Podcast Management SaaS

ChirpFlow

Podcast Guests, Perfectly Prepped. Always.

ChirpFlow streamlines podcast guest management for independent hosts by automating scheduling, episode tracking, and guest preparation. Designed for creators overwhelmed by messy inboxes and spreadsheets, it delivers instant, branded prep packets and podcast-specific workflows that slash no-shows, save hours each week, and keep every episode organized from booking to showtime.

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ChirpFlow

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 indie podcaster to create, connect, and grow fearlessly through seamless, automated show management worldwide.
Long Term Goal
Empower 10,000+ independent podcasts globally to increase episode output by 25% and cut guest no-shows in half within 5 years through seamless, automated show management.
Impact
Cuts guest booking and prep time by 60% for independent podcast hosts, lowers guest no-shows by 40%, and enables creators to release 25% more episodes annually through automated, podcast-specific workflows—eliminating scheduling chaos and driving more consistent, high-quality show production.

Problem & Solution

Problem Statement
Independent podcast hosts waste hours juggling guest schedules, episode tracking, and prep emails because generic booking tools lack podcast-specific workflows, leading to disorganized episodes, communication gaps, and frequent guest no-shows that undermine show quality and consistency.
Solution Overview
ChirpFlow automates podcast guest scheduling and delivers instant, branded prep packets, replacing manual emails and messy spreadsheets. Its podcast-specific workflow ensures every episode is organized and every guest arrives fully prepared, cutting no-shows and saving hosts hours per week on coordination.

Details & Audience

Description
ChirpFlow automates guest scheduling, episode tracking, and feedback for indie podcast hosts. Designed for independent creators who want efficiency without complexity, it slashes no-shows and communication lag by delivering personalized, branded prep packets instantly to guests. Unlike generic scheduling tools, ChirpFlow features podcast-specific workflows that keep every episode organized and every guest experience seamless from booking to showtime.
Target Audience
Independent podcast hosts (22-45) craving streamlined guest management to minimize chaos and maximize show quality.
Inspiration
Sitting beside my friend, I watched her frantically juggle guest emails, bios, and color-coded spreadsheets just to line up a single podcast episode. Each ping of her phone brought more confusion and last-minute scrambles. In that moment, I saw how indie hosts need more than a calendar—a dedicated tool to prep, organize, and delight guests so creators can focus on great conversations, not chaos.

User Personas

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

E

Efficient Emma

- Age 30-45 - Mid-level marketing manager and weekend podcaster - Income $60K-$80K annually - Bachelor's degree in Communication - Suburban location

Background

Emma started her career in corporate marketing, where she mastered project management and email chaos. After launching her biweekly podcast on work-life balance, she struggled with guest coordination amid her busy schedule. Her corporate discipline and craving for order drive her to seek automated, reliable tools.

Needs & Pain Points

Needs

1. Automated guest scheduling without manual follow-ups 2. Centralized episode tracking with calendar sync 3. Instant branded prep packets for guests

Pain Points

1. Double-booked guests due to manual scheduling mix-ups 2. Lost emails hiding crucial prep details 3. Missed episode deadlines from chaotic workflows

Psychographics

- Fiercely deadline-driven, loathes wasted minutes - Champions precision and seamless workflows - Craves automated routines, avoids manual chaos - Finds satisfaction in orderly processes

Channels

1. Gmail - primary booking hub 2. Google Calendar - real-time schedule sync 3. Slack - quick host-guest chats 4. LinkedIn - professional outreach 5. Instagram - casual guest engagement

G

Growth Greg

- Age 25-35 - Full-time podcaster and content strategist - 50K+ monthly downloads - Urban tech hub location

Background

Greg began as a social media marketer, mastering A/B tests and growth hacks. After launching his startup-focused podcast, he learned to pivot content based on listener data. His data-driven mindset shapes every scheduling and guest choice.

Needs & Pain Points

Needs

1. Analytics dashboard showing guest performance 2. Integration with social platforms for metrics 3. Automated outreach to high-influence prospects

Pain Points

1. Lack of unified guest performance metrics 2. Manual outreach wastes growth momentum 3. Inconsistent host-guest scheduling delays episodes

Psychographics

- Obsessively data-driven, chases measurable growth - Values influencer reach and episode virality - Thrives on continuous optimization and testing - Feels validated by subscriber spikes

Channels

1. Twitter - influencer outreach 2. LinkedIn - professional networking 3. Chartable - performance tracking 4. Zapier - automation hub 5. YouTube - snippet sharing

C

Collaborative Chloe

- Age 28-40 - Freelance journalist and co-host - Project-based income $40K–$70K - Remote small town location

Background

Chloe began in local radio, producing community stories and pairing presenters. Transitioning to podcasts, she formed partnerships with fellow creators, tackling coordination pains manually. Her passion for collective storytelling fuels her search for streamlined collaboration tools.

Needs & Pain Points

Needs

1. Shared editing and prep access for all collaborators 2. Unified communication threads per episode 3. Status tracking for each co-host task

Pain Points

1. Misaligned prep leading to off-topic discussion 2. Fragmented conversations across multiple apps 3. Unclear task ownership delaying episode delivery

Psychographics

- Passionate about collective storytelling and shared ownership - Seeks harmony in multi-voice workflows - Values transparency among co-hosts and guests - Enjoys creative brainstorming sessions with partners

Channels

1. Slack - collaborative threads 2. Google Docs - shared notes 3. Zoom - live prep calls 4. Trello - task boards 5. Email - formal updates

B

Brand-Building Ben

- Age 35-50 - Entrepreneur and podcast host - $100K+ annual income - Partners with 3–5 brands per season

Background

Ben started as a startup founder, mastering brand storytelling and sponsor relations. He launched his podcast to deepen audience trust and boost partner ROI. Needing polished materials, he seeks tools to automate branding consistency throughout his guest coordination.

Needs & Pain Points

Needs

1. Customizable branded prep packet templates 2. Analytics for sponsor exposure tracking 3. Quick branding updates across episodes

Pain Points

1. Inconsistent brand visuals across guest materials 2. Manual template edits slow episode turnover 3. Lack of sponsor performance feedback loops

Psychographics

- Obsessed with brand voice and visual identity - Values sponsor satisfaction and measurable ROI - Seeks polished, professional presentation every time - Enjoys crafting cohesive marketing narratives

Channels

1. Canva - template design 2. LinkedIn - sponsor networking 3. Email - formal communications 4. Twitter - audience announcements 5. Google Analytics - performance tracking

T

Tech-Savvy Sam

- Age 22-35 - Developer and independent podcaster - Tech stack: Zapier, Airtable, APIs - Major tech hub city location

Background

Sam studied computer science and built custom bots for social media automation. He started his tech insights podcast to share coding tutorials, manually writing integration scripts. Seeking efficiency, he hunts for platforms that natively support his automated workflows.

Needs & Pain Points

Needs

1. Native API webhooks for custom automations 2. Detailed event triggers for workflow scripting 3. Exportable logs for integration debug analysis

Pain Points

1. Limited webhook events hinder advanced automations 2. API rate limits slow batch processing 3. Fragmented logs complicate troubleshooting processes

Psychographics

- Embraces experimental integrations and hacky solutions - Lives for API-driven efficiency and customization - Values open-source culture and community contributions - Thrives on tech challenges and rapid iterations

Channels

1. GitHub - code collaboration 2. Zapier - integration hub 3. Stack Overflow - troubleshooting queries 4. Twitter - tech community 5. Reddit - podcast dev discussions

Product Features

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

Ninja Nudge

Delivers personalized AI-driven reminders via email, SMS, and in-app alerts at optimal times—24 hours, 1 hour, and 10 minutes before the session—to keep guests informed and engaged, dramatically reducing forgetfulness and last-minute drops.

Requirements

Multi-channel Reminder Delivery
"As a podcast host, I want reminders sent across multiple channels so that I can ensure guests receive notifications in their preferred medium."
Description

Deliver reminders via email, SMS, and in-app alerts at predefined intervals (24 hours, 1 hour, and 10 minutes before the session). Ensure seamless integration with third-party messaging services, handle opt-ins and fallback channels, and guarantee message consistency across all delivery methods.

Acceptance Criteria
24-Hour Email Reminder Delivery
Given a podcast session is scheduled and the guest has opted in to email reminders When the system time equals exactly 24 hours before the session start Then the system sends a branded email reminder to the guest's email address containing session title, date/time, join link, and personalized greeting and logs a successful delivery status.
1-Hour SMS Reminder Delivery
Given the guest has a valid phone number and has opted in to SMS reminders When the system time equals exactly 1 hour before the session start Then the system sends an SMS reminder via the integrated SMS service with session details, host name, and a call-to-action link and records delivery confirmation.
10-Minute In-App Alert Delivery
Given the guest is logged into the application When the system time reaches 10 minutes before the session start Then an in-app push notification appears instantly on the guest's device displaying the session title, countdown timer, and direct access button to join the session and logs user interaction metrics.
SMS Failure Fallback to Email
Given an SMS reminder fails to deliver due to carrier error or invalid number When the system detects the failure then within 5 minutes the system automatically sends an email reminder to the guest's registered email address with the same content, updates the fallback history log, and notifies the admin dashboard of the fallback event.
Guest Opt-In Handling and Unsubscribe Compliance
Given a guest updates their communication preferences When the guest opts out of SMS or email reminders Then the system must cease sending reminders via that channel, respect the guest’s preference, ensure no further messages are dispatched, and record the preference change in the audit logs.
AI-driven Timing Optimization
"As a guest, I want reminders sent at times based on my habits so that I am less likely to miss my session."
Description

Utilize AI algorithms to analyze guest time zones, historical engagement patterns, and response behavior to determine the optimal send times for each reminder interval. Continuously learn from new data to refine scheduling and maximize open rates while respecting timezone and local preferences.

Acceptance Criteria
Determining Timezone-Based Reminder Send Time
Given a guest with a registered timezone, when scheduling reminders for a confirmed session, then the system calculates and schedules reminder emails, SMS, and in-app alerts exactly 24 hours, 1 hour, and 10 minutes before the session start time in the guest’s local timezone.
Personalized Engagement Pattern Optimization
Given historical open and click-through data for a guest, when generating the reminder send schedule, then the AI algorithm selects the specific hour within each reminder window that maximizes the guest’s past engagement probability.
Respecting Local Preferences and Holidays
Given a guest’s locale and public holiday calendar, when determining reminder send times, then the system avoids sending reminders during known local holidays and outside the hours of 8:00 AM to 8:00 PM in the guest’s local timezone.
Continuous Learning and Schedule Refinement
Given new engagement data from sent reminders, when 24 hours have passed since the session, then the AI updates the guest’s timing optimization model and adjusts future reminder schedules accordingly within 12 hours.
Fallback Mechanism for Data Insufficiency
Given insufficient or no historical engagement data for a guest, when optimizing send times, then the system defaults to sending reminders at 9:00 AM local time for the 24-hour interval, and at the exact 1-hour and 10-minute marks before the session start in the guest’s local timezone.
Personalized Message Content
"As a podcast host, I want reminder messages personalized to each guest so that they feel engaged and prepared for the session."
Description

Dynamically generate reminder messages with guest-specific details such as name, session title, date, time, and customized preparation notes. Incorporate host branding elements and personalized calls-to-action to increase engagement and readiness.

Acceptance Criteria
Email Reminder with Personalized Guest Details
Given a podcast session scheduled 24 hours ahead When the system generates the email reminder Then it includes the guest’s full name, session title, date, time, host’s branded header, and customized preparation notes, and the subject line reads “Reminder: [Session Title]”
SMS Reminder with Dynamic Content
Given a podcast session scheduled 1 hour ahead When the system sends the SMS reminder Then it contains the guest’s first name, session title, start time, and a shortened link to the prep packet using the host’s domain
In-App Alert with Session Details
Given a podcast session 10 minutes away When the guest opens the app Then they see an alert displaying their name, session title, and a “Join Now” button styled with the host’s color palette
Branded Template Rendering
Given any reminder channel When the system renders the message template Then it applies the host’s logo, color scheme, and font settings consistently across email, SMS, and in-app alerts
Personalized Call-to-Action Inclusion
Given a generated reminder message When the guest views the reminder Then it features a call-to-action button or link labeled with context-specific text (e.g., “Review Prep Notes,” “Confirm Attendance”) that directs to the appropriate resource
Template Management Interface
"As a podcast host, I want an easy interface to craft and manage reminder templates so that my notifications stay on brand and relevant."
Description

Provide a user-friendly UI for hosts to create, edit, and manage branded reminder templates for email, SMS, and in-app alerts. Support placeholder variables, real-time previews, version control, and channel-specific formatting guidelines.

Acceptance Criteria
Creating a New Email Template
Given the host is on the 'New Template' screen and selects 'Email' as the channel When the host enters a template name, subject line, and body content And chooses branding options (logo and color scheme) And inserts placeholder variables from the dropdown Then the host can click 'Save' and the system stores the template within 2 seconds And the new email template appears in the template list with the correct name and channel label
Editing an Existing SMS Template
Given a saved SMS template exists in the template list When the host clicks 'Edit' on the desired SMS template Then the interface loads the template name and body pre-populated in edit fields And the host can modify text and insert or remove placeholder variables And clicking 'Save' updates the template immediately, reflecting the new content and timestamp in the list
Previewing In-App Alert Template with Placeholders
Given the host has created or edited an in-app alert template When the host clicks 'Preview' Then the system displays a real-time rendered preview using sample data for each placeholder And the preview matches the configured branding (font, colors, logo) And updates instantly as the host modifies content or placeholder values
Managing Template Version History
Given a template has multiple saved versions When the host selects 'Version History' for that template Then the system lists all versions with date, time, and author details And the host can click 'Compare' to view content differences side by side And the host can restore any previous version, making it the current active template
Applying Channel-Specific Formatting Guidelines
Given the host selects a channel type when creating or editing a template When 'SMS' is selected Then the content editor enforces a 160-character limit and displays remaining characters And disables unsupported formatting like HTML tags or images When 'Email' is selected Then the content editor provides an HTML formatting toolbar and allows up to 10,000 characters
Delivery Monitoring and Reporting
"As a podcast host, I want to monitor and analyze reminder performance so that I can adjust strategies to reduce no-shows."
Description

Track reminder delivery statuses, open rates, click-through metrics, and no-show correlations. Offer a dashboard with visualizations and exportable reports to help hosts analyze performance and optimize their guest communication strategy.

Acceptance Criteria
Delivery Status Dashboard Overview
Given the host navigates to the Delivery Monitoring dashboard When the page loads Then real-time delivery statuses for all reminders sent in the past 30 days are displayed with timestamps and channel indicators
Open Rate and Click-through Metrics Visualization
Given the host selects a date range on the dashboard When data is fetched Then the dashboard displays accurate open rates and click-through percentages in graphical form with tooltips showing exact values
No-show Correlation Analysis Report
Given the host filters sessions by no-show occurrence When the filter is applied Then the system shows correlation statistics between reminder engagement and no-show rates with a confidence score
Exportable Report Generation
Given the host clicks the Export button and selects CSV format When the export completes Then a CSV file is downloaded containing columns for date, reminder channel, delivery status, open rate, click-through, and no-show flag
Real-time Data Refresh
Given the host remains on the dashboard for more than five minutes When the auto-refresh timer elapses Then the dashboard data refreshes automatically without page reload and indicates the update timestamp

Auto Slot Filler

Automatically identifies and proposes the next available time slot to guests who miss their appointment, ensuring your calendar stays full without manual intervention and preserving your recording momentum.

Requirements

Missed Appointment Detection
"As a podcast host, I want the system to detect when a guest misses their appointment so that I can proactively fill the slot and avoid downtime."
Description

Automatically monitor scheduled recordings and detect when guests fail to join within a configurable grace period. This function continuously checks appointment statuses, flags no-shows in real time, and triggers downstream workflows for auto slot filling. Integration with the calendar system ensures accurate detection, reduces manual oversight, and maintains recording momentum by immediately identifying gaps that need rescheduling.

Acceptance Criteria
No-Show Detection Within Configurable Grace Period
Given a scheduled recording with a 10-minute grace period configured When the guest has not joined within 10 minutes of the start time Then the system flags the appointment as a no-show in real time
Join Within Grace Period Does Not Trigger No-Show
Given a scheduled recording with a 5-minute grace period configured When the guest joins at minute 4 of the start time Then the system does not flag a no-show and allows the recording session to proceed
Late Arrival After Grace Period Is Handled Correctly
Given a scheduled recording with a 5-minute grace period configured When the guest joins at minute 7 of the start time Then the system clears any no-show flag, marks the session as a late join, and notifies the host
Calendar Update Reflects in No-Show Detection
Given a scheduled recording is rescheduled or canceled in the integrated calendar When the change is processed Then the system updates the appointment status and cancels any pending no-show detection for that slot
Automated Auto Slot Filler Trigger After No-Show
Given an appointment is flagged as a no-show Then the system automatically invokes the auto slot filler workflow within 30 seconds of detection to propose the next available time slot to the guest
Dynamic Availability Retrieval
"As a podcast host, I want the system to fetch my current availability so that proposed time slots are always accurate and conflict-free."
Description

Retrieve and aggregate the host’s up-to-date free time slots across integrated calendar services (e.g., Google Calendar, Outlook) using secure APIs. The requirement ensures the system always proposes valid, conflict-free alternatives, reflecting last-minute changes and synced events. This integration reduces manual calendar checks, enhances accuracy, and streamlines the rescheduling process.

