain pending. It will retrieve real-time ticket statuses from the issue management system, annotate resolved items with resolution timestamps, and list unaddressed issues for immediate follow-up. This tracking fosters accountability and ensures no guest concern is overlooked.

Acceptance Criteria
Shift Digest Generation with Resolved and Pending Tickets
Given a completed shift, when the end-of-shift summary is generated, then it must list all emoji alerts categorized into ‘Resolved’ and ‘Pending’ sections.
Real-time Status Retrieval from Issue Management System
Given active emoji alerts during a shift, when generating the digest, then the system retrieves each ticket’s current status via the issue management API and displays the real-time state in the report.
Highlighting Resolved Alerts with Timestamps
Given resolved tickets, when included in the digest, then each resolved alert must display its resolution timestamp in the format ‘YYYY-MM-DD HH:MM’ next to the alert description.
Listing Unaddressed Issues for Immediate Follow-up
Given unresolved alerts at shift end, when generating the summary, then all pending issues are listed under a ‘Pending’ section sorted by alert receipt time.
Handling API Retrieval Failures
Given an API failure during status retrieval, when generating the digest, then any statuses that cannot be retrieved are marked as ‘Unknown’ and an error flag is included next to those alerts.
Schedule Digest Delivery
"As a hotel manager, I want the digest report to be automatically sent to my email or in-app at the end of each shift so that I don't need to generate it manually."
Description

The system shall support automated scheduling of digest reports at configurable times, such as nightly at the end of each shift. Delivery methods will include in-app notifications, email distribution to specified recipients, and optional SMS alerts. Automated scheduling removes the need for manual initiation and guarantees timely report delivery to all stakeholders.

Acceptance Criteria
Scheduled Nightly Email Delivery
Given a manager configures the digest to run nightly at 11:59 PM, when the scheduled time arrives, then the system automatically generates the digest report and sends it via email to all specified recipients without manual intervention.
Email Distribution to Specified Recipients
Given multiple email addresses are entered in the recipient list, when the digest is generated, then each specified recipient receives the complete digest report in their inbox within five minutes of generation.
SMS Alert for High-Priority Pending Issues
Given a manager enables SMS alerts for pending high-priority issues, when the digest contains unresolved high-priority tickets, then the system sends an SMS summary of those issues to the configured phone numbers immediately upon digest generation.
In-App Notification on Shift Completion
Given a manager is logged into the mobile app at the scheduled end-of-shift time, when the digest is generated, then the manager receives an in-app push notification with a link to view the full report.
Configurable Schedule Setting Update
Given a manager updates the scheduled delivery time in settings, when the new time is saved successfully, then all subsequent digests follow the updated schedule and no digests are sent at the old time.
Digest Dashboard Integration
"As a hotel manager, I want to view the latest and past digests directly within my dashboard so that I can access summaries without leaving the application."
Description

The digest report interface shall be seamlessly integrated into the Guestify manager dashboard. A dedicated widget will display the most recent digest summary, provide quick access to past reports, and offer direct links to detailed trend views or ticket management pages. This integration ensures managers can access performance summaries without navigating away from their primary workflow.

Acceptance Criteria
Viewing Latest Digest on Dashboard
Given a manager is logged into the Guestify dashboard and a new shift has ended When they view the dashboard Then the Digest widget displays the latest summary report including total emoji alerts, top three trends, number of resolved tickets, and pending issues
Accessing Past Digest Reports
Given the Digest widget is visible on the dashboard When the manager selects the 'View Past Reports' option Then a list of previous digest summaries ordered by date is displayed with clickable entries
Navigating to Detailed Trend Views from Widget
Given the Digest widget shows top trends When the manager clicks on a specific trend Then they are navigated to the detailed trend view page filtered for that trend and date range
Direct Ticket Management Access from Digest
Given the Digest widget lists pending and resolved ticket counts When the manager clicks on the pending count Then they are taken to the ticket management page filtered to show only pending tickets from that shift
Responsive Widget Across Devices
Given a manager accesses the dashboard on desktop or mobile When the dashboard loads Then the Digest widget adapts to screen size, maintaining readability and full functionality

ThresholdTuner

Allows managers to set custom alert thresholds for different emoji combinations, adjusting sensitivity to match property size and service style. By tuning notification settings, hotels can avoid alert overload while still capturing every critical moment.

Requirements

Custom Threshold Configuration
"As a hotel manager, I want to define custom alert thresholds for specific emoji feedback combinations so that I can control notification sensitivity and capture only the most relevant guest feedback."
Description

The system shall provide an intuitive configuration interface allowing hotel managers to define custom alert thresholds for individual emoji combinations. Managers can set numeric thresholds per emoji pair or cluster via sliders, input fields, or presets. This interface integrates with existing notification settings and real-time translation modules to ensure that when guest feedback matches or exceeds specified thresholds, alerts are generated accordingly. Benefits include tailored alert sensitivity, reduced noise, and alignment with property size and service style.

Acceptance Criteria
Setting Threshold Using Slider
Given the manager adjusts the slider for a specific emoji combination, when the slider is moved, then the numeric threshold value updates in real time, the ‘Save’ button becomes enabled, and the selected value persists after saving.
Saving Threshold with Manual Input
Given the manager enters a numeric value into the threshold input field, when the value is within allowed range (1–100), then the interface accepts the input, enables ‘Save’, and displays the updated threshold after saving.
Applying Preset Thresholds
Given the manager selects a predefined preset from the dropdown, when the preset is chosen, then the threshold fields auto-populate with correct values, become editable, and persist after saving.
Triggering Alerts at Threshold
Given guest feedback accumulates matching an emoji combination, when the count meets or exceeds the configured threshold, then the system generates an alert notification, includes translated emoji labels, and logs the event.
Suppressing Alerts Below Threshold
Given guest feedback is below the configured threshold for an emoji combination, when counts are below threshold for 24 hours, then no alert is sent, and no log entry for alerts is created.
Real-Time Threshold Impact Preview
"As a hotel manager, I want to see a real-time preview of how my threshold adjustments affect alert volumes so that I can optimize settings without causing alert fatigue."
Description

The feature will display dynamic feedback on expected alert volumes and historical alert implications as managers adjust thresholds. Managers receive visual cues—such as estimated daily alerts count, trend graphs, and risk levels—directly within the threshold tuner interface. This preview helps managers avoid over- or under-notification by providing immediate insight into the operational impact of their threshold settings.

Acceptance Criteria
Real-Time Alert Estimate Update
Given the manager has the threshold tuner open and adjusts the emoji combination threshold slider, when the slider is moved then the estimated daily alerts count updates within 500ms and reflects the new threshold value.
Historical Trend Graph Rendering
Given historical feedback data is available for the past 30 days, when the manager changes the threshold value then the trend graph updates to display historical alert volumes for that threshold with correct data points.
Risk Level Indicator Accuracy
Given the manager adjusts the threshold, when the new threshold is applied then the risk level indicator displays the appropriate level (Low, Medium, High) based on predefined ranges and updates with the correct color-coded visual.
Multiple Emoji Combination Preview
Given the manager selects different emoji combinations, when switching between combinations then the preview panel shows separate estimated alert volumes and trend graphs for each selected combination.
UI Performance Under Rapid Threshold Changes
Given the manager rapidly adjusts thresholds multiple times within 5 seconds, when each change is made then the system processes all changes and updates previews without lag or errors.
Role-Based Threshold Access Control
"As a general manager, I want to restrict threshold configuration access to specific roles so that only authorized personnel can modify alert sensitivity."
Description

Implement role-based permissions controlling which user roles can view, edit, or approve threshold settings. Administrators can assign permissions at the property or group level, ensuring that only authorized staff can adjust sensitivity parameters. Integration with existing user management modules guarantees seamless access control and audit logging of all threshold modifications.

Acceptance Criteria
Administrator Assigning Permissions for Threshold Tuning
Given an administrator with valid credentials When the administrator assigns 'view', 'edit', or 'approve' permissions to a user or group at the property or group level Then the permissions must be persisted in the user management module and reflected in the ThresholdTuner UI for the assigned entities
Property Manager Modifying Threshold Settings
Given a property manager with 'edit' permission When the manager updates the alert threshold for a specific emoji combination and clicks 'Save' Then the new threshold must be applied immediately, a confirmation message displayed, and the updated value stored in the database
Unauthorized Staff Attempting to Access Threshold Settings
Given a staff member without any threshold permissions When the staff member navigates to the ThresholdTuner settings page Then the system must block access, display a 'Permission Denied' message, and log the attempt without exposing any threshold data
Audit Log Records Threshold Modification Events
Given any user with 'edit' or 'approve' permissions When they modify a threshold setting Then an audit log entry must be generated capturing user ID, role, timestamp, property or group context, previous threshold values, and new threshold values
Group-Level Threshold Approval Workflow
Given a manager submits a threshold change at the group level requiring approval When the change is submitted Then the system must mark the change as 'Pending Approval', notify designated administrators, and only apply the new threshold after an administrator approves it
Threshold Template Import/Export
"As an operations manager, I want to export and import threshold settings so that I can quickly apply consistent alert configurations across multiple hotel properties."
Description

Enable managers to export current threshold configurations to a shareable template file (e.g., JSON or CSV) and import configurations back into the system. This facilitates rapid replication of settings across multiple properties or restoration of default configurations. The import/export functionality includes validation checks to prevent invalid thresholds and ensures compatibility with future feature updates.

Acceptance Criteria
Export Threshold Configurations as JSON
Given the manager has configured custom emoji thresholds on the ThresholdTuner page When the manager selects “Export Template” and chooses JSON format Then the system downloads a file named “threshold_config_{YYYYMMDD_HHMMSS}.json” containing all current threshold settings in valid JSON schema and file size ≤ 1MB
Export Threshold Configurations as CSV
Given the manager has configured custom emoji thresholds on the ThresholdTuner page When the manager selects “Export Template” and chooses CSV format Then the system downloads a file named “threshold_config_{YYYYMMDD_HHMMSS}.csv” containing all threshold settings as comma-separated values with headers matching field names
Import Valid Threshold Template File
Given the manager has a valid JSON or CSV threshold template file When the manager uploads the file via the “Import Template” option Then the system validates the file schema, updates all threshold settings accordingly, displays a success message, and persists changes to the database
Prevent Import of Invalid Templates
Given the manager attempts to upload a malformed or out-of-range threshold template file When the system detects schema errors or invalid threshold values Then the import is aborted, the system displays specific error messages for each invalid field, and no changes are applied
Maintain Compatibility with Future Updates
Given the manager imports a threshold template created in an earlier software version When the system encounters deprecated or new fields Then the system automatically maps recognized fields, warns about unrecognized or deprecated fields with actionable guidance, and completes the import of compatible settings
Adaptive Threshold Suggestion Engine
"As a hotel manager, I want the system to suggest optimal threshold settings based on past feedback so that I can quickly achieve effective alert sensitivity without manual trial-and-error."
Description

Introduce an AI-driven assistant that analyzes historical guest feedback patterns and suggests optimized threshold settings for different emoji combinations. The engine considers property size, service style, and historical alert response rates to recommend baseline thresholds. Managers can review and accept suggestions or fine-tune them further, streamlining the configuration process and improving alert relevance over time.

Acceptance Criteria
First-Time Configuration
Given the manager has at least 30 days of historical guest feedback data, when they open the Adaptive Threshold Suggestion Engine for the first time, then the system generates and displays optimized baseline thresholds for at least three emoji combinations with accompanying rationale.
Threshold Acceptance
Given optimized threshold suggestions are displayed, when the manager clicks “Accept” on a suggested threshold set, then the selected thresholds are saved, applied to live alerts immediately, and a confirmation message “Settings Updated” is shown.
Threshold Fine-Tuning
Given a suggested threshold set has been applied, when the manager adjusts any individual threshold value, then the updated values override the AI suggestion, are saved persistently, and an audit log entry is created recording the manual adjustment and timestamp.
Low Data Scenario
Given less than 7 days of feedback data available, when the manager accesses the suggestion engine, then the system displays a warning “Insufficient data for optimized suggestions” and disables suggestion functionality until sufficient data is collected.
Continuous Learning
Given thresholds have been applied for at least one week, when new feedback data is ingested, then the engine recalculates optimized thresholds, flags any changes with “Updated on [date]” labels, and notifies the manager via in-app notification.

OmniNotify

Sends real-time alerts across multiple channels—including SMS, email, and team collaboration tools like Slack or Microsoft Teams—ensuring staff never miss important feedback, even when away from their phones. This feature guarantees consistent, on-time responses.

Requirements

Multi-Channel Notification Delivery
"As a hotel manager, I want feedback alerts sent across multiple channels so that my team always sees important guest comments in real time, even if they’re not on one specific platform."
Description

Enable dispatch of guest feedback alerts through SMS, email, Slack, and Microsoft Teams simultaneously, ensuring no critical notification is missed regardless of staff location or preferred communication tool.

Acceptance Criteria
Successful SMS Alert Delivery
Given a guest submits emoji feedback, When the system triggers notifications, Then an SMS is sent to the assigned staff’s mobile number within 5 seconds with the correct feedback details.
Email Notification Received and Displayed
Given a guest submits emoji feedback, When notifications are dispatched, Then an email containing the feedback emoji, guest identifier, and timestamp is received in the staff inbox within 10 seconds.
Slack Channel Group Notification
Given a guest submits emoji feedback, When notifications are dispatched, Then a message is posted to the configured Slack channel with the feedback details and guest context including translation.
Teams Channel Alert Visible
Given a guest submits emoji feedback, When notifications are dispatched, Then an alert appears in Microsoft Teams channel with the emoji feedback, guest identifier, and clickable link to the app.
All Channels Notification Consistency
Given a guest submits emoji feedback, When notifications are dispatched, Then all enabled channels (SMS, email, Slack, Teams) deliver the alert within defined timeframes and contain identical content fields.
Customizable Notification Templates
"As an operations director, I want to tailor notification templates per channel so that messages align with our brand voice and accommodate guests speaking different languages."
Description

Provide a template management interface allowing administrators to customize message content, branding elements, and localization settings for each notification channel, ensuring consistency with the hotel’s tone and multilingual guest base.

Acceptance Criteria
Email Template Branding Update
Given an administrator accesses the template management interface and updates the email header logo, color scheme, and footer text, when they save the changes, then any subsequent email notifications sent use the updated branding elements.
SMS Template Localization
Given an administrator specifies a language-specific SMS template and maps supported languages to corresponding message content, when the system detects a guest’s preferred language, then it sends the SMS notification in that language.
Slack Notification Variable Insertion
Given an administrator configures a Slack message template with placeholders for guest name, feedback emoji, and room number, when the notification is triggered, then the placeholders are correctly replaced with actual guest data in the Slack message.
Template Version Rollback
Given multiple saved versions of a notification template, when an administrator selects a previous version and clicks rollback, then the selected version becomes the active template and is used for all future notifications.
Real-Time Preview of Notification Templates
Given an administrator is editing a notification template, when they click the ‘Preview’ button, then a real-time, channel-specific preview is displayed reflecting current template content, localization, and branding.
Real-Time Alert Trigger Engine
"As a front-desk supervisor, I want the system to trigger alerts immediately upon receiving feedback so that I can address guest concerns right away and improve satisfaction."
Description

Implement a low-latency trigger engine that processes incoming emoji-based feedback instantly and routes alerts to configured channels within seconds, minimizing response time to guest issues.

Acceptance Criteria
Basic Successful Alert Delivery
Given a guest submits emoji feedback and corresponding channels are configured When the alert trigger engine processes the feedback Then alerts are delivered to all configured channels within 2 seconds and a success status is logged
High-Volume Feedback Spike
Given a burst of 500 emoji feedback messages in 10 seconds When the alert trigger engine processes the messages Then alert delivery latency remains under 3 seconds for 99% of messages and no messages are dropped
Network Latency Resilience
Given intermittent network delays of up to 500ms per request When the engine routes alerts Then it retries failed deliveries up to 3 times with exponential backoff and logs any persistent failures
Missing Channel Configuration Handling
Given some alert channels (e.g., SMS) are not configured When feedback is processed Then the engine sends alerts to available channels, skips unconfigured channels, and logs a warning without errors
Simultaneous Multi-Channel Routing
Given multiple channels (SMS, email, Slack) are configured When an alert is triggered Then the engine concurrently sends alerts to all channels within 2 seconds and records individual delivery statuses
Notification Retry and Backoff Mechanism
"As an IT manager, I want the system to retry failed alerts automatically so that notifications reach staff reliably despite temporary connectivity issues."
Description

Design an automated retry system with exponential backoff for failed notifications across any channel, ensuring high delivery reliability even during transient network or service outages.

Acceptance Criteria
Initial Retry Upon Failure
Given a notification attempt fails due to a transient error When the retry mechanism is triggered Then the system retries delivery up to 3 times with delays of 1s, 2s, and 4s respectively
Exponential Backoff Increase
Given successive notification failures When each retry is scheduled Then the delay between retries doubles from the previous interval until reaching the maximum backoff limit of 60 seconds
Maximum Retry Exhaustion
Given all retry attempts have been exhausted When the final retry fails Then the system marks the notification as failed, logs the failure event with error details, and notifies the fallback handler
Recovery After Service Restoration
Given the notification service becomes available after an outage When a queued retry is due Then the system resumes retry attempts according to the exponential backoff schedule without manual intervention
Channel-Specific Retry Policy
Given different notification channels When scheduling retries Then the system applies channel-specific retry counts and backoff settings (e.g., SMS: 5 attempts, email: 3 attempts)
Channel Failover Handling
"As a hotel manager, I want notifications to reroute automatically if one channel is down so that my team stays informed no matter the circumstances."
Description

Establish failover logic that detects channel outages and reroutes alerts to alternative communication methods (e.g., switch from email to SMS) to guarantee delivery when primary channels are unavailable.

Acceptance Criteria
Primary Email Outage Failover
Given the email channel returns an SMTP error when sending an alert, when the system detects the failure, then it retries via SMS within 30 seconds and confirms delivery with an SMS receipt.
SMS Gateway Downtime
Given the SMS gateway responds with HTTP 503 or does not respond within 10 seconds for three consecutive attempts, when the system records these failures, then it reroutes the alert to Slack with identical content.
Simultaneous Channel Outages
Given both email and SMS channels fail, when a notification attempt is made, then the system sends the alert via Microsoft Teams and logs the event with timestamp, channel errors, and retry counts.
Recovery and Channel Restoration
Given the primary email channel becomes available after an outage, when the system successfully sends a test email within five minutes, then it switches back to email for alerts and sends a restoration notice to Slack.
Rate-Limiting and Failover Threshold
Given outbound notification failures exceed five within one minute, when the threshold is reached, then the system pauses retries and sends a high-priority alert across all available channels.
Notification Logging and Audit Trail
"As a compliance officer, I want a detailed audit trail of all notifications so that I can review delivery performance and user responses for quality assurance."
Description

Maintain a comprehensive log of all sent notifications, including timestamps, channels used, delivery status, and user acknowledgments, providing full traceability and analytics for performance monitoring.

Acceptance Criteria
Notification Log Entry Creation
Given a notification is sent, when the delivery process completes, then the system logs an entry with timestamp, notification channel, delivery status, and unique identifier.
Multiple Channel Logging
Given a notification is dispatched through multiple channels, when each channel delivery is attempted, then the system records separate log entries for each channel with accurate channel identifiers and statuses.
User Acknowledgment Recording
Given a user acknowledges a notification through any channel, when the acknowledgment is received, then the system updates the corresponding log entry with the acknowledgment timestamp and user identifier.
Timestamp Integrity
Given a logged notification entry, when reviewing the entry, then the timestamp reflects the exact UTC time of sending or acknowledgment, matching system time to within one second.
Audit Trail Export
Given the audit trail export is initiated, when a date range is specified, then exporting produces a CSV file containing all relevant fields (timestamp, channel, status, user acknowledgment) with no missing entries.

EscalateFlow

Implements a tiered escalation path that automatically escalates unresolved high-priority alerts to supervisors or on-call managers after a defined interval. This ensures no critical issue falls through the cracks, safeguarding guest satisfaction and minimizing operational risk.

Requirements

Priority-Based Alert Triage
"As an operations manager, I want the system to automatically categorize alerts by priority so that I can focus on the most critical guest issues first."
Description

Implement a configurable rule engine that classifies incoming guest feedback alerts into priority tiers based on predefined criteria such as emoji sentiment, source location, and category. This requirement ensures each alert is automatically assessed, labeled, and routed according to its urgency, streamlining response workflows and preventing critical issues from being overlooked.

Acceptance Criteria
High Priority Negative Emoji Feedback
Given a guest feedback alert with negative emoji sentiment is submitted When the rule engine processes the alert Then the alert must be classified as High priority And labeled "Priority: High" And routed to the high-priority queue within 5 seconds
Low Priority Positive Emoji Feedback
Given a guest feedback alert with positive emoji sentiment is submitted When the rule engine processes the alert Then the alert must be classified as Low priority And labeled "Priority: Low" And routed to the low-priority queue
Medium Priority Neutral Emoji Feedback
Given a guest feedback alert with neutral emoji sentiment is submitted When the rule engine processes the alert Then the alert must be classified as Medium priority And labeled "Priority: Medium" And routed to the medium-priority queue
VIP Location Alert Elevation
Given a guest feedback alert originates from a VIP property location And contains any emoji sentiment When the rule engine processes the alert Then the alert’s priority tier must be elevated by one level above its sentiment-based classification
Cleanliness Category High-Priority Triage
Given a guest feedback alert tagged under the "Cleanliness" category with negative emoji sentiment When the rule engine processes the alert Then the alert must be classified as High priority And escalated to the on-call manager within 2 minutes
Escalation Timer Engine
"As a hotel manager, I want alerts that remain unacknowledged beyond a set timeframe to escalate automatically so that no high-priority issue remains unattended."
Description

Develop a robust timer service that tracks the time elapsed since an alert enters a specific priority tier and automatically triggers an escalation event once the configured interval lapses. The engine must support customizable intervals per priority level, handle retries, and ensure timely handoffs to the next escalation tier.

Acceptance Criteria
High-Priority Alert Escalation
Given a new alert is created with priority 'High' and no user acknowledgment occurs within the configured interval, when the interval expires, then an escalation event is sent to the designated supervisor and a log entry is created with the escalation timestamp
Configurable Interval Enforcement
Given an administrator sets a custom escalation interval of X minutes for 'Critical' priority alerts, when an alert of 'Critical' priority is generated, then the system triggers the escalation event exactly X minutes after alert creation without deviation beyond 5 seconds
Retry Logic on Escalation Failure
Given an escalation event fails to deliver due to a transient error, when the system detects the failure, then it retries delivery up to three times with exponential backoff and logs each attempt, ultimately marking as 'Failed' if all retries fail
Independent Priority Level Handling
Given multiple alerts of varying priorities enter the timer engine concurrently, when their respective intervals elapse, then the system triggers separate escalation events for each alert according to its own priority-configured interval without interference
Accurate Escalation Timing
Given an alert is created and system clocks remain synchronized within ±1 second, when the escalation interval lapses, then the escalation event timestamp recorded must fall within ±2 seconds of the expected expiry time
Supervisor Notification Workflow
"As a supervisor, I want to receive timely notifications with full alert context so that I can quickly acknowledge and address critical guest concerns."
Description

Create an integrated notification module that dispatches real-time notifications to designated supervisors when an alert escalates. Notifications should include alert details, guest context, and action links for acknowledgment or resolution, delivered via multiple channels such as in-app push, SMS, and email.

Acceptance Criteria
Immediate Push Notification Dispatch upon Escalation
Given a high-priority alert escalates to the supervisor When the escalation is triggered Then a push notification is delivered to the supervisor’s mobile device within 10 seconds containing the alert ID, guest name, room number, and links to acknowledge or resolve the alert
SMS Notification Dispatch for Unresolved High-Priority Alerts
Given a high-priority alert escalates and the supervisor’s push notifications fail or are disabled When 5 minutes elapse without acknowledgment Then an SMS is sent to the supervisor’s registered phone number containing the alert details and URL-formatted action links
Email Notification with Embedded Action Links
Given any alert escalation event When email notifications are enabled for the supervisor Then an HTML-formatted email is sent within 10 seconds to the supervisor’s email address containing the alert details, guest context, and clickable links to acknowledge or resolve the alert
Supervisor Acknowledgment via Action Links
Given a supervisor receives a notification via any channel When the supervisor clicks the 'Acknowledge' action link Then the system updates the alert status to 'Acknowledged' in the dashboard and stops further escalation notifications
Channel Fallback and Redundancy Handling
Given push and SMS delivery attempts both fail When the final retry attempt is unsuccessful Then the system logs the delivery failures, triggers the configured alternative channel (e.g., automated phone call), and sends an email to the system administrator with failure details
On-Call Fallback Escalation
"As a duty manager, I want alerts that supervisors miss to be escalated to the on-call manager so that guest issues are addressed 24/7."
Description

Implement a fallback mechanism that reroutes unacknowledged escalated alerts to the on-call manager after a secondary interval. The system should reference an on-call schedule, handle conflicts, and ensure alerts reach the correct on-call personnel, minimizing risk and maintaining coverage during off-hours.

Acceptance Criteria
Unacknowledged Alert After Primary and Secondary Intervals
Given an alert is escalated to the supervisor and remains unacknowledged for the configured primary interval, when the secondary interval elapses without acknowledgment, then the system must reroute the alert to the on-call manager defined for the current time slot.
Fallback to On-Call Manager During Off-Hours
Given the time is outside standard business hours and an escalated alert is unacknowledged after the secondary interval, when the fallback mechanism triggers, then the alert is routed to the on-call manager designated for off-hours according to the schedule.
On-Call Schedule Lookup with Available Personnel
Given the fallback mechanism needs to determine the on-call manager, when querying the on-call schedule API for the current time, then the system must retrieve a unique on-call manager ID and contact details with a response time under 200ms.
On-Call Schedule Conflict Handling
Given overlapping on-call shifts exist for a time slot, when the fallback mechanism identifies a conflict, then the system must apply predefined priority rules and select a single on-call manager, logging the decision path in the audit trail.
Escalation Delivery Confirmation and Logging
Given an alert is routed to an on-call manager after fallback, when the notification is successfully delivered via SMS or push notification, then the system must log a delivery timestamp and update the alert status to 'Escalated to On-Call' within 5 seconds.
Escalation Audit Log
"As a hotel manager, I want to review an audit log of all escalation steps so that I can monitor performance and identify process improvements."
Description

Maintain a detailed, immutable audit trail of all escalation events, including timestamps, user actions, priority changes, and notification outcomes. This log should be accessible via the management dashboard, enabling teams to review past escalations, measure response times, and analyze bottlenecks.