Acceptance Criteria
Initial Free Slot Retrieval
Given the host’s calendar services are connected When the system retrieves free time slots Then it returns all available slots within the next 14 days that do not conflict with any existing events
Conflict Detection and Filtering
Given a time slot overlaps with a newly created event When availability is fetched Then the overlapping slot is excluded from the proposed free slots
Handling Last-Minute Event Changes
Given an event is added or modified after initial availability retrieval When the system refreshes the host’s free slots Then the updated availability excludes any slots now in conflict
Calendar Service Unavailability
Given an API timeout or error from a calendar service When the system attempts to retrieve availability Then it retries the API call up to two times and if still unsuccessful displays a user-friendly error message
Time Zone Consistency
Given the host has events in multiple time zones When aggregating availability Then all proposed slots are normalized to the host’s primary time zone without duplication or offset errors
Automated Rescheduling Proposal
"As a podcast host, I want the system to propose the next available time slot automatically so that I can keep my schedule full without manual effort."
Description

Generate the next optimal available time slot based on host preferences, buffer times, and guest time zones. The system ranks candidate slots, selects the best match, and formats a rescheduling proposal. This feature accelerates guest communication, minimizes decision fatigue, and fills vacated recording slots automatically without host intervention.

Acceptance Criteria
Missed Appointment Rescheduling
Given a guest misses their scheduled appointment and no host action is taken for 1 hour, When the system runs the rescheduling algorithm, Then it identifies the next optimal slot respecting host preferences and buffer times, and sends a rescheduling proposal email to the guest within 5 minutes.
Time Zone Corrected Proposals
Given the guest's time zone differs from the host's, When the system generates the rescheduling proposal, Then the proposed slot is converted to the guest's local time in the email, with a clear UTC reference, and the email subject indicates the local time.
Buffer Time Enforcement
Given a buffer time of 30 minutes between recordings is configured in host preferences, When selecting the next available slot, Then the system skips any slots that violate the buffer requirement and only proposes slots with at least 30 minutes before and after any existing booking.
Availability Preference Compliance
Given the host has set working hours from 9 AM to 5 PM on weekdays and an exclusion on Wednesdays, When proposing slots, Then the system only selects slots within the specified hours and days, excluding all Wednesday slots.
Calendar Conflict Avoidance
Given the host's calendar has multiple existing events across integrated calendars, When generating candidate slots, Then the system cross-checks all integrated calendars to avoid any overlap and only proposes conflict-free slots.
Guest Notification and Confirmation
"As a podcast host, I want the system to notify guests with new time slot proposals and handle their confirmations so that rescheduling is seamless and requires minimal effort from me."
Description

Automatically send branded, customizable notifications to guests with proposed time slots, including clear call-to-action links for confirmation or alternative suggestions. The workflow tracks guest responses, updates the system status, and triggers follow-ups if no response is received within a set timeframe. This process ensures smooth communication, reduces no-show rates, and enhances guest experience.

Acceptance Criteria
Missed Appointment Slot Proposal
Given a guest misses their confirmed appointment, when the system identifies the next available time slot within 24 hours, then it automatically sends a branded notification with the proposed slot to the guest within 5 minutes of the missed appointment.
Guest Slot Confirmation
Given a guest receives a proposed time slot notification, when the guest clicks the confirmation link, then the system marks the slot as confirmed, updates the calendar, and sends a confirmation email with a calendar invite.
Guest Alternative Suggestion
Given a guest receives a proposed slot but selects 'Suggest alternative', when the guest picks an alternative time, then the system validates availability and confirms the new slot, updating all parties within 5 minutes.
No-Response Follow-Up
Given a guest has not responded to a proposed slot within 24 hours, when the 24-hour window elapses, then the system sends a branded follow-up notification prompting confirmation and logs the follow-up action.
System Status Update
Given any guest response (confirmation, alternative suggestion, or no-response), when the response is processed, then the system updates the internal 'appointment status' field and notifies the host via dashboard update and email summary.
Calendar Synchronization
"As a podcast host, I want confirmed reschedules to sync with my calendar automatically so that I don't have to update multiple systems manually."
Description

Upon guest confirmation, automatically update the host’s calendar and ChirpFlow’s recording schedule. The system must handle event creation, modification, and deletion across integrated calendar services, ensure two-way sync accuracy, and send confirmation notifications to all participants. This feature prevents double-booking, maintains a single source of truth, and streamlines calendar management.

Acceptance Criteria
Guest Confirmation Calendar Event Creation
Given a guest confirms an appointment via ChirpFlow, When the system processes the confirmation, Then a new event is created on both the host’s integrated calendar and ChirpFlow’s schedule with matching title, date, time, duration, and guest details.
Host Calendar Modification Sync
Given the host reschedules or updates event details (time, date, or title) in their external calendar, When the change is detected by ChirpFlow within 2 minutes, Then ChirpFlow updates its recording schedule to reflect new event details without data loss or conflicts.
Calendar Event Deletion Propagation
Given a host or guest cancels an appointment by deleting the event in the integrated calendar, When ChirpFlow receives the deletion webhook, Then the corresponding event is removed from ChirpFlow’s schedule and all participants receive a cancellation notification.
Two-Way Synchronization Integrity
Given simultaneous edits to the same event in ChirpFlow and the host’s calendar, When synchronization runs, Then ChirpFlow resolves conflicts by last-write-wins policy and logs changes, ensuring no double-booking or orphaned events.
Participant Notification on Calendar Change
Given any creation, update, or deletion of a scheduled event through synchronization, When the event change is confirmed in ChirpFlow, Then email notifications with full event details are sent to host and guest within 5 minutes.

Smart Waitlist

Maintains a dynamic waitlist of qualified candidates from past inquiries and previous guests. When a slot opens, top-ranked backups receive instant invites, filling gaps seamlessly and cutting downtime.

Requirements

Candidate Qualification Sync
"As a podcast host, I want the system to automatically identify and sync qualified waitlist candidates based on predefined criteria so that I always have relevant backups ready."
Description

Automatically identifies and syncs qualified candidates from past inquiries and previous guests based on configurable criteria such as topics, expertise, and availability, ensuring the waitlist remains populated with relevant profiles.

Acceptance Criteria
Daily Waitlist Refresh Operation
Given the system’s scheduled sync runs at 00:00 daily When qualification criteria (topics, expertise, availability) are applied Then the waitlist is updated to include only candidates meeting current criteria and outdated entries are archived
Manual Qualification Sync Trigger
Given a host clicks “Sync Qualifications” in the dashboard When the sync request is submitted Then the system completes the sync within 60 seconds and displays counts of added, updated, and removed candidates
Updated Criteria Applied on Next Sync
Given the host modifies qualification settings in their profile When the changes are saved Then the subsequent sync operation uses the new settings to refresh the waitlist accordingly
Real-Time Availability Filtering
Given a candidate’s external availability is updated When the next sync runs Then only candidates available within the next 30 days remain on the waitlist
Sync Error Handling and Alerts
Given a sync operation fails due to data retrieval errors When an error occurs Then the system retries up to three times and sends an email notification to the admin with detailed error information
Dynamic Waitlist Ranking Algorithm
"As a podcast host, I want the waitlist to rank candidates dynamically based on relevant metrics so that the best-fit guests are invited first."
Description

Implements a dynamic ranking system that scores waitlist candidates based on recency, past performance metrics, engagement level, and availability to ensure the most suitable backups are prioritized when slots open.

Acceptance Criteria
Prioritize Recent High-Performing Guests
Given a waitlist of candidates with recorded appearance dates and performance scores When the dynamic ranking algorithm runs Then candidates with more recent appearances and higher performance scores appear above those with older appearances or lower scores
Incorporate Engagement Level into Ranking
Given candidate engagement data including response times and prep packet access rates When the dynamic ranking algorithm computes scores Then candidates with responses within 24 hours and prep packet access rates above 80% receive a 10% score boost
Assess Availability for Open Slot Notification
Given candidates’ synced availability calendars When a slot opens at a specific date and time Then only candidates marked available during that slot timeframe receive an invitation notification
Recalculate Rankings Post-Booking
Given a candidate is confirmed for booking When the booking is finalized Then the booked candidate is removed from the waitlist and the algorithm recalculates the rankings of the remaining candidates
Handle Ties in Candidate Scores
Given two or more candidates share the same composite score When the ranking list is generated Then the candidate with the earliest last appearance date is placed higher in the list
Instant Invite Dispatch
"As a producer, I want the system to send instant, branded invites to backup guests when a slot opens so that recording schedules stay full without delay."
Description

Automatically sends personalized, branded email invitations to top-ranked waitlist candidates immediately when a recording slot becomes available, reducing downtime and manual outreach efforts.

Acceptance Criteria
Immediate Dispatch on Slot Opening
Given a recording slot becomes available, when the system identifies the top-ranked candidate on the waitlist, then a personalized, branded invitation email is dispatched within 5 seconds to the candidate’s registered email address.
Fallback to Next Candidate on Failure
Given the email dispatch to the top-ranked candidate fails (bounce or server error), when the system detects the failure, then it retries once and if still unsuccessful, it automatically sends the invitation to the next-ranked candidate within 10 seconds.
Branding and Personalization Verification
Given a candidate receives an invitation, when the email is opened, then it displays the host’s custom branding (logo, colors) and dynamically inserts the candidate’s name, the podcast title, and the available recording date and time correctly.
Email Delivery Tracking and Notification
Given an invitation email is sent, when the email status changes (sent, delivered, opened), then the system records the event and updates the recording slot dashboard in real time, and notifies the host of delivery and open statuses within 1 minute.
Opt-Out Handling Before Dispatch
Given a candidate has opted out of communications, when a slot opens, then the system excludes the candidate from the dispatch list and immediately selects the next eligible candidate without manual intervention.
Waitlist Management Dashboard
"As a podcast host, I want a visual dashboard showing waitlist details and statuses so that I can monitor and manage backups effectively."
Description

Provides a centralized dashboard where hosts can view real-time waitlist status, candidate rankings, invitation history, and slot availability, enabling transparent tracking and manual overrides when needed.

Acceptance Criteria
Real-Time Waitlist Dashboard Visibility
Given the host accesses the Waitlist Management Dashboard, when there are active waitlist entries, then the dashboard automatically refreshes every 30 seconds and displays the current total number of candidates, their names, and slot availability.
Candidate Ranking Refresh
Given a new candidate is added to the waitlist, when the ranking algorithm processes the update, then the candidate appears in the correct position based on qualification score and the top five candidates are highlighted on the dashboard.
Invitation History Display
Given the host views the invitation history section, when selecting any candidate entry, then the dashboard displays the invitation timestamp, delivery status (sent, accepted, declined), and any attached notes or responses.
Manual Slot Assignment
Given the host identifies an open slot, when manually selecting a candidate from the waitlist, then the system assigns the slot to the candidate, removes them from the active waitlist, updates the slot availability counter, and logs the assignment in the invitation history.
Instant Backup Invitation Notification
Given a previously confirmed guest cancels and a slot opens, when the system identifies the top-ranked backup candidate, then it sends an email invitation to the candidate within one minute and updates the dashboard with the invitation status.
Auto-Fallback Handling
"As a podcast host, I want the system to automatically escalate invites to the next candidates if the first invites are declined so that slots are filled without manual intervention."
Description

If primary waitlist candidates decline or do not respond within a configurable timeframe, the system automatically escalates invitations to the next-ranked candidates and logs each interaction for auditability.

Acceptance Criteria
Primary Candidate Declines Invitation
Given a primary waitlist candidate declines the invitation within the configured timeframe, when the system detects the decline, then it automatically sends an invitation to the next-ranked candidate and logs the decline event.
Primary Candidate No Response Timeout
Given a primary candidate does not respond within the configured timeframe, when the timeout expires, then the system escalates the invitation to the next-ranked candidate and records the non-response timestamp in the audit log.
Multiple Sequential Declines
Given multiple waitlist candidates decline in succession, when each decline is processed, then the system continues down the ranked list, sending invites until a candidate accepts or the list is exhausted, and logs each interaction.
Configurable Timeframe Adjustment
Given an administrator updates the fallback response timeframe setting, when the new timeframe is saved, then all subsequent primary invitations use the updated timeframe to trigger automatic fallbacks.
Audit Logging of Invitation Events
Given any invitation or fallback action occurs, when the action is executed, then the system logs the candidate ID, timestamp, action type (invite, decline, non-response), and fallback level in an immutable audit record.

Adaptive Follow-Up

Crafts AI-optimized follow-up messages tailored to each guest’s communication style and past responsiveness. These re-engagement sequences boost rescheduled confirmations and keep your pipeline moving.

Requirements

Guest Communication Profiling
"As a podcast host, I want the system to analyze each guest’s communication style so that follow-up messages feel personalized and increase response rates."
Description

The system analyzes each guest’s past communication patterns—including tone, formality, preferred phrasing, and typical response times—to build a unique profile. This profile informs how follow-up messages are crafted, ensuring they resonate with the guest’s style and improve the likelihood of engagement. Integration with existing email and messaging workflows enables seamless data collection and profile updates.

Acceptance Criteria
New Guest Profile Initialization
Given a newly imported guest with no prior interactions, when the system processes the guest's initial email exchanges, then it stores tone, formality, typical response time, and phrasing preferences in a profile. The profile contains at least three stylistic attributes and one average response time. Data fields are populated within 5 seconds of processing.
Ongoing Profile Update from Email Interactions
Given an existing guest profile, when a new email message is received, then the system updates the profile attributes if there's a statistically significant change in tone or formality. The system logs the update event with timestamp. The profile update process completes without overwriting unchanged fields.
Tailored Follow-Up Message Generation
Given a guest profile is available, when generating a follow-up, then the AI crafts a message matching the guest's identified tone and formality. The follow-up message achieves at least 80% style similarity score against the profile benchmarks. The message is generated in under 2 seconds.
Profile Integration with Scheduling Workflow
Given a guest scheduling workflow is triggered, when preparing the message, then the system fetches the guest's profile and applies a greeting and phrasing consistent with the profile. All scheduling messages sent to the guest use profile-informed templates.
Response Time Prediction Accuracy
Given the guest's historical response times, when predicting expected response time for a new message, then the prediction error is within +/- 10% of actual response time in 90% of cases. Prediction results are stored in analytics for review.
AI-Driven Message Composer
"As a podcast host, I want the system to generate tailored follow-up messages so that I can quickly re-engage guests with minimal effort and maintain a consistent brand voice."
Description

An AI-powered engine generates follow-up messages tailored to each guest profile and past responsiveness. The composer produces draft messages that reflect the guest’s tone and the host’s brand voice, with options for quick edits before sending. This feature streamlines outreach, reduces manual writing time, and maintains high personalization levels.

Acceptance Criteria
Guest Tone Matching in Message Drafts
Given a guest profile with communication style data, when the AI-Driven Message Composer generates a follow-up draft, then the draft message must reflect the guest's tone by including at least two style-specific phrases from the profile.
Brand Voice Consistency Check
Given a host's brand voice guidelines, when a draft message is generated, then the draft must include the brand's signature greeting and closing and maintain the brand's formality level.
Quick Edit Efficiency
Given a generated draft message, when the host uses quick-edit tools to adjust text snippets or placeholders, then each edit operation must complete within 5 seconds without data loss.
Reschedule Confirmation Rate Improvement
Given a sequence of follow-up messages sent to rescheduled guests, when using the AI-Driven Message Composer, then the confirmation rate must be at least 80% for rescheduled sessions booked within two weeks.
Pipeline Progress Tracking
Given multiple guests with pending follow-ups, when drafts are generated and sent, then each follow-up must be automatically logged in the pipeline with a timestamp and updated status.
Dynamic Follow-Up Sequence Planner
"As a podcast host, I want to automate and schedule follow-up sequences so that I can ensure timely re-engagement without manual tracking."
Description

A scheduling module automatically creates multi-step follow-up sequences with customizable intervals. The planner adapts the timing and content of each message based on real-time responsiveness data, and syncs with calendar and email systems to avoid conflicts and ensure timely delivery.

Acceptance Criteria
Initial Sequence Generation
Given a confirmed guest booking When the system processes the booking details Then a multi-step follow-up sequence with default intervals of 2, 5, and 10 days is created automatically
Real-Time Responsiveness Adjustment
Given a guest who replies to a follow-up message When the system detects the reply timestamp Then subsequent message intervals are recalculated and updated based on predefined responsiveness rules
Calendar Conflict Avoidance
Given the host’s connected calendar When a follow-up message is scheduled Then the system checks for conflicting events and adjusts the send time to the next available slot
Email System Sync Verification
Given an integrated email account When the follow-up sequence is deployed Then all messages are sent via the connected email system without delivery errors
Custom Interval Configuration
Given the user updates interval settings in the planner When new values are saved Then the follow-up sequence uses the custom intervals for all subsequent messages
Engagement Performance Tracking
"As a podcast host, I want visibility into the performance of my follow-up messages so that I can understand their effectiveness and optimize my approach."
Description

A dashboard displays key metrics for follow-up campaigns, including open rates, reply rates, conversion to confirmed bookings, and no-show reductions. Hosts can filter by guest segments, timeframes, and message variations, enabling data-driven adjustments to outreach strategies.