Acceptance Criteria
Recording Escalation Initiation
Given a user escalates an alert, when the escalation is submitted, then the system logs an entry with escalation ID, timestamp, user ID, and original priority.
Tracking Priority Change
Given an existing escalation entry, when the priority is updated, then the audit log records the previous and new priority values along with the updater’s user ID and timestamp.
Documenting Notification Delivery
Given an escalation is processed, when notifications are sent, then the log captures each notification’s recipient, delivery status (sent or failed), and timestamp.
Accessing Audit Log via Dashboard
Given a manager accesses the audit log dashboard, when filters for date range, priority, or user are applied, then the system displays matching log entries in chronological order.
Immutable Log Verification
Given an attempt to modify or delete an audit entry, when the action is executed, then the system prevents the change, returns an error, and records the attempt in a separate security log.

TimeFlow Slider

Smoothly navigate the heatmap across customizable time ranges, empowering managers to pinpoint peak problem hours and adjust staffing or services in real time.

Requirements

Custom Time Range Selection
"As a hotel manager, I want to select any custom time range on the heatmap slider so that I can analyze guest feedback patterns during specific hours relevant to my operations."
Description

Enable managers to define arbitrary start and end times for the heatmap slider, using drag handles or input fields. This functionality allows for precise examination of guest feedback patterns within any chosen timeframe, helping to identify trends and issues outside standard time blocks. The component should support both manual entry and interactive slider dragging, validate input ranges, and seamlessly integrate with the heatmap visualization to refresh data accordingly.

Acceptance Criteria
Slider Dragging Adjusts Time Range
Given the manager drags the start and end handles to desired times, when the handles are released, then the heatmap updates to display data within the new time range.
Manual Input of Time Values
Given valid times are entered in the start and end input fields, when the manager confirms the input, then the slider handles reposition to the entered times and the heatmap refreshes accordingly.
Input Validation for Invalid Time Ranges
Given the start time entered is later than the end time, when the manager attempts to apply the range, then an inline error message appears and the apply action is disabled until corrected.
Seamless Integration with Heatmap
Given a valid custom time range is set, when the range is applied, then the heatmap data reloads and displays feedback intensity accurately for the specified interval within two seconds.
Responsive Performance Under Rapid Changes
Given the manager drags slider handles rapidly, when the dragging stops, then the final time range is applied and the heatmap updates only after 500ms of no further dragging, ensuring smooth UI performance.
Predefined Time Interval Shortcuts
"As a hotel manager, I want quick-access buttons for common time intervals so that I can rapidly view standard reporting periods without manual setting the slider."
Description

Provide a set of predefined time interval shortcuts (e.g., last 24 hours, last 7 days, today, yesterday) accessible via buttons adjacent to the slider. These shortcuts allow managers to quickly jump to commonly used timeframes without manually adjusting the slider, improving efficiency when analyzing frequent reporting periods. The solution must update the slider handles and heatmap data instantly upon selection.

Acceptance Criteria
Selecting Last 24 Hours Shortcut
Given the user is viewing the heatmap; When the user clicks the "Last 24 Hours" button; Then the slider handles move to cover the period from now minus 24 hours to now; And the heatmap reloads to show data from that period within 2 seconds.
Selecting Last 7 Days Shortcut
Given the heatmap interface is loaded; When the user clicks the "Last 7 Days" button; Then the slider handles adjust to span the last 7 days from the current timestamp; And the heatmap refreshes to display data for that full week within 2 seconds.
Selecting Today Shortcut
Given the current date is displayed; When the user clicks the "Today" button; Then the slider handles snap to cover the start of today at 00:00 and the current time; And the heatmap updates to show today's data immediately.
Selecting Yesterday Shortcut
Given the heatmap is active; When the user clicks the "Yesterday" button; Then the slider handles move to cover the 24-hour period of the previous calendar day; And the heatmap reloads to present data for that day without delay.
Ensuring Instant Heatmap Update Performance
Given any predefined interval button is selected; When the button action triggers a data fetch; Then the heatmap must render the new data and reposition the slider handles within 2 seconds of selection.
Smooth Slider Animation
"As a hotel manager, I want the heatmap slider transitions to animate smoothly so that I can maintain context while navigating through different time periods."
Description

Implement smooth, real-time animations when sliding between time ranges to enhance visual continuity and user engagement. The animation should interpolate data points fluidly, avoiding abrupt jumps, and complete within 300 milliseconds to balance responsiveness and perceptibility. It must be optimized to run smoothly on both desktop and mobile devices.

Acceptance Criteria
Slider Transition Duration
Given the user drags or clicks the time slider, when the slider moves to a new time range, then the animation completes within 300 milliseconds.
Data Point Interpolation Continuity
Given adjacent time ranges with differing data sets, when the slider animates between them, then intermediate heatmap values are interpolated smoothly without abrupt jumps.
Frame Rate Performance
Given the slider animation is in progress, when observing the animation, then it renders at a minimum of 60 frames per second on desktop and 30 frames per second on mobile devices.
Cross-Device Performance
Given the slider animation is triggered on a supported device, when tested on modern desktop browsers and iOS/Android devices, then the animation remains smooth without dropped frames or stutters.
User Interaction Responsiveness
Given the user initiates a rapid series of slider movements, when moving the slider thumb back and forth, then the system queues animations appropriately and remains responsive without lag.
Loading State Handling
Given data for a newly selected time range is still loading, when the slider animation reaches the target range, then a low-opacity loading overlay appears and is removed once data is fully rendered.
Real-Time Heatmap Data Refresh
"As a hotel manager, I want the heatmap to refresh instantly as I adjust the time slider so that I can see up-to-date feedback insights without manual page reloads."
Description

Ensure that the heatmap visualization updates in real time as the slider is moved, fetching and displaying feedback data dynamically for the current time window. The implementation should minimize latency, with data loading times under 1 second, and include loading indicators when fetching data. It must handle large datasets efficiently to prevent UI freezing or delays.

Acceptance Criteria
Slider Adjusts Time Range
Given the user moves the time slider to a new range, when the slider is released, then the heatmap refreshes to display feedback data for the selected range within 1 second.
Loading Indicator Display
When new data is being fetched, then a visible loading indicator appears and remains until the heatmap render completes.
Handle Large Dataset
Given a large dataset exceeding 10,000 feedback entries, when the slider is moved, then the heatmap loads the new data and updates within 1 second without freezing the UI.
Simulated Network Latency
Given network latency up to 500ms, when the slider is adjusted, then the heatmap refresh completes and displays updated data within 1 second of user input.
Continuous Slider Interaction
When the user continuously drags the slider, then the system cancels any in-flight requests and processes only the latest request, updating the heatmap without lag.
Data Integrity Verification
After multiple slider adjustments, then the heatmap must accurately reflect no duplicate or missing data points for each time range selected.
Peak Hours Highlight
"As a hotel manager, I want the slider to highlight peak problem hours so that I can focus on the times with the most negative feedback and address issues proactively."
Description

Automatically identify and visually highlight the top three hours with the highest density of negative emoji feedback within the selected time range. Highlighted hours should be marked with distinct colors or icons on the slider and in the heatmap legend, helping managers quickly spot critical periods. The feature should recalculate dynamically whenever the time range changes.

Acceptance Criteria
Initial Time Range Selection
Given a full-day time range is selected When the heatmap and slider render Then the top three hours with the highest negative emoji feedback are highlighted with distinct colors or icons
Time Range Adjustment
Given the manager adjusts the start or end time of the range When the slider selection changes Then the system recalculates and updates the three top negative-feedback hours in real time
Heatmap Legend Highlight Consistency
Given highlighted hours appear on the slider When the heatmap legend is displayed Then the same distinct colors or icons are shown next to the corresponding hours in the legend
Handling Ties in Negative Feedback Counts
Given two or more hours share identical negative feedback counts for the top position When determining the top three hours Then the system highlights all tied hours without excluding any beyond three, and logs the tie event
Selection Below Three Hours Range
Given the selected time range covers fewer than three hours When the slider and heatmap render Then all hours in the range are highlighted and no errors occur

PeriodCompare

Overlay two heatmap snapshots (e.g., week-over-week or pre- and post-campaign) to visually compare guest mood trends and evaluate the impact of service changes.

Requirements

Time Period Selector
"As an independent hotel manager, I want to select two different time periods to compare guest mood heatmaps so that I can evaluate the impact of service changes over time."
Description

Allow managers to select two distinct time periods (e.g., week-over-week or pre- and post-campaign) via an intuitive date-range picker, with support for custom ranges up to 90 days. The selector validates that the first period precedes the second and automatically populates the overlay comparison tool with corresponding heatmap data sets. This feature ensures accurate period pairing and seamless integration with existing date controls, enabling timely trend evaluation.

Acceptance Criteria
Valid Custom Range Selection
Given the manager selects two custom date ranges each within 1–90 days When both ranges are valid and non-overlapping Then the date-range picker accepts both ranges and enables the Compare action
Maximum Range Limit Enforcement
Given the manager attempts to select a date range longer than 90 days When the end date exceeds the 90-day limit from the start date Then the picker displays a validation error and disables the Compare action
Start Date Must Precede End Date
Given the manager selects a start date that is after the end date When the selection is made Then the picker shows an error message and prevents setting the invalid range
Automatic Heatmap Data Population
Given two valid periods are selected When the manager confirms the selection Then the overlay comparison tool automatically loads and displays the corresponding heatmap snapshots for both periods
Consistency with Existing Date Controls
Given the date-range picker is presented within the PeriodCompare feature When the manager interacts with it Then its behavior, styling, and date format match the existing date controls in the application
Heatmap Overlay Visualization
"As an independent hotel manager, I want an overlay visualization of two heatmaps so that I can easily identify differences in guest mood patterns across time."
Description

Generate an overlay view of two heatmap snapshots using distinct color gradients and adjustable opacity blending. The visualization aligns grid coordinates precisely, updates in real time, and includes legend annotations to clarify period-specific intensities. Users can switch between overlay, side-by-side, and single-period views, ensuring clear visual differentiation and context preservation for quick sentiment comparison.

Acceptance Criteria
Heatmap Overlay Rendering on Dashboard
Given the user selects two distinct heatmap snapshots and activates the overlay view, when the overlay is displayed then both heatmaps appear on the same grid with distinct color gradients, precise coordinate alignment, adjustable blending opacity, and accompanying legend annotations that match each period’s color scale.
Opacity Slider Adjustment
Given the overlay view is active, when the user moves the opacity slider, then the transparency of the top heatmap layer updates in real time without lag, smoothly blending between the two periods while preserving underlying grid clarity.
Legend Annotation Accuracy
Given the overlay view is displayed, when the user reviews the legend, then each color gradient is labeled with the correct period name and intensity range, and the legend colors correspond exactly to the overlay intensities on the grid.
View Toggle Between Overlay and Side-by-Side
Given any heatmap view, when the user toggles to side-by-side or single-period views, then the display switches instantly, preserving grid alignment and updating legends to reflect the selected view format.
Real-Time Data Synchronization
Given new guest feedback data becomes available for one of the selected periods, when the data update is processed, then the overlay heatmap refreshes automatically within five seconds, maintaining selected opacity and view settings.
Interactive Comparison Controls
"As an independent hotel manager, I want interactive controls to adjust the overlay settings so that I can focus on specific mood changes."
Description

Provide on-map interactive controls—such as opacity sliders, intensity threshold toggles, and emoji-category filters—that update the overlay visualization dynamically. Controls must be touch-friendly for mobile devices and seamlessly integrated into the heatmap interface. This interactivity enables managers to isolate specific mood shifts, focus on positive or negative feedback zones, and customize the comparison view for deeper analysis.

Acceptance Criteria
Adjust Overlay Opacity
Given the heatmap overlay is displayed, when the user drags the opacity slider to a new position, then the overlay’s opacity updates immediately to match the selected percentage without delay.
Toggle Intensity Threshold
Given the intensity threshold toggles are visible, when the user enables or disables a threshold level, then only the heatmap data above or below that threshold appears in the overlay in real-time.
Filter by Emoji Category
Given a list of emoji categories, when the user selects or deselects one or more categories, then the overlay updates to display only the data points corresponding to the selected emoji feedback types.
Combine Multiple Control Adjustments
Given all interactive controls are available, when the user adjusts opacity, toggles thresholds, and filters categories simultaneously, then the overlay reflects all changes concurrently without errors or performance degradation.
Mobile Touch Interaction Usability
Given the interface is displayed on a mobile device, when the user uses touch gestures (tap, swipe, pinch) on the controls, then each control responds accurately and the overlay updates accordingly without misfires.
Inline Statistical Summary
"As an independent hotel manager, I want a statistical summary of mood trends for compared periods so that I can quickly grasp quantitative changes."
Description

Automatically compute and display key metrics for each selected period and their differences, including average sentiment scores, positive vs. negative emoji ratios, and identified hotspots. The summary panel appears alongside the heatmap overlay and refreshes instantly when date ranges or filters change. This quantitative insight helps managers prioritize actions based on measurable shifts.

Acceptance Criteria
Date Range Update Refresh
Given the user selects or modifies either date range in PeriodCompare, when the change is confirmed, then the inline statistical summary panel updates automatically within 1 second to display metrics for both periods and their differences.
Filter Application Update
Given the user applies or removes guest filters (e.g., room type, demographic), when any filter change occurs, then the summary panel recalculates and displays metrics reflecting only the filtered dataset without manual intervention.
Metric Difference Accuracy
Given two periods with predefined guest feedback data, when metrics are computed, then the average sentiment scores, positive vs negative emoji ratios, and hotspot counts must exactly match pre-calculated values and correctly display the numerical deltas.
Summary Panel Visibility
Given the PeriodCompare feature is active, when the heatmap overlay is displayed, then the inline statistical summary panel appears adjacent to the overlay, remains visible at all times, and aligns properly during map interactions.
Real-Time Update Performance
Given any change in date range or filter settings, when the update triggers, then the summary panel refresh completes in under 500 milliseconds to ensure real-time responsiveness.
Exportable Comparison Report
"As an independent hotel manager, I want to export comparison reports so that I can share insights with my team and stakeholders."
Description

Enable export of the overlay heatmap, applied filters, and statistical summary into a branded, high-resolution PDF or image report. The exported report uses a template optimized for presentations and includes metadata such as date ranges and key findings. Users can download or email the report directly from the app, facilitating stakeholder communication and documentation of service performance over time.

Acceptance Criteria
Exporting Branded PDF Report with Heatmap Overlay
Given a manager has selected two heatmap snapshots and applied date range filters, when they initiate a PDF export, then a high-resolution PDF is generated that displays the overlaid heatmaps, includes the selected filters, and presents the date range metadata and branded header and footer; PDF resolution is at least 300 DPI; no visual artifacts or cropping occur.
Downloading Exported Report Directly to Device
Given the PDF export is generated, when the manager clicks the 'Download' button, then the file is saved to the device's default downloads folder with a filename that includes the hotel name, feature name, and date range (e.g., 'Guestify_PeriodCompare_2025-07-01_to_2025-07-07.pdf'); and the download completes without errors and is accessible offline.
Emailing Exported Report via In-App Functionality
Given a generated report is ready, when the manager selects the 'Email Report' option and enters a valid recipient address, then the report is attached to an email draft with a predefined subject line including the report title and date range; the email populates the recipient and opens in the default mail client or in-app email composer; sending the email notifies success or failure to the user.
Exporting Report as High-Resolution PNG Image
Given the manager opts to export the overlay as an image, when the PNG export is initiated, then a high-resolution PNG (minimum 1920×1080 pixels) is generated, including the same overlaid heatmap, applied filters, metadata, and branding; the image opens or downloads correctly without distortion.
Export Performance and Error Handling
Given any export (PDF or image) is requested, when the user triggers the export, then the file generation completes within 10 seconds under normal load conditions; if generation fails or exceeds the timeout, the system displays a clear error message with retry option.

DetailDrilldown

Click any cell to reveal underlying emoji responses, timestamps, guest comments, and auto-translated notes, providing rich context for targeted issue resolution.

Requirements

Cell Interaction Handler
"As a hotel manager, I want to click on a summary cell to open detailed feedback so that I can quickly understand the underlying guest responses and address issues."
Description

Implement an interactive event handler on each data cell within the feedback dashboard that listens for click or tap actions. When triggered, this handler should capture the selected cell’s identifiers and context, then initiate the drilldown workflow. This functionality ensures that managers can seamlessly transition from a high-level summary view to detailed guest feedback with a single, intuitive interaction, enhancing investigative efficiency.

Acceptance Criteria
Cell Click Triggers Drilldown
Given the user is viewing the feedback dashboard, When the user clicks on any data cell, Then the system captures the cell’s identifiers and context and opens the detailed drilldown panel populated with the corresponding emoji responses, timestamps, guest comments, and translations.
Mobile Tap Initiates Drilldown
Given the user is accessing the dashboard on a mobile device, When the user taps on a data cell, Then the system initiates the drilldown workflow and displays the detailed view optimized for touch interaction.
Prevent Duplicate Drilldown on Rapid Clicks
Given the user clicks on a data cell repeatedly within 300ms, When the system processes the first click, Then all subsequent clicks within that timeframe are ignored to prevent multiple drilldown panels opening.
Handle Cells with No Feedback Gracefully
Given a data cell has no underlying feedback entries, When the user clicks the cell, Then the system displays a clear “No detailed feedback available” message without errors or empty UI elements.
Performance of Drilldown Loading
Given the user clicks on a data cell, When the drilldown panel is requested, Then the system loads and renders the full set of underlying feedback data within 2 seconds.
Feedback Data Retrieval Service
"As a hotel manager, I want the system to fetch detailed feedback data for a selected metric so that I can see the full context of guest experiences behind summary statistics."
Description

Develop a backend API endpoint that, given a cell identifier, retrieves all associated emoji responses, timestamps, original guest comments, and auto-translated notes from the database. The service must handle pagination, sorting, and error conditions, returning structured JSON for the UI. This ensures reliable, performant access to detailed feedback data for every drilldown request.

Acceptance Criteria
Retrieve feedback details for a valid cell
Given a valid cell identifier is provided, When the Feedback Data Retrieval Service endpoint is called without pagination parameters, Then the response status is 200 and the JSON body contains an array of objects with emoji responses, timestamps, original guest comments, and auto-translated notes.
Handle pagination for large feedback sets
Given a valid cell identifier with more than 50 feedback entries, When the endpoint is called with page and pageSize query parameters, Then the response includes the correct subset of feedback entries for that page and a totalCount field indicating the total number of entries.
Sort feedback results by timestamp
Given a valid cell identifier, When the endpoint is called with a sort=timestamp&order=asc or order=desc parameter, Then the feedback entries in the JSON response are returned in the specified chronological order.
Manage invalid cell identifier requests
Given an invalid or non-existent cell identifier is provided, When the endpoint is called, Then the response status is 404 and the JSON body contains an error code and descriptive error message indicating that the cell was not found.
Ensure performance under high load
Given a burst of 500 concurrent drilldown requests, When the service processes them, Then each response time remains below 500ms and no requests result in 5xx server errors.
Drilldown UI Panel
"As a hotel manager, I want to view a formatted list of guest responses in a drilldown panel so that I can easily scan and interpret each piece of feedback."
Description

Create a responsive UI component (e.g., modal or side panel) that displays the retrieved feedback details in a clear, scrollable format. The panel should list each entry with emoji icons, timestamps, original comments, and translated text, with options to sort or filter entries. This interface provides a coherent, user-friendly presentation of detailed guest feedback for targeted analysis.

Acceptance Criteria
Feedback Details Display
Given a user clicks on a feedback cell, when the Drilldown UI Panel opens, then the panel displays a scrollable list of feedback entries showing each emoji icon, timestamp, original comment, and translated text.
Sorting Feedback Entries
Given feedback entries are loaded in the panel, when the user selects sort by timestamp ascending or descending, then the feedback list reorders correctly according to the selected sort order.
Filtering by Emoji Type
Given feedback entries contain various emoji reactions, when the user applies a filter for a specific emoji, then only entries with that emoji are displayed in the panel.
Responsive Mobile Layout
Given a user accesses the Drilldown UI Panel on a mobile device, when the panel is rendered, then its layout adapts for small screens with readable text, properly sized icons, and functional scroll, sort, and filter controls.
Translation Accuracy Display
Given original comments in a foreign language accompany emoji feedback, when the panel displays these entries, then each original comment is shown with its correct auto-translated text beneath.
Auto-Translation Display
"As a hotel manager, I want to see translated guest comments alongside the original text so that I can accurately interpret feedback from guests who speak different languages."
Description

Integrate the existing translation engine to show both the original guest comment and its auto-translated version within the drilldown panel. Indicate translation confidence or quality scores when available, and ensure that text wrapping and line breaks maintain readability. This feature bridges language barriers, enabling managers to understand non-native responses without external tools.

Acceptance Criteria
Display Original and Translated Comments
Given a drilldown panel opened for a guest comment in a non-native language When the panel loads Then both the original comment and its auto-translated version are displayed clearly within the panel
Translation Quality Indicator Visible
Given the translation engine provides a confidence score When the translated comment is rendered Then a “Confidence: {score}%” label appears adjacent to the translated text
Maintain Readability with Text Wrapping
Given a guest comment that exceeds the panel width or contains line breaks When the comment is displayed Then text wraps properly, preserves line breaks, and no horizontal scrolling is required
Fallback Display for Translation Errors
Given the translation engine fails or returns a score below the acceptable threshold When the panel attempts to display the translated text Then the panel shows “Translation unavailable” while still displaying the original comment
Ensure Real-Time Translation Performance
Given a drilldown panel is triggered by clicking a cell When the panel opens Then both original and translated comments, along with any confidence scores, load within 500 milliseconds
Real-Time Update Mechanism
"As a hotel manager, I want the drilldown panel to automatically refresh with new feedback so that I can monitor guest satisfaction in real time."
Description

Implement a real-time update or manual refresh capability for the drilldown panel so that new feedback entries arriving during an active session are immediately visible. Use WebSocket or polling strategies to push updates and signal changes. This ensures managers always have the latest guest feedback without needing to exit and re-enter the detail view.

Acceptance Criteria
Live Feedback Streaming Activation
Given a drilldown panel is open and the WebSocket connection is active, When new guest feedback entries are submitted, Then those entries appear in the panel within 2 seconds without manual refresh.
Manual Refresh Trigger Efficiency
Given a drilldown panel is open, When the manager clicks the refresh button, Then the panel retrieves and displays all new feedback entries within 3 seconds and shows a loading indicator.
Reconnection Data Sync
Given a temporary network disconnection during an active session, When connectivity is restored, Then the system performs a full sync and displays any missed feedback entries in the drilldown panel.
High Volume Feedback Handling
Given more than 100 feedback entries arrive within one minute, When entries stream in, Then the drilldown panel batches updates smoothly, remains responsive, and displays all entries accurately.
Session Timeout and Data Refresh
Given the drilldown panel has been idle for 30 minutes, When the manager interacts again (scrolls or clicks), Then the panel automatically fetches and displays the latest feedback entries.
Responsive Design & Accessibility
"As a hotel manager, I want the drilldown interface to work on any device and support accessibility features so that I can use it comfortably and inclusively."
Description

Ensure the drilldown panel and its interactive elements are fully responsive across devices (desktop, tablet, mobile) and comply with accessibility standards (WCAG 2.1). Provide keyboard navigation, ARIA labels for screen readers, and sufficient color contrast. This requirement guarantees that all users, including those with disabilities, can effectively access and use the drilldown feature.

Acceptance Criteria
Desktop Drilldown Responsiveness
Given a browser window width of 1024px or greater, when the user clicks any data cell, then the drilldown panel must fully display within the viewport without horizontal scrolling, maintain correct layout of emojis, timestamps, comments, and translation notes, and ensure all interactive elements are visible and operational.
Tablet Drilldown Responsiveness
Given a browser or device width between 768px and 1023px, when the user clicks any data cell, then the drilldown panel must resize appropriately, adjust layout for touch interactions, and ensure all content and controls are accessible without clipping or overlap.
Mobile Drilldown Responsiveness
Given a mobile viewport width of 767px or less, when the user taps any data cell, then the drilldown panel must open as an overlay or full-screen view, allow vertical scrolling for content overflow, and ensure all interactive elements remain accessible and tappable.
Keyboard Navigation Accessibility
Given the user is navigating via keyboard only, when focusing on the drilldown trigger and pressing Enter or Space, then the panel must open, and all interactive elements within the panel must be reachable via Tab, display a visible focus indicator, and be operable with Enter or Space.
Screen Reader Support
Given a screen reader is active, when the drilldown panel opens and the user navigates its contents, then each element (emojis, timestamps, comments, translation notes) must have appropriate ARIA roles and labels, and the screen reader must announce panel open/close events and element context.
Color Contrast Compliance
Given default and high-contrast display modes, when viewing all text and icons within the drilldown panel, then color contrast ratios must meet WCAG 2.1 AA standards (4.5:1 for normal text, 3:1 for large text) to ensure readability for users with visual impairments.

PriorityHighlight

Automatically flag rooms and hours where sentiment drops below custom thresholds, drawing immediate attention to critical service gaps and streamlining response workflows.

Requirements

Custom Threshold Configuration
"As a hotel manager, I want to set custom sentiment thresholds for different rooms and time periods so that I only receive alerts for significant drops in guest satisfaction relevant to my hotel's standards."
Description

Allow hotel managers to define and adjust sentiment score thresholds for rooms and time intervals, enabling tailored sensitivity to guest feedback. The configuration interface should support applying different thresholds per room type, date range, or service category, ensuring the system flags only the most relevant sentiment drops. Benefits include precise control over alert conditions, reduced false positives, and alignment with individual property standards.

Acceptance Criteria
Configuring Thresholds by Room Type
Given a hotel manager is on the Threshold Configuration page, When they select a specific room type and enter a sentiment score threshold between 1 and 5 and click Save, Then the system stores the threshold for that room type and applies it to subsequent feedback.
Applying Thresholds to Date Ranges
Given a hotel manager defines a start and end date and sets a sentiment threshold for that period, When feedback is received within the date range, Then the system compares the sentiment score to the custom threshold and flags feedback that falls below it during that timeframe.
Setting Category-Specific Thresholds
Given a hotel manager chooses a service category (e.g., housekeeping) and assigns a sentiment threshold, When guest feedback is categorized under that service, Then the system uses the specified threshold to determine whether to flag the feedback.
Editing Existing Threshold Configurations
Given a hotel manager views existing threshold settings, When they modify the threshold value or applicable scope and click Update, Then the system validates the new threshold, saves the changes, and applies them immediately to incoming feedback.
Validation of Threshold Input Values
Given a hotel manager enters non-numeric or out-of-range values for a sentiment threshold, When they attempt to save, Then the system displays an inline error message and prevents saving until a valid value is provided.
Real-Time Sentiment Monitoring
"As a hotel manager, I want the system to continuously monitor guest feedback as it arrives so that I can immediately identify and address service issues before they escalate."
Description

Continuously analyze incoming emoji-based feedback and translate sentiment scores in real time, comparing them against configured thresholds. The system must process each feedback entry instantly, updating sentiment analytics for rooms and hourly segments. This functionality ensures immediate detection of potential service issues and supports proactive problem resolution.