Acceptance Criteria
Overall Campaign Metrics Overview
Given a host navigates to the Engagement Performance dashboard When no filters are applied Then the dashboard displays open rates, reply rates, conversion to confirmed bookings, and no-show reduction percentages for the default period
Filtering by Guest Segment
Given a host selects a specific guest segment filter When the filter is applied Then the dashboard updates to show all metrics exclusively for that guest segment
Timeframe Selection
Given a host chooses a custom date range When the date range is applied Then all displayed metrics reflect data only within the selected timeframe
Comparing Message Variations
Given a host selects two follow-up message variations for comparison When the comparison view is activated Then the dashboard displays side-by-side open rates, reply rates, and booking conversion rates for each variation
Booking Conversion Drill-Down
Given a host clicks on the booking conversion metric When the detail view opens Then a list of guest interactions that led to confirmed bookings is displayed with timestamps and message versions
No-Show Reduction Trend Analysis
Given a host drills into no-show reduction metrics When the trend view is displayed Then a graph shows no-show rate changes over time with comparison to the previous equivalent period
Feedback Loop Integration
"As a podcast host, I want the system to learn from guest responses and my feedback so that follow-up suggestions continually improve."
Description

The system captures guests’ responses and hosts’ feedback on message effectiveness to continuously refine the AI models. This learning loop ensures that profiles and message templates improve over time, increasing personalization accuracy and engagement outcomes.

Acceptance Criteria
Guest Response Logging
Given a guest replies to a follow-up message, when the system receives the reply, then the reply content and metadata must be stored in the feedback database within 2 minutes and linked to the correct guest profile.
Host Feedback Submission
Given a host rates a follow-up message’s effectiveness on a scale of 1–5, when the host submits the rating, then the rating must be recorded and associated with the specific message template within 1 minute.
Data Export to Training Pipeline
Given new feedback entries exist in the database, when the nightly sync process runs, then all new entries must be exported and ingested into the AI training dataset without errors.
Automated Model Retraining Trigger
Given the feedback dataset grows by 1,000 new entries, when this threshold is reached, then the system must automatically schedule and notify teams of a retraining job for the personalization AI models.
Post-Deployment Engagement Verification
Given the updated AI model is deployed, when follow-up messages are sent for the first campaign post-deployment, then the engagement rate (open or reply rate) must increase by at least 10% compared to the previous campaign.

No-Show Insights

Provides a comprehensive dashboard analyzing no-show trends by guest demographics, time slots, and reminder channels. Offers predictive insights and actionable recommendations to continuously improve booking reliability.

Requirements

Demographic Segmentation Analysis
"As a podcast host, I want to view no-show rates by guest demographics so that I can tailor my scheduling and outreach strategies to reduce cancellations."
Description

Enable hosts to filter and visualize no-show rates across various guest demographics such as location, industry, past engagement frequency, and audience size. Integrate interactive charts and tables within the No-Show Insights dashboard to allow deep dives into demographic segments, identify patterns of high-risk groups, and drive targeted outreach strategies. Expected outcome is a reduction in no-shows by tailoring booking approaches based on demographic trends.

Acceptance Criteria
Location-Based No-Show Analysis
Given the host views the No-Show Insights dashboard and selects the “Location” filter When the host chooses “United States” and sets the time period to “Last 30 Days” Then the system displays an interactive map and chart showing no-show rates for each state, highlighting states with a rate above 20%
Industry No-Show Trend Analysis
Given the host filters the dashboard by “Industry” and selects “Technology” When the time range is set to the last 3 months Then the dashboard displays a sortable table listing sub-industries with their respective no-show percentages in descending order
Past Engagement Frequency Insights
Given the host applies a filter for guests with more than three past engagements When the filter is active Then the insights panel shows the no-show rate for this group alongside a comparative metric for first-time guests
Audience Size Segmentation Overview
Given the host selects audience size buckets (<1,000; 1,000–10,000; >10,000) When the host applies these buckets Then the system renders a bar chart displaying no-show rates per bucket and allows clicking on any bar to list all guests in that segment
Combined Demographic Pattern Identification
Given the host selects multiple demographic filters (e.g., location = “Canada” and industry = “Health”) When filters are applied simultaneously Then the dashboard updates to show the combined no-show rate for that segment and flags it if the rate exceeds the overall average
Time Slot Reliability Metrics
"As an independent host, I want to analyze no-show trends by time slots so that I can schedule recordings during periods with higher guest reliability."
Description

Provide detailed analytics on no-show frequency by time of day, day of week, and seasonal periods. Incorporate heatmaps and trend lines in the dashboard to highlight high-risk time slots. Integration with the scheduling module ensures seamless data flow, helping hosts optimize booking windows for maximum attendance. Outcome is improved scheduling decisions and lower no-show rates.

Acceptance Criteria
Viewing Time-of-Day No-Show Heatmap
Given the user has at least one week of booking data, When they select the time-of-day heatmap filter on the No-Show Insights dashboard, Then a color-coded heatmap displays hourly no-show rates for each day without any blank cells.
Analyzing Day-of-Week No-Show Trends
Given the user opens the weekly trends view, When they select the day-of-week analysis option, Then a trend line graph shows average no-show rates for each weekday over the past 30 days, updated within 5 seconds.
Assessing Seasonal No-Show Patterns
Given the user selects a custom date range spanning at least three months, When they generate seasonal comparison insights, Then two side-by-side trend lines compare no-show rates for the selected period versus the same period in the previous year.
Real-Time Data Synchronization with Scheduling Module
Given a booking is created, rescheduled, or canceled in the scheduling module, When the change occurs, Then the No-Show Insights dashboard updates the relevant time slot metrics within one minute.
Scheduling Optimization Recommendation Display
Given the dashboard identifies any hourly time slot with a no-show rate above the defined threshold, When the user views the recommendations panel, Then the system suggests the top three alternative time slots with the lowest historical no-show rates, ranked by reliability score.
Reminder Channel Effectiveness
"As a podcast coordinator, I want to see which reminder channels work best so that I can send reminders via the most effective medium and minimize no-shows."
Description

Track and compare the performance of different reminder channels (email, SMS, in-app notifications) on guest attendance. Include A/B testing capabilities to experiment with reminder frequency, timing, and message templates. Visualize channel-specific no-show rates and engagement metrics, enabling hosts to adopt the most effective reminder strategies and reduce no-shows.

Acceptance Criteria
Channel Selection and Data Collection
Given the host has scheduled reminders via email, SMS, and in-app notifications to a population of guests within the last 30 days, When at least 100 guest responses (attendances and no-shows) are recorded, Then the system displays a table and chart showing no-show rates and engagement metrics (open and click rates) for each channel, broken down by guest demographics.
A/B Testing Setup for Reminder Frequency
Given the host configures two reminder frequency schedules (Schedule A: 48h and 24h before, Schedule B: 72h and 24h before) for a single episode, When reminders are sent to randomly assigned guests in equal groups, Then the dashboard presents comparative no-show rates for Schedule A and Schedule B including confidence intervals and p-values.
A/B Testing of Reminder Timing
Given the host sets up two reminder delivery times (Morning vs. Evening) for the same reminder channel, When guests receive reminders at their assigned times over a two-week period, Then the system displays which timing yielded a statistically lower no-show rate with visual graphs and significance indicators.
A/B Testing of Message Templates
Given the host creates two distinct reminder message templates and assigns them equally across the guest list, When reminders are sent, Then the dashboard shows open rates, click-through rates, and attendance outcomes for each template, highlighting the better-performing template.
Predictive Reminder Channel Recommendation
Given the system has historical data on guest attendance and engagement across channels and demographics, When the host requests channel recommendations, Then the system uses predictive analytics to suggest the top channel per demographic segment and estimates the expected percentage reduction in no-shows.
Predictive No-Show Modeling
"As a show producer, I want predictive insights on which guests are likely to no-show so that I can follow up proactively and ensure my recording schedule stays on track."
Description

Leverage machine learning algorithms to predict the likelihood of a guest no-show based on historical data, demographic factors, scheduling behavior, and reminder engagement. Display predictive scores next to each booking, with confidence intervals and explanatory factors. Integration with booking workflows allows hosts to proactively follow up with high-risk guests. Expected outcome is preemptive intervention and fewer missed recordings.

Acceptance Criteria
Display of Predictive No-Show Scores on Booking List
Given a host views the upcoming bookings page, when the page loads, then each booking entry displays a predictive no-show score between 0% and 100%, a confidence interval, and the top three contributing factors.
Filtering by High-Risk Guests
Given the host is on the No-Show Insights dashboard, when they apply a filter for guests with a predictive score above 75%, then only bookings with scores above 75% are displayed.
Proactive Follow-Up Workflow Trigger
Given a booking has a predictive no-show score of 80% or higher, when the booking is saved or updated, then the system automatically generates a follow-up reminder email draft and prompts the host to confirm sending it.
Accuracy of Predictive Model
Given historical booking and attendance data for the past three months, when the predictive model is evaluated, then it achieves at least 85% accuracy and a calibration error of no more than 5%.
Explanatory Factors Display
Given a booking with a displayed predictive score, when the host clicks the info icon next to the score, then a tooltip lists at least three key factors with their relative weights (e.g., past cancellations, demographic risk, reminder engagement).
Actionable Recommendation Engine
"As a podcast host, I want actionable recommendations from no-show data so that I can continuously improve my booking processes and reduce cancellations."
Description

Generate personalized, actionable recommendations based on no-show analytics, such as optimal reminder schedules, best-performing demographics for rebooking, and time slots to avoid. Recommendations are surfaced as alerts and task prompts within the dashboard and scheduling interface. This continuous improvement loop helps hosts refine their processes and maintain high booking reliability over time.

Acceptance Criteria
Reminder Schedule Optimization Scenario
Given the host views no-show risk analytics, When the recommendation engine generates reminder schedules, Then it suggests a schedule that reduces predicted no-show risk by at least 20% compared to the default schedule.
Demographic Rebooking Targeting Scenario
Given historical no-show data segmented by demographics, When the engine analyzes the segments, Then it identifies the top three demographic groups with the lowest no-show rates and recommends rebooking outreach with tailored messaging for each group.
Time Slot Avoidance Alert Scenario
Given booking time slot performance metrics, When a time slot’s no-show rate exceeds the configurable threshold, Then the system surfaces an alert recommending the host avoid that slot for future bookings.
Alert Delivery Workflow Scenario
Given actionable recommendations are generated, When the host navigates between the dashboard and scheduling interface, Then alerts and task prompts appear contextually in both views within two seconds of generation.
Continuous Improvement Loop Tracking Scenario
Given the host implements recommended actions, When one month of booking data is available, Then the engine recalculates no-show trends showing at least a 10% improvement and updates future recommendations accordingly.

Channel Optimizer

Automatically selects and switches between email, SMS, WhatsApp, or in-app notifications based on each guest’s preferred communication channel and past interaction success, maximizing reminder effectiveness.

Requirements

Preference Profile Management
"As a podcast host, I want the system to maintain a profile of each guest’s communication preferences so that reminders are delivered via the channel they respond to best."
Description

Collect and maintain a comprehensive profile for each podcast guest, capturing their preferred communication channels (email, SMS, WhatsApp, in-app) and storing historical interaction metrics. This enables tailored message delivery, ensures higher engagement rates, and integrates seamlessly with the guest database and notification service.

Acceptance Criteria
Initial Guest Preference Profile Setup
Given a host creates a new guest entry, when the host or guest submits contact preferences, then the system stores the preferred channel (email, SMS, WhatsApp, in-app) for that guest and displays a confirmation message.
Updating Guest Preferences Post-Booking
Given an existing guest profile, when the guest updates their communication preferences via the settings page or update link, then the system updates the stored preferences, logs the change timestamp, and sends a confirmation notification through the newly selected channel.
Preference-based Channel Selection for Notifications
Given a scheduled episode reminder, when preparing to send notifications, then the system selects the guest’s highest-priority channel based on their preference profile and past interaction success rate, and sends the reminder through that channel.
Historical Interaction Metrics Tracking
Given notifications have been sent to a guest, when the guest interacts (opens email, clicks link, replies to SMS/WhatsApp), then the system captures the interaction type, timestamp, and outcome, updates the guest’s interaction history, and recalculates channel success metrics.
Preference Profile Data Export
Given the host requests an export of guest data, when generating the export file, then the system produces a CSV containing each guest’s preferred communication channels, interaction metrics, and last updated timestamp, including only profiles updated within the last 12 months.
Interaction Success Tracking
"As a host, I want to see which channels produce the best response from my guests so that I can maximize reminder effectiveness."
Description

Monitor and record the delivery and response rates of messages sent through each channel, logging metrics such as delivery status, open rates, and response times. This data feeds into analytics for refining channel selection and helps identify the most effective communication methods per guest.

Acceptance Criteria
Delivery Status Logging
Given a message is sent via any channel When the message dispatch process completes Then the system logs a delivery record containing timestamp, channel type, message ID, and status (Delivered, Failed, Pending) within 5 seconds
Open and Read Rate Tracking
Given an email or in-app notification When the recipient opens the message Then the system records an open event with timestamp and correlates it to the original message ID
Response Time Measurement
Given a message has been delivered When the recipient replies or interacts Then the system calculates response time (in seconds) from delivery timestamp and logs it under the recipient’s interaction history
Metrics Aggregation for Analytics
Given interaction logs exist for multiple messages When an analytics query runs Then the system aggregates delivery rates, open rates, and average response times per channel and generates a summary report within 30 seconds
Data Feed to Channel Optimizer
Given updated interaction metrics When new data is available Then the system feeds delivery, open, and response metrics into the Channel Optimizer model API in the specified JSON schema, successfully returning a 200 OK response
Dynamic Channel Selection Algorithm
"As a podcast host, I want reminders to be sent via the optimal channel for each guest so that I minimize no-shows and miscommunications."
Description

Implement an algorithm that analyzes each guest’s preference profile and past interaction success to automatically choose the optimal communication channel for each reminder. The algorithm should weigh factors like recent engagement, channel reliability, and guest time zones.

Acceptance Criteria
Guest with SMS as Top Channel
Given a guest whose preference profile indicates SMS as the top channel and whose last three interactions via SMS had open rates above 80%, when scheduling a reminder, then the system selects SMS as the communication channel.
Guest Across Different Time Zones
Given a guest whose location is updated to a different time zone, when scheduling reminders, then the system adjusts send times to 9:00 AM local time and selects the channel with the highest reliability score from their preference profile.
Guest with Equal Channel Engagement
Given a guest with equal recent engagement rates across email and WhatsApp and similar reliability scores, when sending a reminder, then the system selects the channel with the lower average message delivery latency.
Fallback for Unresponsive Guest
Given a guest who does not engage with the first reminder within two hours of sending, when determining the next reminder, then the system automatically switches to the next most preferred channel and logs the fallback action.
New Guest with No Interaction History
Given a new guest with no prior interaction data, when sending the first reminder, then the system uses the guest’s stated channel preference or defaults to email if none is stated and records the initial engagement outcome for future weighting.
Channel Failover Mechanism
"As a host, I want the system to reroute reminders through another channel if the first one isn’t effective so that messages always reach my guests."
Description

Design a failover process that automatically retries message delivery via an alternate channel if the primary channel fails or shows low engagement. The mechanism should detect failures or low open rates and trigger secondary channel notifications without manual intervention.

Acceptance Criteria
Primary Email Delivery Failure
Given an email reminder attempt returns a bounce or delivery failure notification within 10 minutes, when detected, then the system retries the reminder via SMS within 5 minutes of failure.
Low Email Engagement
Given an email reminder is sent and no open event is recorded within 24 hours, when the time threshold is reached, then the system automatically sends the same reminder via the guest’s secondary preferred channel.
SMS Delivery Failure
Given an SMS reminder is sent and no delivery receipt is received within 10 minutes, when the delivery failure is detected, then the system sends the reminder via WhatsApp within 5 minutes.
WhatsApp Failover Trigger
Given a WhatsApp reminder attempt fails or the message is not read within 24 hours, when the failure or low engagement is confirmed, then the system sends an in-app notification to the guest.
All-Channel Exhaustion
Given reminders via email, SMS, and WhatsApp have all failed or shown no engagement within 48 hours, when the final channel attempt fails, then the system logs the failover event and escalates to host via email.
Notification Delivery Logging
"As a technical user, I want comprehensive logs of every notification sent so that I can troubleshoot delivery issues and refine communication workflows."
Description

Implement detailed logging for all notification dispatches, capturing timestamps, channel used, status codes, and error messages. These logs support auditing, troubleshooting, and provide insights for improving channel selection strategies.

Acceptance Criteria
Successful Notification Dispatch Logging
Given a notification is dispatched successfully, when the notification service confirms delivery, then a log entry is created containing the timestamp of dispatch, the communication channel used, and the 200 status code, with the error message field empty.
Failed Notification Dispatch Logging
Given a notification dispatch fails, when the notification service returns an error, then a log entry is created containing the timestamp of attempt, the communication channel used, the returned status code, and the complete error message.
Channel Selection Audit Logging
Given the Channel Optimizer determines the preferred channel for a guest, when a notification is scheduled, then a log entry records the timestamp, the selected channel, and the channel selection rationale identifier.
Log Retrieval and Query Functionality
Given a user invokes the logs API with valid filters (date range, channel, status code), when the request is processed, then the API returns all matching log entries sorted by timestamp.
Performance Impact of Logging
Given the system is under normal operational load, when logging is enabled for notification dispatches, then the average notification dispatch latency increases by no more than 50 milliseconds.