Acceptance Criteria
Instant Feedback Processing
Given a guest submits emoji-based feedback in any language When the feedback is received by the system Then the sentiment score is translated and stored and the real-time sentiment analytics update within 2 seconds of submission
Threshold Breach Alert Generation
Given a configured sentiment threshold for rooms or hourly segments When a newly computed sentiment score falls below the threshold Then the system generates a high-priority alert visible to the manager within 1 minute
Hourly Sentiment Dashboard Update
Given the system clock reaches the top of each hour When the next hourly segment begins Then the sentiment analytics dashboard refreshes and displays the updated sentiment scores for the previous 60-minute period
Room-Level Sentiment Flagging
Given multiple feedback entries for a specific room When the rolling average sentiment for that room drops below its custom threshold Then the room is automatically flagged and highlighted in the room sentiment view
Custom Threshold Configuration
Given a manager updates the custom sentiment thresholds in the settings When the new thresholds are saved Then subsequent real-time sentiment analyses use the updated values without delay or system restart
Alert Visualization Dashboard
"As a hotel manager, I want to see a visual display of rooms and time slots with low guest sentiment so that I can quickly understand where and when service issues are occurring."
Description

Design a dashboard widget that visually highlights rooms and hours where sentiment falls below thresholds. Use clear visual cues—such as color-coded heatmaps, flags, or icons—to draw attention to critical service gaps. The dashboard should display current and historical trends, allowing managers to quickly assess problem areas and prioritize operational responses.

Acceptance Criteria
Real-Time Heatmap Display
Given the manager accesses the dashboard When sentiment data is updated for any room-hour segment Then the heatmap cell for that segment updates its color according to the defined sentiment scale within 5 seconds
Critical Service Gap Flag
Given sentiment for a room during a specific hour falls below the custom threshold When the dashboard is viewed Then a red flag icon appears next to the corresponding room-hour cell
Sentiment Trend Analysis
Given a manager selects a specific room or time range When historical sentiment data is requested Then a line chart displays sentiment trends for the past 7 days with tooltips showing exact timestamps and values
Threshold Adjustment Feedback
Given a manager updates the custom sentiment threshold in settings When the dashboard reloads Then alerts and heatmap colors immediately reflect the new threshold and a confirmation message displays "Threshold updated successfully"
Dashboard Accessibility on Mobile
Given the manager accesses the dashboard via the mobile app When the screen orientation changes or device size varies Then the heatmap, flags, and trend charts adjust layout responsively and remain fully interactive
Automated Alert Notifications
"As a hotel manager, I want to receive immediate notifications when guest sentiment drops below my set threshold so that I can respond to issues in real time."
Description

Implement an automated notification system that sends instant alerts via email, in-app notifications, or mobile push messages when sentiment drops below thresholds. Notifications should include room number, time segment, sentiment score, and a brief summary of feedback. This feature ensures managers are promptly informed, even when away from the dashboard, enabling rapid intervention.

Acceptance Criteria
Threshold Breach Email Alert
Given the sentiment score for a room in a specific time segment falls below the manager-defined threshold, when the event is detected, then the system sends an email within 2 minutes to the manager's email address containing the room number, time segment, sentiment score, and brief summary of feedback.
In-App Notification for On-Duty Manager
Given the manager is logged into the Guestify dashboard, when a sentiment drop occurs, then an in-app notification appears in the notification center within 1 minute displaying room number, time segment, sentiment score, and feedback summary.
Mobile Push Notification Delivery
Given the manager's mobile device is registered for push notifications, when a sentiment alert is triggered, then a push notification is delivered within 30 seconds containing room number, time segment, sentiment score, and feedback summary.
Notification Content Accuracy
Given an alert notification is generated, when it is sent via email, in-app, or push, then the notification includes accurate room number, correct time segment, exact sentiment score, and an automatically translated brief feedback summary with no missing or incorrect fields.
Notification Failure Fallback
Given a notification attempt via the primary channel fails, when the system retries, then it automatically retries delivery up to 2 additional times within 5 minutes and logs the failure, and if still unsuccessful, sends the notification via an alternative channel.
Response Workflow Integration
"As a hotel manager, I want alerts to automatically generate service tasks and assign them to staff so that issues are tracked and resolved systematically."
Description

Integrate alert handling with existing guest service workflows or ticketing systems. Upon alert generation, automatically create a task or ticket, assign it to the appropriate staff member, and track resolution status. Provide links to the original feedback and translation context, facilitating efficient root cause analysis and ensuring accountability in issue resolution.

Acceptance Criteria
Automatic Task Creation on Alert
Given a sentiment threshold breach occurs, when the alert is generated, then a new task must be created in the connected ticketing system with the alert details within 30 seconds.
Task Assignment to Relevant Staff
Given an alert with room and shift context, when the task is created, then it is automatically assigned to the staff member responsible for that room and shift based on predefined staff-role mappings.
Inclusion of Original Feedback and Translation
Given a generated alert, the created task description must contain a direct link to the original feedback entry and include the machine-translated text alongside the original emoji-based feedback.
Resolution Status Synchronization
Given a task created by the alert system, when the staff updates the ticket status to 'Resolved' in the ticketing system, then the alert status in Guestify must update to 'Resolved' and log the timestamp.
Error Handling and Retry Mechanism
Given a failure to create or assign a task due to a system error, when an error occurs, then the system retries the operation up to three times and logs an error if all retries fail, notifying administrators via email.

LiveAlert Grid

Tie real-time push notifications to heatmap thresholds, ensuring that emerging low-mood zones trigger actionable alerts delivered to the right staff member.

Requirements

Threshold Management
"As a hotel manager, I want to configure heatmap threshold levels so that I can customize alert sensitivity to my property's feedback patterns."
Description

Allows hotel managers to define, adjust, and save mood threshold levels on the heatmap grid. The interface enables setting multiple threshold bands (e.g., low, medium, high) with customizable emoji-based scoring values. Integrates with the Guestify backend to persist settings per property and supports real-time updates of threshold changes across the mobile and web dashboards. This requirement ensures that managers can tailor alert sensitivity to their hotel's guest feedback patterns, preventing false positives and enabling timely responses to genuine low-mood zones.

Acceptance Criteria
Initial Threshold Setup
Given the hotel manager opens the Threshold Management screen, When they define three distinct threshold bands with unique emoji scores and labels and click Save, Then the system persists the thresholds in the backend and displays them immediately on the heatmap grid.
Threshold Adjustment and Persistence
Given the hotel manager edits an existing threshold band by changing its emoji score or label, When they click Update, Then the system updates the threshold in the backend, retains previous guest feedback associations, and reflects the changes on both mobile and web dashboards in real time.
Real-time Threshold Update Propagation
Given the hotel manager adjusts threshold levels on one device, When the change is saved, Then all other active instances of the Guestify web and mobile apps receive the updated thresholds within 5 seconds and automatically refresh the heatmap grid without manual reload.
Invalid Threshold Input Handling
Given the hotel manager enters emoji scores outside the allowed range or overlapping values between bands, When they attempt to save, Then the system displays a clear validation error message, highlights the invalid fields, and prevents saving until the input is corrected.
Threshold Band Customization Verification
Given the hotel manager defines custom emojis and descriptive labels for each threshold band, When thresholds are saved, Then the heatmap grid on both mobile and web dashboards accurately uses the custom emojis and labels, and the backend stores the customization settings per property.
Heatmap Data Synchronization
"As a front-desk staff member, I want the heatmap to update instantly with new guest feedback so that I can see emerging low-mood zones in real time."
Description

Implements a real-time data synchronization mechanism that streams current guest feedback sentiment values to the heatmap grid. Utilizes WebSocket connections or push services to update the grid within two seconds of receiving new feedback. Ensures data integrity by handling dropped connections, reconciling missed updates on reconnection, and providing visual indicators during sync lags. This requirement guarantees that the heatmap accurately reflects current guest sentiment and that alerts trigger promptly when thresholds are crossed.

Acceptance Criteria
WebSocket Connection Establishment
Given the heatmap view is opened When the client attempts to connect to the WebSocket endpoint Then the connection must be established within 2 seconds with a 95% success rate
Real-Time Feedback Update
Given new guest feedback sentiment is received When the feedback is streamed through the WebSocket Then the heatmap grid updates the corresponding cell with the correct sentiment value within 2 seconds
Connection Drop and Reconnect
Given the WebSocket connection is interrupted When the client detects the drop Then it must automatically reconnect within 5 seconds and resume updates
Missed Updates Reconciliation
Given the client missed feedback updates during a disconnect When the connection is reestablished Then all missed sentiment changes must be fetched and applied in correct chronological order
Sync Lag Visual Indicator
Given ongoing data synchronization When updates are delayed beyond 2 seconds Then a visual indicator appears on the heatmap signaling a sync lag to the manager
Push Notification Delivery
"As a staff member, I want to receive instant notifications when guest mood drops below a threshold so that I can take immediate action to resolve issues."
Description

Develops a reliable push notification system that sends alerts to designated staff through mobile and web channels whenever heatmap thresholds are breached. Notifications include location, sentiment score, and recommended action text. Integrates with APNs and FCM for mobile, and with in-app toast messages for web. Ensures delivery confirmation and retry logic for failed attempts. This requirement ensures staff receive actionable alerts immediately to address guest issues.

Acceptance Criteria
Mobile Push Notification Received on Threshold Breach
Given a staff member’s mobile device is registered with APNs, When a heatmap threshold breach occurs, Then a push notification containing location, sentiment score, and recommended action is sent via APNs and received on the device within 5 seconds.
Android Push Notification Delivered via FCM
Given a staff member’s Android device is registered with FCM, When a heatmap threshold breach occurs, Then a push notification containing location, sentiment score, and recommended action is sent via FCM, delivered within 5 seconds, and displayed in the device notification tray.
In-App Web Toast Notification Display
Given a staff user is logged into the Guestify web app, When a heatmap threshold breach occurs, Then an in-app toast notification appears in the web interface within 3 seconds displaying location, sentiment score, and recommended action.
Delivery Confirmation and Retry Logic
Given a notification is sent to a registered device, When the initial delivery attempt fails, Then the system retries delivery up to three times at 10-second intervals and logs each attempt, marking the notification as delivered only after a successful attempt or failed after all retries.
Notification Routing to Designated Staff Member
Given multiple staff members are assigned to a location, When a heatmap threshold breach occurs at that location, Then the system sends the notification only to the designated on-duty staff member as defined in the staff assignment settings.
Role-Based Alert Routing
"As a hotel manager, I want alerts to be sent to staff members responsible for specific areas so that issues are addressed by the appropriate team."
Description

Configures rule-based routing of alerts based on staff roles and responsibilities. Allows mapping of hotel zones or issue types to specific user groups (e.g., housekeeping, front desk). Supports fallback routing if primary staff are unavailable. Integrates with the organization's user directory and permission system to fetch roles and availability status. This requirement ensures that alerts reach the right person for swift issue resolution.

Acceptance Criteria
Primary Role Routing for Available Staff
Given a guest mood alert triggers in Zone A mapped to housekeeping, when housekeeping staff with Active status exist, then a push notification is sent to all Active housekeeping users within 30 seconds.
Fallback Routing When Primary Unavailable
Given a guest mood alert triggers in Zone B mapped to front desk, when no front desk staff are Active, then the alert is routed to the fallback role 'Duty Manager' and notifications sent within 30 seconds.
Issue Type to Role Mapping
Given an alert classified as 'Maintenance' type, when maintenance mapping exists for Engineering team, then only users in the Engineering role receive the notification and no other roles are notified.
User Directory Integration for Role and Availability
Given the user directory provides role and availability data, when a staff member's status changes to Inactive, then the routing engine excludes that member from receiving new alerts within 5 minutes.
Real-Time Role Update Propagation
Given a staff role is updated in the organization directory, when the change is detected, then the system updates routing configurations and applies them to new alerts within 1 hour.
Alert Escalation Protocol
"As a hotel manager, I want unacknowledged alerts to escalate automatically so that no guest issue goes unnoticed."
Description

Implements an escalation workflow that re-sends unacknowledged alerts to managers after a configurable timeout period. Tracks acknowledgement status and timestamps each alert event. Provides an escalation chain configuration UI for managers to define secondary contacts and escalation intervals. Integrates with the notification delivery system to enforce escalation rules. This requirement minimizes overlooked alerts and ensures critical issues receive managerial attention.

Acceptance Criteria
Initial Alert Delivery and Acknowledgement
Given a guest satisfaction alert is generated and the primary staff member is online When the alert is sent Then the staff member receives a push notification within 5 seconds And an acknowledgement button is displayed
Escalation After Timeout
Given an alert remains unacknowledged for the configured timeout period When the timeout elapses Then the system automatically re-sends the alert to the next contact in the escalation chain And logs the escalation event with a timestamp
Configuring Escalation Chain
Given a manager accesses the escalation chain UI When they add, remove, or reorder contacts and set escalation intervals Then the changes are saved within 2 seconds And persist after page reload
Notification Delivery Failure Handling
Given the system attempts to send a notification to an escalation contact When the delivery fails Then the system retries according to the notification policy And logs the failure event with a retry count and timestamp
Audit Trail Verification
Given an alert has multiple escalation events When viewing the alert history Then each event displays the correct timestamp, contact name, escalation level, and acknowledgement status in chronological order

SnapshotExport

Export heatmap views as high-resolution images or data files (CSV/PDF) for reporting, presentations, or archival, simplifying stakeholder communication and performance tracking.

Requirements

High-Resolution Image Export
"As a hotel manager, I want to export heatmap views as high-resolution images so that I can include clear, detailed visuals in stakeholder presentations and printed reports."
Description

Enable hotel managers to export current heatmap views as high-resolution image files (e.g., PNG or JPEG) directly from the mobile app. This functionality should capture full-screen heatmap visuals at a minimum resolution of 300 DPI, ensuring clarity when zoomed or printed. The exported images must preserve color gradients, annotations, and scale indicators, and integrate seamlessly with existing share/download workflows within Guestify. This feature allows managers to create visually compelling reports and presentations for stakeholders and marketing purposes, enhancing communication and data-driven decision-making.

Acceptance Criteria
Exporting Heatmap as High-Resolution Image
Given a Guestify user is viewing a heatmap, When they tap the export button and select PNG format, Then the system generates a full-screen PNG image file at a minimum resolution of 300 DPI.
Ensuring JPEG Export Quality
Given a hotel manager selects JPEG format for export, When the download completes, Then the exported JPEG image preserves all original color gradients and annotations without distortion or artifacting.
Validating Resolution Standards
Given an exported image file is generated, When inspecting its properties or metadata, Then the resolution must be confirmed to be at least 300 DPI and the dimensions match the full-screen heatmap view.
Integration with Share/Download Workflow
Given a manager has successfully exported an image, When they choose to share it via email, messaging, or other apps from within Guestify, Then the file is correctly attached and transmitted without loss of image fidelity.
Exporting Scale Indicators and Annotations
Given the heatmap includes scale bars and annotations, When exporting as an image, Then the exported file must include all scale indicators and annotations in their correct positions and sizes.
CSV Data Export
"As a data analyst, I want to download heatmap data as a CSV file so that I can perform custom analyses and integrate with BI tools."
Description

Provide an option to download underlying heatmap data points as CSV files, including coordinates, intensity values, timestamps, and session identifiers. The CSV export should be customizable, allowing selection of date ranges and filter criteria, and must integrate with the app's data export module to ensure consistency with access controls and reporting standards. This feature enables managers and analysts to perform custom data analysis, import into BI tools, and archive raw feedback data for compliance and audit purposes.

Acceptance Criteria
Default CSV Export
Given a user with export permissions When they initiate a CSV export without applying any filters Then the system generates and downloads a CSV file containing all heatmap data points with columns for x-coordinate, y-coordinate, intensity value, timestamp, and session identifier within 30 seconds
CSV Export with Date Range Filter
Given a user selects a start and end date filter When they apply the date range and initiate export Then the CSV file includes only data records whose timestamps fall within the selected date range
CSV Export with Custom Filter Criteria
Given a user configures additional filters (e.g., intensity threshold, specific session IDs) When they apply these filters and initiate export Then the CSV file contains only data points matching all selected filter criteria
Access Control Enforcement on CSV Export
Given a user without export permissions When they attempt to export CSV Then the system denies the request and displays an appropriate 'Access Denied' error message
CSV Format and Compatibility Validation
Given a generated CSV file When opened in common BI tools or spreadsheet software Then the file uses UTF-8 encoding, contains the correct column headers in the expected order, and parses without errors
PDF Report Generation
"As a hotel manager, I want to generate PDF reports of heatmap views and key metrics so that I can easily share polished reports with stakeholders."
Description

Implement functionality to generate comprehensive heatmap reports in PDF format, combining high-resolution heatmap images, summary metrics, and customizable titles/legends. The report template should support adding a hotel logo, date range, and contextual notes. PDFs must adhere to A4 and Letter sizing standards and be optimized for both digital sharing and print. This integration with the reporting module streamlines stakeholder updates and supports consistent branding.

Acceptance Criteria
Hotel Manager Exports Branded PDF Heatmap Report
Given the hotel manager is on the reporting module When the manager initiates PDF report generation Then the exported PDF displays the hotel logo at the top without distortion
Hotel Manager Specifies Date Range in PDF Report
Given the hotel manager selects a start and end date for the heatmap data When the manager generates the PDF report Then the report header includes the exact date range in the format MMM DD, YYYY
Hotel Manager Adds Contextual Notes to Heatmap Report
Given the hotel manager enters custom notes in the notes field When the PDF is generated Then the notes appear below the legend section, preserving line breaks and formatting
PDF Report Includes High-Resolution Heatmap Images and Summary Metrics
Given heatmap data is available When the PDF report is generated Then the heatmap image is at least 300 DPI and summary metrics (response count, average rating) are displayed clearly
Hotel Manager Selects Page Size for PDF Report
Given the hotel manager chooses A4 or Letter as the page size When the PDF is generated Then the PDF dimensions match the selected standard and content is properly scaled
Export Customization Options
"As a hotel manager, I want to customize heatmap export settings (color scheme, date range, annotations) so that the exported outputs meet the needs of different stakeholders and use cases."
Description

Allow users to customize export parameters including color schemes (e.g., thermal, monochrome), annotation layers (guest comments, timestamps), date range filters, and inclusion of legends. The customization interface should be intuitive and integrated into the export dialog, providing real-time previews of selected options. These configurable settings enable managers to tailor exports to specific presentation needs and stakeholder preferences, increasing the utility and relevance of the exported assets.

Acceptance Criteria
Color Scheme Selection
Given the user opens the export dialog and selects the 'Thermal' color scheme, when the real-time preview updates, then the preview displays the correct thermal colors and the final exported file uses the thermal color scheme.
Annotation Layer Toggle
Given the user enables the 'Guest Comments' annotation layer in the export settings, when the export is generated, then the exported image or PDF includes all guest comments displayed at their corresponding heatmap locations.
Date Range Filter Application
Given the user sets the start and end dates in the date range filter, when the real-time preview refreshes, then only data within the selected date range is shown and the exported CSV/PDF contains only that filtered data.
Legend Inclusion
Given the user selects the option to include a legend, when the export is generated, then the exported file contains a correctly formatted legend that matches the heatmap color scheme and annotation symbols.
Real-Time Preview Accuracy
Given the user applies multiple customization options (color scheme, annotation layers, date range, legend), when changes are made, then the real-time preview accurately reflects all selected options and the final export matches the preview exactly.
Scheduled Export Automation
"As a hotel manager, I want to schedule automatic heatmap exports to be sent to my email or cloud storage so that I consistently receive updated reports without manual effort."
Description

Develop a scheduling feature that allows users to automate regular exports of heatmap data and reports at predefined intervals (daily, weekly, monthly). Scheduled exports should support multiple formats (image, CSV, PDF) and delivery methods (email, cloud storage integration). The scheduling configuration must be accessible via the admin panel, with options to manage, edit, or disable schedules. This automation saves time and ensures stakeholders receive up-to-date insights without manual intervention.

Acceptance Criteria
Daily Export Schedule Creation
Given the admin accesses the Scheduled Export page, when they set an export interval to 'Daily' at a specified time and select CSV format, then a scheduled job is saved in the system with daily execution at the specified time and CSV as the output format.
Weekly Email Delivery
Given a weekly schedule configured for PDF heatmap export via email every Monday at 8:00 AM, when the scheduled job runs, then all designated email recipients receive an email with the heatmap PDF attached and a delivery confirmation is logged.
Monthly Cloud Storage Integration
Given a monthly schedule set to export a high-resolution heatmap image on the first day of each month, when the job executes, then the image is uploaded to the configured cloud storage folder with the correct filename and timestamp metadata.
Editing an Existing Schedule
Given an existing export schedule listed in the admin panel, when the admin updates the interval or output format and saves changes, then the updated configuration is persisted, displayed in the schedule list, and the next run time reflects the new settings.
Disabling a Scheduled Export
Given an active scheduled export, when the admin disables the schedule via the admin panel, then the schedule is marked as 'Disabled', no subsequent exports are generated, and the last run timestamp remains unchanged.

SmartFollow Prompts

AI-driven follow-up questions that dynamically adapt to guests’ initial emoji choices, guiding them to provide richer, more meaningful feedback. By analyzing sentiment patterns and guest profiles, it crafts the perfect question to clarify vague responses, boosting insight accuracy and enabling staff to address specific concerns promptly.

Requirements

Dynamic Prompt Generation
"As a hotel manager, I want the system to automatically generate follow-up questions based on guests’ emoji feedback so that I can obtain more detailed insights without manual intervention."
Description

The system uses AI to generate follow-up questions in real-time, analyzing the guest’s initial emoji feedback to craft contextually relevant prompts that encourage richer responses and clarify sentiments.

Acceptance Criteria
Positive Emoji Follow-Up
Given a guest selects a positive emoji, when the system generates a follow-up prompt, then the prompt asks for specific aspects of their positive experience and provides at least two tailored options for elaboration.
Negative Emoji Follow-Up
Given a guest selects a negative emoji, when the system generates a follow-up prompt, then the prompt identifies potential issues and asks for detailed examples of their dissatisfaction in a single open-ended question.
Neutral Emoji Follow-Up
Given a guest selects a neutral emoji, when the system generates a follow-up prompt, then the prompt clarifies whether their experience was average or mixed and offers one follow-up question and one rating-scale option.
Ambiguous Emoji Combination
Given a guest selects multiple emojis with conflicting sentiments, when the system generates a follow-up prompt, then the prompt addresses each sentiment conflict by asking two separate clarifying questions, one per sentiment.
No Emoji Selected
Given a guest submits feedback without selecting an emoji, when the system detects missing emoji input, then the system prompts the guest to choose at least one emoji before proceeding and displays an error message if they attempt to continue without selection.
Sentiment Analysis Integration
"As a product owner, I want accurate sentiment detection for emoji feedback so that follow-up questions are aligned with guests’ true emotions and concerns."
Description

Integrate a sentiment analysis engine capable of detecting nuanced emotional tones from emoji inputs and textual data to ensure follow-up prompts accurately address positive, neutral, or negative feedback contexts.

Acceptance Criteria
Positive Emoji Sentiment Classification
Given a guest selects a positive emoji, when the sentiment analysis engine processes the input, then it must return a sentiment score of ≥ 0.7 and classify the feedback as positive.
Negative Emoji Sentiment Classification
Given a guest selects a negative emoji, when the sentiment analysis engine processes the input, then it must return a sentiment score of ≤ 0.3 and classify the feedback as negative.
Neutral Emoji Sentiment Classification
Given a guest selects a neutral emoji, when the sentiment analysis engine processes the input, then it must return a sentiment score > 0.3 and < 0.7 and classify the feedback as neutral.
Combined Emoji and Text Sentiment Analysis Consistency
Given a guest provides both an emoji and a short text comment, when the sentiment analysis engine processes both inputs, then the combined sentiment classification must align with individual emoji and text sentiment scores within a 10% variance.
Real-time Sentiment-driven Prompt Generation
Given the sentiment classification result, when the engine generates a follow-up prompt, then the prompt must be delivered within 2 seconds and contextually appropriate to the sentiment category (positive, neutral, negative).
Guest Profile Personalization
"As a returning guest, I want prompts that consider my prior preferences so that the feedback feels personalized and meaningful."
Description

Leverage guest profile data—such as previous stays, preferences, and demographics—to tailor follow-up prompts, ensuring questions resonate with individual guests and increase response relevance.

Acceptance Criteria
Returning Guest Preference Prompting
Given a guest with a recorded preference for high-floor rooms, when they select any emoji rating, then the system must ask: 'How satisfied were you with the floor assignment during your recent stay?' in the guest’s preferred language.
Business Traveler Itinerary Insight
Given a guest identified as a business traveler, when they submit an emoji rating, then the follow-up question must inquire: 'Did our Wi-Fi and workspace meet your business needs today?'
Loyalty Member Exclusive Feedback
Given a loyalty member with a history of complimentary breakfast, when they provide an emoji rating, then the system must prompt: 'Was the loyalty member breakfast experience satisfactory?'
First-Time International Guest Translation
Given a first-time international guest with Spanish as their preferred language, when they choose an emoji, then the follow-up question must be displayed in Spanish and ask: '¿Cómo calificaría la limpieza de su habitación?'
Family Guest Amenities Query
Given a guest profile indicating a family stay with children, when they select a neutral or negative emoji, then the prompt must ask: 'Did our children’s play area and family amenities meet your expectations?'
Multi-language Prompt Translation
"As an international guest, I want follow-up questions in my native language so that I can provide feedback accurately without language barriers."
Description

Implement automatic translation for follow-up prompts into guests’ preferred languages, ensuring comprehension and comfort, and support bidirectional translations for guest responses.

Acceptance Criteria
Guest Language Preference Detection
Given a guest has selected a preferred language in their profile, when a follow-up prompt is generated, then the prompt is automatically translated into the guest's preferred language with at least 95% linguistic accuracy.
Real-time Prompt Translation Delivery
Given a guest initiates feedback on the mobile app, when the AI-driven follow-up prompt is ready, then the translated prompt is displayed on the guest’s device within 1 second of generation.
Bidirectional Translation of Guest Responses
Given a guest submits a free-text response in their preferred language, when the response is received by the system, then it is translated into English (or the manager’s interface language) with at least 90% accuracy within 2 seconds.
Translation Fallback Handling
Given a translation request fails due to network or API errors, when the system cannot complete translation, then it displays the original text alongside a clear error notification and logs the failure for support review.
Translation Performance Monitoring
Given translation operations are executed, when reviewing system metrics, then 95% of all prompt and response translations complete within 500ms and overall translation error rate remains below 1%.
Contextual Feedback Threading
"As a hotel staff member, I want to see the sequence of follow-up prompts and responses so that I can understand the full context and evolution of a guest’s feedback."
Description

Maintain conversational context by threading follow-up prompts and guest responses, preventing repetitive questions and enabling managers to track feedback progression over multiple interactions.