Dynamic Agenda

Auto-generates a time-stamped episode outline with key topics, segment transitions, and talking points, giving guests clear visibility into the show flow and helping them prepare precisely for each segment.

Requirements

Agenda Generation Engine
"As a podcast host, I want the system to automatically generate a detailed, time-stamped episode outline so that I can focus on content quality rather than manual agenda creation."
Description

Develop a core engine that analyzes episode metadata, guest profiles, and host inputs to auto-generate a structured, time-stamped outline. The engine should identify key topics, segment durations, and transitions, assembling them into a coherent sequence. It must integrate with existing scheduling and episode tracking modules to pull relevant data and utilize NLP techniques to summarize talking points. The expected outcome is a reliable, dynamically generated agenda that reflects show flow and reduces manual preparation time.

Acceptance Criteria
Agenda generation upon episode confirmation
Given valid episode metadata and host inputs, When the host confirms a new episode booking, Then the engine generates a time-stamped outline including key topics, segment transitions, and talking points within 10 seconds of confirmation.
Integration with scheduling module
Given the episode is scheduled in the calendar module, When the agenda engine runs, Then it automatically pulls date, time, guest profile, and episode title data without manual intervention.
Accurate NLP summarization of talking points
Given the engine analyzes guest profiles and host notes, When generating talking points, Then each point is summarized to under 15 words and reflects the guest’s expertise at least 90% accuracy based on manual review.
Customizable segment durations
Given default segment durations are set, When the host adjusts any segment duration in the interface, Then the engine recalculates and redistributes remaining segment timestamps proportionally within 5 seconds.
Handling incomplete metadata
Given missing episode metadata fields, When the engine generates an agenda, Then it uses sensible defaults, flags missing data in the UI, and proceeds without errors.
Timestamp Alignment Module
"As a producer, I want the agenda’s timestamps to automatically adjust when I change segment durations so that the timeline remains accurate throughout production."
Description

Implement a module that synchronizes agenda items with precise timestamps based on episode length and segment transitions. This component should calculate start and end times for each topic, adjust dynamically if segment durations change, and ensure alignment with recording schedules. It must provide real-time updates when the host modifies time allocations, ensuring the agenda remains accurate and consistent with the show’s pacing.

Acceptance Criteria
Initial Segment Scheduling
Given the host defines a 60-minute episode with three segments of 20 minutes each When the Timestamp Alignment Module initializes Then it generates timestamps: Segment 1 start 00:00 end 00:20, Segment 2 start 00:20 end 00:40, Segment 3 start 00:40 end 01:00
Dynamic Segment Adjustment
Given an existing agenda with timestamps When the host changes Segment 2 duration from 15 to 20 minutes Then the module updates start/end times for Segment 2 and all subsequent segments in real time without manual refresh
Guest View Preparation
Given the host shares the agenda link Before recording begins Then the guest sees finalized timestamps that match the current episode schedule and any last-minute adjustments are reflected immediately
Overall Episode Length Change
Given the host updates the total episode length from 60 to 75 minutes While segments remain defined Then the module proportionally adjusts segment end times or prompts host to redistribute durations and updates the timestamps accordingly
Overlap Prevention
Given the host reduces Segment 3 duration causing potential overlap with Segment 4 When the adjustment is made Then the module detects the conflict, prevents overlapping timestamps, and displays an alert indicating the need to resolve scheduling conflicts
Guest-Facing Preview Interface
"As a guest, I want to view and interact with the show’s agenda in a branded portal so that I can prepare effectively and provide feedback on topics."
Description

Create a secure, branded portal where guests can preview the dynamic agenda, including time-stamped segments, talking points, and transition notes. The interface should allow guests to navigate the outline, leave feedback on topics, and download prep materials. It must support user authentication, customizable branding elements, and mobile responsiveness to ensure a seamless experience across devices.

Acceptance Criteria
Guest Authentication and Secure Access
Given a registered guest enters valid credentials on the login screen, when they submit the form, then they are granted secure access to the branded portal within 2 seconds without any authentication errors.
Viewing Dynamic Agenda on Desktop and Mobile
Given the guest is authenticated, when they open the preview interface on desktop or mobile devices, then the full time-stamped outline, segment transitions, and talking points display correctly, fully visible within the viewport, and styled with the custom branding.
Feedback Submission on Talking Points
Given the guest reviews the agenda, when they click the ‘Leave Feedback’ icon next to a talking point, then a modal opens allowing up to 500 characters of input, and upon submission the feedback is saved and a confirmation message appears within 3 seconds.
Downloading Branded Prep Materials
Given the guest is viewing the agenda, when they click ‘Download Prep Materials,’ then a PDF containing the full agenda, episode metadata, and custom branding (logo and colors) is generated and starts downloading within 5 seconds.
Responsive Design Across Devices
Given the guest accesses the portal using any common device or browser, when they resize or switch devices, then the interface adapts seamlessly for screen widths between 320px and 1920px, maintaining full functionality and readability without layout issues.
Transition Indicator System
"As a host, I want clear visual markers for segment transitions so that I can seamlessly guide the conversation and keep track of topics during recording."
Description

Design a visual system within the agenda that highlights segment transitions and key topic shifts. This system should use icons, color-coding, or labels to clearly demarcate when one segment ends and another begins, aiding both hosts and guests in following the show flow. It must integrate with the Agenda Generation Engine and Timestamp Alignment Module to reflect real-time changes and maintain visual clarity.

Acceptance Criteria
Host Pre-Recording Transition Review
Given the host opens the dynamic agenda before recording, When the agenda is loaded, Then each segment transition is visually highlighted with a unique icon, consistent color band, and labeled with the segment name adjacent to its timestamp.
Guest Prep Packet Transition Visibility
Given the guest receives the branded prep packet PDF, When the guest reviews the document, Then every segment transition is indicated with a colored icon and label, and a legend explaining icon meanings is present on the first page.
Live Recording Transition Adjustment
Given the host adjusts a segment's start time during a live session, When the new time is saved, Then the transition indicator moves to the updated timestamp within 2 seconds and maintains the correct icon and color.
Exported Agenda Transition Integrity
Given the host exports the agenda to PDF or DOCX, When the file is generated, Then all transition indicators appear correctly with original colors, icons, and labels, matching the on-screen view.
Accessibility Compliance for Transition Indicators
Given a user with visual impairments accesses the agenda, When navigating with a screen reader or in high-contrast mode, Then the transition indicators provide alt-text descriptions, meet WCAG AA color contrast ratios, and are keyboard-navigable.
Agenda Export & Sharing
"As a production assistant, I want to export and share the agenda in various formats so that I can distribute preparation materials efficiently across different tools."
Description

Enable exporting of the dynamic agenda in multiple formats (PDF, DOCX, and plain text) and provide sharing options via email or direct link. The export feature should preserve formatting, timestamps, and visual indicators, offering both branded and unbranded templates. Integration with calendar invites and messaging platforms is required to streamline distribution to guests and production team members.

Acceptance Criteria
Branded PDF Export
Given the user has a completed dynamic agenda, when they select 'Export' and choose 'PDF' with the branded template, then the system generates and downloads a PDF that includes all timestamps, formatting, visual indicators, and the user's custom branding (logo and colors).
Unbranded DOCX Export
Given the user has a completed dynamic agenda, when they select 'Export' and choose 'DOCX' with the unbranded template, then the system generates and downloads a Word document that preserves the agenda structure, timestamps, and segment markers without any branding elements.
Plain Text Export
Given the user has a completed dynamic agenda, when they select 'Export' and choose 'Plain Text', then the system generates and downloads a .txt file that lists each segment with its timestamp and topic in plain text format without any styling or visual indicators.
Email Sharing Integration
Given the user has exported an agenda in any format, when they click 'Share via Email', then the system opens a new email draft populated with a subject line 'Your Episode Agenda', the agenda file attached, and the guest's email address prefilled, using the user's default email client or integrated email service.
Calendar Invite Attachment
Given the user has finalized the episode date in their calendar, when they export the agenda and choose 'Attach to Calendar Invite', then the system generates a calendar event with the agenda file attached, populated with the episode title, date/time, and location, and adds it to the selected calendar.
Direct Link Sharing
Given the user has a completed dynamic agenda, when they select 'Generate Shareable Link', then the system creates a unique, access-controlled URL that opens the agenda in a web view preserving formatting and timestamps, and copies the link to the clipboard.

Interactive Notes

Allows guests to annotate the prep brief with comments, questions, and suggestions directly in the document, enabling real-time collaboration and giving hosts consolidated feedback before recording.

Requirements

Real-time Collaborative Editing
"As a podcast host, I want to collaborate with my guest in real-time on the prep brief so that we can clarify questions and refine the outline together before the interview."
Description

Enable multiple guests and hosts to add annotations, comments, and suggestions to the prep brief document simultaneously, ensuring that all inputs appear in real-time. This feature integrates a collaborative editor that tracks and displays each user’s cursor and changes, facilitating immediate feedback and dynamic brainstorming sessions before recording.

Acceptance Criteria
Simultaneous Guest Annotations
Given the host and two guests have opened the prep brief, When guest A adds a comment to paragraph 3 and guest B highlights text in paragraph 5, Then both comments and highlights appear instantly for all participants without requiring a page refresh.
Real-Time Cursor Tracking
Given multiple users are editing the document, When a user moves their cursor, Then the cursor position and user identifier are visible to all other participants in real-time.
Immediate Change Synchronization
Given a guest updates an annotation, When the change is made, Then all connected users see the updated annotation within 500ms across desktop and mobile clients.
Concurrent Edit Conflict Resolution
Given two users edit the same sentence simultaneously, When both edits are submitted, Then the system merges non-overlapping changes automatically and prompts users to resolve overlapping changes through a clear conflict resolution dialog.
Annotation Version History
Given that annotations have been added to the document, When a user views the history panel, Then they can see a chronological list of changes with timestamps, authors, and have the ability to revert to any previous state.
Inline Comment Threading
"As a guest, I want to attach threaded comments to specific parts of the prep brief so that my questions and suggestions remain contextually linked to relevant content."
Description

Allow users to select text within the prep brief and attach comments that spawn threaded discussions. Each comment thread should be linked to the specific text selection, supporting nested replies, @mentions, and timestamps. This enhances contextual feedback and keeps conversations organized.

Acceptance Criteria
Highlight Selection Comment Creation
Given a user selects a range of text in the prep brief, when the user clicks the “Add Comment” button, then a comment input box is anchored to the selected text and the user can submit a new comment thread linked to that text selection.
Nested Reply Functionality
Given an existing comment thread, when a user replies to a comment, then the reply appears indented beneath the parent comment, preserving chronological order and thread hierarchy.
Mention Notification Trigger
Given a user types “@” in a comment input, when the user selects a username from the autocomplete list and posts the comment, then the mentioned user receives a notification containing a link to the specific comment thread.
Timestamp Display Accuracy
Given any comment or reply is posted, when the thread is viewed, then each comment and reply displays the correct creation timestamp in the user’s local time zone.
Thread Resolution Workflow
Given a comment thread is no longer relevant, when a user with appropriate permissions marks the thread as resolved, then the thread is visually collapsed and a “Resolved” label is applied, while still allowing users to expand and view its content.
Comment Notifications
"As a guest, I want to receive notifications when my comment receives a reply so that I can stay informed and respond promptly."
Description

Implement a notification system that alerts hosts and guests of new comments, replies, or mentions. Notifications should be configurable (email, in-app) and include snippets of the comment and direct links to the discussion thread, ensuring timely responses and continuous engagement.

Acceptance Criteria
Host Receives Email Notification for New Comment
Given a host has enabled email notifications, When a guest posts a new comment on the prep brief, Then the host receives an email within 60 seconds including the comment snippet and a direct link to the discussion thread.
Guest Receives In-App Notification for Mention
Given a guest is mentioned in a comment, When the host adds '@guest' in the comment, Then the guest receives an in-app notification immediately upon saving the comment.
Notification Delivery Preference Configuration
Given a user accesses notification settings, When they choose notification types (email/in-app) and save preferences, Then the system saves their settings and sends notifications only via selected channels.
Notification Contains Comment Snippet and Direct Link
Given a notification is sent, When the system prepares the notification, Then it includes the first 200 characters of the comment and a hyperlink to the specific comment thread.
Real-Time Notification for Thread Replies
Given there is a reply in an existing comment thread, When a reply is posted, Then all participants in the thread receive an in-app notification within 30 seconds.
Comment Resolution Workflow
"As a podcast host, I want to mark comments as resolved once addressed so that I can track which feedback has been implemented and which requires follow-up."
Description

Introduce a mechanism for marking comments as resolved or open, with visual indicators for resolved threads. Hosts and guests can filter comments by status and view an overview of outstanding unresolved items to ensure all feedback is addressed before recording.

Acceptance Criteria
Host Resolves a Comment Thread
Given an open comment thread, when the host clicks the "Resolve" button on the comment, then the thread status updates to "Resolved" and a checkmark icon appears next to it.
Guest Reopens a Resolved Comment
Given a comment thread marked as "Resolved", when the guest clicks the "Reopen" option, then the thread status reverts to "Open" and the checkmark icon is removed.
Filter Comments by Status
Given multiple comment threads with mixed statuses, when the user applies the "Open" or "Resolved" filter, then only comment threads matching the selected status are displayed.
Display Overview of Unresolved Comments
Given the prep brief overview panel is viewed, then it displays a count of all open comment threads and provides a link to navigate to each unresolved comment.
Visual Indicator for Resolved Threads
Given a list of comment threads, then all threads marked as "Resolved" are displayed with a faded background and a checkmark icon, distinguishing them from open threads.
Version History Tracking
"As a podcast host, I want to review previous versions of my prep brief and annotations so that I can track changes over time and revert if necessary."
Description

Maintain a complete revision history of the prep brief and annotations, allowing users to view, compare, and restore previous document states. Each version entry should detail changes made, by whom, and when, aiding in accountability and the ability to rollback if needed.

Acceptance Criteria
Viewing Version History
Given a user is on a prep brief page When they click the ‘Version History’ button Then a chronological list of all versions is displayed showing version number, timestamp, author, and change summary
Comparing Two Versions
Given the version history list is displayed When the user selects two versions to compare Then the system highlights additions, deletions, and modifications side by side
Restoring a Previous Version
Given the comparison view of a previous version When the user clicks ‘Restore This Version’ Then the prep brief content reverts to the selected version and a new version entry is created documenting the restoration
Filtering Version History
Given the user is viewing version history When they apply filters by date range or author Then only versions matching those filters are shown in the history list
Viewing Change Details
Given a version entry in the history list When the user expands its details Then a list of individual changes is shown, specifying the affected text, type of change (added, modified, deleted), and the contributor who made the change
Annotation Formatting Options
"As a guest, I want to format my comments with styling and lists so that my feedback is clear and easy to read."
Description

Provide formatting tools within the annotation interface, including text styling (bold, italic, underline), bullet lists, links, and emojis. This ensures comments are clear, expressive, and aligned with the host’s branding policies.

Acceptance Criteria
Annotating with Text Styling
Given a guest is editing an annotation, when they apply bold, italic, or underline, then the text displays correctly with the selected style.
Creating Bullet Lists in Annotations
Given a guest selects the bullet list tool, when they add list items, then the annotation shows each item with a bullet point and proper indentation.
Inserting Links into Notes
Given a guest highlights text and adds a URL, when they save the annotation, then the highlighted text is clickable and opens the link in a new tab.
Adding Emojis to Annotations
Given a guest opens the emoji picker, when they select an emoji, then the emoji appears at the cursor position within the annotation.
Combined Formatting in Single Annotation
Given a guest uses multiple formatting options in one annotation, when they save, then all formatting (text style, lists, links, emojis) is preserved and rendered correctly.

Brand Customizer

Offers drag-and-drop branding tools—custom colors, fonts, logos, and templates—so hosts can tailor each prep packet’s appearance to fit their show’s identity or sponsor requirements in seconds.

Requirements

Drag-and-Drop Asset Editor
"As a podcast host, I want to drag and drop branding elements onto my packet template so that I can quickly design a professional-looking prep packet without needing design skills."
Description

Provide an interactive canvas where hosts can drag and drop branding assets—such as headers, footers, images, and text blocks—into predefined slots within prep packet templates. The editor should support snapping, layering, resizing, and aligning elements to ensure precise placement and maintain brand consistency across all pages.

Acceptance Criteria
Header Asset Placement
Given a prep packet template is open in the editor, when the host drags a header image asset onto the header slot, then the image snaps into place within the header boundaries without distortion and displays at 100% opacity.
Footer Asset Layering and Alignment
Given multiple footer assets are present on the canvas, when the host reorders layers or aligns them using grid guides, then the assets adjust their z-index and align to grid lines within 5px accuracy.
Image Resizing and Aspect Ratio Preservation
Given an image asset is placed on the canvas, when the host resizes it using corner handles, then the image maintains its original aspect ratio and resizes smoothly without pixelation.
Text Block Drag-and-Drop
Given a text asset is available in the asset panel, when the host drags it onto any predefined text slot, then the text block snaps into the slot, inherits template font settings, and remains editable.
Multi-Element Snapping and Grouping
Given multiple assets are selected, when the host drags the group near alignment guides or other assets, then the group snaps collectively to guides and can be moved or resized together.
Color Palette Manager
"As a host, I want to set and save a brand color palette so that every prep packet matches my show's visual identity without manual color adjustments each time."
Description

Offer a dedicated interface for creating, saving, and applying custom color palettes. Users should be able to define primary, secondary, and accent colors via HEX, RGB, or selection tools. Palettes must be reusable across multiple templates and prep packets, ensuring consistent brand identity.