Acceptance Criteria
Maintain Thread Continuity Across Sessions
Given a guest has answered an initial prompt and later returns, When the guest reopens the feedback thread, Then the system displays the previous prompts and responses in chronological order within the same thread.
Prevent Duplication of Follow-up Prompts
Given a guest has already responded to a specific follow-up question, When the system generates the next question, Then it ensures not to repeat any previously asked prompt within the same thread.
Full Conversation History Visibility for Managers
Given a manager opens a guest’s feedback thread, When viewing any follow-up interaction, Then the manager can see the complete history of all guest responses and AI-generated prompts in one view.
Context-Driven Prompt Selection
Given the AI analyzes a guest’s previous responses, When crafting the next follow-up question, Then it chooses a question that builds on prior context and avoids irrelevant or contradictory prompts.
Preserve Context After Language Translation
Given a guest provides responses in any language, When the system translates and threads follow-up prompts, Then the original meaning and context are preserved with at least 95% translation accuracy.

PromptFlow Builder

A drag-and-drop interface that lets managers design, test, and deploy custom prompt templates in multiple languages. With reusable blocks for greetings, clarifying questions, and thank-you notes, hotels can tailor the tone and structure to match their brand voice and guest demographics, ensuring more engaging interactions and higher response rates.

Requirements

Drag-and-Drop Flow Designer
"As a hotel manager, I want to visually arrange prompt elements by dragging and dropping them, so that I can design and customize guest feedback flows without coding."
Description

Provide an intuitive visual interface where hotel managers can assemble, rearrange, and configure prompt blocks—such as greetings, questions, and closing messages—using drag-and-drop functionality. This empowers non-technical users to build custom conversation flows quickly, reduces reliance on developer support, and accelerates deployment of brand-aligned feedback prompts.

Acceptance Criteria
Assembling Prompt Blocks
Given the manager is on the flow designer page, When they drag a 'Greeting' block from the block library onto the canvas, Then the block should appear at the drop location and snap into place.
Reordering Prompt Blocks
Given multiple blocks on the canvas, When the manager drags one block above or below another, Then the order of the blocks should update and reflect the new sequence.
Configuring a Prompt Block
Given a block placed on the canvas, When the manager clicks the block to open its configuration panel and edits the text or settings, Then the changes should be saved and immediately reflected on the block.
Saving and Previewing the Flow
Given a completed flow, When the manager clicks the 'Save and Preview' button, Then the system should save the flow, generate a preview of the conversation, and display it in the preview pane.
Handling Invalid Drop Operations
Given the manager attempts to drop a block outside of a valid drop area, When the block is released, Then the block should return to its original position and an error tooltip should display.
Multilingual Template Support
"As a hotel manager, I want to design prompts in various languages with automatic translation, so that I can engage guests from different regions in their native tongue."
Description

Enable creation and editing of prompt templates in multiple languages, automatically integrating real-time translation for each block. This ensures seamless communication with international guests, maintains consistent brand voice across languages, and boosts response rates by presenting prompts in the guest’s preferred language.

Acceptance Criteria
New Multilingual Template Creation
Given the manager selects English, Spanish, and Japanese for a new template, When the manager confirms the language selection, Then the PromptFlow Builder generates separate blocks for each language within 2 seconds, And each block displays the initial English text and its machine-translated version, And the manager can independently edit any block with changes saved automatically.
Editing an Existing Multilingual Block
Given an existing template with English and German blocks, When the manager modifies the German block text, Then the system preserves the original English block, And marks the German block as "Edited", And synchronizes any subsequent re-translation requests without overwriting edits.
Real-Time Translation Accuracy
Given a manager edits the English greeting block, When the manager clicks "Translate", Then the system updates all foreign language blocks with translations achieving at least 95% similarity to professional translation standards, And displays a timestamp indicating when the last translation occurred.
Brand Voice Consistency Across Languages
Given the manager sets a tone profile (e.g., friendly, formal) for the template, When the system generates or updates translated text, Then each language block reflects the selected tone with consistent vocabulary, And no text exceeds the original character limit by more than 10%.
Template Export with Multilingual Content
Given the manager exports a completed template, When the export file is downloaded, Then the file includes all language blocks with correct labels, And the translated text matches the builder preview with no missing or truncated segments.
Reusable Block Library
"As a hotel manager, I want to save and reuse frequently used prompt blocks, so that I can build new feedback flows faster and maintain consistency."
Description

Implement a centralized library where commonly used prompt components—like welcome messages, clarifying questions, and thank-you notes—can be saved, categorized, and reused across multiple templates. This streamlines template creation, ensures consistency in tone and structure, and reduces duplication of effort.

Acceptance Criteria
Create New Reusable Block
Given the manager is on the Reusable Block Library page, When they click 'Add New Block', enter a unique block name, select a category, and input content, Then the system saves the block, displays a success message, and lists the block under the chosen category.
Categorize and Filter Blocks
Given the manager has multiple blocks saved in the library, When they apply a filter by category or tag, Then only blocks matching the selected criteria are displayed in the list.
Search for a Reusable Block
Given the manager has library blocks saved, When they enter a keyword or block name in the search bar and submit, Then the system returns all blocks containing the keyword in their name or content within three seconds.
Edit an Existing Block
Given the manager selects an existing block from the library and clicks 'Edit', When they update the block name, category, or content and save, Then the changes are persisted and reflected immediately in the library list.
Insert Block into Template
Given the manager is building or editing a prompt template, When they open the Reusable Block Library and select a block to insert, Then the chosen block content is inserted at the cursor position in the template editor without formatting errors.
Live Preview and Testing Sandbox
"As a hotel manager, I want to test my custom prompt flows in a sandbox environment, so that I can verify the interaction and translations work as intended before going live."
Description

Provide a real-time preview environment where managers can simulate guest interactions, test conversation logic, and view translations before deployment. This feature helps validate flow correctness, catch errors early, and deliver a polished experience to guests.

Acceptance Criteria
Live Preview Initialization
Given the manager opens the testing sandbox, when they modify or add a prompt block, then the live preview updates within 1 second without requiring a page reload.
Guest Interaction Simulation
Given a simulated guest response in the sandbox, when the manager steps through the conversation flow, then each subsequent prompt and translation appears correctly according to the designed logic.
Multi-language Display
Given a prompt template is created in one language, when the manager selects an alternate language, then the live preview displays both the original and translated versions side by side.
Error Handling in Flow Logic
Given an invalid or incomplete flow configuration, when the manager runs the simulation, then an error message identifies the problematic block and suggests corrective actions.
Performance under Load
Given the manager runs 10 consecutive simulations, when each interaction is executed, then the live preview responds within 1 second for each step with no unexpected errors.
Versioning and Deployment Control
"As a hotel manager, I want to manage versions of my prompt templates and deploy updates selectively, so that I can safely iterate on feedback flows without risking guest experience."
Description

Incorporate version management for prompt templates, allowing managers to save, compare, roll back, and deploy specific versions. This ensures safe updates, auditability of changes, and the ability to revert to a known good configuration if issues arise.

Acceptance Criteria
Creating and saving a new template version
Given a manager has edited an existing prompt template When they click 'Save as new version' Then a new version ID is generated incrementally And the new version appears in the version list with timestamp and author And the content matches the saved edits
Comparing changes between two template versions
Given a manager selects two versions from the version history When they click 'Compare' Then a side-by-side diff view displays the changes highlighting additions, deletions, and modifications
Rolling back to a previous template version
Given a manager identifies an older version in the history When they select 'Rollback to this version' and confirm Then the selected version becomes the active draft And a new version entry is created referencing the rollback action And all subsequent edits apply to this version
Deploying a selected template version to production
Given a manager chooses a version from the version list When they click 'Deploy' Then the selected version becomes live immediately And an indicator marks it as 'Currently Deployed' And guests interacting with the system receive prompts from this deployed version
Viewing version audit history
Given a manager opens the audit log for a prompt template When they view the log Then each entry displays version number, timestamp, author, and change summary in descending chronological order

RealTime Linguist

Automatic, bidirectional translation of guest follow-up answers in over 50 languages, maintaining nuance and context. Guests receive prompts in their native tongue, while managers see instant, accurately translated responses—eliminating language barriers and empowering teams to act swiftly on multilingual feedback without misinterpretation.

Requirements

Automated Language Detection
"As a hotel manager, I want the system to detect the guest’s language automatically so that I don’t need to configure language settings manually and can receive accurate translations immediately."
Description

The system automatically identifies the guest's input language upon message receipt, routing it to the appropriate translation pipeline without user intervention. This enables seamless, hands-free processing for over 50 supported languages, ensuring guests can provide feedback in their native tongue. Integration with existing mobile interfaces and backend services guarantees minimal latency and accurate detection, laying the foundation for instant translation and improved user experience.

Acceptance Criteria
Feedback Submission in Supported Language
Given a guest submits feedback in Spanish, When the message is received by the system, Then the system must detect the language as Spanish with at least 99% accuracy and route it to the Spanish translation pipeline within 200 ms.
Feedback Submission in Multiple Languages
Given a guest’s feedback contains both English and French sentences, When the message is processed, Then the system must identify and label each language segment correctly with at least 95% accuracy before translation.
Feedback Submission with Code-Switching
Given a guest mixes languages mid-sentence (e.g., English and Korean), When the system analyzes the text, Then it must detect each language segment and tag them for appropriate translation with at least 90% segment-level accuracy.
Feedback Submission in Unsupported Language
Given a guest submits feedback in an unsupported language, When the system fails to match it to supported languages, Then it must default to English detection, flag the input as unsupported, and notify the manager within 300 ms.
Simultaneous Feedback from Multiple Guests
Given 100 guests submit feedback simultaneously in different supported languages, When processed in a single batch, Then the system must detect each message’s language with at least 95% accuracy and an average processing time per message under 500 ms.
Bidirectional Translation Engine
"As a guest, I want my responses translated instantly into the manager’s language so that my feedback is understood accurately and addressed quickly."
Description

Implement a robust translation engine that performs real-time, bidirectional translation between guest and manager languages. The engine leverages neural machine translation models optimized for hospitality terminology and slang, preserving tone and intent. It integrates with cloud translation APIs and on-device fallback to maintain performance and reliability, ensuring continuous translation services even under variable network conditions.

Acceptance Criteria
Spanish Guest Feedback Submission
Given a guest submits feedback in Spanish when checking out, the translation engine translates the feedback into English within 2 seconds with at least 95% accuracy measured against a hospitality-optimized BLEU score.
Manager Reply Display to Guest
Given a manager responds in English to feedback, the system translates the response into the guest’s original language within 2 seconds, preserving emojis and tone; if cloud API is unavailable, on-device fallback provides translation within 1 second.
Network Interruption Fallback
Given the network connection drops during translation, the engine automatically switches to on-device translation within 1 second without data loss, and resumes cloud-based translation once the connection is restored.
Hospitality Slang and Idioms Handling
Given feedback includes hospitality-specific slang or idioms in any supported language, the engine accurately translates the meaning and tone into the target language in at least 90% of test cases in a predefined slang validation set.
High-Volume Concurrent Translations
Given 100 simultaneous guest-manager translation sessions, the engine maintains an average translation latency under 500 ms and error rate below 2% during peak usage.
Contextual Nuance Preservation
"As a manager, I want translations to preserve the guest’s tone and intent so that I can interpret feedback correctly and respond appropriately."
Description

Incorporate advanced NLP techniques to maintain context, sentiment, and cultural nuances in translations. This feature analyzes idioms, emojis, and colloquialisms, adjusting translations to retain the guest’s original meaning. It works in tandem with the translation engine to flag ambiguous phrases and provide alternative translations or manager prompts for clarification, reducing misunderstandings and enhancing service quality.

Acceptance Criteria
Real-Time Translation Display
"As a manager, I want to see translations appear in real time as guests type so that I can engage in live, meaningful conversations without delays."
Description

Design the user interface to display translated messages instantly within the mobile app. Incoming guest messages appear alongside original text with a toggle option for managers. The display updates in real time as guests type, enabling live chat-like interactions. UX considerations include smooth scrolling, readability adjustments, and language indicators, ensuring clarity and efficient communication for busy hotel staff.

Acceptance Criteria
Instant Translation Toggle Activation
Given a guest message is displayed in the chat, when the manager enables the translation toggle, then the translated text must replace the original message within 300ms without requiring a manual refresh.
Live Typing Translation Display
Given a guest is typing in their native language, when each character is entered, then the manager’s view must update in real time with the translated character stream within 200ms of input.
Original Text Toggle and Persistence
Given a translated message is displayed, when the manager disables the translation toggle, then the original text must reappear, and the manager’s toggle state persists across screen navigations until changed.
Language Indicator Visibility
Given multiple messages in different languages appear in the chat, then each message must display a language code badge (e.g., “EN”, “FR”) adjacent to the text, updating correctly when translation is toggled.
Smooth Scrolling Under High Message Throughput
Given a rapid influx of translated and original messages, when the manager scrolls through the chat, then message loading must be smooth without frame drops (>55 FPS) and no translation delays.
Translation Quality Feedback Loop
"As a manager, I want to correct mistranslations and provide feedback so that the system improves future translations and adapts to our property’s terminology."
Description

Enable managers to rate translation quality and submit corrections directly within the app. Feedback is collected to train and refine translation models over time. The system tracks correction history, identifies recurring errors, and prioritizes model updates. This continuous improvement loop ensures translation accuracy increases with usage, adapting to hotel-specific vocabulary and guest preferences.

Acceptance Criteria
Manager Submits Translation Correction
Given a manager reviews an automatically translated guest response When the manager rates the translation quality and submits corrected text Then the system saves the rating and correction linked to the original response
Accessing Correction History
Given a manager wants to review past corrections When the manager opens the correction history for a guest response Then the system displays all submitted corrections in chronological order
Flagging Recurring Translation Errors
Given the system aggregates translation corrections When five or more corrections for the same phrase occur within seven days Then the system flags the phrase as a recurring error and sends a notification to the translation admin
Prioritizing Corrections for Model Training
Given a list of flagged recurring errors When the system prepares the next translation model training batch Then it orders corrections by descending frequency and queues them for retraining
Aggregating Quality Ratings on Dashboard
Given managers submit translation quality ratings for multiple languages When the system compiles rating data Then it displays overall accuracy metrics per language on the manager dashboard

QuickTap Clarify

Predefined, one-tap clarification buttons (e.g., “Comfort,” “Cleanliness,” “Service”) presented alongside follow-up prompts, allowing guests to elaborate on their emoji choice with minimal effort. This frictionless micro-survey boosts engagement and ensures granular insights with just a tap, speeding up the feedback loop and improving data quality.

Requirements

Clarification Button Library
"As a guest, I want to tap a clearly labeled button that matches my feedback category so that I can elaborate on my experience without typing."
Description

Develop a predefined library of one-tap clarification buttons (e.g., “Comfort,” “Cleanliness,” “Service”) that can be easily configured and updated by hotel managers. This library should integrate seamlessly with the mobile app UI, allowing for quick selection by guests and ensuring consistency across different properties. The implementation must support categorization, ordering, and localization of buttons.

Acceptance Criteria
Manager Adds New Clarification Buttons
Given the manager is on the Clarification Button Library settings page When they click 'Add Button', enter label 'Comfort', assign category 'Room', and click 'Save' Then the 'Comfort' button appears in the library list under 'Room' category with default ordering.
Guest Selects Clarification Button Post-Emoji Feedback
Given a guest submits an emoji feedback on the mobile app When the Clarification Buttons load Then the predefined buttons 'Comfort','Cleanliness','Service' are displayed beneath the emoji And tapping any button records the selected clarification.
Guest Views Localized Clarification Buttons
Given a guest's mobile app language is set to French When Clarification Buttons render Then all buttons are displayed in French translation matching manager's configured labels.
Manager Reorders Clarification Button Categories
Given the manager is on the Clarification Button Library settings page When they drag and drop the 'Service' category above 'Cleanliness' Then the new order is saved and reflected in the live button preview.
Buttons Update Propagated Across Properties
Given the manager updates the button library at the group level When the sync flag is enabled and the manager clicks 'Propagate to Properties' Then all associated property apps receive the updated button list within 5 minutes.
Dynamic Prompt Rendering
"As a hotel manager, I want guests to see targeted follow-up questions based on their initial feedback so that I can gather meaningful details quickly."
Description

Implement logic to display context-specific follow-up prompts based on the guest’s selected emoji and clarification button. Prompts should be concise, relevant, and optimized for mobile screens, adjusting dynamically to different feedback flows. This ensures guests receive the most pertinent questions to elicit detailed insights with minimal friction.

Acceptance Criteria
Contextual Prompt Display After Emoji Selection
Given the guest taps the “Cleanliness” emoji, When the system processes the selection, Then a follow-up prompt specifically addressing cleanliness appears within 200ms.
Dynamic Clarification Prompt Based on Button Choice
Given the guest taps the “Service” clarification button, When the button state is registered, Then the app displays a concise service-related question without reloading the page.
Responsive Prompt Layout on Various Screen Sizes
Given the app is opened on devices with screen widths ranging from 320px to 768px, When a clarification prompt is rendered, Then it displays fully visible text and buttons without horizontal scrolling.
Optimized Prompt Text Length
Given a follow-up prompt is shown, When measured, Then the prompt text does not exceed 100 characters and remains contextually relevant to the selected emoji and clarification.
Seamless Prompt Transition Without Data Loss
Given the guest changes their emoji selection before submitting feedback, When the new emoji is selected, Then the previously displayed prompt is replaced by the correct prompt for the new selection without retaining old content.
One-Tap Feedback Submission
"As a guest, I want to complete my feedback with just a few taps so that I can share my opinion quickly and effortlessly."
Description

Enable a streamlined feedback flow where guests can select an emoji, choose a clarification button, and submit their feedback in three taps or fewer. The process should minimize load times and visual clutter, providing immediate confirmation once feedback is sent. This encourages higher completion rates and faster feedback loops.

Acceptance Criteria
Real-Time Emoji Response
Given the feedback screen is loaded, when a guest taps an emoji icon, then the tapped emoji is highlighted and clarification options appear within 300ms.
Clarification Button Visibility
Given an emoji has been selected, when the UI renders clarification options, then at least three predefined buttons (Comfort, Cleanliness, Service) are visible without scrolling.
Three-Tap Submission Flow
Given a guest has selected an emoji and a clarification button, when they tap the submit icon, then the feedback is sent successfully and the total taps count does not exceed three.
Visual Confirmation Display
Given feedback is successfully submitted, when submission completes, then a confirmation message is displayed on the feedback screen within 200ms of submission.
Load Time Performance
Given the feedback prompt is invoked, when the screen loads, then all interactive elements (emoji icons and clarification buttons) are fully loaded and tappable within 1 second on a 4G network.
Contextual Translation Engine
"As a hotel manager, I want clarifications translated immediately into my language so that I can understand and act on guest feedback without delay."
Description

Integrate a real-time translation service that automatically translates guest clarifications into the hotel manager’s preferred language. Translations should maintain context and nuance, updating instantly as guests submit their micro-survey responses. This feature ensures language barriers do not impede timely issue resolution.

Acceptance Criteria
Single Input Instant Translation
Given a guest submits a clarification in French, when the manager views the response, then the clarification is translated into English within 2 seconds and retains all original keywords.
Multiple Concurrent Translations
Given multiple guests submit clarifications in different languages simultaneously, when the manager dashboard refreshes, then each clarification is translated into the manager's preferred language within 3 seconds of submission.
Contextual Nuance Preservation
Given a guest uses idiomatic expressions or slang in the clarification, when the translation is displayed, then the translated output preserves equivalent context and nuance with a translation confidence score of at least 90%.
Live UI Update
Given real-time incoming clarifications, when a new translation is ready, then the user interface updates automatically without requiring a page refresh, displaying the translated text immediately.
Translation Failure Fallback
Given the translation service is unavailable or fails to recognize the language, when a clarification cannot be translated, then the original text is displayed with a 'Translation Unavailable' indicator within 1 second of submission.
Analytics Integration Dashboard
"As a hotel manager, I want to see reports on which clarification buttons are used most often so that I can focus on areas needing improvement."
Description

Extend the existing analytics dashboard to include metrics for clarification usage, response rates, and category-specific insights. The dashboard should visualize trends over time, highlight common issues per property, and support exporting reports. This empowers managers to identify areas for improvement and track the impact of interventions.

Acceptance Criteria
Clarification Usage Trends Visualization
Given the manager selects a date range on the analytics dashboard When the system processes clarification usage data Then the dashboard displays a line chart plotting daily counts of clarification taps within the selected period And the chart updates within 2 seconds of range selection
Response Rate Tracking
Given the manager selects a property and date range When the dashboard loads response data Then the dashboard displays the overall and category-specific clarification response rates as percentages And values match backend calculations within a 1% tolerance
Category-Specific Insights Display
Given the manager filters by a clarification category When the filter is applied Then the dashboard lists the top five most frequent free-text follow-up comments for that category, sorted by occurrence count
Property Issue Highlights
Given the manager navigates to the property overview section When data is loaded Then the dashboard highlights the top three recurring clarification categories for the property over the past month, including percentage change from the previous month
Report Export Functionality
Given the manager clicks the 'Export Report' button When export options are displayed Then the manager can select date range and file format (CSV, PDF) And after confirmation, the system generates and downloads the report within 5 seconds

ContextCard Display

A concise, at-a-glance card in the manager dashboard that collates the original emoji, guest’s follow-up text, and auto-translation. ContextCards highlight key sentiment drivers and suggest recommended actions based on the clarified response, equipping staff with all the information they need to resolve issues fast and personalize guest experiences.

Requirements

Real-time Feedback Aggregation
"As a hotel manager, I want live updates of guest feedback so that I can address issues instantly and enhance guest satisfaction."
Description

Develop a backend service that collects and consolidates guest feedback data including the original emoji, follow-up text, and automatic translations, delivering this information to the manager dashboard in real time. Ensure low latency data transfer, error handling for network interruptions, and data consistency so managers receive the freshest feedback immediately.

Acceptance Criteria
Real-time Feedback Delivery
Given a guest submits feedback, when the backend service receives it, then the feedback (emoji, text, translation) appears on the manager dashboard within 2 seconds.
Network Interruption Recovery
Given a brief network interruption occurs during data transmission, when the connection is restored, then the backend service re-sends any unsent feedback without duplication and displays it on the dashboard within 5 seconds.
Data Consistency Verification
Given multiple feedback entries arriving simultaneously, when the backend aggregates them, then the sequence and content of emojis, texts, and translations remain accurate and no entries are lost or reordered incorrectly.
High Load Performance
Given 500 feedback submissions per minute, when the backend processes them, then the average latency for displaying feedback on the dashboard remains below 3 seconds with no errors.
Error Handling and Alerts
Given an internal service error occurs during feedback aggregation, when the error is detected, then the system logs the error, triggers an alert to the operations team, and retries the aggregation up to 3 times automatically.
ContextCard UI Component
"As a dashboard user, I want a clear, at-a-glance card that shows all relevant guest feedback details so that I can quickly understand and act on issues."
Description

Design and implement a modular, responsive UI component for the manager dashboard that displays the ContextCard. The component must present the original emoji, guest text, auto-translation, sentiment drivers, and recommended actions in a clear and visually appealing layout. Ensure accessibility compliance, cross-browser compatibility, and easy integration with the existing dashboard framework.

Acceptance Criteria
Original Feedback Display
Given a ContextCard is rendered, the original emoji must appear at 24×24px; the guest’s follow-up text must display in 14px font, support special characters, truncate after three lines with a hover tooltip for full text; the layout must prevent overlap with adjacent UI elements.
Translation and Sentiment Visibility
Given a ContextCard with auto-translation, the translated text displays directly below the original text in italics; sentiment drivers within the translation are highlighted with underlined text and tooltips; all text meets a minimum contrast ratio of 4.5:1.
Recommended Actions Presentation
Given sentiment analysis results, recommended actions appear at the bottom of the ContextCard as a bulleted list; each action includes an icon and opens a detail modal on click; up to three recommendations are shown, with a “View More” link if additional actions exist.
Responsive Design on Multiple Devices
Given different viewport widths, the ContextCard reflows without horizontal scrolling: in mobile (<640px) elements stack vertically; in tablet (641–1024px) elements display in two columns; in desktop (>1024px) elements display in three columns.
Accessibility Compliance Verification
All ContextCard elements meet WCAG 2.1 AA: text contrast ratio ≥4.5:1; interactive elements are keyboard-navigable with visible focus states; ARIA labels provided for non-text content; screen readers announce emoji, texts, and recommendations accurately.
Sentiment Driver Highlighting
"As a hotel staff member, I want highlighted sentiment drivers within guest comments so that I can quickly pinpoint critical feedback themes."
Description

Integrate sentiment analysis to identify and visually emphasize key drivers of guest sentiment within the follow-up text. Use color coding or icons to distinguish positive, neutral, and negative drivers. Provide tooltips or inline explanations of sentiment cues to help managers interpret the context accurately.

Acceptance Criteria
Highlight Mixed Sentiment Drivers
Given a ContextCard with follow-up text containing both positive and negative sentiment drivers, when the card is rendered, then positive drivers are highlighted in green with a ‘thumbs-up’ icon and negative drivers are highlighted in red with a ‘thumbs-down’ icon.
Positive Driver Visual Emphasis
Given follow-up text with exclusively positive sentiment phrases, when displayed, then all positive drivers are highlighted in green, include a ‘thumbs-up’ icon, and display a tooltip reading ‘Positive sentiment driver’ on hover.
Neutral Driver Visual Emphasis
Given follow-up text with neutral sentiment phrases, when rendered, then neutral drivers are highlighted in grey with an ‘info’ icon and display a tooltip reading ‘Neutral sentiment driver’ on hover.
Negative Driver Tooltip Explanation
Given a highlighted negative sentiment driver, when the manager hovers over the highlight, then a tooltip appears with a concise explanation ‘Negative sentiment driver’ along with an example suggestion for action.
Color Coding Accessibility Compliance
Given the color-coded sentiment highlights, when displayed in both light and dark modes, then all colors maintain a minimum contrast ratio of 4.5:1 in accordance with WCAG 2.1 AA guidelines.
Action Recommendation Engine
"As a hotel manager, I want actionable suggestions tied to guest feedback so that I can resolve issues effectively and personalize guest experiences."
Description

Implement a rules-based recommendation engine that suggests appropriate actions based on the translated feedback and sentiment analysis. Recommendations should be context-aware (e.g., offer a room upgrade for complaints about noise) and customizable by the hotel. Provide an interface to manage and update recommendation rules.