Acceptance Criteria
Creating a New Color Palette
Given the user is on the Color Palette Manager page When they click “New Palette,” enter a name, and define primary, secondary, and accent colors via HEX, RGB, or color picker Then the new palette is saved, displayed in the list with its name and color swatches, and available for immediate use
Applying Saved Palette to a Prep Packet Template
Given the user selects a prep packet template in the Brand Customizer When they choose a saved palette from the Color Palette Manager Then the template preview updates to reflect the primary, secondary, and accent colors correctly and a confirmation message displays
Editing an Existing Color Palette
Given the user views their list of palettes in the Color Palette Manager When they select “Edit” for a palette, modify one or more color values using HEX, RGB, or color picker, and save changes Then the palette updates in the list with the new colors and all templates using that palette reflect the changes
Deleting an Unused Color Palette
Given the user identifies a palette with no associated templates When they click the “Delete” action and confirm the deletion Then the palette is removed from the list and no longer available for selection
Importing Colors Using HEX and RGB
Given the user wants precise colors When they input valid HEX codes or RGB values into the color fields and save the palette Then the entered colors are displayed accurately in the palette preview and saved as defined
Font Library Integration
"As a host, I want to choose and pair fonts from a library so that my prep packets reflect my show’s tone and improve readability."
Description

Enable users to upload or select from a library of Google and system fonts. The feature must support custom font pairing, size adjustments, weights, and styles, with preview functionality. Uploaded fonts should be stored securely and available across all workspaces.

Acceptance Criteria
User uploads a custom font to the library
Given a host navigates to the Font Library page and selects Upload Font, when they choose a valid .ttf or .otf file under 5MB and confirm, then the font is added to the library list displaying its name, style, and weight.
User selects a Google font in the customizer
Given a host opens the font dropdown in the Brand Customizer and searches for a Google font by name, when they click on a font from the results, then the font is applied to the preview text and available for use in prep packet templates.
User previews font pairings and styles
Given a host selects two fonts from the library, when they enable Pairing Preview, then the system displays side-by-side examples of headings and body text with adjustable size, weight, and style controls reflecting the selected fonts.
Font assets are accessible across multiple workspaces
Given a host uploads or selects a font in one workspace, when they switch to another workspace within the same account, then the previously added fonts are listed and ready for immediate use in that workspace’s Brand Customizer.
Uploaded fonts are securely stored
Given a host uploads a custom font file, when the upload process completes, then the font file is encrypted at rest in storage and accessible only through authenticated API calls under the host’s account.
Logo Uploader and Placement
"As a host, I want to upload and position my show or sponsor logo on the packet so that my branding remains prominent and consistent."
Description

Allow hosts to upload logos in various formats (PNG, SVG) and place them within templates. The system should automatically optimize resolution, maintain aspect ratio, and provide alignment guides. Logos must be stored in a media library for reuse.

Acceptance Criteria
Uploading High-Resolution PNG Logo
Given a host selects a PNG logo file under 10MB and up to 5000x5000 px, when they upload the file, then the system optimizes the resolution to a maximum of 1920x1080 px while preserving the original aspect ratio, stores the optimized image, and shows a success notification.
Uploading and Placing a SVG Logo
Given a host uploads an SVG logo file, when they place it onto a template, then the logo renders crisply at any scale without pixelation, and the system stores it in vector format for future reuse.
Maintaining Aspect Ratio on Oversized Logos
Given a host uploads a logo with non-standard dimensions exceeding template boundaries, when the system optimizes it, then the output logo fits within the template's maximum width or height constraints, scaling down proportionally without distortion.
Alignment Guides Functionality
Given a host drags a placed logo near template edges or center, when the alignment guides activate, then visual lines appear to indicate center, margin, and edge alignments, and the logo snaps to guides if within 5 pixels of alignment positions.
Media Library Logo Retrieval
Given a host accesses the media library, when they search by logo name or filter by file type, then the system displays all matching uploaded logos with thumbnails, and selecting a logo inserts it into the current template at its last saved size and position.
Template Library and Management
"As a host, I want a variety of ready-made templates that I can customize and save so that I can quickly generate packets tailored to different episodes or sponsors."
Description

Curate a library of customizable templates covering different prep packet layouts—single-page, multi-page, sponsor-focused—and categorize by style. Users should be able to duplicate, modify, and save templates. Template metadata (name, tags) must support search and filtering.

Acceptance Criteria
Creating a New Template from Scratch
Given the user opens the Template Library and clicks 'New Template', when the user selects a layout, adds branding elements (colors, fonts, logos), and clicks 'Save', then the new template appears in the library with the correct name, preview thumbnail, and metadata.
Duplicating an Existing Template
Given the user views an existing template in the library, when the user clicks 'Duplicate' on that template, then a new template appears in edit mode with 'Copy' appended to the name, retaining all design elements and metadata, and is listed in the library after saving.
Modifying Template Metadata
Given the user selects a template to edit, when the user updates the template name and tags and clicks 'Save', then the library displays the updated name and tags, and the template is discoverable via search and filter using the new metadata.
Filtering Templates by Tag
Given the library contains multiple templates tagged with different keywords, when the user applies a filter for a specific tag, then only templates containing that tag are displayed, and the displayed count matches the number of relevant templates.
Deleting an Unused Template
Given the user identifies a template they no longer need, when the user clicks 'Delete' and confirms the action, then the template is removed from the library and no longer appears in search results or counts.
Real-Time Preview and Export
"As a host, I want to see updates in real time and export a print-ready PDF so that I can send finalized prep packets to guests without formatting issues."
Description

Implement a live preview mode that reflects branding changes instantly. Users must be able to toggle between edit and preview views and export the final packet as PDF or shareable link. Exports should preserve all styling, ensure print-ready quality, and embed necessary assets.

Acceptance Criteria
Instant Branding Preview Updates
Given a user modifies branding elements in the Brand Customizer, When the change is made, Then the live preview must update within 1 second to reflect the new color, font, or logo without requiring a page reload.
Toggle Edit and Preview Modes
Given the user is in the edit view, When the user clicks the preview toggle, Then the interface must switch to a read-only preview mode showing the packet exactly as it will appear in export, and when toggled back, return to edit mode with all unsaved edits preserved.
Export to PDF with Preserved Styling
Given the user has finalized branding, When the user clicks 'Export as PDF', Then the system must generate a PDF that preserves all styling (colors, fonts, logos), embeds necessary assets, and matches the live preview with no visual discrepancies.
Generate Shareable Link with Embedded Assets
Given the user completes branding changes, When the user selects 'Generate Shareable Link', Then the system must create a unique, publicly accessible URL that renders the branded packet with all assets embedded or properly referenced, matching the live preview.
Print-Ready Quality Assurance
Given the user exports the packet, When printed on standard A4 or Letter paper, Then the document must maintain correct margins, render images at 300 dpi, ensure text is not truncated or misaligned, and adhere to the preview layout.

Instant Share

Enables one-click distribution of the prep snapshot via email, SMS, Slack, or calendar invites, with built-in tracking to confirm delivery and viewing, ensuring guests receive and review materials promptly.

Requirements

Multi-Channel Distribution
"As a podcast host, I want to share the episode prep snapshot via my preferred channel in one click so that I can quickly ensure guests receive all necessary materials."
Description

Enable hosts to share prep snapshots with a single click across multiple channels including email, SMS, Slack, and calendar invites. This capability integrates with existing communication APIs and the user's configured communication preferences, providing seamless distribution. The system should automatically format the content for each channel, ensuring consistency and reliability. Benefits include reducing manual effort, minimizing errors in copy-paste, and increasing the speed of guest preparation.

Acceptance Criteria
Email Distribution Workflow
Given the host is on the prep snapshot page and has configured the guest's email address, when the host clicks the 'Share via Email' button, then the system generates and sends an email containing the correctly formatted prep snapshot using the host's branding template; And the system displays a confirmation message 'Email sent successfully'; And the email API log records a successful send with status code 200.
SMS Distribution Workflow
Given the host has entered the guest's phone number and selected 'Share via SMS', when the host clicks the 'Send SMS' button, then the system sends an SMS containing a shortened link to the branded prep snapshot; And the system displays a 'SMS sent successfully' notification; And the SMS gateway logs record the message delivery as 'Delivered'.
Slack Distribution Workflow
Given the host has authorized their Slack workspace and chosen a channel or direct message, when the host clicks 'Share via Slack', then the system posts the prep snapshot content as a formatted Slack message with branding elements; And the system shows 'Message posted successfully' confirmation; And the Slack API response returns a 200 OK status.
Calendar Invite Distribution Workflow
Given the host is creating a calendar invite for the guest, when the host selects 'Add Prep Snapshot' and sends the invite, then the calendar event description includes a link to the branded prep snapshot; And guests receive an invite notification with the snapshot link; And the calendar API confirms event creation with status code 200.
Delivery and Viewing Tracking
Given any shared channel (Email, SMS, Slack, or Calendar), when the guest opens the link or preview, then the system records a 'viewed' timestamp against the guest record; And the host dashboard updates to show 'Viewed' status within 5 minutes of the guest opening the content.
Delivery Confirmation Tracking
"As a podcast host, I want to know if my prep snapshot was delivered successfully so that I can follow up if there are any issues delivering the materials."
Description

Implement real-time delivery tracking to confirm when a prep snapshot has been successfully sent through each selected channel. The system should log delivery statuses, handle different response codes from communication APIs, and surface failures for retry or manual intervention. This ensures hosts have visibility into whether guests have received materials, reducing the risk of no-shows due to undelivered content.

Acceptance Criteria
Email Delivery Logging
Given a prep snapshot is sent via email, when the email API returns a 250 success code, then the system logs the email as 'Delivered' in the delivery tracking dashboard within 10 seconds.
Email Delivery Failure Handling
Given a prep snapshot sending attempt via email fails with a bounce code (e.g., 550), when the system receives the failure code, then the delivery status is updated to 'Failed' and a retry is queued for manual review.
SMS Delivery Confirmation
Given a prep snapshot is sent via SMS, when the SMS provider API returns a delivery receipt, then the system updates the delivery status to 'Delivered' and time-stamps the confirmation.
SMS Delivery Failure Retry
Given an SMS send attempt fails due to a temporary error code, when the system detects the temporary error, then the system automatically retries up to 3 times and, if still unsuccessful, marks status as 'Failed' and alerts the host.
Slack Message Delivery Tracking
Given a prep snapshot is sent via Slack DM, when the Slack API acknowledges message receipt, then the system logs status as 'Delivered' and displays the message timestamp in the dashboard.
Calendar Invite Delivery Verification
Given a calendar invite is sent, when the calendar API confirms the invite has been delivered, then the system logs the invite as 'Delivered' and makes it visible in the guest preparation timeline.
View Tracking and Notifications
"As a podcast host, I want to know when my guest has viewed the prep materials so that I can be confident they are prepared for the episode."
Description

Introduce view tracking to detect when guests open or view the prep snapshot. The feature should trigger notifications or status updates in the host’s dashboard when a guest accesses the material. Integration with email open tracking, link click monitoring, and Slack message read indicators is required. This functionality enhances visibility into guest engagement and enables timely host follow-up.

Acceptance Criteria
Email Open Tracking Initiates Dashboard Update
Given a prep snapshot email is sent with a tracking pixel, when the guest opens the email, then the system must record the open event within 5 seconds and update the guest's status to 'Email Opened' on the host dashboard.
Link Click Monitoring Updates Access Status
Given a prep snapshot link is shared via SMS, when the guest clicks the link, then the system logs the click event, marks the status as 'Link Clicked' on the dashboard, and notifies the host within 10 seconds.
Slack Read Indicator Reflects Message View
Given a prep snapshot is posted to Slack with a read indicator, when the guest's Slack client marks the message as read, then the system captures the read receipt and updates the host dashboard to show 'Slack Message Read' within 10 seconds.
Host Dashboard Displays Real-Time Guest Engagement
Given any view tracking event (email open, link click, or Slack read), when the event is recorded, then the host dashboard must reflect the latest guest engagement status in real time without requiring a page refresh.
Notification Sent Upon First Snapshot Access
Given the first tracking event for a guest accessing the prep snapshot, when this event occurs, then the system sends a push notification to the host's dashboard alerting them of the access within 10 seconds.
Branded Prep Snapshot Formatting
"As a podcast host, I want the prep snapshot to reflect my podcast’s branding so that my guests receive a professional, consistent experience."
Description

Support branded and customizable templates for prep snapshots, allowing hosts to include their podcast logo, color scheme, and personalized messaging. The system should render previews in each channel’s format and ensure responsive design for both desktop and mobile. This enhances professionalism and reinforces brand identity in guest communications.

Acceptance Criteria
Template Customization Preview
Given a host uploads a podcast logo, selects primary and secondary colors, and enters a personalized message When the host saves the template and opens the preview Then the preview displays the logo at the correct size and position, applies the selected colors to header and footer, and shows the personalized message exactly as entered
Email Desktop Preview
Given a branded template is selected When the host clicks 'Preview in Email' on a desktop Then the system renders the preview in a desktop email client layout showing correct logo placement, color scheme applied to header and footer, consistent typography, and the personalized message
Email Mobile Preview
Given a branded template is selected When the host clicks 'Preview in Email' on a mobile device emulator Then the system renders the preview responsively with optimized image sizes, scalable text, and maintains logo clarity and color consistency
Slack Message Preview
Given a branded template is selected When the host clicks 'Preview in Slack' Then the system displays the preview as it will appear in Slack, including the logo as a message attachment thumbnail, color accents in the message card, and correct formatting of the personalized message
Calendar Invite Preview
Given a branded template is selected When the host clicks 'Preview in Calendar Invite' Then the system generates a calendar event preview (.ics) showing the logo in the event banner, applies the color scheme to event details, includes the personalized message in the description, and is compatible with Google Calendar and Outlook
Automatic Retry on Delivery Failure
"As a podcast host, I want the system to automatically retry sending prep snapshots if the first attempt fails so that my guests receive materials without me manually retrying."
Description

Develop an automatic retry mechanism for failed deliveries. The system should detect failures, queue retries with exponential backoff, and notify the host if all retries fail. Retry logic must respect rate limits and avoid spam triggering. This requirement ensures reliable delivery of prep materials even when transient errors occur.

Acceptance Criteria
Initial Delivery Failure Detection
Given a prep snapshot delivery attempt fails with a transient error (e.g., network timeout or 5xx response), When the system detects the failure, Then it logs the failure with timestamp and error details and marks the message as 'retry_pending'.
Exponential Backoff Retry Scheduling
Given a message is marked 'retry_pending', When scheduling retries, Then the system queues retry attempts at intervals following exponential backoff starting at 1 minute and doubling each time, up to a maximum interval of 1 hour, for a maximum of 5 attempts.
Rate Limit Compliance
Given the system has sent N messages in the past minute, When scheduling or executing a retry, Then the system ensures that the total sends do not exceed the configured rate limit of M messages per minute by delaying retry execution as needed.
Host Notification on Exhausted Retries
Given a message has failed all retry attempts, When the retry count exceeds the maximum allowed, Then the system sends a notification to the host summarizing the failure details and logs the event in the failed deliveries registry.
Retry Queue Persistence Across Restarts
Given the application restarts unexpectedly, When the system initializes, Then all pending retry entries are reloaded from persistent storage and resume retry scheduling according to their original backoff timing.

Real-Time Sync

Automatically updates previously generated prep briefs whenever hosts modify schedules, topics, or resources, ensuring guests always have the latest information without manual regeneration.

Requirements

Dynamic Prep Brief Refresh
"As a podcast host, I want prep briefs to update automatically when I change schedules or topics so that my guests receive the latest details without me having to regenerate the document manually."
Description

System automatically detects when hosts modify schedules, topics, or resource links and instantly regenerates and updates prep briefs in real time, ensuring guests always have the most current information without manual intervention.

Acceptance Criteria
Host updates episode schedule
Given an existing prep brief; When the host modifies the episode date or time; Then the system regenerates the prep brief within 30 seconds and sends an updated version to the guest
Host modifies topic outline
Given an existing prep brief; When the host updates one or more topic headings or descriptions; Then the system regenerates the prep brief reflecting the new topics and notifies the guest
Host changes resource link
Given an existing prep brief; When the host edits or replaces a resource link; Then the prep brief is instantly regenerated with the updated link and the guest receives the updated brief
Multiple simultaneous updates
Given multiple fields (schedule, topics, resources) are updated at once; When the host saves all changes; Then the system regenerates a single coherent prep brief that incorporates all updates within one minute
Guest retrieves updated brief
Given a guest accessing the prep brief after updates; When the guest opens the prep brief link or app; Then the guest sees the latest regenerated brief without needing to refresh manually
Schedule Change Webhook Integration
"As a host using Google Calendar, I want any schedule adjustment to be captured and updated in prep briefs so that guests see the correct date and time."
Description

Implement webhook listeners that capture schedule modifications from integrated calendar services (e.g., Google Calendar, Outlook) and trigger the real-time sync process, ensuring external changes are reflected immediately in prep briefs.

Acceptance Criteria
Prep Brief Updates on Episode Time Change
Given the host modifies the episode start time in Google Calendar When the webhook listener receives the schedule update Then the system updates the prep brief within 30 seconds to reflect the new time And the guest’s prep packet shows the updated start time
Bulk Episode Reschedule Handling
Given the host reschedules multiple episodes at once in Outlook When the webhook listener processes the batch update Then all corresponding prep briefs are updated within 2 minutes And no prep brief is missed or duplicated
Event Deletion Propagates to Prep Brief
Given the host deletes a scheduled episode from Google Calendar When the webhook listener detects the deletion Then the corresponding prep brief is archived and removed from the guest’s view within 1 minute
New Episode Scheduling Triggers Brief Generation
Given the host creates a new episode event in Outlook When the webhook listener captures the new event Then a new prep brief is generated automatically within 30 seconds And the guest receives the initial prep packet with correct date, time, and topics
Recurring Episode Time Adjustment
Given the host updates the time for a recurring episode series in Google Calendar When the webhook listener receives the update for one occurrence Then only that occurrence’s prep brief is updated within 30 seconds And future occurrences remain unchanged unless separately updated
Topic & Resource Sync Engine
"As a host, I want to update discussion topics or resource links and have these changes instantly appear in the guest prep packet to ensure guests have the latest context and materials."
Description

Build a synchronization engine that monitors topic updates and resource attachments (links, documents) within the platform and propagates these changes to existing prep briefs, maintaining consistency across all guest-facing materials.

Acceptance Criteria
Host updates episode topic before prep brief distribution
Given an existing prep brief for an upcoming recording, when the host modifies the episode topic in the schedule, then the system automatically updates the topic section in the guest’s prep brief within 2 minutes.
Host attaches additional resource link post-brief creation
Given a prep brief already generated, when the host adds a new resource link in the episode’s resource section, then the new link is injected into the prep brief and visible in the guest’s dashboard in real-time.
Host removes outdated attached document after brief issuance
Given a prep brief distributed to a guest, when the host removes a previously attached document from the episode’s resources, then the document is removed from the guest’s prep brief view within 2 minutes.
Host updates multiple resource attachments concurrently
Given multiple resource attachments to an episode, when the host adds, updates, or removes resources in quick succession, then all changes are synchronized accurately with no data loss or duplication in the guest’s prep brief.
Host modifies episode recording schedule time
Given a prep brief generated with a scheduled recording time, when the host adjusts the date or time of the recording session, then the prep brief’s schedule section reflects the updated time and the guest receives a notification about the change within 2 minutes.
Conflict Resolution Mechanism
"As a co-host, I want to be alerted of conflicting edits so that I can choose the correct version and ensure the prep brief contains accurate, agreed-upon information."
Description

Design a conflict detection and resolution system that handles simultaneous edits by multiple hosts, prompting users to review conflicts and apply the correct changes to prep briefs, preventing data loss or inconsistencies.

Acceptance Criteria
Concurrent Schedule Edit Conflict
Given two hosts simultaneously modify the same episode’s schedule, When the second save is attempted, Then the system detects a conflict and displays both versions side-by-side for user review.
Simultaneous Topic Update Conflict
Given two hosts edit the episode topic at the same time, When both changes are submitted, Then the system flags the differing topic fields and requires the user to select the preferred value before saving.
Overlapping Resource Assignment Conflict
Given simultaneous edits to guest resource lists by multiple hosts, When changes overlap on the same resource entry, Then the system highlights conflicting entries and prevents merge until resolved.
Conflict Resolution Workflow Accessibility
Given a detected conflict, When the user opens the resolution dialog, Then the conflict resolution interface loads within 2 seconds and allows selection, editing, or rejection of each conflicting change.
Automatic Sync Post-Conflict Resolution
Given a conflict has been resolved by a user, When the resolution is confirmed, Then the system automatically merges the selected changes into the prep brief and updates all connected clients in under 5 seconds.
Real-Time Notification System
"As a guest, I want to receive a notification when the prep brief is updated so that I'm always prepared with the most current information."
Description

Provide real-time notifications via email, in-app messages, or SMS to guests and hosts when prep briefs are updated, ensuring all stakeholders are aware of the latest changes without requiring manual checks.

Acceptance Criteria
Guest Receives Email Notification on Brief Update
Given a host updates a prep brief, when the system sends an email notification to the guest, then the guest receives an email within 1 minute containing the updated schedule, topics, and resources, along with a link to the latest brief.
Guest Views In-App Notification on Brief Update
Given a host modifies a prep brief, when the guest is logged into the app, then an in-app notification appears within 30 seconds showing a summary of the changes, and tapping the notification directs the guest to the updated brief.
Guest Receives SMS Notification on Brief Update
Given a guest without an email address but with a phone number on file, when a prep brief is updated, then the system sends an SMS within 2 minutes containing a concise update message and a URL to view the updated brief.
Host Receives In-App Confirmation After Notification Sent
Given a host makes changes to a prep brief, when the system dispatches notifications to all guests, then the host receives an in-app confirmation notification indicating that notifications were successfully sent to each recipient.
System Retries and Alerts on Notification Failures
Given a notification fails to deliver after three retry attempts, when delivery still fails, then the system logs the failure, marks the guest’s notification status as undelivered, and sends an alert to the host detailing which notifications failed and the associated error messages.
Offline Change Queue
"As a host working offline, I want my changes to be queued and synced when I reconnect so that guests receive the final, correct prep brief."
Description

Develop an offline queue for schedule or topic changes made while the user is disconnected, which syncs automatically once connectivity is restored, ensuring updates are not lost and prep briefs remain up to date.

Acceptance Criteria
Queuing Offline Schedule Changes
Given the user is offline When the user modifies an episode’s scheduled date or time Then the change is stored in a local offline queue with a timestamp and identifier
Queuing Offline Topic Changes
Given the user is offline When the user updates the episode topic or discussion points Then the update is saved to the offline queue and visible in the pending changes list
Automatic Sync on Reconnection
Given there are pending offline changes in the queue When network connectivity is restored Then all queued schedule and topic changes are automatically sent to the server and marked as synced
Conflict Resolution for Concurrent Changes
Given a queued change conflicts with a remote update made while offline When the system attempts to sync Then the user is prompted with options to merge, overwrite local, or keep remote changes
Data Integrity After Sync
Given changes have been synced When the prep brief is regenerated Then it accurately reflects all schedule and topic updates without data loss or duplication

Insight Analytics

Tracks guest engagement metrics—open rates, time spent on sections, and highlighted items—so hosts can identify areas of confusion or interest and refine prep materials for maximum impact.

Requirements

Engagement Metrics Dashboard
"As a podcast host, I want a single dashboard displaying all guest engagement metrics so that I can easily monitor trends and optimize my prep materials."
Description

Develop a centralized dashboard within ChirpFlow that aggregates guest engagement data, including open rates, time spent on sections, and highlighted items. This dashboard should provide hosts with a visual overview of engagement metrics over time, support filtering by episode and guest, and integrate seamlessly with existing episode tracking interfaces. The feature will enable hosts to quickly identify trends, assess the effectiveness of prep materials, and make data-driven adjustments to their workflows.

Acceptance Criteria
Episode-Specific Engagement Overview
Given the host is on the Engagement Metrics Dashboard When they select an episode from the episode filter dropdown Then the dashboard displays open rate, average time spent per section, and total highlighted items for that episode
Guest-Level Engagement Filtering
Given the host has multiple guests on the dashboard When they apply a filter for a specific guest name Then only engagement metrics for that guest across all episodes are shown
Trend Visualization Over Time
Given the host selects a time range (e.g., last 7 days, 30 days, custom) When the time range is applied Then line or bar charts update to show engagement metric trends over that period
Seamless Integration from Episode Tracking
Given the host is viewing an episode’s details in the episode tracking interface When they click the “View Engagement Metrics” button Then the system navigates directly to the Engagement Metrics Dashboard filtered to that episode
Accurate Highlighted Items Count
Given a guest highlights items in their prep packet When the engagement data is fetched Then the total highlighted items count on the dashboard matches the actual number recorded for each section
Section Interaction Tracking
"As a podcast host, I want to see how long guests spend on each section of the prep packet so that I can identify areas of confusion or disinterest."
Description

Implement detailed tracking of how long guests spend on each section of the prep materials. This will capture dwell time at a section level, provide heatmap visualizations, and log deep-dive interactions such as link clicks and resource downloads. By integrating with the prep packet viewer, this requirement ensures hosts can pinpoint which sections engage guests most and which are overlooked.

Acceptance Criteria
Section Dwell Time Recording
Given a guest views a prep packet section, when the guest navigates away or closes the section, then the system logs the total time spent on that section with a timestamp and section identifier.
Link Click Logging
Given a guest clicks a hyperlink within a prep packet section, when the click event occurs, then the system records the event with the section ID, link URL, and timestamp.
Resource Download Tracking
Given a guest downloads a resource from a prep packet section, when the download is initiated, then the system logs the download event including resource name, section ID, and guest identifier.
Heatmap Visualization Generation
Given collected section interaction data from multiple guests, when a host requests the heatmap view, then the system produces a visual overlay highlighting sections based on aggregated dwell time and interaction counts.
Export of Section Interaction Metrics
Given section-level interaction data is available, when the host exports analytics, then the system generates a file (CSV or XLSX) containing metrics for each section: dwell time, click count, and download count.
Highlighted Items Analysis
"As a podcast host, I want to know which parts of the prep materials guests highlight so that I can understand their focus areas and improve content clarity."
Description

Capture and analyze the items that guests highlight or annotate in their prep materials. This feature will record highlighted text, comments, and annotations, aggregate frequently highlighted passages, and provide hosts with insights into key areas of interest. Integration with the engagement dashboard will allow for cross-referencing highlights with overall engagement patterns.

Acceptance Criteria
Guest Highlights Prep Material
Given a guest is viewing their prep packet, when they highlight a passage and add a comment, then the system records the highlighted text and comment with a timestamp linked to the correct episode and guest profile.
Aggregation of Frequent Highlights
Given multiple guests have highlighted prep materials across episodes, when the host views the Frequent Highlights dashboard, then the system aggregates passages highlighted by at least three guests and displays them sorted by highlight count.
Host Access to Highlight Insights
Given a host accesses the dashboard, when they filter by episode or date, then the system displays highlighted items along with annotations and the number of guests who highlighted each item.
Cross-Reference Highlights with Engagement Patterns
Given the host analyzes engagement data, when they select a highlighted item, then the system displays correlated metrics such as time spent on the page and open rates alongside the highlight.
Export Highlighted Items Report
Given the host requests an export, when they click Export Highlights Report, then the system generates a CSV or PDF containing all highlighted items, comments, and associated engagement metrics.
Real-time Engagement Alerts
"As a podcast host, I want to receive alerts when a guest hasn’t engaged with prep materials so that I can follow up and prevent last-minute no-shows or gaps in preparation."
Description

Create a real-time alert system that notifies hosts when a guest shows low engagement metrics, such as not opening materials within a specified timeframe or spending minimal time on critical sections. Alerts should be configurable, sent via email or in-app notifications, and include suggested actions to re-engage the guest before recording.

Acceptance Criteria
Materials Not Opened Within 24 Hours
Given a guest is sent prep materials, when 24 hours elapse without the materials being opened, then the system sends an alert notification to the host.
Minimal Time Spent on Critical Section
Given a guest opens the prep materials, when the time spent on the "Recording Guidelines" section is less than 2 minutes, then the system triggers a low-engagement alert.
Configurable Alert Thresholds
Given a host updates alert thresholds to custom values for open-time and section engagement, when a guest’s behavior crosses these custom thresholds, then alerts are generated according to the configured settings.
Multi-Channel Alert Delivery
Given an alert is triggered for low engagement, then the system delivers the notification via both email to the host’s registered address and an in-app notification within 5 minutes.
Suggested Re-engagement Actions Included
Given an alert is generated, then the notification includes at least one suggested action to re-engage the guest, such as sending a reminder email or sharing a quick tip video.
Prep Material Recommendation Engine
"As a podcast host, I want automated suggestions for enhancing my prep materials so that I can increase guest engagement and reduce confusion."
Description

Develop a recommendation engine that suggests improvements to prep materials based on aggregated engagement data. Leveraging machine learning, the engine will identify sections with low engagement or frequent highlights and propose content restructuring, additional examples, or clarifications. Recommendations will be displayed in the dashboard and incorporated into templates for future episodes.

Acceptance Criteria
Low Engagement Section Detection
Given aggregated engagement data for an episode’s prep materials with sections below the 20% engagement threshold, when the recommendation engine runs, then it flags each low-engagement section in the recommendations output.
Content Restructuring Suggestion
Given a flagged low-engagement section, when the engine analyzes similar high-engagement content patterns, then it generates at least one restructuring suggestion per section specifying new headings or bullet-point arrangements.
Additional Examples Proposal
Given a section with highlight counts above the average but below-average time spent, when the recommendations are produced, then the engine suggests at least two concrete examples or clarifications to improve comprehension.
Dashboard Recommendation Display
Given generated recommendations for an episode, when the host opens the dashboard, then each recommendation displays the section title, key engagement metrics, and actionable suggestion text with a link to edit the prep material.
Template Integration of Recommendations
Given a new episode template, when generating the template for future episodes, then the engine automatically inserts approved past recommendations into designated placeholders for host review.

Language Flex

Automatically translates the prep snapshot into a guest’s preferred language, breaking down language barriers and enabling hosts to work with a diverse range of international guests effortlessly.

Requirements

Automatic Language Detection
"As a podcast host, I want the system to automatically detect a guest’s preferred language so that I can send prep packets without having to select the language manually."
Description

Automatically identify the guest’s preferred language based on their profile settings or initial communication. The system should analyze guest data or email headers to determine language preference without manual input, ensuring that each prep snapshot is translated into the correct language. This feature reduces host workload by eliminating manual language selection and ensures guests receive materials in their native language seamlessly.

Acceptance Criteria
Guest Profile Language Detection
Given a guest’s profile has a preferred language set to Spanish, When generating the prep snapshot, Then the system identifies the preference as Spanish and translates the entire snapshot into Spanish.
Email Header Language Parsing
Given a guest’s initial email includes a French locale in the header, When the system processes the email, Then it automatically detects ‘fr’ and sets the guest’s preferred language to French.
Fallback Default Language Handling
Given no language preference is available in the guest’s profile or email, When generating the prep snapshot, Then the system defaults to English and displays a prompt for the host to confirm or change the language.
Language Detection Accuracy Reporting
Given the system processes language detection for 100 guest samples, When reviewing detection outcomes, Then at least 95% of the detected languages must match the guests’ actual preferences.
Prep Packet Translation Verification
Given a prep packet is generated after detecting the guest’s preferred language, When the packet is downloaded or emailed, Then all text elements within the packet must be translated into the detected language.
Translation Engine Integration
"As a podcast host, I want the system to translate prep snapshots accurately so that international guests receive instructions in their own language without misunderstandings."
Description

Integrate a third-party translation API (e.g., Google Translate, DeepL) to translate the full prep snapshot content accurately. The integration must support multiple languages, handle API rate limits, and cache translations for performance. It should allow the translation of text, links, and formatted content, ensuring prep materials are complete and contextually correct.

Acceptance Criteria
Translate Prep Snapshot to Guest's Preferred Language
Given a generated prep snapshot and a selected guest language (e.g., Spanish), When the host triggers translation, Then all text, links, and formatting must be returned fully translated into the selected language within 5 seconds.
Preserve Formatting and Links in Translated Content
Given a prep snapshot containing bold, italics, bullet lists, and embedded links, When translated, Then the translated output must maintain the original formatting and functional links exactly as in the source.
Handle API Rate Limits Gracefully
Given multiple concurrent translation requests approaching the API rate limit, When the limit is reached, Then the system should queue further requests with exponential backoff and notify the host of any delay, without losing data.
Cache Translations for Repeated Requests
Given a prep snapshot previously translated into a specific language, When the same snapshot is requested again, Then the system should retrieve the translation from cache and return it in under 1 second, bypassing the API call.
Support Detection of Unsupported Languages
Given a guest selects a language not supported by the translation API, When translation is requested, Then the system should display a clear error message and default to the original language content without disrupting workflow.
Custom Terminology Glossary
"As a podcast host, I want to maintain a custom glossary of podcast-specific terms so that translations remain consistent with my brand and industry terminology."
Description

Provide a glossary management interface where hosts can define brand-specific terms, jargon, and names to ensure consistent translation. The glossary should allow adding, editing, and prioritizing terms, which the translation engine will reference to maintain correct translations of specialized vocabulary across all translated prep snapshots.