Acceptance Criteria
Noise Complaint Recommendation
Given the sentiment analysis detects a negative sentiment and identifies 'noise' in the translated feedback When the recommendation engine processes the feedback Then it suggests at least one appropriate action such as offering a room upgrade, complimentary earplugs, or relocation to a quieter floor
Positive Dining Feedback Recommendation
Given the feedback contains a positive sentiment with keywords related to breakfast or dining When the engine evaluates the feedback Then it recommends a complimentary breakfast voucher or personalized dining experience upgrade
Temperature Adjustment Recommendation
Given the guest mentions issues with room temperature and a neutral to negative sentiment When the recommendation engine analyzes the sentiment and context Then it suggests actions like sending a maintenance team to adjust the thermostat or offering a portable heater/fan
Connectivity Issue Recommendation
Given the translated feedback indicates frustration with slow or unreliable Wi-Fi When the recommendation engine assesses the complaint Then it recommends solutions such as resetting the router, providing an alternative connection, or offering a Wi-Fi upgrade
Custom Rule Update Interface
Given a hotel manager navigates to the recommendation engine settings When they create, update, or delete a custom rule Then the new rules are saved, validated, and immediately applied to future feedback processing
Dashboard Filtering and Sorting
"As a hotel operations lead, I want to filter and sort feedback cards by priority and date so that I can focus on the most urgent guest issues first."
Description

Add capabilities to filter and sort ContextCards by sentiment level, feedback recency, and action urgency. Enable managers to search by keywords in the guest text and to group feedback by room type or booking period. Ensure filters can be combined and persist across sessions.

Acceptance Criteria
Filtering ContextCards by Sentiment Level
Given the manager selects a sentiment filter (Positive, Neutral, Negative) on the dashboard When the filter is applied Then only ContextCards tagged with the selected sentiment level are displayed
Sorting ContextCards by Feedback Recency
Given the manager chooses to sort ContextCards by recency When the sort option is activated Then ContextCards are ordered from newest to oldest feedback timestamp
Searching Guest Text for Keywords
Given the manager enters a keyword into the search bar When the search is executed Then only ContextCards containing the keyword in the guest’s follow-up text or translation are shown
Grouping Feedback by Room Type
Given the manager selects a room type group filter When the filter is applied Then ContextCards are grouped and displayed under headers for each selected room type
Persistent Filter Settings Across Sessions
Given the manager finishes a session with active filters and sorting When they return to the dashboard in a new session Then their last used filter and sort settings are automatically reapplied
Performance and Load Optimization
"As a system administrator, I want the feedback dashboard to remain responsive under heavy load so that managers can reliably view and act on data."
Description

Optimize the ContextCard feature to handle high volumes of feedback without degrading dashboard performance. Implement lazy loading of cards, efficient caching strategies, and pagination or infinite scroll. Monitor key performance metrics and set up alerts for service degradation.

Acceptance Criteria
Initial Dashboard Load Under High Feedback Volume
Given the system contains 10,000 ContextCards, when the manager opens the dashboard, then the first 20 cards must render within 2 seconds.
Scrolling Through Massive Feedback Cards
Given more than 20 ContextCards are available, when the manager scrolls down, then each subsequent batch of 20 cards must load within 500ms without freezing the UI.
Cache Hit Performance During Repeated Access
Given a manager revisits the dashboard within 5 minutes, when retrieving previously viewed ContextCards, then the data must be served from cache and render within 1 second.
Handling Real-Time Feedback Spikes
Given an influx of 100 new feedback items within one minute, when processing incoming data, then CPU and memory usage must remain below 80% and response times must stay under 2 seconds.
Triggering Alerts on Performance Degradation
Given average API response time exceeds 3 seconds for more than 5 consecutive minutes, when monitoring detects the degradation, then an alert must be sent to DevOps within 1 minute.

PatternPulse

Analyzes long-term emoji patterns to surface the most persistent guest concerns, providing managers with a ranked list of areas requiring attention for strategic improvements.

Requirements

Emoji Trend Analyzer
"As a hotel manager, I want to analyze emoji feedback trends over time so that I can identify persistent guest sentiments and prioritize improvements accordingly."
Description

Develop a component that processes historical guest feedback emojis over customizable time windows, identifying recurring patterns and fluctuations. This functionality should leverage time-series analysis algorithms to detect statistically significant trends and generate insights on emerging or waning guest sentiments. The component must integrate with the existing feedback ingestion pipeline, operate in real time as new data arrives, and support adjustable parameters (e.g., window size, significance threshold). Expected outcomes include clear visualization inputs for the PatternPulse dashboard and accurate detection of long-term sentiment shifts to guide managerial actions.

Acceptance Criteria
30-Day Trend Detection
Given historical guest emoji feedback for the past 30 days, when the analyzer runs with window size set to 30 days and default significance threshold, then it returns a ranked list of emojis whose frequency change is statistically significant (p < 0.05) and includes at least three emerging or waning trends.
Real-Time Data Processing
Given a new batch of emoji feedback is ingested, when the data enters the feedback pipeline, then the trend analyzer updates its time-series calculations and reflects any trend shifts on the PatternPulse dashboard within 5 seconds of ingestion.
Parameter Adjustment for Window Size
Given a user adjusts the window size parameter to 7 days, when the analyzer executes, then output trends must reflect only the last 7 days of feedback, excluding any data older than the specified window.
Significance Threshold Filtering
Given the significance threshold parameter is set to 0.01, when the analyzer evaluates emoji frequency changes, then only trends with p-values below 0.01 are included in the final output list.
Visualization Data Formatting
Given the trend analyzer generates pattern data, when preparing data for the PatternPulse dashboard, then each entry must include emoji identifier, trend direction (rising or falling), significance score, and timestamp in valid JSON format.
Persistent Concern Ranker
"As a hotel manager, I want a ranked list of my most persistent guest concerns so that I can focus on the issues that matter most to long-term satisfaction."
Description

Implement a ranking engine that aggregates detected emoji patterns into a prioritized list of guest concerns. The engine should score each concern based on frequency, persistence across multiple periods, and severity inferred from negative emojis. This ranking must support weighted scoring, allowing product managers to adjust weights for recent trends versus historical persistence. The output is a dynamic, sorted list of top ten concerns that can be consumed by the PatternPulse dashboard and exported for reporting.

Acceptance Criteria
Top Ten Ranked Concerns Display
Given the ranking engine has aggregated emoji feedback, When a manager views the PatternPulse dashboard, Then the system displays a list of the top ten concerns sorted by descending score, including each concern's label, numeric score, and severity indicator.
Weighted Score Adjustment
Given a product manager adjusts weight sliders for recent trends versus historical persistence, When the configuration is saved, Then the ranking engine recalculates scores using the updated weights and refreshes the top ten list within 2 seconds.
Persistence Threshold Filtering
Given a minimum persistence threshold is configured, When the ranking engine processes concern data, Then only concerns persisting across at least three distinct time periods are included in the ranked list.
Severity-Based Scoring
Given negative emojis are mapped to severity levels, When the engine calculates concern scores, Then frequency counts are multiplied by the corresponding severity factor and reflected in the final score for each concern.
Export Ranked Concerns
Given a manager requests an export, When the 'Export CSV' action is triggered, Then the system generates and downloads a CSV file containing the current top ten concerns with fields for concern label, score breakdown, persistence count, and timestamp within 5 seconds.
PatternPulse Dashboard Integration
"As a hotel manager, I want to view long-term emoji patterns and ranked concerns within my dashboard so that I can quickly access strategic insights without context switching."
Description

Extend the existing Guestify dashboard to include a dedicated PatternPulse view. This view must display trend charts, ranked concerns, and drill-down details for each pattern (e.g., time span, associated emoji counts). It should support filtering by date range, property location, and guest segment. The UI components must adhere to Guestify’s design system, ensure responsive layouts for desktop and tablet, and update in real time as new data is processed.

Acceptance Criteria
Display of Emoji Trend Charts for a Selected Date Range
Given a date range is selected When the PatternPulse view loads Then trend charts display accurate emoji counts over time with tooltips on data points
Presentation of Ranked Guest Concerns
Given processed emoji patterns When the PatternPulse view is viewed Then concerns are ranked by frequency in descending order and displayed in a sortable list
Drill-Down Details for Selected Emoji Pattern
Given a ranked concern is selected When drill-down action is triggered Then detailed view shows time span, total emoji counts, and breakdown by date and segment
Filtering Controls Functionality
Given filters for date range, property location, and guest segment When any filter is applied Then the trend charts and ranked concerns update in real time to reflect only the filtered data
Responsive Layout on Desktop and Tablet
Given the PatternPulse view is accessed on desktop or tablet When the viewport size changes Then all UI components adapt to screen size according to the design system with no layout breakages
Automated Alert System
"As a hotel manager, I want to be notified when a new persistent concern emerges so that I can take swift action before issues escalate."
Description

Create a notification service that monitors the ranked concerns list and automatically alerts managers when a concern’s rank crosses predefined thresholds or when an unexpected spike in negative emojis is detected. Alerts should be configurable per property and delivered via email or in-app notifications. The system must allow threshold configuration (e.g., top 3 concerns, rank increase by X positions) and include links to the relevant PatternPulse dashboard view for immediate context.

Acceptance Criteria
Manager Configures Alert Thresholds
Given a manager accesses the Alert Settings page When the manager sets a concern rank threshold to Top 3 and a rank increase threshold to 2 positions Then the system saves the configuration and displays a confirmation message indicating thresholds are active
Alert Triggered on Rank Threshold Crossing
Given a configured threshold of Top 3 concerns When a concern’s rank moves from position 4 to position 3 in the ranked list Then the system generates an alert and records the event in the alert log
Unexpected Spike Alert
Given real-time emoji feedback is monitored continuously When a concern’s negative emoji count increases by more than 50% within one hour Then the system triggers an unexpected spike alert and flags it for review
Alert Delivery via Email
Given an alert has been triggered When the manager has a valid email address configured Then the system sends an email containing the alert details and a direct link to the relevant PatternPulse dashboard view
Alert Delivery via In-App Notification
Given an alert has been triggered When the manager is logged into the mobile or web app Then the system displays an in-app notification with the alert summary and a button linking to the PatternPulse dashboard
Longitudinal Data Export
"As a hotel operations analyst, I want to export long-term sentiment data so that I can perform deeper analysis and share findings with stakeholders."
Description

Provide functionality to export compiled emoji trend data and ranked concerns as CSV or Excel files for offline analysis. The export should include timestamped entries, pattern metrics (e.g., duration, frequency, score), and raw emoji counts. Exports can be requested for specific time frames and filtered by property. The feature must integrate with the existing Guestify export API, ensure data security and compliance, and support scheduled or on-demand exports.

Acceptance Criteria
Manual On-Demand Export for a Specific Property and Time Frame
Given an authenticated hotel manager selects a specific property and defines a start and end date, when they request an export in CSV format, then the system generates a downloadable CSV file containing timestamped entries, pattern metrics (duration, frequency, score), and raw emoji counts limited to the selected property and time frame.
Scheduled Weekly Export via API Integration
Given a hotel manager configures a weekly export schedule via the Guestify export API, when the scheduled time arrives, then the system automatically generates and delivers the requested data file to the designated storage or email address without manual intervention.
Filtered Export with Custom Date Range and Property Selection
Given a manager applies multiple filters including one or more properties and a custom date range, when they initiate an export request, then only the data matching all selected filters is included in the exported file.
Exported File Format and Data Integrity Verification
Given an exported file is received, when opened in a spreadsheet application or parsed programmatically, then it includes correctly formatted headers (timestamp, property, duration, frequency, score, raw_emoji_counts), ISO 8601 timestamps, no missing or corrupted data, and matches the requested file type (CSV or Excel).
Export Security and Compliance Validation
Given an authenticated export request, when the data is transmitted and stored, then the system uses TLS 1.2 or higher for data in transit and encryption at rest standards, and enforces access controls to ensure only authorized users can download or schedule exports.

PainPoint Radar

An interactive overlay highlighting recurring issues by category, time, and location, enabling managers to drill into hotspots and address root causes with precision.

Requirements

Real-Time Data Aggregation
"As a hotel manager, I want the PainPoint Radar to display live-updated guest feedback data so that I can spot and address emerging issues immediately."
Description

The system must continuously collect and process feedback data from multiple channels (emoji responses, manual comments, location tags) in real time, normalize and categorize the input by type and sentiment, and deliver an up-to-the-minute data stream to the PainPoint Radar overlay. This ensures managers always see the latest emerging issues, enabling immediate identification and response to guest concerns as they unfold. The aggregation service will integrate with the existing feedback ingestion API, support high-volume data throughput, and provide a low-latency feed to the visualization layer.

Acceptance Criteria
Continuous Emoji Feedback Ingestion
Given a guest submits an emoji feedback via the mobile app, when the feedback is sent, then the system ingests and stores the feedback within 500ms with its timestamp and guest ID.
Manual Comment Normalization
Given a guest submits a manual text comment in any language, when the comment is processed, then the text is normalized, translated to English, and sentiment-scored with at least 95% translation accuracy.
Location Tag Categorization
Given feedback includes a location tag, when the data is aggregated, then the feedback is correctly categorized by hotel area (e.g., lobby, room, restaurant) with a success rate of 99%.
High-Volume Data Throughput
Given concurrent feedback streams of up to 10,000 events per minute, when the aggregation service processes the data, then no more than 0.1% of events are dropped, and throughput meets the SLA.
Low-Latency Data Delivery
Given processed feedback, when the data is ready for visualization, then the system delivers the up-to-the-minute data to the PainPoint Radar overlay with end-to-end latency under 1 second 95% of the time.
Interactive Map Overlay
"As a hotel manager, I want to view feedback hotspots on an interactive map of my property so that I can quickly understand where issues are occurring."
Description

Build a geospatial overlay on the hotel floor plan that visually represents feedback hotspots by location. The overlay will use heatmap shading and cluster markers to denote the frequency and severity of issues in specific areas (e.g., lobby, pool, rooms). Users can zoom, pan, and click on hotspots to reveal summary metrics and link to detailed feedback entries. This feature will integrate with the mapping module and support responsive performance across devices.

Acceptance Criteria
Display Heatmap on Floor Plan
Given the manager opens the floor plan overlay, when the overlay loads, then a heatmap is rendered on the floor plan with shading intensity accurately representing the frequency of feedback in each area.
Cluster Marker Display and Drill-Down
Given multiple feedback entries in proximity, when the map is viewed at a zoomed-out level, then cluster markers appear with counts, and clicking a cluster zooms in and redistributes markers at a finer granularity.
Hotspot Detail Popup
Given the manager clicks on a hotspot marker, when the click event is triggered, then a popup displays summary metrics (total entries, average severity) and a link to view detailed feedback entries.
Map Navigation Controls
Given the overlay is active, when the user pans or zooms using controls on desktop or pinch-to-zoom on mobile, then the map and overlay respond fluidly (under 200ms latency) and maintain correct alignment with the floor plan.
Performance on Mobile Devices
Given the manager uses a mobile device, when they interact with the overlay, then interactions maintain at least 30 FPS and the initial load time does not exceed 3 seconds on typical network conditions.
Category Drill-Down
"As a hotel manager, I want to filter feedback by category and drill into specific hotspots so that I can focus on the most critical issues."
Description

Enable managers to filter the PainPoint Radar by feedback category (e.g., cleanliness, staff, amenities) and severity level (e.g., positive, neutral, negative). Upon selecting a filter, the overlay updates to highlight only relevant hotspots. Drill-down functionality will allow managers to click on a specific hotspot or time range to view a detailed list of individual feedback entries, complete with timestamp, translation, and guest identifier. This enhances the ability to isolate and investigate root causes of recurring issues.

Acceptance Criteria
Category and Severity Filter Application
Given the manager is viewing the PainPoint Radar, When they select the 'Cleanliness' category and 'Negative' severity, Then the overlay updates to display only hotspots related to negative cleanliness feedback.
Hotspot Detail Drill-Down
Given the overlay highlights multiple hotspots, When the manager clicks on a specific hotspot, Then a detailed list of individual feedback entries is displayed showing timestamp, translated comment, and guest identifier.
Time Range Drill-Down
Given the manager has applied a time range filter, When they select a specific time segment on the radar, Then the overlay narrows down to that segment and the drill-down shows feedback entries only from that time period.
Filter Reset Functionality
Given one or more filters are applied, When the manager clicks 'Reset Filters', Then all filters clear and the overlay returns to showing all feedback hotspots by default.
Combined Filter Persistence
Given the manager has set category, severity, and time range filters, When they log out and later log back in, Then the previously applied filters are restored and the overlay reflects those filters immediately.
Temporal Heatmap
"As a hotel manager, I want to see how feedback hotspots change over time so that I can identify patterns and allocate resources effectively."
Description

Implement a time-series slider control that dynamically updates the PainPoint Radar to show feedback patterns over selectable time windows (hourly, daily, weekly). The overlay will animate through time, illustrating trends in issue occurrence and enabling managers to detect peak problem periods. Integrated with the existing data pipeline, the temporal heatmap will support customizable date ranges and playback speed controls, aiding in trend analysis and resource planning.

Acceptance Criteria
Default Time Window Initialization
Given the PainPoint Radar loads, When the temporal heatmap component initializes, Then the slider defaults to the weekly view covering the last seven days and the heatmap displays corresponding feedback data.
Hourly Granularity Selection
Given the user selects the 'Hourly' granularity option, When the slider updates, Then the heatmap segments change to hourly intervals and data points reflect feedback counts per hour.
Custom Date Range Filtering
Given the user sets a Start and End date using the date range picker, When the date range is applied, Then the heatmap updates to display feedback patterns only within the selected dates.
Playback Speed Control
Given the user initiates playback of the temporal heatmap, When playback speed is adjusted to low, medium, or high, Then the heatmap animates changes per interval at the selected speed without lag or frame drops.
High-Volume Data Performance
Given a data set containing feedback entries over a one-year period, When the user adjusts the slider across large date ranges, Then the heatmap updates within two seconds without UI freezing or errors.
Hotspot Alerting
"As a hotel manager, I want to receive real-time alerts when a feedback hotspot crosses a critical threshold so that I can intervene before issues escalate."
Description

Build an event-driven alert system that notifies managers via in-app notifications and optional email or SMS when a feedback hotspot exceeds predefined thresholds for volume or severity within a short timeframe. Managers can configure threshold rules by category, location, or time period. Alerts link directly to the affected area on the PainPoint Radar, providing quick access to the underlying feedback. This feature ensures critical issues receive immediate attention, reducing response times and improving guest satisfaction.

Acceptance Criteria
Category Threshold Breach Notification
Given a manager has set a threshold of 20 ‘cleanliness’ feedbacks within 30 minutes, When 21 ‘cleanliness’ feedbacks are received in that window, Then the system sends an in-app alert titled ‘Cleanliness Hotspot Exceeded’ linking to the relevant radar area.
Location Threshold Breach Notification
Given a manager has configured a threshold of 15 negative feedbacks for the ‘Lobby’ location in 1 hour, When 16 negative feedbacks for ‘Lobby’ arrive within that hour, Then the system generates an in-app notification ‘Lobby Hotspot Alert’ with the hotspot overlay.
Time Period Threshold Breach Notification
Given a manager defines a threshold of 10 high-severity feedbacks between 8PM and 10PM, When 11 high-severity feedbacks are recorded in that timeframe, Then an alert ‘Peak Hour Severity Alert’ is sent in-app and queued for external notification.
External Notification Delivery
Given a manager has opted in for email and SMS alerts, When any hotspot threshold is breached, Then the system dispatches an email and an SMS with alert details within 60 seconds of the in-app notification.
Radar Deep Link Navigation
Given a manager receives an alert notification, When the manager taps the alert, Then the PainPoint Radar opens centered on the affected hotspot with feedback details loaded.

ShiftSuggester

AI-driven daily service tweak recommendations based on detected trends—such as adjusting staffing levels or refining amenities—helping managers proactively enhance guest satisfaction.

Requirements

Trend Detection Engine
"As a hotel manager, I want the system to automatically detect daily service trends so that I can proactively adjust staffing and amenities to improve guest satisfaction."
Description

Aggregate and analyze daily emoji-based guest feedback, occupancy data, and amenity usage to detect patterns, anomalies, and emerging trends. By implementing this engine, the system identifies potential service issues and evolving guest preferences without manual intervention. Integrates seamlessly with the existing feedback database and AI pipelines to deliver accurate daily insights that drive actionable recommendations.

Acceptance Criteria
Anomaly Detection in Emoji Feedback
Given daily aggregated emoji feedback, occupancy data, and amenity usage When the Trend Detection Engine runs at the scheduled end-of-day interval Then it identifies anomalies (e.g., a ≥10% increase in negative emojis with a ≥5% drop in occupancy compared to the previous week) and logs them for review
Cross-Source Trend Analysis
Given integrated feedback, occupancy, and amenity metrics When the engine processes the combined dataset Then it generates the top three emerging guest preferences and service issues, with detection accuracy within 5% of baseline manual analysis
Daily Insights Report Generation
Given completion of trend analysis for the prior day When the engine finalizes results Then it produces a concise, timestamped report and makes it available on the manager dashboard by 07:00 local time
Real-Time Data Pipeline Integration
Given new feedback entries in the existing database When the Trend Detection Engine ingests data Then it connects seamlessly to the current schema, processes updates within 10 minutes, and handles schema changes without errors
Emerging Issue Alert Notification
Given detection of a service issue trend (e.g., a sustained rise in negative emoji feedback for a specific amenity) When the threshold is crossed Then the system sends an automated email alert to the manager within 15 minutes with relevant details
Personalized Recommendations Generator
"As a hotel manager, I want AI-driven daily service recommendations so that I can make informed operational decisions quickly without manual data analysis."
Description

Leverage AI algorithms to transform detected trends into clear, actionable daily service tweak suggestions—such as adjusting staff shifts, modifying amenities offerings, or changing service schedules. Ensures recommendations are context-aware and aligned with guest preferences. Integrates with the Trend Detection Engine and feeds output directly into the mobile app UI.

Acceptance Criteria
Shift Adjustment Recommendation for Morning Peak
Given the Trend Detection Engine identifies a >20% increase in morning occupancy over the past three days, when generating daily recommendations, then the system suggests increasing morning staff by at least two employees and displays this suggestion in the mobile app UI.
Amenities Offering Suggestion Post Feedback Analysis
Given guest feedback indicates repeated comments about lack of healthy breakfast options, when generating recommendations, then the system recommends adding a healthy breakfast item, specifies peak serving times, and presents the suggestion in the mobile app UI.
Service Schedule Tweaks for Peak Checkout Times
Given a detected trend of 80% of checkouts occurring between 10:00 AM and 11:00 AM, when generating recommendations, then the system advises staggering checkout service times by adding an extra front desk staff at 10:00 AM and displays this in the mobile app UI.
Context-Aware Personalization Based on Guest Language
Given a guest segment prefers Spanish, when delivering recommendations, then the suggestions appear in Spanish and account for regional amenity preferences, and are visible in the mobile app UI.
Real-Time Recommendation Updates Integration
Given a new trend is detected within one hour before a shift start, when the recommendations refresh, then the system updates the daily service tweak suggestions and pushes a real-time notification in the mobile app.
Real-time Suggestion Notifications
"As a hotel manager, I want to receive immediate notifications of recommended service adjustments so that I can implement them promptly and enhance guest experience."
Description

Deliver push notifications and in-app alerts to mobile devices with daily suggestion summaries and high-priority anomaly warnings when critical thresholds are exceeded. Notifications must be configurable by time and severity level to ensure timely awareness. Utilizes a reliable mobile push service and integrates with the recommendation pipeline.

Acceptance Criteria
Daily Summary Notification Delivery
Given the system generates daily suggestion summaries; When the configured delivery time arrives; Then a push notification with the daily summary is sent to all subscribed mobile devices via the push service.
In-app Alert for High-Priority Anomaly
Given a critical threshold is exceeded; When an anomaly is detected in real time; Then an in-app alert appears immediately on the manager's mobile app with anomaly details and severity level.
Notification Configuration by Time and Severity
Given the manager accesses notification settings; When they adjust time and severity preferences; Then the system saves settings and schedules notifications according to the updated criteria.
Reliable Push Service Integration
Given a push notification request is issued; When the push service fails to deliver; Then the system retries delivery up to three times and logs each attempt’s outcome.
Multi-language Notification Content
Given a manager’s preferred language is set; When a notification is generated; Then the notification content is automatically translated into the manager’s language before delivery.
Feedback Loop and Continuous Learning
"As the system, I want to learn from which recommendations were implemented and their impact so that future suggestions become more accurate and relevant."
Description

Capture manager interactions with suggestions—including acceptance, rejection, and implemented changes—and correlate these with subsequent guest feedback to refine AI models. Establishes a closed-loop system that continuously improves recommendation accuracy. Integrates a feedback module that logs execution data and outcome metrics for ongoing model training.

Acceptance Criteria
Logging Manager Acceptance of AI Suggestions
Given an AI-generated service improvement suggestion is presented, when the manager clicks 'Accept', then the system logs the suggestion ID, timestamp, manager ID, and changes the suggestion state to 'Accepted'.
Capturing Manager Rejection of AI Recommendations
Given an AI-generated suggestion is presented, when the manager clicks 'Reject', then the system logs the suggestion ID, timestamp, manager ID, rejection reason if provided, and changes the suggestion state to 'Rejected'.
Recording Implemented Service Changes
Given a suggestion is accepted, when the manager marks it as implemented in the dashboard, then the system logs the implementation details, including date, time, scope of change, and links them to the original suggestion ID.
Linking Guest Feedback to Implemented Suggestions
Given a suggestion has been implemented, when guests submit feedback within 7 days, then the system automatically associates the feedback entries with the implemented suggestion ID and stores the correlation data.
Automated Model Retraining Trigger
Given at least 50 logged interactions and correlated feedback entries exist, when the threshold is reached, then the system triggers an automated model retraining job, records the training initiation timestamp, data version, and confirms job submission.
Insights Dashboard Visualization
"As a hotel manager, I want to view an interactive dashboard of service trends and past recommendations so that I can assess performance and understand patterns behind guest satisfaction."
Description

Provide an interactive, in-app dashboard displaying trend graphs, recommendation histories, and impact metrics. Enables managers to explore performance over time, filter by service category, and visualize the relationship between implemented tweaks and guest satisfaction scores. Integrates with the analytics backend to render real-time visuals.