Acceptance Criteria
Adding New Glossary Terms
Given the host enters a new term, definition, and translation and saves it, then the term appears in the glossary list with correct details and a default priority.
Editing Existing Glossary Terms
Given the host selects an existing term and modifies its label, definition, or translation and saves changes, then the updated details are reflected in the glossary list immediately.
Prioritizing Glossary Terms Order
Given the host drags and drops a term to a new position in the priority list and confirms, then the term order is updated and the new order persists across sessions.
Glossary Integration with Translation
Given a prep snapshot translation request and the glossary contains a matching term, then the translated output uses the specified glossary translation instead of the default translation engine output.
Deleting Glossary Terms
Given the host deletes a term from the glossary and confirms the action, then the term no longer appears in the glossary list and is excluded from subsequent translations.
Language Preference Management
"As a podcast host, I want to set default language preferences for my guests so that the system applies my chosen languages without manual adjustment each time."
Description

Enable hosts to set global and per-guest language preferences in their account settings. Hosts should be able to specify a default target language for all guests, with the option to override the language for individual guests. Preference settings should be visible on guest profiles and applied automatically to new and existing prep snapshots.

Acceptance Criteria
Host sets a default global language preference
Given the host is on the account settings page When the host selects “Spanish” from the default language dropdown and saves changes Then the system persists “Spanish” as the global preference and displays it in the settings page
Host overrides language for an individual guest
Given the host is viewing a guest’s profile When the host selects “German” from the guest-specific language selector and confirms the change Then the guest’s profile displays “German” as the chosen language and this override takes precedence over the global setting
Prep snapshot automatically translated based on language preference
Given a new prep snapshot is generated for a guest with a language preference of “French” When the snapshot is created Then all text content in the snapshot is translated into French and delivered to the host and guest
Existing guest snapshots update when default language changes
Given the host changes the global default language from “English” to “Portuguese” When the change is saved Then all existing prep snapshots for guests without individual overrides are translated into Portuguese within 5 minutes
Language preference visible on guest profile
Given the host navigates to any guest’s profile When the profile page loads Then a “Language Preference” field is visible and shows either the global default or the guest’s override language
Real-Time Translation Preview
"As a podcast host, I want to preview translated content before sending so that I can verify accuracy and make edits if necessary."
Description

Allow hosts to preview the translated prep snapshot before sending it to the guest. The preview should display both source and translated text side by side, highlighting any glossary substitutions. Hosts can approve, request re-translation, or edit segments directly in the preview interface to ensure accuracy and tone.

Acceptance Criteria
Opening Translation Preview
Given a prep snapshot and a selected target language When the host clicks the "Preview Translation" button Then the system displays the source text and translated text side by side within 2 seconds
Highlighting Glossary Substitutions
Given the translated preview When translated text includes glossary-substituted terms Then those terms are highlighted in a distinct color and display a tooltip with the original glossary term
Inline Editing of Segments
Given the side-by-side preview When the host edits a translated segment and clicks "Save" Then the system updates that segment in the preview and flags it as a custom edit
Requesting Re-translation
Given a translated segment in the preview When the host clicks "Request Re-translation" Then the system marks the segment as pending re-translation and queues it for automated re-processing
Approving Translations
Given all segments reviewed When the host clicks "Approve Translation" Then the system marks the entire prep snapshot as approved and enables the "Send to Guest" button

SynergyMatch

Leverages AI to identify and pair guests with podcasters sharing similar audiences and themes, ensuring collaborations resonate with both listener bases and maximize mutual growth potential.

Requirements

Audience Similarity Analysis
"As a podcast host, I want to understand which guest audiences overlap with mine so that I can invite guests who resonate with my listeners and drive mutual growth."
Description

Implement a service that profiles podcast hosts and potential guests by analyzing their existing listener demographics, content themes, and engagement metrics. This service will normalize and store audience data in a unified format, enabling accurate similarity scoring and ensuring that matches align with shared listener interests for higher engagement rates.

Acceptance Criteria
Host Audience Data Normalization
Given raw host demographic and engagement data When ingested by the profiling service Then all fields are mapped to the unified schema with 100% field coverage and no null values
Guest Audience Data Ingestion
Given API-sourced guest listener metrics When processed by the service Then all metrics are normalized to the standardized engagement scale within 5 seconds and stored without data loss
Similarity Score Calculation
Given two normalized audience profiles When similarity scoring runs Then the service returns a numeric score between 0 and 100 using the weighted demographic and engagement factors and matches the benchmark dataset with at least 95% accuracy
Handling Incomplete Data
Given a profile missing one or more demographic attributes When normalization occurs Then the service logs a warning, applies predefined imputation rules, and still produces a valid similarity score
Performance Under High Load
Given 100 concurrent similarity scoring requests When the service is under peak load Then 95% of requests complete within 200ms with zero request failures logged
Automated Guest Matching Algorithm
"As a podcast host, I want the system to suggest the best guest matches automatically so that I can efficiently find collaborators who will appeal to my audience without manual research."
Description

Develop an AI-driven algorithm that processes the normalized audience profiles and content themes to generate ranked match suggestions. The algorithm should weigh factors like listener overlap, thematic relevance, and past collaboration success to optimize pairing quality and maximize audience cross-promotion potential.

Acceptance Criteria
Initial Match Generation Request
Given two podcasters with normalized audience profiles and content themes in the database, When the host initiates a match generation process on the SynergyMatch feature, Then the system returns a list of top 10 guest suggestions ranked by a composite score factoring listener overlap (>=30%), thematic relevance (>=80%), and past collaboration success rate (>=50%), within 2 seconds.
Bulk Match Suggestions API Call
Given a scheduled batch process for weekly match updates, When the system triggers the API to generate matches for all active podcasters, Then the system processes up to 1000 profiles and produces a complete ranked list for each within 60 seconds, without errors.
Host Manual Ranking Adjustment
Given a host reviews the generated match list, When the host manually reorders, removes, or adds a guest suggestion, Then the system persists the updated ranking and reflects changes in subsequent API calls and the dashboard view.
Feedback-Driven Algorithm Tuning
Given hosts provide feedback on match quality post-collaboration, When at least 100 feedback entries are collected for a given host, Then the algorithm automatically recalibrates weighting factors to improve relevance for future match suggestions in the next run.
High-Load Performance Test
Given 10,000 concurrent match generation requests during peak hours, When the system processes requests, Then 95% of requests complete within SLA of 5 seconds and system CPU/memory utilization remains below 80%.
Match Filter & Customization
"As a podcast host, I want to filter and adjust match criteria so that I can find guests who not only share my audience but also fit my content focus and schedule."
Description

Create a set of interactive filters and customization options that allow hosts to refine match suggestions based on criteria such as audience size range, content category, geographic region, and availability. This feature ensures hosts can tailor suggestions to their specific requirements and scheduling constraints.

Acceptance Criteria
Audience Size Filter Selection
Given the host sets a minimum and maximum audience size; when the filters are applied; then only guests with audience sizes within the specified range are displayed.
Content Category Filter Application
Given the host selects one or more content categories; when the filters are applied; then only guests tagged with the selected categories appear in the match suggestions.
Geographic Region Filtering
Given the host chooses a geographic region; when the filter is applied; then all guest suggestions outside the selected region are excluded from the results.
Availability Constraint Filtering
Given the host enters their available date and time ranges; when the filters are applied; then only guests whose availability overlaps with the host’s specified slots are suggested.
Combined Filter Usage
Given the host applies multiple filters (audience size, content category, geographic region, availability); when the filters are applied simultaneously; then the system returns guests meeting all criteria within two seconds.
Match Insights Dashboard
"As a podcast host, I want a visual dashboard showing match metrics so that I can quickly assess and compare potential guests’ fit with my show."
Description

Design a dashboard interface that presents detailed insights for each match suggestion, including similarity scores, shared keywords, audience overlap percentages, and predicted engagement lift. The dashboard will visualize key metrics to help hosts make informed collaboration decisions at a glance.

Acceptance Criteria
Viewing Similarity Scores for Matches
Given the host has selected a match suggestion When the Match Insights Dashboard loads the match details Then it displays a similarity score as a percentage between 0% and 100% with two decimal places.
Identifying Shared Keywords
Given a selected match suggestion When the host views the keyword section Then the dashboard lists all shared keywords sorted by relevance and highlights the top five keywords.
Analyzing Audience Overlap
Given match suggestions are available When the host navigates to the audience overlap panel Then it shows the overlap percentage between the host's and guest's audiences, and the value updates within two seconds of selection.
Estimating Engagement Lift
Given the host views a specific match suggestion When the predicted engagement lift metric is calculated Then the dashboard displays the estimated percentage increase in listens with a confidence interval.
Exporting Match Insights Report
Given the host has reviewed match insights When the host clicks the export button Then the system generates and downloads a PDF report containing similarity scores, shared keywords, audience overlap, and predicted engagement lift.
Continuous Learning & Optimization
"As a podcast host, I want the system to learn from past collaborations so that future match suggestions become more accurate and effective over time."
Description

Implement a feedback mechanism that collects post-collaboration performance data—such as listener retention, downloads, and feedback—and feeds it back into the matching algorithm. This will allow the system to learn from real outcomes and continuously improve future match accuracy and relevance.

Acceptance Criteria
Performance Data Collection Trigger
Given an episode is published, when 24 hours have elapsed, then the system ingests listener retention, download counts, and feedback metrics for that episode.
Automated Model Retraining
Given new performance data is available, when the scheduled update runs, then the matching algorithm retrains using the latest data and logs the retraining completion.
Matching Accuracy Benchmark
Given baseline matching accuracy is recorded at launch, when three feedback cycles complete, then the system’s match relevance score increases by at least 10%.
Data Completeness Verification
Given performance data ingestion, when validation runs, then at least 95% of records are complete and error-free, and any invalid entries are logged.
User Correction Handling
Given a podcaster submits a data correction, when within 24 hours, then the correction is applied to the performance dataset and utilized by the algorithm on the next retraining cycle.

CoPromo Scheduler

Automates the timing and delivery of joint promotional content across multiple podcasts, seamlessly coordinating emails, social posts, and show mentions to drive collective visibility without manual planning.

Requirements

CoPromo Timeline Designer
"As a podcast host, I want to visually design and adjust the schedule of all co-promotion activities across multiple podcasts so that I can ensure coordinated timing and avoid overlaps."
Description

Provide an intuitive drag-and-drop timeline builder for scheduling all co-promotion activities—emails, social posts, and in-show mentions—across participating podcasts. Hosts gain a visual overview of the campaign schedule, ensuring coherent, staggered rollouts that maximize audience reach. Integrated with ChirpFlow’s calendar data, it sends real-time updates to hosts and guests, reducing manual planning errors and improving coordination of promotional efforts.

Acceptance Criteria
Visual Timeline Creation
Given a host opens the CoPromo Timeline Designer and selects a promotional activity type, when they drag and drop the activity onto the timeline canvas at a specific date and time slot, then the activity is placed correctly with a visual label and can be repositioned or edited.
Calendar Integration Sync
Given a user saves the designed timeline, when the system processes the save action, then all scheduled promotional activities automatically sync with the host’s ChirpFlow calendar and trigger real-time notifications to hosts and guests.
Conflict Detection and Alert
Given existing scheduled promotional activities on the timeline, when a host attempts to place a new activity that overlaps in time, then the system displays a conflict alert and prevents saving until the overlap is resolved.
Exporting Campaign Timeline
When the host clicks the export button, then the system generates a PDF or image file that displays all scheduled promotional events with dates, times, podcast names, and activity types in a clear chronological layout.
Live Campaign Preview
Given a fully scheduled co-promotion campaign, when the host initiates a live preview, then the system displays a chronological list of all activities including email sends, social posts, and show mentions for final review.
Multi-Channel Content Hub
"As a podcast host, I want a centralized hub to create and manage emails, social posts, and in-show scripts for co-promotion so that I can maintain consistent branding and simplify content preparation."
Description

Include a centralized content repository where hosts can create, edit, and store promotional materials tailored to each channel—HTML email templates, social media post drafts, and in-show mention scripts. All content is versioned and linked to the campaign timeline, ensuring consistency and easy retrieval. Integration with third-party email services and social schedulers enables seamless deployment of materials, simplifying content management and maintaining on-brand messaging across all channels.

Acceptance Criteria
Creating and Saving an HTML Email Template
Given the host is in the Content Hub and selects “New Email Template” for a campaign, When they fill in the subject, body (with placeholders), and branding elements then click “Save,” Then the template is stored in the repository with correct metadata (creator, timestamp, campaign association) and is immediately visible in the template list.
Editing and Versioning a Social Media Post Draft
Given an existing social media post draft in the hub, When the host edits the content or attachments and clicks “Save,” Then the system creates a new version, retains the previous version in version history, and displays version numbers, timestamps, and editor information.
Associating Promotional Materials with a Campaign Timeline
Given a campaign timeline is defined, When the host links an email template, social post, or script to a specific timeline date, Then the content item appears under that date in the timeline view, and any unscheduled items are flagged for scheduling.
Deploying Content via Third-Party Integration
Given the host has authenticated with a supported email service or social scheduler, When they select content items and click “Deploy” with scheduling details, Then the system sends the correct API requests, confirms successful scheduling, and logs deployment status for each item.
Retrieving and Previewing Stored In-Show Mention Scripts
Given multiple in-show mention scripts are stored in the hub, When the host searches by keyword or filters by campaign and selects a script, Then the script content is displayed in a preview pane with formatting, metadata, and an option to copy or edit.
Searching Across Channels and Campaigns
Given the host enters a search term and applies channel and campaign filters, When they execute the search, Then the system returns a list of matching templates, posts, and scripts with relevant metadata, sorted by relevance or date.
Host Approval & Notification System
"As a podcast host, I want automated notifications and an approval workflow for co-promo materials so that I can review and approve content before it goes live and avoid last-minute changes."
Description

Trigger automated notifications to hosts and guests at key milestones—such as content ready for review or upcoming recording slots—via email and in-app alerts. Include an approval workflow allowing recipients to accept, request changes, or reject items directly within ChirpFlow. This ensures all stakeholders sign off before publication, minimizing oversights and reducing last-minute edits.

Acceptance Criteria
Content Ready for Review Notification
Given a host marks episode content as 'Ready for Review' When the status is updated Then the system sends an email and in-app notification with a review link
Upcoming Recording Slot Notification
Given a recording slot is scheduled When there are 24 hours remaining Then the system dispatches email and in-app alerts to both host and guest with date, time, and joining details
In-App Approval Actions
Given a host or guest receives a review notification in-app When they select 'Approve', 'Request Changes', or 'Reject' Then the system logs the action, updates the workflow status, and sends a confirmation notification
Email Approval Response Handling
Given a host replies to the review email with an approval keyword ('Approve', 'Change', 'Reject') When the system receives the email Then it parses the response, updates the approval status, and records the action in the episode log
Change Request Workflow
Given a host requests changes during review When changes details are submitted through the app or email Then the system notifies the content creator, tracks requested modifications, and reissues the review notification once updates are applied
Promo Asset Generator & Distributor
"As a podcast host, I want the system to automatically generate and distribute branded promotional assets to guests and platforms so that I can save time and ensure consistent quality."
Description

Automatically generate branded promotional assets—graphics sized for social platforms, email-ready HTML, and in-show mention cards—based on host-defined templates. Distribute these assets to guests, integrate with social scheduling tools, and send emails at the scheduled times without manual intervention. By automating asset creation and delivery, hosts save hours of manual work and ensure consistent, polished branding across all promotional channels.

Acceptance Criteria
Template-Based Asset Generation
Given a host-defined template and episode metadata When the host triggers asset generation Then the system produces correctly sized graphics for Facebook (1200x630), Twitter (1024x512), Instagram (1080x1080), an email-ready HTML asset, and an in-show mention card within 60 seconds
Automated Asset Distribution to Guests
Given generated assets and a list of guest email addresses When the distribution process is initiated Then each guest receives an email with all assets attached or linked and a delivery receipt within 5 minutes
Integration with Social Scheduling Tools
Given a connected social scheduling tool (e.g., Hootsuite) When the host selects assets to social-schedule Then draft posts are created in the external tool with the correct asset file, caption template, and scheduled publish time matching the host’s settings
Scheduled Email Dispatch
Given an email schedule is configured When the scheduled send time arrives Then the system automatically sends the HTML email asset to the defined recipient list and logs a successful send status for each recipient
In-Show Mention Card Availability
Given generated mention cards When the host views the episode dashboard Then high-resolution mention cards are available for download with correct branding, and each file size is under 5MB
CoPromo Performance Analytics
"As a podcast host, I want to see performance metrics for each co-promo campaign in a dashboard so that I can measure success and optimize future promotions."
Description

Provide a real-time dashboard displaying key metrics for each joint promotional campaign: email open and click-through rates, social impressions and engagements, and post-promo listenership uplift. Pull data from integrated services (email provider, social platforms, and listening analytics) and present both campaign-level and channel-level breakdowns. Enable hosts to identify the most effective tactics and derive actionable insights to refine future co-promotion strategies.