Acceptance Criteria
Viewing Real-Time Trend Graphs
Given a logged-in hotel manager, when they access the Insights Dashboard, then trend graphs for guest satisfaction over the past 30 days load within 2 seconds and reflect the latest data from the analytics backend.
Filtering Recommendations by Service Category
Given the manager selects a service category filter (e.g., housekeeping, front desk), when the filter is applied, then the dashboard updates to show only recommendation histories and metrics related to the selected category.
Correlating Implemented Tweaks with Satisfaction Scores
Given the manager marks one or more tweaks as implemented with corresponding dates, when viewing the impact metrics section, then the dashboard displays a correlation graph comparing pre- and post-implementation satisfaction scores for those tweaks.
Exporting Dashboard Data
Given the manager clicks the export button, when they choose a file format (.csv or .pdf), then the system generates and downloads a file containing the current dashboard view, including graphs, filters, and metrics, within 5 seconds.
Responsive Dashboard Layout on Mobile
Given the manager uses the mobile app on a smartphone, when rotating the device or resizing the view, then all dashboard components (graphs, filters, tables) adjust to fit the screen without horizontal scrolling or content overlap.

SeasonSync

Correlates feedback trends with seasons, holidays, and local events, empowering managers to tailor offerings and promotions to align with shifting guest sentiments.

Requirements

Seasonal Data Aggregator
"As a hotel manager, I want the system to automatically aggregate guest feedback by season, holiday, and local event so that I can identify patterns and tailor offerings accordingly."
Description

Develop a module that ingests and consolidates guest feedback data, tagging each entry with relevant seasonal markers (e.g., spring, summer), holidays (e.g., Christmas, New Year), and local event identifiers. The component should normalize and store this enriched data in the analytics database, enabling downstream trend analysis. It improves data accuracy and enables correlation between guest sentiment and temporal factors.

Acceptance Criteria
Seasonal Marker Assignment
Given a guest feedback entry with a timestamp, When the Seasonal Data Aggregator processes the entry, Then it applies the correct seasonal tag (e.g., spring, summer, autumn, winter) based on the date according to the defined seasonal boundaries.
Holiday Tagging
Given a guest feedback entry with a date matching a configured holiday, When processed, Then the entry is tagged with the exact holiday identifier (e.g., Christmas, New Year) and stored without loss of feedback content.
Local Event Identification
Given a guest feedback entry with location metadata, When the aggregator cross-references the date and location with the local events database, Then all matching local event identifiers are appended to the feedback record.
Data Normalization and Storage
Given an enriched feedback record containing seasonal, holiday, and event tags, When saved to the analytics database, Then the record adheres to the schema definitions, duplicates are resolved, and all tag fields are normalized to the standard format.
Trend Analysis Query Retrieval
Given stored enriched feedback data, When queried by season, holiday, or event filters, Then the system returns accurate filtered results with associated sentiment scores within the defined performance threshold (e.g., under 200ms).
Error Handling for Missing Metadata
Given a guest feedback entry missing date or location information, When processed by the aggregator, Then the system logs a clear error message, skips enrichment for that entry, and does not store incomplete data in the analytics database.
Trend Analysis Engine
"As a hotel manager, I want the system to highlight sentiment trends for specific seasons and events so that I can adjust staffing and promotions in advance."
Description

Implement an analytics engine that processes the aggregated feedback dataset to detect statistically significant sentiment trends across defined time periods (seasons, holidays, events). The engine should support customizable time windows, apply smoothing algorithms, and surface emerging positive or negative sentiment spikes. This capability empowers managers to anticipate guest needs and adapt strategies proactively.

Acceptance Criteria
Custom Time Window Selection
Given a manager configures a custom time window between 7 and 365 days, when the engine runs, then it processes feedback only within that window and returns aggregated sentiment scores.
Seasonal Trend Detection
Given predefined seasons (Spring, Summer, Fall, Winter), when the engine analyzes feedback, then it identifies and reports sentiment changes with statistical significance (p-value < 0.05) between consecutive seasons.
Holiday Spike Identification
Given a specified holiday period, when the engine processes feedback data, then it detects sentiment spikes exceeding a 20% deviation from the baseline period and flags them.
Smoothing Algorithm Application
Given daily sentiment data containing noise, when the smoothing algorithm (moving average with window size 7) is applied, then the output shows at least 30% reduction in volatility compared to raw data.
Emerging Negative Sentiment Alert
Given continuous real-time feedback input, when a negative sentiment spike of 15% over the previous week is detected, then the system generates an alert notification within 5 minutes.
Holiday & Event Calendar Integration
"As a hotel manager, I want holiday and local event dates to be automatically imported so that trend analyses reflect real-world occasions without manual updates."
Description

Integrate an external calendar API to automatically fetch local and global holiday schedules and regional event listings. The system should map these entries to the hotel’s locale, update them monthly, and flag relevant dates in the feedback analysis workflow. This ensures that feedback correlations remain accurate and context-aware without manual calendar maintenance.

Acceptance Criteria
Monthly Calendar Sync Execution
Given the system schedule triggers at 00:00 on the first day of each month, when the sync job runs, then the system fetches holiday and event entries from the external calendar API for the hotel's configured locale within 10 minutes and stores them in the local database.
API Data Accuracy Validation
Given the fetched calendar data is stored, when the system compares entries to known holiday lists, then all entries must have valid dates, names, and locale matching, with no duplicates or missing mandatory fields.
Locale-based Event Mapping
Given the hotel’s locale settings, when calendar data is processed, then only events and holidays relevant to that locale and its surrounding region are flagged, excluding global events not applicable.
Feedback Workflow Date Flagging
Given a guest feedback submission, when the feedback date matches a flagged holiday or event date, then the system tags the feedback with the corresponding holiday/event ID in the analysis workflow.
Error Handling and Retry Mechanism
Given the external API call fails or returns an error, when the sync job encounters an error, then the system retries up to 3 times with exponential backoff and logs the failure if all retries fail.
Customizable Reporting Dashboard
"As a hotel manager, I want an interactive dashboard showing sentiment trends by season and event so that I can generate reports and share insights with my team."
Description

Design a user interface within Guestify that visualizes seasonal sentiment trends, event correlations, and holiday-based feedback insights. The dashboard should allow filtering by time frame, sentiment category, and event type, and support exporting reports in CSV and PDF formats. This feature gives managers a clear, interactive view of guest sentiment shifts to inform decision-making.

Acceptance Criteria
Filtering Feedback by Time Frame
Given the manager selects a custom date range, when they apply the filter, then only feedback entries within that date range are displayed on the dashboard.
Visualizing Sentiment Trend Charts
Given seasonal feedback data exists, when the dashboard loads, then sentiment trend charts display aggregated positive, neutral, and negative emoji feedback over the selected period with distinct color coding.
Correlating Feedback with Local Events
Given event tags are associated with feedback entries, when the manager selects an event type filter, then only feedback related to occurrences of that event is shown alongside the corresponding event dates.
Exporting Reports to CSV Format
Given any filters are applied, when the manager clicks the 'Export CSV' button, then a CSV file downloads that includes header rows and data matching the current dashboard view.
Exporting Reports to PDF Format
Given any filters are applied, when the manager clicks the 'Export PDF' button, then a well-formatted PDF report is generated containing charts, tables, and branding that reflect the current dashboard view.
Automated Promotion Recommendation Alerts
"As a hotel manager, I want to receive alerts when guest sentiment shifts around key seasons or events so that I can deploy targeted promotions immediately."
Description

Build a notification system that triggers alerts when significant positive or negative sentiment shifts are detected around specific seasons or events. Alerts should include context (e.g., ‘Summer satisfaction dropped by 15% during local festival’) and suggest actionable promotions or service adjustments. This real-time guidance enables managers to respond swiftly to evolving guest preferences.

Acceptance Criteria
Seasonal Sentiment Shift Detection
Given at least 20 feedback entries tagged to a specific season or event, when the system computes sentiment analysis then it detects and calculates a percentage change relative to the previous baseline period. An alert is automatically triggered if the detected sentiment shift is greater than or equal to 10% in either positive or negative direction.
Contextual Alert Content Generation
When an alert is triggered then the notification message includes the season or event name, exact percentage change, and relevant date range (e.g., “Summer satisfaction dropped by 15% between June 1 and June 30 during the local festival”). All context fields populate correctly from the metadata store without manual input.
Actionable Promotion Suggestion Accuracy
For negative sentiment shifts, the system suggests at least two tailored promotions or service adjustments relevant to the affected season/event (e.g., discounted spa packages for off-peak season). For positive sentiment shifts, the system suggests at least two upsell or loyalty-enhancement offers aligned with guest preferences.
Real-Time Notification Delivery
Once a sentiment shift is detected and alert content generated, the system delivers an in-app notification within 5 minutes to logged-in managers. The same alert is emailed to the manager’s registered address within 10 minutes, with correct subject line and body content matching the in-app notification.
User Interface Alert Presentation
New alerts appear in the dashboard’s Alerts panel with color-coded indicators (green for positive shifts, red for negative shifts) and are sorted by timestamp. Clicking an alert expands a detail view showing full context, sentiment graphs, and recommended promotions.

ForecastFix

Predictive modeling projects next month’s potential pain points and suggests preventative measures, helping managers preempt issues before they impact guest experiences.

Requirements

Historical Data Integration
"As a data engineer, I want a robust pipeline that aggregates and preprocesses historical hotel data so that the predictive models have reliable and comprehensive input."
Description

Implement a unified data ingestion pipeline that consolidates historical guest feedback, service logs, booking details, and environmental metrics. The pipeline should normalize and preprocess diverse data sources for use in predictive modeling, ensuring data completeness, consistency, and quality.

Acceptance Criteria
Legacy Feedback Data Import
Given historical guest feedback files in CSV and JSON formats, when the ingestion pipeline runs, then all feedback records are imported into the unified database with parsed timestamps and associated guest IDs.
Service Logs Consolidation
Given multiple service log sources (e.g., housekeeping, maintenance), when the pipeline processes them, then records are normalized to a standard schema including date, location, and service type, with duplicates removed.
Booking Details Harmonization
Given booking records from different reservation systems, when ingested, then the data is mapped to a common schema with guest name, booking dates, room type, and booking source standardized.
Environmental Metrics Normalization
Given environmental sensor readings in varying units and frequencies, when processed, then values are converted to standard units (e.g., Celsius, percentage) and aggregated hourly with missing data imputed.
Data Quality Validation
Given normalized data in the unified pipeline, when validation occurs, then the system generates a quality report showing completeness (> 99%), consistency (no conflicting records), and highlights errors for manual review.
Predictive Model Engine
"As a hotel operations manager, I want predictive analytics that forecast next month’s potential issues so that I can proactively address them."
Description

Develop and integrate a machine learning engine capable of analyzing historical and current data to forecast potential guest pain points for the upcoming month. The engine should support configurable model selection (e.g., time series, classification) and provide performance metrics for accuracy evaluation.

Acceptance Criteria
Monthly Forecast Generation
Given historical and current guest feedback data is available When the predictive model engine runs for the upcoming month Then it outputs a ranked list of the top five potential guest pain points with associated confidence scores
Configurable Model Selection
Given multiple forecasting models are registered in the system When a manager selects a specific model type in the configuration settings Then the engine trains and generates forecasts using only the chosen model
Performance Metrics Reporting
Given the model completes forecast generation When the process finishes Then the engine displays accuracy, precision, recall, and F1 score metrics for the selected model in the dashboard
Data Pipeline Validation
Given new data is ingested into the system When the predictive model engine starts training Then it validates incoming records against the schema, skips invalid entries, and logs validation errors
Real-time Forecast Update Notification
Given updated guest feedback data arrives before month end When the engine re-runs the forecast Then it sends a notification to the manager summarizing any changes in the top three predicted pain points
Preventative Action Recommendations
"As a hotel manager, I want actionable suggestions for mitigating predicted issues so that I can prevent negative guest experiences."
Description

Implement a recommendation system that analyzes forecasted pain points and suggests tailored preventative measures. Recommendations should include specific operational actions, resource reallocations, and customer engagement strategies to mitigate identified risks.

Acceptance Criteria
Viewing Preventative Action Recommendations
Given a hotel manager views the ForecastFix dashboard for next month’s risks, when the manager clicks on the “Preventative Actions” tab, then the system displays at least three actionable recommendations, each with a title, description, and associated risk category.
Recommendation Content Coverage
Given the displayed recommendations list, for each recommendation, the system includes at least one operational action, one resource reallocation suggestion, and one customer engagement strategy in its description.
Severity-Based Prioritization
Given multiple preventative action recommendations are available, when the recommendations list is rendered, then the recommendations are ordered in descending order based on their forecasted impact severity score.
Exporting Recommendations Report
Given the manager has reviewed the recommendations, when the manager selects the “Export” button and chooses a format (PDF or CSV), then the system generates and downloads a file containing all recommendations with their details and metadata.
Real-Time Recommendation Updates
Given updated forecast data is received by the system, when new risk data is processed, then the recommendations list automatically refreshes within 5 seconds to reflect the latest preventative actions without requiring a manual page reload.
Forecast Dashboard Visualization
"As a hotel manager, I want a clear visual dashboard of upcoming potential issues so that I can quickly understand and prioritize actions."
Description

Design and build an interactive dashboard within the Guestify app that visualizes forecasted pain points, trends, and key performance indicators. The dashboard should allow drill-down into categories (e.g., cleanliness, service speed) and support filtering by date range and hotel sections.

Acceptance Criteria
Data Rendering on Dashboard Load
Given the manager navigates to the Forecast Dashboard When the dashboard loads Then all forecasted pain point charts and KPIs are displayed within 3 seconds without errors
Drill-down into Pain Point Categories
Given the manager views a summary chart When the manager clicks on a specific pain point category Then the dashboard displays a detailed breakdown of subcategories and their trend over the selected period
Date Range Filter Application
Given the manager selects a custom date range When the manager applies the date filter Then all dashboard visualizations refresh to show only data within that range and the applied dates are clearly indicated
Hotel Section Filter Functionality
Given the manager selects one or more hotel sections When the manager applies the section filter Then only forecast data for the selected sections is displayed and other sections remain hidden
KPI Trend Line Visualization
Given the manager switches to the KPI trend view When the manager hovers over a data point Then a tooltip shows the exact KPI value and date and the trend line updates dynamically
Real-time Alerting & Notifications
"As a hotel manager, I want immediate alerts for critical upcoming issues so that I can respond promptly."
Description

Set up a notification system that triggers real-time alerts when the model forecasts high-risk pain points. Alerts should be delivered via in-app notifications, email, or SMS, with configurable thresholds and escalation paths.

Acceptance Criteria
High-Risk Forecast Threshold Breach
Given a manager has configured a pain-point risk threshold in the notification settings; When the predictive model forecasts next month’s risk exceeding that threshold; Then the system sends an in-app notification within 60 seconds; And an email alert to the manager’s registered address.
Custom Notification Channel Configuration
Given a manager accesses notification preferences; When they select or deselect email and SMS channels and save changes; Then all subsequent alerts are delivered via only the selected channels; And the channel preferences persist across user sessions.
Unacknowledged Alert Escalation
Given an alert is issued and remains unacknowledged for 15 minutes; When the 15-minute acknowledgment window expires; Then the system automatically escalates by sending an SMS to the escalation contact; And logs the escalation event in the alert history.
Alert History Dashboard Display
Given the manager navigates to the ForecastFix dashboard; When they open the alert history view; Then the system displays all alerts from the past 30 days with timestamp, status, and delivery channel; And provides filters for date range and alert status.
Multi-Language Alert Content Delivery
Given the hotel’s primary language is set to Spanish in settings; When an alert is triggered; Then in-app notifications, emails, and SMS messages are automatically translated into Spanish; And the translated content is verified against the language setting before dispatch.

ActionPlanner

Generates prioritized action plans complete with timelines and resource estimates, transforming insights into executable tasks that drive measurable operational improvements.

Requirements

Automated Action Plan Generation
"As a hotel manager, I want the system to automatically generate a detailed action plan from guest feedback so that I can swiftly implement improvements without manual task planning."
Description

The system automatically transforms guest feedback insights into a structured action plan with prioritized tasks, deadlines, and required resources. It ensures that hotel managers receive immediate, actionable guidance tailored to each identified issue, improving operational responsiveness. This requirement integrates with the existing feedback analysis module and leverages real-time translation data to generate context-aware tasks. The outcome is a clear, step-by-step plan that can be executed by staff to enhance guest satisfaction and reduce negative reviews.

Acceptance Criteria
New Feedback Triggers Plan Generation
Given a newly analyzed feedback insight for a housekeeping issue When the ActionPlanner process is invoked Then the system generates an action plan including at least one housekeeping remediation task with assigned priority, a deadline within the next 24 hours, and estimated staff-hours allocated
Context-Aware Resource Estimation
Given feedback in a non-English language with associated translation metadata When generating the action plan Then each task includes a resource estimate (e.g., staff-hours, materials) derived from translation context, with the estimate accuracy within 10% of a manual benchmark
Prioritization of Tasks Based on Severity
Given multiple feedback insights labeled with severity levels (low, medium, high) When prioritizing tasks Then the system orders tasks by severity descending, assigns High severity tasks a priority flag, and schedules them within 12 hours
Integration with Translation Data
Given real-time translated guest feedback input When creating task descriptions Then the action plan reflects the original context accurately, with no mistranslations detected in task titles or descriptions
Action Plan Delivery to Manager Dashboard
Given a generated action plan When the hotel manager accesses their dashboard Then the plan appears in the “Action Plans” section within 2 seconds, displaying all task details and offering export and assignment options
Priority Weight Configuration
"As a hotel manager, I want to adjust priority weightings for guest feedback factors so that the action plans reflect my hotel's specific operational priorities."
Description

Enable customization of the priority scoring algorithm by allowing hotel managers to adjust weightings for various factors such as guest sentiment, issue severity, and guest loyalty status. This requirement ensures that the generated action plans align with individual hotel business goals and resource constraints. The feature should provide an intuitive interface for setting weights and previewing how changes affect task prioritization, integrating seamlessly with the plan generation engine.

Acceptance Criteria
Adjusting Priority Weightings via Interface
Given the hotel manager accesses the Priority Weight Configuration interface, when they adjust the weight slider for a factor (e.g., guest sentiment, issue severity, guest loyalty), then the system updates the numeric weight in real time within the allowed range (0-100) and visually highlights any weights that have been modified.
Real-Time Prioritization Preview
Given the manager modifies one or more weightings, when they click the 'Preview' button, then the action plan list reorders tasks based on the updated weights within 2 seconds and displays the new priority scores alongside each task.
Saving Customized Weight Settings
Given the manager has adjusted the weightings, when they click the 'Save' button, then the system persists the customized weights to the manager’s profile, displays a confirmation message 'Settings saved successfully', and retains those weights on page reload.
Resetting to Default Weights
Given the manager views previously saved custom weights, when they click 'Reset to Defaults', then all weight sliders revert to the system’s default values and the preview panel immediately updates to reflect the default prioritization.
Handling Invalid Weight Inputs
Given the manager attempts to input a non-numeric or out-of-range value (below 0 or above 100) in a weight field, when they focus out or attempt to save, then the system displays an inline error 'Please enter a number between 0 and 100', disables the 'Save' button, and prevents any invalid data from being persisted.
Interactive Timeline Visualization
"As a hotel manager, I want to see tasks plotted on an interactive timeline so that I can easily adjust schedules and track progress visually."
Description

Provide an interactive timeline view that displays each task in the action plan along a chronological axis, highlighting start and end dates, dependencies, and progress status. The visualization should support drag-and-drop adjustment of timelines, zoom in/out, and filtering by task owner or status. Integration with the resource estimation module allows managers to understand time commitments at a glance, facilitating efficient scheduling and resource allocation.

Acceptance Criteria
Viewing Task Timelines
Given a logged-in manager with an existing action plan containing tasks with defined start and end dates, When the manager opens the Interactive Timeline Visualization, Then all tasks are displayed accurately along a chronological axis with correct start and end dates, color-coded progress status, and visible dependency lines.
Adjusting Task Dates via Drag-and-Drop
Given tasks rendered on the timeline with draggable start and end markers, When the manager drags a task bar to adjust its dates, Then the task’s start and/or end date is updated in the backend, the timeline re-renders in real time, dependencies are validated (no overlap with predecessors), and a confirmation message appears.
Zooming Timeline View
Given the timeline is fully loaded, When the manager uses the zoom-in or zoom-out controls or pinch gestures, Then the timeline scales appropriately, task bars adjust their visual length proportionally, timeline labels remain legible, and the visible date range updates accordingly.
Filtering Tasks by Owner and Status
Given multiple tasks from different owners and statuses are present on the timeline, When the manager applies filters for specific task owners or statuses, Then only tasks matching the selected filters remain visible, the timeline axis re-centers to the filtered tasks’ range, and clearing filters restores the full view.
Viewing Resource Estimates on Timeline
Given the resource estimation module is integrated, When the timeline loads, Then each task bar displays an icon or label indicating estimated resources or hours, and hovering or clicking a task reveals a tooltip with detailed resource estimates and timeline commitment.
Resource Estimation Engine
"As a hotel manager, I want accurate resource estimates for each task so that I can plan budgets and staff assignments effectively."
Description

Incorporate a resource estimation engine that calculates required personnel, materials, and costs for each task in the action plan based on predefined templates and historical data. The engine should factor in task complexity, duration, and hotel-specific parameters, producing granular estimates that help managers allocate budgets and staff. This module must integrate with the timeline visualization and export functionality to provide comprehensive planning insights.

Acceptance Criteria
Estimate Resources for Standard Room Cleaning Task
Given a standard room cleaning task is selected from the template library, when the Resource Estimation Engine runs, then it outputs the required number of staff, cleaning materials, and cost estimates based on historical data with a variance of no more than 10% from actuals.
Estimate Resources for Complex Maintenance Task
Given a hotel manager configures a complex maintenance task with custom parameters, when the estimation engine executes, then it calculates personnel hours, specialized materials, and total costs, adjusting for task complexity and duration within a 15% accuracy threshold.
Generate Cost Estimate for Seasonal Staffing Task
Given a seasonal staffing task is scheduled for peak season, when the engine processes the template and seasonal parameters, then it produces granular staffing headcount, shift schedules, and cost totals, reflecting hotel-specific occupancy rates with accuracy of 5%.
Integrate Resource Estimates into Timeline View
Given resource estimates are generated for all action items, when the manager views the timeline visualization, then each task displays its resource allocation bars and cost overlays correctly aligned with the task schedule.
Export Resource Estimates in Planning Report
Given an action plan is finalized, when the manager exports the report, then the export file includes detailed resource breakdowns, cost summaries, and personnel allocations for each task in PDF and CSV formats.
Export & Sharing Actions
"As a hotel manager, I want to export and share the action plan so that my team can collaborate on executing tasks using their preferred tools."
Description

Allow hotel managers to export generated action plans in multiple formats (PDF, Excel, and shareable link) and share them with team members via email or the Guestify app. The export should preserve formatting, timelines, and resource estimates, and include options for selecting which elements to include. This requirement ensures that all stakeholders have access to the plan in their preferred format and can collaborate easily on implementation.

Acceptance Criteria
Export Action Plan as PDF
Given the manager selects 'Export as PDF', when the export is confirmed, then a PDF file is downloaded containing the full action plan with original formatting, timelines, and resource estimates preserved.
Export Action Plan as Excel
Given the manager selects 'Export as Excel', when the export is executed, then an .xlsx file is generated with separate sheets for tasks, timelines, and resource estimates, and all data correctly mapped.
Generate Shareable Link for Action Plan
Given the manager requests a shareable link, when the link is created, then a unique URL is generated that grants view-only access to the complete action plan with preserved formatting and data.
Selective Export of Action Plan Elements
Given the manager chooses specific elements (e.g., tasks, timelines, resources), when the export options are applied, then only the selected elements appear in the exported file without missing or extra data.
Share Action Plan via Email
Given the manager opts to share via email, when email addresses are entered and the share action is confirmed, then recipients receive an email with the exported file attached or the shareable link included.
Share Action Plan via Guestify App
Given the manager selects 'Share in App' and chooses team members, when the share is confirmed, then each member receives an in-app notification with access to the exported plan or link.

SmoothExit Survey

Delivers a one-tap, emoji-based survey the moment guests check out, capturing final impressions with minimal effort. The frictionless format boosts response rates and provides immediate sentiment data, helping managers identify last-minute wins or pain points before guests leave.

Requirements

One-Tap Emoji Survey UI
"As a hotel guest, I want to select my checkout sentiment with a single emoji tap so that I can quickly provide feedback without typing."
Description

Design and implement a one-tap emoji-based survey interface that appears upon checkout, allowing guests to select their sentiment with a single touch. The UI must be intuitive, visually engaging, and responsive across all mobile devices, ensuring minimal effort and maximum engagement. This interface integrates seamlessly with the Guestify mobile app, leveraging existing design systems and ensuring accessibility compliance. The expected outcome is a significant increase in response rates due to reduced friction.

Acceptance Criteria
Checkout Trigger Activation
Given a guest completes the checkout process, When the final confirmation screen loads, Then the one-tap emoji survey interface appears automatically within 2 seconds
Emoji Selection Response Capture
Given the survey interface is displayed, When the guest taps an emoji sentiment, Then the response is recorded and a confirmation message is shown
UI Responsiveness Across Devices
Given the survey interface on a mobile device, When the device is rotated or screen size changes, Then all UI elements resize and reposition without overlap or truncation
Accessibility Compliance Verification
Given the survey interface is displayed, When a screen reader is active or high-contrast mode is enabled, Then each emoji option has an accessible label and meets WCAG 2.1 AA contrast ratios
Integration with Feedback Dashboard
Given a guest submits an emoji response, When the data sync completes, Then the sentiment result appears in the manager’s real-time dashboard with no data loss
Checkout Event Trigger
"As a hotel manager, I want the survey to launch automatically at the exact moment of checkout so that I capture my guests' final impressions while they're still on property."
Description

Develop a mechanism to detect when a guest completes the checkout process in the property management system (PMS) or within the app, automatically triggering the SmoothExit survey. This requires integration with the PMS API or app session management, ensuring the survey appears exactly at the checkout moment. The feature must support real-time detection with fallback retry logic. This ensures timely feedback capture and improves data accuracy.

Acceptance Criteria
PMS Checkout Completion
Given a valid checkout event is received from the PMS API, when the event timestamp is within the last minute, then the SmoothExit survey is launched in the guest's mobile app within 2 seconds and the launch event is logged with event ID and timestamp.
In-App Checkout Session End
Given the guest completes the in-app checkout process, when the session endpoint confirms checkout, then the SmoothExit survey is triggered automatically and a confirmation notification is displayed to the guest.
API Failure Fallback Retry
Given the PMS API checkout trigger fails, when the first retry occurs after 5 seconds, then the system re-attempts the trigger up to 3 times and displays the survey if any retry succeeds; otherwise logs an error.
Duplicate Survey Prevention
Given a checkout event has already triggered a survey, when the guest reopens the app within the same session, then the SmoothExit survey must not re-trigger; ensuring only one survey per checkout per guest.
Accurate Timestamp Logging
Given the survey is triggered, when the request is sent to the backend, then the survey trigger event in the database includes the correct checkout timestamp and guest ID matching the PMS record.
Instant Sentiment Dashboard Update
"As a hotel manager, I want to see sentiment data update in real time so that I can address any negative feedback immediately."
Description

Implement live data pipelines that funnel incoming SmoothExit survey responses directly into the manager's dashboard, updating sentiment metrics in real time. This requires setting up WebSocket or push notifications, ensuring low-latency updates, and integrating with existing analytics modules. Managers should see updated charts and alerts immediately after each response, enabling proactive issue resolution.

Acceptance Criteria
WebSocket Connection Establishment
Given the manager logs into the dashboard, when the dashboard loads, then a persistent WebSocket connection is established with the sentiment data service within 2 seconds and the connection status indicator turns green.
Real-Time Data Reception
Given a new SmoothExit survey response is submitted, when the sentiment service pushes the data, then the dashboard receives the complete payload within 500 milliseconds.
Chart Update on Incoming Data
Given the dashboard receives new sentiment data, when the visualization component processes it, then the sentiment chart updates within 300 milliseconds to include the latest data point.
Negative Sentiment Alert Trigger
Given a response is classified as negative sentiment (emoji rating ≤2), when the data arrives, then the dashboard displays a prominent alert banner within 400 milliseconds.
Batch Data Consistency Check
Given ten or more survey responses arrive within one second, when processed, then the aggregated sentiment metrics on the dashboard exactly match the sum of individual data points without any loss or duplication.
Offline Feedback Capture
"As a guest in areas with limited connectivity, I want to submit my survey offline so that my feedback is recorded once I'm back online."
Description

Enable the SmoothExit survey to function without an active internet connection by caching survey responses locally on the device. Once connectivity is restored, the app should automatically sync stored responses with the server, preserving response timestamps and guest identifiers. This ensures no data loss in areas with poor connectivity and maintains the integrity of feedback collection.

Acceptance Criteria
Survey Completion on Offline Mode
Given the user completes a SmoothExit survey with no internet connection, When the final emoji is selected and submitted, Then the response is saved to the device’s local storage without errors.
Local Storage of Survey Data
Given multiple offline survey responses exist, When viewing local storage, Then all responses are queued in chronological order with intact response data.
Automatic Synchronization After Connectivity Restoration
Given cached responses and restored internet connectivity, When the app detects a valid network connection, Then all stored responses are automatically synced to the server within 30 seconds.
Preservation of Response Metadata
Given a synced survey response, When viewed on the server dashboard, Then the original response timestamp and guest identifier match the locally recorded values.
Handling Synchronization Errors
Given a failed sync due to a server or network error, When the app retries, Then it retries up to 5 times with exponential backoff and reports an error after final failure.
Customizable Survey Prompts
"As a hotel manager, I want to customize the survey emojis and prompts so that the feedback aligns with my hotel's branding and specific service goals."
Description

Provide hotel managers with a configuration interface within the admin portal to customize the survey's emojis, prompt text, and optional follow-up questions. Changes should reflect in the mobile app dynamically without requiring app updates. This feature enhances brand alignment and allows personalization based on hotel-specific needs.

Acceptance Criteria
Emoji Set Customization Scenario
Given the hotel manager accesses the Survey Prompts settings, when they select the emoji configuration panel and choose a new set of emojis, then the selected emojis are saved and displayed in the preview without errors.
Prompt Text Customization Scenario
Given the manager is editing the survey prompt text, when they input custom text and save changes, then the new text appears accurately in the survey interface preview.
Follow-Up Question Configuration Scenario
Given the manager enables an optional follow-up question, when they enter the question text and designate it as mandatory or optional, then the setting is persisted and displayed correctly in both the admin portal and the mobile app preview.
Dynamic Update Propagation Scenario
Given changes are made to emojis, prompt text, or follow-up questions, when the mobile app next loads the survey, then it fetches and displays all updates without requiring an app update.
Configuration Input Validation Scenario
Given the manager submits new configuration settings, when required fields are missing or inputs exceed character limits, then the system displays clear validation errors and prevents saving until corrections are made.

GratitudeGenius

Automatically crafts personalized thank-you messages using guest names, stay details, and emoji feedback. By tailoring tone and content—complete with local language support—it fosters genuine connections, drives positive reviews, and encourages repeat bookings.

Requirements

Emoji Sentiment Analysis
"As a hotel manager, I want the system to analyze guest emojis and determine their sentiment so that thank-you messages reflect the guest’s true feelings."
Description

Implement a system that interprets emoji-based guest feedback by mapping each emoji to a sentiment score and tone indicator. This requirement ensures accurate understanding of guest emotions, enabling the personalization engine to craft messages that resonate with the guest’s mood. It integrates with the feedback collection module and feeds processed sentiment data into the message generation workflow for seamless end-to-end functionality.

Acceptance Criteria
Basic Emoji Sentiment Mapping
Given a single emoji input, when processed, then the system assigns the correct sentiment score from -1 to +1 based on the mapping table and returns the matching tone indicator within 200ms.
Mixed Emoji Input Aggregation
Given a feedback submission with multiple emojis, when processed, then the system calculates an aggregate sentiment score by averaging individual scores and identifies the dominant tone indicator.
Unsupported Emoji Handling
Given an emoji not present in the mapping table, when processed, then the system flags it as 'unknown', assigns a neutral sentiment score of 0, and logs the occurrence for review.
Integration with Personalization Engine
Given processed sentiment data, when passed to the personalization engine, then the engine incorporates the score and tone indicator correctly into the message template without data loss or formatting errors.
Real-Time Feedback Processing
Given a live guest feedback session, when an emoji is submitted, then the system processes and stores sentiment data in real time, updating the dashboard within 500ms.
Personalized Message Generator
"As a hotel manager, I want the system to auto-create individualized thank-you notes so that I can engage guests with relevant and timely appreciation."
Description

Develop the core engine that merges guest names, stay details, and sentiment insights to automatically generate tailored thank-you messages. This requirement covers assembling dynamic content placeholders, integrating tone adjustments based on sentiment, and ensuring messages adapt to each guest’s profile. It ties into the content template system and language module for cohesive message production.

Acceptance Criteria
Positive Feedback Thank-You Message Generation
Given a guest stays and provides a positive emoji rating, when the engine generates a thank-you message, then the message includes the guest’s name, stay details, positive sentiment tone, and appropriate emojis.
Negative Feedback Tone Adjustment
Given a guest leaves a negative emoji rating, when the message is generated, then the tone is empathetic and apologetic, acknowledges the issue, and offers assistance or compensation.
Language Localization Accuracy
Given a guest’s preferred language is different from the property’s default, when the message is generated, then all dynamic content and sentiment-based phrasing are correctly translated and localized.
Dynamic Placeholder Substitution
Given a guest record with name, stay dates, room type, and feedback, when generating a message, then all placeholders are replaced with correct data without missing or incorrect values.
Integration with Content Template System
Given the content template system is available, when the generator runs, then it selects the appropriate template based on sentiment and guest profile and produces a cohesive final message.
Language Localization Support
"As a hotel manager, I want thank-you messages delivered in each guest’s language so that international visitors feel genuinely appreciated."
Description

Build multi-language translation and localization capabilities to ensure messages are crafted in the guest’s preferred language. This includes integrating with a translation API, handling locale-specific date/time formats, and applying cultural nuances in phrasing. It enhances global reach and ensures gratitude messages feel authentic to international guests.

Acceptance Criteria
Guest's Preferred Language Detection
Given a guest has a preferred language set in their profile, when the GratitudeGenius generates a thank-you message, then the message language matches the guest’s preferred language code.
Translation API Integration
Given a message template and guest feedback content, when the system invokes the translation API, then the API returns a successful translation response and the translated text is applied to the final message.
Locale-Specific Date/Time Formatting
Given the guest’s locale settings, when the gratitude message includes dates or times, then those dates and times are formatted according to the locale’s conventions.
Cultural Nuance Phrasing
Given the guest’s locale is identified, when generating gratitude text, then idiomatic expressions are substituted with culturally appropriate phrasing for that locale.
Fallback for Unsupported Languages
Given a guest’s preferred language is not supported by the translation API, when generating the message, then the system defaults to English, logs the fallback event, and notifies the operations team.
Template Customization Interface
"As a hotel manager, I want to customize thank-you message templates so that communications align with our brand’s tone and style."
Description

Create an intuitive UI for managers to customize message templates, including selecting tone (formal, casual), adding branded elements, and defining placeholder rules. This requirement empowers staff to tailor baseline messages, manage template versions, and preview outputs before deployment, ensuring consistency with the hotel’s voice and branding.

Acceptance Criteria
Tone Selection and Preview
Given a manager is editing a message template in the UI When they select the 'Formal' tone option Then the message preview updates instantly to display formal language tone and proper placeholders And selecting the 'Casual' tone updates the preview to casual language accordingly.
Branded Element Insertion
Given a manager is in the template customization screen When they upload or select a hotel logo and add a custom signature Then the UI displays these elements correctly in the preview pane And maintains aspect ratio and placement rules.
Placeholder Definition and Validation
Given a manager defines a new placeholder variable (e.g., {{guest_name}}) When they save placeholder rules Then the system validates the placeholder format And rejects invalid patterns with an error message And includes the placeholder in the preview with sample data.
Template Versioning and Reversion
Given multiple saved versions of a message template exist When a manager views version history Then they can select a previous version and click 'Revert' And the system restores the template content to that version And logs the revert action in the audit trail.
Real-Time Message Preview with Live Data
Given a manager has entered customization settings When they click 'Preview with Live Data' Then the system fetches sample guest stay details and emoji feedback And displays a fully rendered message in the local language Matching the selected tone, branding, and placeholders.
Automated Delivery Scheduler
"As a hotel manager, I want messages sent automatically after a guest’s stay so that no follow-up is overlooked."
Description

Implement scheduling logic to automatically send generated thank-you messages via email or SMS at predefined intervals post-checkout. This requirement includes queue management, retry mechanisms for failed deliveries, and channel selection based on guest preferences. It guarantees timely message dispatch without manual intervention.

Acceptance Criteria
Schedule Message Dispatch Based on Checkout Time
Given a guest checks out at 11:00 AM, When the scheduler processes delivery tasks, Then the thank-you message is sent via the guest’s preferred channel exactly 2 hours post-checkout.
Retry Mechanism for Failed Deliveries
Given a message delivery fails due to a network error, When the retry count is less than 3, Then the system retries delivery up to 3 times at 10-minute intervals; If all retries fail, the system marks the delivery as failed and logs the failure.
Channel Selection Based on Guest Preference
Given a guest’s delivery preference is set to SMS, When the scheduler initiates message dispatch, Then the system selects SMS; If SMS fails or is unavailable, the system falls back to email.
Queue Management Under Peak Load
Given 1,000 messages queued for delivery, When peak load occurs, Then the queue processes messages without delay, ensuring average dispatch latency remains under 5 seconds per message.
Logging and Notification of Delivery Outcomes
Given a message dispatch completes or fails, When delivery status is determined, Then the system logs the outcome with timestamp and message ID and updates the admin dashboard in real time.
Performance Monitoring Dashboard
"As a hotel manager, I want to view performance metrics for thank-you messages so that I can evaluate and improve guest engagement."
Description

Develop a dashboard that tracks key metrics such as messages sent, open rates, click-throughs, and guest responses. This requirement includes real-time charts, filtering by date or property, and exportable reports. It provides insights into campaign effectiveness and helps managers refine messaging strategies.

Acceptance Criteria
Dashboard Data Accuracy Validation
Given a set of message metrics from the past week When the dashboard loads Then the messages sent, open rates, click-throughs, and guest responses values match the source data within a 1% discrepancy
Real-Time Chart Rendering
Given new messaging events occur When messages are sent or responses received Then the real-time charts update within 5 seconds without requiring a page reload
Date Range Filtering Functionality
Given a selected date range on the dashboard When the user applies the filter Then only metrics corresponding to that date range are displayed and correct totals are recalculated
Report Export Capability
Given the user clicks the Export Reports button When export is initiated Then a CSV file is generated containing all displayed metrics and is available for download within 10 seconds
User Interface Responsiveness
Given the dashboard is accessed on desktop and mobile devices When the screen size changes Then all UI elements adapt correctly without overlap or loss of functionality

PromoPulse Offers

Embeds dynamic, sentiment-based promotions or discount codes into post-checkout messages. Guests who express high satisfaction receive VIP perks, while neutral or critical feedback triggers targeted incentives, turning mixed reviews into loyalty-building opportunities.

Requirements

Real-time Sentiment Analysis
"As a hotel manager, I want guest feedback to be analyzed in real time so that I can trigger appropriate promotions based on their satisfaction level immediately after checkout."
Description

Implement an automated natural language processing engine that evaluates guest feedback immediately upon submission, classifying responses as positive, neutral, or negative. The system must integrate with the existing Guestify feedback pipeline, support continuous learning to improve accuracy, and provide real-time sentiment tags that drive the generation of contextually relevant promotions. This capability enables instantaneous, data-driven decision making, ensuring that guests receive personalized offers aligned with their satisfaction level.

Acceptance Criteria
Positive Feedback Triggers VIP Promotion
Given a guest submits feedback that conveys positive sentiment, when processed by the NLP engine, then the feedback is tagged 'positive' within 2 seconds and a VIP promotion code is generated and attached to the post-checkout message.
Neutral Feedback Suggests Incentive Offer
Given a guest submits neutral sentiment feedback, when evaluated by the NLP engine, then the feedback is tagged 'neutral' within 2 seconds and a tailored discount offer of at least 10% off is generated.
Negative Feedback Prompts Immediate Alert
Given a guest submits negative sentiment feedback, when analyzed by the NLP engine, then the feedback is tagged 'negative' within 2 seconds and a real-time alert is sent to the manager via email or in-app notification.
Multilingual Feedback Classification
Given feedback is submitted in a non-English language, when processed by the NLP pipeline, then the message is automatically translated, classified with at least 90% accuracy, and tagged within 3 seconds.
Continuous Model Learning Update
Given new labeled feedback data is added daily, when the continuous learning pipeline retrains the model, then the production model's sentiment classification accuracy does not degrade by more than 2% and the updated model is deployed within a 4-hour maintenance window.
Dynamic Promotion Generator
"As a marketing manager, I want promotions to be automatically generated based on guest sentiment so that I can convert neutral or critical feedback into loyalty-building offers without manual intervention."
Description

Develop a rules-driven engine that creates and assigns unique promotion or discount codes based on the sentiment category of each guest’s feedback. The generator must support configurable promotion templates (e.g., VIP perks for positive sentiment, targeted incentives for neutral or critical sentiment), ensure code uniqueness, enforce usage limits, and integrate seamlessly with the hotel’s existing reservation and billing systems. This system transforms feedback insights into tailored offers that encourage repeat bookings and guest loyalty.

Acceptance Criteria
VIP Perk for Positive Feedback
Given the guest feedback sentiment is classified as 'positive' When the Dynamic Promotion Generator processes the feedback Then the system generates a promotion code using the VIP perks template and assigns it to the guest's reservation with a valid expiration date
Targeted Incentive for Neutral Feedback
Given the guest feedback sentiment is classified as 'neutral' When the Dynamic Promotion Generator processes the feedback Then the system generates a promotion code using the neutral sentiment template and links it to the guest's reservation record
Discount Offer for Critical Feedback
Given the guest feedback sentiment is classified as 'critical' When the Dynamic Promotion Generator processes the feedback Then the system generates a promotion code using the critical response template and attaches it to the guest's reservation record
Promotion Code Uniqueness Enforcement
Given multiple feedback entries are processed concurrently When promotion codes are generated for each feedback Then every promotion code must be unique across all existing codes and stored without duplication
Promotion Code Usage Limit Enforcement
Given a guest attempts to redeem an assigned promotion code When the guest redeems the code Then the system enforces the predefined usage limit (e.g., one-time use per guest per stay) and rejects any further redemption attempts with an appropriate error message
Post-Checkout Message Integration
"As a guest, I want to receive a clear and visually engaging message containing my promotion immediately after checking out so that I can easily redeem the offer on my next stay."
Description

Extend the post-checkout messaging module to embed dynamically generated promotions within the automated thank-you notifications sent to guests. Messages must be formatted for mobile display, support rich text and emojis, and include clear call-to-action buttons linking to promotional codes or booking confirmation pages. The integration should leverage existing messaging APIs, ensure deliverability across multiple channels (e.g., SMS, email, in-app notifications), and maintain consistency with brand guidelines.

Acceptance Criteria
Embedding Promotions in SMS Thank-You Messages
Given a guest completes checkout and provides feedback, when the post-checkout SMS is generated, then the message includes a dynamically selected promotion based on the guest's sentiment, formatted with rich text and emojis, and a CTA button linking to the promotional code or booking page.
Email Notification with Rich Text and Emojis
Given a guest completes checkout, when the post-checkout email is sent, then the email content uses the brand-approved rich text styling and emojis, displays the correct promotion code, and includes a clickable CTA that redirects to the booking confirmation page.
In-App Notification Deliverability Across Channels
Given multiple messaging channels are configured (SMS, email, in-app), when the post-checkout notification is dispatched, then the system attempts delivery on all channels and logs success or failure statuses for each channel, ensuring at least one channel delivers the message.
Brand Consistency in Promotional Messages
Given the brand guidelines specify font, color, and tone, when generating a promotional post-checkout message, then the styling and language of the message strictly adhere to these guidelines for all channels.
Real-Time Translation of Promotions
Given a guest's preferred language differs from the default, when composing the post-checkout message with a promotion, then the promotion text and CTA label are automatically translated in real-time to the guest’s language with at least 95% translation accuracy.
Successful API Integration for Message Dispatch
Given the messaging API credentials are configured, when the system invokes the API to send a promotion-laden post-checkout message, then the API call returns a 200 OK response and the message ID is logged in the system database.
VIP Perk Assignment Logic
"As a returning guest, I want my consistently positive feedback to be recognized with VIP perks so that I feel valued and am motivated to book again."
Description

Create a decision framework that identifies high-satisfaction guests (e.g., guests with consistently positive or 5-star emoji feedback) and elevates them to VIP status for exclusive perks. The logic must track guest tier eligibility criteria, record historical feedback trends, and automatically assign higher-value rewards or upgrades (e.g., room upgrades, free amenities). It should integrate with the guest profile database and loyalty management system to ensure personalized treatment in future stays.

Acceptance Criteria
Elevating Guest to VIP Based on Consecutive Positive Feedback
Given a guest has submitted three consecutive stays with 5-star emoji feedback When the system runs the nightly feedback evaluation Then the guest’s profile VIP status is set to true and a room upgrade perk is queued for delivery
VIP Assignment Triggered by Average Satisfaction Score
Given a guest’s average satisfaction score over the past 30 days is 4.5 or higher When the system processes monthly feedback trends Then the guest is assigned VIP status and a corresponding perk tier is generated
Excluded Guests with Recent Negative Feedback
Given a guest has provided neutral or negative emoji feedback in two or more stays within the last 30 days When the system evaluates VIP eligibility Then the guest is not elevated to VIP status regardless of other positive feedback
VIP Status Persistency Across Future Stays
Given a guest has been assigned VIP status When the guest makes a subsequent booking Then the booking confirmation automatically includes VIP-exclusive amenities and perks
Seamless Integration with Loyalty Management System
Given VIP assignment logic updates a guest’s profile When the profile update is committed Then the loyalty management system reflects the new VIP status within five minutes
Multilingual Promo Localization
"As an international guest, I want my promotional offer delivered in my native language so that I can fully understand and redeem it without confusion."
Description

Ensure that all promotional offers and messages are automatically translated and localized into the guest’s preferred language in real time. The system should leverage the existing translation engine within Guestify, support over 20 languages, handle language-specific formatting (e.g., date, currency), and allow manual overrides by hotel managers. This requirement guarantees that promotions are culturally appropriate and easily understood by international guests.

Acceptance Criteria
Auto-Translate Promotional Messages
Given a guest’s preferred language is set, when a post-checkout promotion is triggered, then the system must automatically translate the entire promotional message and any discount codes into the selected language with no missing text.
Date and Currency Localization
Given a promotion includes dates or monetary values, when displaying the offer to the guest, then dates must follow the locale’s date format and currency must be displayed using the correct symbol, decimal separators, and placement for that language.
Manual Translation Override
Given a hotel manager views a translated promotion, when they apply a manual override, then their custom translation must replace the automated translation and persist for all future guests using that language until changed again.
Fallback Language Handling
Given a guest’s preferred language is unsupported or translation fails, when a promotion is sent, then the system must default to English, notify the manager of the fallback event in the dashboard, and include a clear note to the guest that English is the displayed language.
Real-Time Translation Performance
Given a promotion is generated at checkout, when translation is requested, then the localized message must be returned within 500ms 95% of the time and within 1 second in all cases.

InsightSnapshot

Generates a concise, visual summary of each guest’s exit feedback—highlighting overall mood, key compliments, and areas for improvement—and delivers it to managers’ dashboards or inboxes. This real-time snapshot streamlines post-stay debriefs and informs quick operational tweaks.

Requirements

Feedback Data Aggregation
"As a hotel manager, I want all guest feedback to be aggregated and standardized instantly so that I can trust the accuracy and completeness of the data powering my InsightSnapshots."
Description

Collect, normalize, and translate emoji-based guest feedback in real time, consolidating responses into a unified dataset that powers the InsightSnapshot feature. This requirement ensures that all guest feedback—regardless of language or platform—is automatically captured, sanitized, and stored in a structured format. The system will handle emoji sentiment mapping, timestamping, and guest identifiers to support downstream analysis and visualization.

Acceptance Criteria
Real-Time Feedback Capture
Given a guest submits emoji feedback via the mobile app, When the submission occurs, Then the system captures the feedback within 2 seconds and stores the raw emoji alongside the guest identifier and timestamp.
Emoji Translation Accuracy
Given an emoji-based feedback from any language, When processed, Then the system translates emoji sentiment into standard English labels with at least 95% accuracy against a manual review baseline.
Feedback Normalization
Given multiple feedback entries in various formats, When processed, Then the system normalizes all entries into the defined dataset schema, including guestID, timestamp, emojiCode, and translatedText fields.
Dataset Consolidation
Given feedback inputs from web and mobile platforms, When aggregated, Then the system consolidates them into a single unified dataset without duplicates, preserving data integrity and chronological order.
Sentiment Mapping and Timestamping
Given a feedback entry with an emoji and submission time, When processed, Then the system maps the emoji to a sentiment score between -1 and 1 and records the timestamp in ISO 8601 format.
Mood Visualization Charts
"As a hotel manager, I want visual charts that show guest mood trends so that I can quickly understand how satisfaction levels change over time."
Description

Generate interactive, color-coded charts that depict overall guest mood trends over a specified time frame. This requirement covers the design and implementation of bar graphs, line charts, and heatmaps that clearly illustrate positive, neutral, and negative sentiment distributions. Integrating seamlessly with the aggregated feedback dataset, these visualizations will allow managers to quickly gauge mood shifts and identify peak satisfaction or dissatisfaction periods.

Acceptance Criteria
Viewing 7-Day Mood Trends
Given the manager selects the past 7 days view, when the system renders the bar graph, then it displays counts of positive, neutral, and negative feedback for each day with green, yellow, and red colors respectively.
Filtering by Custom Date Range
Given the manager inputs a custom start and end date, when the system generates the line chart, then it plots daily sentiment scores within the range with correct date labels and consistent color coding.
Drilling Down Daily Sentiment Distribution
Given the manager clicks on a specific day’s bar in the mood chart, when the drill-down action triggers, then the system displays an hourly sentiment heatmap for that day with accurate color intensity based on feedback counts.
Highlighting Peak Negative Periods
Given multiple days of feedback data, when the heatmap is rendered, then the time slots with the highest negative sentiment are marked in the darkest red shade and labeled with the corresponding time period.
Exporting Mood Charts
Given the manager clicks the export button, when they select an image format (PNG or JPG), then the system downloads the currently viewed chart as a high-resolution image preserving all colors, labels, and data points.
Key Highlights Extraction
"As a hotel manager, I want the system to highlight the most frequent compliments and concerns so that I can address critical issues without sifting through raw feedback."
Description

Automatically extract and summarize the top three compliments and top three improvement areas from each guest’s feedback using natural language processing techniques. This requirement will enable the system to identify recurring themes, categorize feedback into positive and negative sets, and surface the most impactful comments in the InsightSnapshot summary. It enhances manager focus on high-priority operational tweaks.

Acceptance Criteria
Extraction of Top Three Compliments
Given a guest feedback containing at least three positive sentiments, When NLP processes the feedback, Then the system extracts the three most impactful compliments ranked by sentiment strength.
Extraction of Top Three Improvement Areas
Given a guest feedback containing at least three negative sentiments or suggestions, When NLP processes the feedback, Then the system extracts the three most critical improvement areas ranked by severity.
Sentiment Categorization Accuracy
Given the extracted comments, When the system categorizes them, Then 100% of compliments are tagged as positive and 100% of improvement areas are tagged as negative.
Multilingual Feedback Handling
Given feedback written in a non-English language, When the system receives the input, Then it automatically translates the feedback and accurately extracts top three compliments and improvement areas with equal accuracy to English inputs.
InsightSnapshot Display Integration
Given the processed guest feedback, When the InsightSnapshot summary is generated, Then the extracted top three compliments and improvement areas appear in the manager’s dashboard and inbox within 30 seconds of feedback submission.
Instant Snapshot Delivery
"As a hotel manager, I want to receive a concise feedback snapshot immediately after a guest checks out so that I can act on issues before they escalate."
Description

Deliver the generated InsightSnapshot to managers via their preferred channels (dashboard, email, or in-app notification) within 60 seconds of feedback submission. This requirement ensures low latency end-to-end processing, from ingestion and analysis to delivery. It covers queue management, retry logic for failures, and channel-specific formatting to maintain consistency and reliability of real-time alerts.

Acceptance Criteria
In-App Notification Delivery
Given a guest submits feedback, when the InsightSnapshot is generated, then an in-app notification appears on the manager’s mobile app within 60 seconds of submission.
Email Delivery to Manager’s Inbox
Given a manager has selected email as the preferred channel, when feedback is submitted, then the InsightSnapshot email is delivered to the manager’s inbox within 60 seconds, with the subject line prefixed by “[Guestify Snapshot]” and including the guest’s name, overall mood emoji, and key insights in the email body.
Dashboard Update within 60 Seconds
Given a manager is viewing their dashboard, when new feedback arrives, then the InsightSnapshot widget updates automatically without manual refresh, reflecting the new guest’s mood, highlights, and areas for improvement within 60 seconds of feedback submission.
Automatic Retry Logic on Delivery Failure
Given a transient delivery error (e.g., network timeout) occurs, when the system attempts to send the InsightSnapshot, then it retries delivery up to three times with exponential backoff and logs each retry attempt; if all retries fail, an alert is created in the error monitoring dashboard.
Consistent Formatting Across Channels
Given multiple delivery channels (in-app notification, email, dashboard) are used, when the InsightSnapshot is delivered, then the layout, color scheme, emoji set, and summary structure remain consistent across all channels.
Dashboard Integration API
"As a technical administrator, I want an API to retrieve InsightSnapshots so that I can integrate reports into our existing management dashboard."
Description

Provide a secure, well-documented REST API that allows the hotel's management dashboard to fetch InsightSnapshots on demand. This requirement specifies authentication methods, rate limits, data schemas, error handling, and versioning guidelines. It will enable third-party dashboard vendors or custom in-house solutions to embed snapshot data natively, ensuring consistent user experience across platforms.

Acceptance Criteria
API Authentication Request
Given valid API credentials are provided in the Authorization header When a GET request is made to /api/v1/snapshots/{snapshotId} Then the response returns HTTP 200 with a valid JSON payload
Rate Limit Enforcement
Given more than 100 requests are made within one minute to any endpoint When the 101st request is received Then the API responds with HTTP 429 Too Many Requests and includes a Retry-After header
Snapshot Data Schema Validation
When a request is made to fetch an InsightSnapshot Then the JSON response must conform to the documented schema: mood (string), compliments (array of strings), improvements (array of strings)
Handling Non-Existent Snapshot Requests
Given a request with an invalid or non-existent snapshotId When the request is processed Then the API returns HTTP 404 Not Found with error code ERR_SNAPSHOT_NOT_FOUND and an explanatory message
API Version Negotiation
Given the client specifies API version v2 in the Accept header When requesting an InsightSnapshot Then the API responds with HTTP 200 and the response payload includes the v2 schema with the additional "summary" field
Email Notification Templates
"As a hotel manager, I want to customize the look and feel of the feedback snapshot emails so that they reflect my brand identity and are clear to my team."
Description

Design and implement customizable email templates for InsightSnapshot alerts, including branding options, dynamic content placeholders, and responsive layouts. This requirement ensures that emails rendered across devices maintain readability and align with hotel branding. It covers template storage, version control, and an interface for managers to preview and modify template elements before activation.

Acceptance Criteria
Custom Template Branding Application
Given a hotel manager accesses the email template editor, When they select or upload the hotel's logo, color palette, and header/footer images, Then the preview pane displays the template with the applied branding, And the system saves the branding settings persistently for all future alerts.
Template Preview Responsiveness
Given a customized email template, When the manager switches preview modes between desktop (600px width) and mobile (320px width), Then the layout adjusts appropriately without overflow or misalignment, And all text, images, and buttons remain legible and functional.
Placeholder Data Rendering
Given an email template containing dynamic placeholders (e.g., {{guestName}}, {{feedbackMood}}, {{keyCompliments}}), When an InsightSnapshot is generated for a guest, Then the system replaces each placeholder with the corresponding guest data, And the rendered email shows accurate and correctly formatted information.
Version Control Rollback
Given multiple saved versions of an email template, When the manager selects a previous version and clicks "Restore", Then the selected version becomes the active template in both the editor and preview, And the system logs the rollback action with timestamp and user ID.
Template Activation and Delivery
Given an active email template for InsightSnapshot alerts, When a guest checks out and the snapshot is generated, Then the system sends an email using the active template to the manager's configured inbox within 2 minutes, And the email passes standard spam and deliverability checks.

Follow-Up Flow

Schedules automated, multi-channel follow-up emails or SMS messages based on checkout sentiment. Satisfied guests receive review prompts and referral invites, while dissatisfied guests get apology notes and service recovery offers—ensuring every guest feels heard and valued.

Requirements

Sentiment Analysis Integration
"As a hotel manager, I want the system to automatically analyze guest feedback sentiment so that follow-up messages are tailored to guest feelings without manual review."
Description

Implement an automated sentiment analysis module that processes guest feedback patterns using natural language processing to categorize emotions as positive, neutral, or negative. This integration enables the system to trigger targeted follow-up actions based on accurate sentiment detection across multiple languages, improving response relevance and guest satisfaction.

Acceptance Criteria
Multi-language Feedback Processing
Given a guest submits feedback in Spanish, Mandarin, or German When the sentiment analysis module processes the text Then the system categorizes the sentiment as positive, neutral, or negative with at least 90% accuracy
Neutral Sentiment Handling
Given feedback is classified as neutral When the follow-up flow is triggered Then the system sends a neutral acknowledgment message within 5 minutes of checkout and does not send a review prompt or apology
Negative Sentiment Escalation
Given feedback is classified as negative When the sentiment analysis flags the feedback Then the system sends an apology email or SMS within 15 minutes of checkout, logs the issue for service recovery, and notifies the support team
Positive Sentiment Review Prompt
Given feedback is classified as positive When the sentiment analysis completes Then the system sends a review invitation and referral offer via the guest’s preferred channel within 1 hour of checkout
Real-time Sentiment Dashboard Update
Given new feedback entries arrive When the sentiment analysis categorizes each entry Then the analytics dashboard reflects updated positive, neutral, and negative counts within 30 seconds without manual refresh
Multi-Channel Delivery Scheduler
"As a operations coordinator, I want follow-up messages to be sent via the best channel at the right time so that guests are more likely to read and respond."
Description

Develop a scheduling engine that automatically selects and dispatches follow-up communications via email or SMS based on guest preferences, checkout sentiment, and predefined timing rules. This component ensures messages reach guests in their preferred channel at the optimal time to maximize engagement.

Acceptance Criteria
Channel Selection Based on Guest Preference
Given a guest’s preferred communication channel is recorded in their profile When the delivery scheduler initiates a follow-up dispatch Then the message is sent via the recorded preferred channel
Sentiment-Based Message Template Selection
Given the checkout sentiment score is retrieved When the scheduler processes the guest record Then the system selects the positive template for scores ≥4 and the recovery template for scores ≤2
Timing Rule Adherence
Given the guest checkout timestamp is T When the scheduler triggers follow-up Then the message is dispatched between T+2 hours and T+4 hours according to business hours
Multi-Channel Fallback Mechanism
Given the primary delivery attempt fails (bounced email or undelivered SMS) When failure is detected Then the scheduler retries via the alternate channel within 30 minutes
Locale and Language Routing
Given a guest’s language preference is Spanish When constructing the follow-up message Then the scheduler selects and sends the Spanish-language template
Template Customization Engine
"As a marketing manager, I want to customize follow-up message templates so that communications reflect our brand voice and address guests personally."
Description

Create a flexible template system that allows managers to design and customize apology, review request, and referral invite messages with dynamic placeholders (e.g., guest name, stay details). This ensures brand consistency and personalized communication at scale.

Acceptance Criteria
Template Editor Interface Access
Given the hotel manager is logged into the Guestify dashboard, when they navigate to the Template Customization page, then the template editor interface displays options to select message type (apology, review request, referral invite) and a list of existing templates.
Dynamic Placeholder Insertion
Given the manager is editing a message template, when they place the cursor in the message body and choose a dynamic placeholder from the dropdown, then the placeholder (e.g., {{guest_name}}, {{stay_date}}) is inserted at the cursor position and the editor preview updates to show a sample placeholder value.
Template Preview with Live Data
Given the manager has customized the content of a template and clicks the 'Preview' button, when a sample guest record is selected, then the system renders a full message preview replacing all placeholders with actual sample guest data.
Template Saving and Versioning
Given the manager has made changes to an existing template, when they click 'Save', then the system stores the new version, archives the previous version for rollback, and displays a confirmation notification stating 'Template saved successfully.'
Multi-Channel Template Assignment
Given the manager configures the follow-up flow settings, when they assign specific templates for email and SMS channels, then the selected templates are applied correctly to outgoing messages sent via each channel.
Real-Time Delivery Monitoring
"As a support agent, I want to see the live status of follow-up message deliveries so that I can quickly address any failed sends."
Description

Implement a dashboard for tracking the status of all follow-up messages, displaying delivery success rates, open/click metrics, and failure alerts. This monitoring capability helps managers identify and resolve issues in real time to maintain high deliverability.

Acceptance Criteria
Initial Dashboard Load
Given the manager navigates to the Real-Time Delivery Monitoring dashboard When the page loads Then the dashboard displays delivery success rate, open rate, and click rate within 5 seconds
Automatic Metrics Refresh
Given the dashboard is open When 60 seconds pass Then the delivery metrics automatically refresh without a full page reload
Delivery Failure Alert Trigger
Given message delivery failures exceed 5% in any 10-minute window When the threshold is reached Then a visible alert is displayed and emailed to the manager within 1 minute
Click and Open Rate Visualization
Given the manager selects the click or open rate metric When the metric is selected Then a time-series chart appears showing the last 7 days of rates with daily breakdown
Export Delivery Metrics Report
Given the manager clicks the export button When the export is initiated Then a CSV file with timestamped delivery metrics for the selected date range is downloaded within 10 seconds
Service Recovery Workflow
"As a guest relations manager, I want the system to automatically offer recovery options to unhappy guests so that we can resolve issues before they leave negative public reviews."
Description

Design an automated service recovery workflow that proactively issues compensation offers or priority support tickets to dissatisfied guests identified by negative sentiment. This requirement ensures prompt remedial action, fostering guest trust and loyalty.

Acceptance Criteria
Detect Negative Feedback and Initiate Service Recovery
Given a guest submits feedback with a negative emoji, when the system processes the feedback, then the service recovery workflow is triggered within 1 minute and a priority support ticket is created in the hotel's support dashboard.
Automated Compensation Offer Email Delivery
Given a service recovery workflow is triggered for a dissatisfied guest, when the workflow executes, then the guest receives an email with an appropriate compensation offer within 5 minutes and a corresponding entry is logged in the compensation records.
SMS Follow-Up for High-Value Guests
Given a high-value guest with negative sentiment, when the negative feedback is detected, then the system sends an SMS follow-up within 2 minutes including apology and customized service recovery offer, and delivery status is logged.
Priority Support Ticket Assignment
Given the service recovery workflow creates a support ticket, when the ticket is created, then it is automatically assigned to the "Priority Response" queue and tagged with "Service Recovery" label.
Admin Dashboard Notification
Given a support ticket is created for a dissatisfied guest, when the ticket is logged, then the hotel manager receives an in-app notification and an email alert within 1 minute.

LanguageFlair

Auto-detects each guest’s preferred language and translates post-checkout surveys and thank-you messages with cultural nuance. By communicating in guests’ native tongues, hotels break down barriers, enhance perceived care, and boost engagement across diverse audiences.

Requirements

Auto Language Detection
"As a hotel manager, I want the system to automatically detect my guest’s preferred language so that I can send surveys and messages that they can easily understand without additional configuration."
Description

Implement a detection module that automatically identifies each guest’s preferred language using device settings, IP geolocation, and profile preferences. This functionality ensures that post-checkout surveys and thank-you messages are delivered in the guest’s native tongue without manual input, reducing friction and improving engagement across diverse audiences.

Acceptance Criteria
Device Language Detection
Given a guest’s device locale is set to French, when the post-checkout survey page loads, then the survey interface language is French; the language code "fr" is detected within 100ms; no manual language selection is required.
IP Geolocation as Fallback
Given a guest’s device locale is unavailable, when the system cannot read the locale, then the system uses the guest’s IP address to infer location-based language; the inferred language matches a supported language and is applied within 200ms; the survey is displayed without errors.
Profile Preference Override
Given a returning guest with a language preference set to Japanese in their profile, when the survey loads, then the system selects Japanese regardless of device locale or IP geolocation; the preference is honored in 100% of cases.
Unsupported Language Fallback
Given a guest’s detected language is unsupported (e.g., Welsh), when preparing the survey, then the system defaults to English; all survey elements render correctly in English; the fallback occurs without user intervention.
Detection Failure Handling
Given both device locale and IP geolocation detection fail, when the survey is triggered, then the system defaults to English; an alert is logged in the monitoring system; a notification email is sent to the support team within 5 minutes.
Cultural Nuance Translation
"As a returning guest, I want survey questions and thank-you messages to feel natural and culturally appropriate so that I feel genuinely understood and valued."
Description

Integrate an advanced translation engine with context-aware, culturally nuanced translations for survey questions and thank-you messages. The system will handle idiomatic expressions, polite forms, and local dialects to convey genuine care and prevent misinterpretations that could harm guest satisfaction.

Acceptance Criteria
Polite Japanese Survey Translation
Given a survey question in English containing polite tone When a Japanese-preferring guest receives the survey Then the Japanese translation uses keigo forms appropriate for formal guest communication
Regional Spanish Thank-You Message
Given a thank-you message template in English When sent to a guest in Mexico Then the Spanish translation uses Mexican colloquialisms and regional greetings accurately
Idiomatic Expression Handling in French
Given an English survey question containing the idiom "break the ice" When translated for a French-speaking guest Then the translation replaces the idiom with a culturally equivalent French phrase
Local UK English Dialect Survey
Given a survey question in English using standard US English When received by a guest preferring British English Then the text is adapted to use UK spellings and common British terms without altering meaning
Polite Korean Thank-You Note
Given a thank-you message in English When translated for a Korean-preferring guest Then the Korean text uses the honorific speech level suitable for addressing guests in hospitality contexts
Real-Time Translation Preview
"As a hotel manager, I want to review and edit auto-generated translations in real time so that I can ensure each message aligns with my brand’s tone and specific guest context."
Description

Provide a preview interface for hotel managers to review and, if necessary, adjust automated translations before sending. This feature allows managers to fine-tune phrasing, add personal touches, and ensure accuracy in critical communications, enhancing brand voice consistency.

Acceptance Criteria
Post-Checkout Survey Preview
Given a manager has selected a post-checkout survey template and the system has auto-detected the guest's language When the manager clicks the 'Preview Translation' button Then the interface displays the original text and translated text side-by-side within 2 seconds And the translated text matches the output from the translation API
Thank-You Message Preview
Given a manager is viewing a thank-you message template When the manager requests a translation preview Then the interface shows both the original and translated messages in a scrollable view And the translation accurately reflects the guest’s preferred language with cultural nuance
Inline Editing and Saving
Given a manager reviews a translated text in the preview interface When the manager edits any portion of the translated text and clicks 'Save' Then the edited translation is persisted to the message template And the preview updates immediately to reflect the changes
Placeholder and Format Validation
Given a translation containing placeholders like {guest_name} or formatting tags When displayed in the preview interface Then all placeholders and tags appear correctly in both the original and translated texts And placeholders remain non-editable And any formatting tags are preserved exactly
Unsupported Language Error Handling
Given a manager attempts to preview a translation for an unsupported language When the manager clicks 'Preview Translation' Then the interface displays an error message 'Language not supported, please select another language' And the preview pane remains blank
Character Limit Enforcement
Given a translated text exceeds 200 characters in the preview When the manager views the preview Then the exceeded portion is highlighted in red And a warning 'Text exceeds maximum allowed length' is displayed And the 'Send' button is disabled until text length is within limit
Multi-Language Survey Dispatch
"As a front-desk operator, I want surveys to be sent in the guest’s language automatically so that I don’t have to manually segment lists or worry about language mismatches."
Description

Develop survey dispatch logic that automatically selects and sends post-checkout surveys in the detected language, with fallback to a default language if detection fails. This ensures that every guest receives feedback requests in the language they understand best, maximizing response rates and feedback quality.

Acceptance Criteria
Successful Language Detection
Given a guest checks out and their preferred language is detected, When the survey dispatch logic runs, Then the post-checkout survey is sent in the detected language within 5 minutes of checkout.
Fallback to Default Language
Given a guest’s preferred language cannot be detected or is unsupported, When the survey dispatch logic runs, Then the survey is sent in the hotel’s default language.
Translation Verification
Given a survey template exists, When the dispatch logic applies auto-translation, Then each translated survey message is validated against the translation API response and contains no untranslated placeholders.
Retry on Dispatch Failure
Given the initial survey send attempt fails due to network or server error, When the dispatch logic retries, Then the survey is successfully sent within 2 retry attempts spaced 2 minutes apart.
Accurate Survey Logging
Given a survey is dispatched, When the system logs the dispatch event, Then the log entry includes guest ID, language code, timestamp, and survey status.
Personalized Thank-You Messaging
"As a guest, I want to receive a thank-you message in my own language that mentions highlights of my stay so that I feel personally appreciated and more likely to return."
Description

Enable dynamic insertion of guest-specific details (name, stay highlights) into culturally adapted thank-you messages. Messages will be automatically composed in the guest’s language and include personalized elements to reinforce a sense of individual attention and care.

Acceptance Criteria
Guest receives personalized thank-you message with name and stay highlights
Given a guest record with first name and stay highlights, When the thank-you message is composed, Then the message must include the guest's first name and at least one stay highlight in the correct placeholder positions.
System auto-translates messages into guest's preferred language
Given a guest's preferred language is Spanish, When the personalized message is generated, Then the entire message text is translated into Spanish and retains personalization accuracy.
Cultural nuances in translated thank-you messages
Given a guest's preferred language is Japanese, When composing the translated message, Then the translation uses culturally appropriate phrases and honorifics.
Fallback to default language when preferred language unsupported
Given the guest's preferred language is unsupported, When generating the thank-you message, Then the message is composed in English with personalization tokens correctly replaced.
Message length within SMS and email constraints
Given the personalized message content, When the combined name, highlights, and translation are inserted, Then the total character count must not exceed 500 characters for email or 160 characters for SMS.

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Press Coverage

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Guestify Empowers Hoteliers with AI-Driven Multilingual Feedback via SmartFollow and RealTime Linguist

Imagined Press Article

City, State – July 30, 2025 – Guestify, the pioneering mobile app that transforms guest sentiment into actionable insights through emoji-based feedback, today announced the launch of two major AI enhancements: SmartFollow Prompts and RealTime Linguist. These new features work together to deliver deeper, richer feedback from international guests and empower hotel teams to resolve issues faster than ever before. Introduction Guestify has reimagined guest feedback with a playful, emoji-driven system that eliminates language barriers and streamlines real-time issue resolution. With the rollout of SmartFollow Prompts, managers can now deploy dynamic, context-sensitive follow-up questions that adapt to each guest’s initial emoji response. When paired with RealTime Linguist’s bidirectional translation in over 50 languages, these capabilities ensure that hotel teams receive precise, culturally nuanced feedback regardless of the guest’s native tongue. How SmartFollow Prompts Works SmartFollow Prompts uses machine learning to analyze the sentiment behind each emoji and craft the perfect follow-up question. For example, a guest who taps a neutral face emoji when asked about room temperature might receive a tailored question like: “Was your room too warm or too cool this morning?” This context-aware approach increases response depth by 40% on average, according to early beta tests. Breaking Language Barriers RealTime Linguist delivers automatic, bidirectional translation that preserves nuance and context. Guests see prompts in their native language, while managers view instant, accurately translated responses. Whether a guest writes “Il letto era troppo duro” or “床太硬了,” staff receive the same clear message—“The bed was too hard”—eliminating confusion and enabling swift corrective action. Early Adopter Insights “By combining SmartFollow Prompts with RealTime Linguist, we’ve unlocked a new dimension of guest feedback,” said Alex Martinez, CEO of Guestify. “Hoteliers can now drill into sentiment drivers with unprecedented clarity and respond in real time, regardless of cultural or linguistic differences.” Independent hotel manager Anna Garcia from The Coastal Inn adds, “Before Guestify’s AI enhancements, our non-English speaking guests often left vague or no comments. Now we fix issues on the spot, translating their responses instantly and delivering personalized service that earns five-star reviews.” Impact on Guest Satisfaction Guestify’s latest features are designed to reduce negative reviews and increase repeat bookings. By guiding guests through frictionless micro-surveys and translating every response accurately, hotels can intervene before minor concerns escalate. Early metrics indicate a 25% drop in negative online reviews and a 15% boost in repeat stays among properties using the new features. Availability and Pricing SmartFollow Prompts and RealTime Linguist are available immediately to all Guestify subscribers at no additional cost for the first six months. Starting January 2026, these AI-driven tools will be included in the Premium and Enterprise plans. Interested managers can sign up for a free 30-day trial at www.guestify.com/free-trial. About Guestify Guestify empowers independent hoteliers to collect instant, emoji-based guest feedback—regardless of language—via a playful mobile app with automatic real-time translation. Managers spot and resolve issues on the spot, boosting guest satisfaction, minimizing negative reviews, and turning diverse feedback into more personalized stays that drive loyal, repeat bookings. Media Contact: Emily Chen Director of Communications, Guestify email: emily.chen@guestify.com phone: +1 (555) 123-4567 website: www.guestify.com

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Guestify Unveils ShiftSuggester and ForecastFix to Proactively Optimize Guest Experiences

Imagined Press Article

City, State – July 30, 2025 – Guestify, the industry-leading feedback platform for independent hoteliers, today introduced two groundbreaking AI features—ShiftSuggester and ForecastFix—designed to help managers anticipate guest needs, allocate resources effectively, and prevent service gaps before they occur. Overview Building on its success in real-time emoji-based feedback, Guestify now adds predictive intelligence to its toolkit. ShiftSuggester leverages historical and live sentiment data to recommend optimal staffing levels, amenity adjustments, and service tweaks for each shift. ForecastFix uses advanced predictive modeling to identify potential pain points for the coming weeks and propose preventative measures, ensuring hoteliers stay one step ahead of guest expectations. Smart Staffing with ShiftSuggester ShiftSuggester analyzes mood heatmaps, peak check-in times, and past incident patterns to generate daily staffing recommendations. For instance, if multiple rooms recorded “neutral” or “sad” emojis around breakfast service in the past two weeks, the feature will suggest adding an extra server or extending breakfast hours. This data-driven approach can reduce staff burnout and improve guest satisfaction by up to 20%, according to initial trials. Preventative Action via ForecastFix ForecastFix examines seasonality trends, local events, and past feedback to predict upcoming service challenges. Before a major conference in town, ForecastFix might flag potential pressure on housekeeping and recommend preemptive team training or temporary contract hires. By addressing these issues ahead of time, hoteliers can avoid last-minute scrambles and deliver seamless experiences that delight guests. Executive Perspective “Proactive management is the key to exceptional hospitality,” said Guestify CTO Priya Desai. “With ShiftSuggester and ForecastFix, we’re giving hotel teams the foresight they need to staff smarter, allocate resources strategically, and continuously elevate their service standards.” Case Study: The Alpine Retreat The Alpine Retreat, a 15-room boutique lodge in Colorado, piloted the new features over the winter season. Manager Luke Thompson reports, “ShiftSuggester helped us balance front-desk coverage during a busy ski weekend, and ForecastFix alerted us to staffing risks around New Year’s Eve. As a result, our guest satisfaction scores climbed by 18% compared to last winter.” Pricing and Availability Both ShiftSuggester and ForecastFix are now available to Guestify Enterprise subscribers. Existing Premium users can upgrade to access these AI-driven recommendations starting at $199 per month. Guestify also offers customized implementation support and training for teams of all sizes. About Guestify Guestify empowers independent hoteliers to collect instant, emoji-based guest feedback—regardless of language—via a playful, mobile app with automatic real-time translation. Managers spot and resolve issues on the spot, boosting guest satisfaction, minimizing negative reviews, and turning diverse feedback into more personalized stays that drive loyal, repeat bookings. Media Contact: Michael Alvarez Head of Public Relations, Guestify email: michael.alvarez@guestify.com phone: +1 (555) 987-6543 website: www.guestify.com

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Guestify Expands into Europe with Localized Support and SeasonSync for Seasonal Operators

Imagined Press Article

City, Country – July 30, 2025 – Guestify, the platform revolutionizing guest feedback for independent hoteliers, today announced its official expansion into the European market. To support seasonal operators and boutique hotels across the region, the company is launching localized language packs, region-specific analytics, and its innovative SeasonSync feature to help hosts adapt offerings based on holidays, events, and local travel patterns. European Launch and Localization Guestify’s expansion brings full support for 12 additional European languages, including German, French, Spanish, Italian, Swedish, Dutch, Portuguese, Polish, Greek, Norwegian, Danish, and Finnish. Each language pack includes culturally nuanced translations for prompts and AI-generated thank-you messages. Guests will receive surveys in their mother tongue, while managers enjoy instant, accurate translations. Adapting to Seasonal Trends with SeasonSync SeasonSync is a powerful analytics module that correlates collected emoji feedback with seasonal events such as summer festivals, ski season, holiday markets, and local conferences. By overlaying sentiment trends against event calendars, hosts can fine-tune amenities, staffing, and promotions to match guest expectations. For example, a seaside inn in Spain could identify a spike in “sad” emojis during midsummer due to limited evening entertainment and respond by partnering with local entertainers. Support for Seasonal Operators Seasonal Operator Maria Lund of Fjordside Cottages in Norway tested SeasonSync during the busy summer months. “SeasonSync highlighted low guest mood around mid-July when local guides took breaks,” she says. “We arranged extra boat tours on demand, and our guest satisfaction jumped 30% in three weeks.” Strategic Partnership Network To ensure seamless onboarding, Guestify has teamed up with European hospitality associations and regional tech integrators. New partners like EuroStay Solutions and Alpine Innovate will provide training, installation support, and customized consultation for hoteliers adopting the platform. Local Data Compliance and Security Guestify’s European services adhere to GDPR and local data protection regulations. All feedback data is stored in regionally certified data centers, and hotel managers retain full control over information retention and access policies. Availability and Pricing The localized European package, including SeasonSync, is available now with regional pricing starting at €49 per property per month. Early adopters can benefit from waived setup fees and a complimentary three-month trial. Sign-up and more information are available at www.guestify.com/europe. About Guestify Guestify empowers independent hoteliers to collect instant, emoji-based guest feedback—regardless of language—via a playful, mobile app with automatic real-time translation. Managers spot and resolve issues on the spot, boosting guest satisfaction, minimizing negative reviews, and turning diverse feedback into more personalized stays that drive loyal, repeat bookings. Media Contact: Charlotte Moreau EMEA Communications Lead, Guestify email: charlotte.moreau@guestify.com phone: +44 20 7946 0123 website: www.guestify.com/europe

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