Acceptance Criteria
Accessing Real-Time Campaign Overview
Given the CoPromo Performance Analytics dashboard is opened, When a co-promotion campaign is active, Then the dashboard displays real-time metrics (email open rate, click-through rate, social impressions, social engagements, and listenership uplift) updated within the last five minutes.
Viewing Email Metrics for Selected Campaign
Given a specific campaign is selected, When the email metrics section is loaded, Then the system lists each email blast with its open and click-through rates reflecting data from the integrated email provider API with 99% data consistency.
Viewing Social Media Engagements
Given a specific campaign is selected, When the social metrics section is loaded, Then the system displays impressions, likes, shares, and comments for each social channel, with metrics matching data from each social platform’s API for the past 30 days.
Analyzing Post-Promo Listenership Uplift
Given the campaign date range is defined, When the listenership uplift section is loaded, Then the system calculates and displays episode listens before and after promotion along with percentage uplift for each episode.
Exporting Campaign and Channel Reports
Given the user requests a report export, When the export action is triggered, Then the system generates and downloads a CSV file containing both campaign-level summaries and channel-level metric breakdowns with timestamps and data source annotations.
CoPromo Campaign Templates
"As a podcast host, I want to save and reuse co-promo campaigns as templates so that I can quickly launch new collaborations without reconfiguring every detail."
Description

Enable hosts to save fully configured co-promo campaigns—including timeline settings, content, and asset templates—as reusable templates. Allow users to clone templates for new collaborations, reducing setup time and ensuring best practices are applied consistently. Support categorization and sharing of templates across the team to accelerate campaign launches and standardize workflows.

Acceptance Criteria
Saving a New CoPromo Campaign Template
Given a user has fully configured a co-promo campaign timeline, content blocks, and asset placeholders, When the user selects “Save as Template” and provides a unique template name, Then the system stores the template with all configurations and lists it in the Template Library.
Cloning an Existing Template for a New Collaboration
Given an existing co-promo campaign template in the Template Library, When the user selects “Clone Template” and assigns a new campaign name and dates, Then the system creates a new campaign pre-populated with the template’s timeline, content, and assets without altering the original template.
Categorizing a Template for Team Accessibility
Given multiple co-promo templates in the Template Library, When the user applies or edits category tags on a template, Then the system displays the template correctly under the selected categories and allows filtering by those categories.
Sharing a Template with Team Members
Given a saved co-promo template, When the user chooses “Share Template,” selects team members or groups, and sets permissions, Then the system grants access permissions to the selected members, and the shared template appears in their Template Library.
Ensuring Template Integrity After Updates
Given a user updates the timeline settings, content sections, or asset placeholders within a saved template, When the user saves changes, Then the system persists the updates to the template, and future clones reflect the updated configuration without modifying previously cloned campaigns.

Collaboration Dashboard

Provides a centralized hub where hosts can track active cross-show partnerships, upcoming promo campaigns, assigned tasks, and timelines—keeping collaborations organized and on schedule.

Requirements

Real-time Task Status Tracking
"As a podcast host, I want to see real-time status updates of collaboration tasks so that I can quickly identify bottlenecks and ensure timely completion."
Description

Provide live, up-to-the-minute updates on the progress of tasks within each cross-show collaboration, allowing hosts to instantly see which tasks are completed, in progress, or overdue. This feature integrates seamlessly with existing project workflows and updates in real-time as team members update their tasks, reducing manual check-ins and helping hosts quickly identify and resolve bottlenecks.

Acceptance Criteria
Viewing Real-Time Task Status on Collaboration Dashboard
Given the host navigates to the Collaboration Dashboard, when any team member updates a task status, then the dashboard reflects the new status for that task within 5 seconds without requiring a manual page refresh.
Highlighting Overdue Tasks
Given the current date and time exceed a task’s due date and the task status remains not completed, then the task row on the dashboard is visually flagged as overdue immediately upon dashboard load or update.
Reflecting External Workflow Updates
Given the Collaboration Dashboard is integrated with an external project management tool, when a task status changes in the external tool, then the dashboard updates the corresponding task status within 10 seconds of the external change.
Task Progress Indicators for Multiple Collaborators
Given tasks are assigned to multiple collaborators, when individual collaborators update their portion of the task, then the dashboard displays separate progress indicators for each collaborator and an aggregated overall completion percentage.
Real-Time Notifications on Status Changes
Given a task status changes to “In Progress” or “Completed”, when this change occurs, then all subscribed hosts receive an in-app notification within 5 seconds.
Interactive Timeline View
"As a host, I want an interactive timeline of collaboration milestones so I can track progress and upcoming deadlines."
Description

Present a dynamic, interactive timeline that maps out key milestones, deadlines, and campaign phases for each partnership. Hosts can zoom in and out, drag milestones to adjust dates, and click on events for detailed task lists. This visual tool enhances planning accuracy and keeps all stakeholders aligned on upcoming deliverables.

Acceptance Criteria
Timeline Initialization
Given the host navigates to the Collaboration Dashboard and selects the Interactive Timeline View, When the timeline loads, Then all key milestones, deadlines, and campaign phases for the selected partnership are displayed in chronological order within the default 6-month view.
Zoom Functionality
Given the timeline is displayed, When the host uses the zoom controls to zoom in or out, Then the timeline scales accordingly and milestones adjust their positions without overlapping or truncation.
Milestone Rescheduling
Given the host views a milestone on the timeline, When the host drags the milestone to a new date and releases it, Then the milestone’s date updates in the system, and a confirmation message appears indicating the successful date change.
Event Detail Access
Given the host sees events on the timeline, When the host clicks on an event icon, Then a side panel opens displaying the detailed task list, assigned team members, and any notes related to that event.
Responsive Timeline Display
Given the host accesses the Interactive Timeline on different devices (desktop, tablet, mobile), When the screen size changes, Then the timeline layout adapts to maintain readability, ensuring milestones and labels remain visible and accessible.
Automated Notification Alerts
"As a user, I want automated alerts for upcoming collaboration deadlines so that I never miss important dates and tasks."
Description

Implement configurable alerts that notify hosts and collaborators via email, in-app messages, or SMS when tasks are assigned, updated, or approaching their due dates. Notifications can be tailored per collaboration or per user role, ensuring everyone stays informed without manual follow-ups.

Acceptance Criteria
Task Assignment Notification
Given a host assigns a collaboration task to a user, When the assignment is saved, Then the assigned user receives an email, in-app, and SMS notification within 60 seconds containing task name, due date, assigner, and a link to the task detail.
Upcoming Due Date Reminder
Given a task is within 24 hours of its due date and still incomplete, When the system runs its nightly job, Then the task owner and collaborators receive an in-app and email reminder listing overdue tasks and time remaining.
Notification Preferences Configuration
Given a user accesses their notification settings, When they enable or disable email, in-app, or SMS alerts per collaboration or role, Then the system saves preferences and sends a confirmation message reflecting the updated channels.
Role-Based Alert Customization
Given a collaboration has multiple roles (host, editor, guest manager), When a notification rule is configured for a specific role, Then only users in that role receive the alert channel defined for that event.
Failure and Retry Handling
Given an SMS fails to deliver due to a transient error, When the notification service detects the failure, Then it retries delivery up to two times and logs any undelivered message for administrator review.
Branded Collaboration Workspace
"As a host, I want a branded workspace for each collaboration so that I can maintain consistent show identity and professionalism when sharing with guests."
Description

Allow hosts to customize each collaboration dashboard with show-specific branding elements such as logos, color schemes, and cover images. This workspace can be shared via a unique URL with partners, providing a professional, on-brand experience when collaborating and sharing materials.

Acceptance Criteria
Logo Upload and Display
Given a host is on the branding settings page When they upload a PNG or JPEG file no larger than 5MB Then the logo displays in the workspace header at correct aspect ratio And unsupported formats or oversized files are rejected with an error message
Color Scheme Customization
Given a host opens the color customization panel When they select primary and secondary colors via the color picker Then the workspace background, buttons, and text elements update to use the selected colors And the color contrast ratio meets WCAG AA standards
Cover Image Addition
Given a host navigates to cover image settings When they upload an image between 1200x300 and 3000x750 pixels and no larger than 10MB Then the image appears in the workspace banner area Responsively with no distortion
Shared Workspace Access
Given a host has completed branding customization When they generate and share the workspace URL Then partners accessing the URL see the branded workspace with logos, colors, and cover image intact And no default styling is visible
Branding Persistence Across Sessions
Given branding elements have been saved When any user (host or partner) revisits the workspace in a new browser session Then the customized logo, colors, and cover image load correctly And settings persist across different devices and browsers
Shared Document and Asset Repository
"As a host, I want a shared repository for collaboration assets so that I and my partners can access and edit relevant documents in one place."
Description

Create a centralized repository within the dashboard for all collaboration-related documents, media assets, prep packets, and promotional materials. Users can upload, preview, comment on, and version-control files directly in the platform, ensuring all partners have access to the latest resources.

Acceptance Criteria
Uploading New File to Repository
- The upload button is visible on the repository page. - Clicking upload opens a file selection dialog. - Supported file types (.pdf, .docx, .png, .jpg, .mp3, .mp4) are accepted. - Files under 50MB upload in under 30 seconds. - A progress indicator displays and reaches 100% upon completion. - The file appears in the list with correct filename, size, upload date, and uploader name.
Previewing an Uploaded Asset
- A preview icon is shown next to each supported file. - Clicking the preview icon opens a modal within 5 seconds. - PDF and image files render accurately in the modal. - Audio and video files play from the beginning with working playback controls. - Users can close the preview modal and return to the repository list.
Commenting on a Document
- Users can highlight text or select an area to add a comment. - A comment input appears inline and can be submitted. - Submitted comments include author name and timestamp. - Comments are visible to all collaborators immediately. - Users can reply to or resolve comments, and status updates accordingly.
Version Control for Updated Files
- Uploading a file with the same name creates a new version entry. - The repository lists all versions with version number, upload date, and uploader. - Users can select and view any previous version. - A “current version” label highlights the latest version. - Restoring a previous version updates it as the current version.
Access Control and Permissions
- Only users with Editor role see upload and delete actions. - Viewers can preview and comment but cannot upload, delete, or restore versions. - Attempting unauthorized actions displays a clear error message. - Role changes propagate immediately without requiring page refresh.

Shared Media Vault

Offers a cloud-based repository for co-branded assets like logos, audio clips, graphics, and social templates, enabling hosts and guests to access, customize, and distribute promotional materials effortlessly.

Requirements

Cloud Storage Integration
"As a podcast host, I want a centralized cloud vault for all my co-branded assets so that I can easily access and share promotional materials without juggling multiple platforms."
Description

Implement a secure, scalable cloud-based repository that allows hosts and guests to store, retrieve, and manage a variety of media asset types (logos, audio clips, graphics, social templates). Ensure seamless integration with existing ChirpFlow workflows, encrypted storage, redundancy, and fast retrieval times to support real-time collaboration and distribution.

Acceptance Criteria
Asset Upload and Organization
Given a host or guest uploads a media file (logo, audio clip, graphic, or social template) When the upload is initiated Then the file is stored in the cloud repository under the selected folder and asset type And the upload progress bar displays real-time progress And the upload completes within 30 seconds for files up to 50MB
Access Control and Permissions
Given a host shares an asset with a guest When the guest attempts to access the shared asset Then the guest can view and download the asset in read-only mode And the guest cannot modify or delete the asset And unauthorized users receive a ‘Permission Denied’ message
Asset Retrieval Performance
Given the vault contains 1,000+ assets When a user searches by asset name, type, or tag Then search results are returned within 2 seconds And results are paginated with 50 assets per page And each asset thumbnail and metadata load without delay
Data Encryption and Security
Given any asset is at rest in the repository Then the asset is encrypted using AES-256 encryption And any asset retrieved or uploaded uses TLS 1.2 or higher And audit logs record each upload, download, or access event with timestamp and user ID
Integration with Existing Workflows
Given a new asset is uploaded to the vault When the host creates or updates a podcast episode workflow Then the uploaded asset is immediately available in the episode’s media selection panel And any changes to the asset metadata are reflected in the workflow in real time
Asset Upload and Metadata Management
"As a guest, I want to upload my headshot, logo, and audio snippets into the vault with appropriate tags so that the host can quickly find and include them in prep packets and promotions."
Description

Provide an intuitive interface for uploading media assets in various formats, tagging them with metadata (e.g., type, episode number, brand, tags), and categorizing into folders or collections. Include validations for file size and type, progress indicators, and bulk upload capabilities to streamline asset organization.

Acceptance Criteria
Single File Upload
Given a user selects a supported media file under the maximum allowed size When the user clicks “Upload” Then the file is uploaded successfully to the vault and a confirmation message appears
Bulk File Upload
Given a user selects multiple supported media files within size limits When the user initiates the bulk upload Then all files are uploaded concurrently, and each shows a completion status
File Type and Size Validation
Given a user selects an unsupported file type or a file exceeding size limits When the user attempts upload Then the system rejects the file and displays an error message specifying the violation
Metadata Tagging and Persistence
Given a user uploads a file and enters metadata fields (type, episode number, brand, tags) When the user saves metadata Then the system stores the metadata and it is retrievable via search and filters
Upload Progress Indicator
Given a user uploads one or more large files When the upload starts Then a progress bar displays real-time percentage and updates until reaching 100%
Customizable Template Editor
"As a social media manager, I want to personalize co-branded graphics directly in the vault so that I can quickly generate on-brand promotional materials without switching tools."
Description

Offer a built-in editor that enables users to customize social media graphics and promotional templates with text, logos, and color schemes. Ensure real-time preview, version control, and one-click export in multiple formats (JPG, PNG, PDF) while preserving brand consistency using predefined style guides.

Acceptance Criteria
Template Customization Interface Load
Given a user navigates to the template editor, when the page loads, then all customization tools (text, logo, color pickers) are visible and interactive within 2 seconds.
Logo Upload and Placement
Given a user uploads a logo file in JPG or PNG format under 5MB, when the upload completes, then the logo appears at the intended position adjustable by drag-and-drop without distortion.
Real-Time Preview Update
Given a user modifies text, color, or layout in the editor, when a change is made, then the real-time preview updates within 500ms accurately reflecting the new customization.
Version Control and Rollback
Given a user saves a new template version, when they select a previous version from the history panel, then the editor restores the template to the exact state of that version including all customizations.
Multi-Format Export
Given a user clicks the export button and selects JPG, PNG, or PDF, when the export is initiated, then the system generates and downloads the file within 5 seconds at the correct resolution and brand-consistent styling.
Brand Style Guide Enforcement
Given a user applies custom colors or fonts outside the predefined style guide, when they attempt to save, then the editor displays a warning and prevents saving until they adjust to approved styles.
Role-Based Access Control
"As a podcast host, I want to control who can view or modify each asset in the vault so that I can protect sensitive materials and ensure only authorized collaborators have access."
Description

Implement fine-grained permissions that allow hosts to assign roles (owner, editor, viewer) for each vault or asset. Ensure guests can only view or edit assets as permitted, support invitation via email, and allow hosts to revoke access at any time to maintain security and privacy.

Acceptance Criteria
Vault Owner Invites Guest with Editor Role
Given the vault owner enters a valid guest email and selects the "Editor" role, When the owner sends the invitation, Then the guest receives an email with an invitation link and, upon accepting, is granted editor permissions for all assets in the vault.
Guest with Viewer Role Cannot Edit Assets
Given a guest is assigned the "Viewer" role, When the guest attempts to make changes to any asset, Then the system blocks the action and displays a "Permission Denied" error message.
Host Revokes Guest Access
Given the host navigates to the vault’s access management panel and revokes a guest’s access, When the guest next attempts to access the vault or its assets, Then the system denies access and removes the guest from the access list.
Role Change from Viewer to Editor
Given the host updates a guest’s role from "Viewer" to "Editor" in the vault settings, When the guest logs in again, Then the guest can modify assets but cannot invite new users or change roles.
Invitation Expiration After Seven Days
Given an invitation is sent to a guest, When seven days elapse without acceptance, Then the invitation automatically expires, and the guest is unable to use the invitation link.
One-Click Download and Sharing
"As a PR coordinator, I want to share a folder of promotional assets via a single link so that media outlets and sponsors can quickly access and use the materials without manual distribution."
Description

Enable users to download individual assets or entire collections with a single click, generate shareable links (with optional expiration dates), and embed promotional packs into emails or landing pages. Provide analytics on link clicks and downloads to track asset engagement.

Acceptance Criteria
Single Asset Download via One-Click
Given a user views an individual asset in the Shared Media Vault, When they click the 'Download' button for that asset, Then the asset file is downloaded in its original format with the correct filename within 5 seconds
Collection Download via One-Click
Given a user selects multiple assets or an entire collection, When they click the 'Download All' button, Then a single ZIP file containing all selected assets is generated and downloaded within 10 seconds
Shareable Link Creation
Given a user views an asset or collection, When they click 'Generate Link', Then a unique, shareable URL is created and displayed to the user
Link Expiration Configuration
Given a user generates a shareable link, When they specify an expiration date before link creation, Then the link expires automatically at 23:59 on the specified date and is no longer accessible
Asset Engagement Analytics
Given a user has shared a link, When they view the analytics dashboard, Then they see accurate counts of link clicks and downloads for each asset or collection in the last 30 days

Audience Echo

Aggregates and visualizes cross-podcast engagement metrics—such as listens, shares, and follower spikes—allowing hosts to measure the impact of co-promotion and optimize future collaborations.

Requirements

Data Ingestion Pipeline
"As a podcast host, I want to automatically gather engagement data from all my podcasts so that I can trust the metrics I see in the Audience Echo dashboard and avoid manual data collection."
Description

Build a robust pipeline to collect and centralize listens, shares, and follower changes across multiple podcast platforms in near real-time. This ensures consistent, up-to-date data feeding into analytics, enabling hosts to accurately measure cross-podcast engagement and inform collaboration decisions.

Acceptance Criteria
Real-Time Data Collection Across Platforms
Given multiple podcast platforms are connected, When new listen, share, or follower events occur, Then the system ingests and stores each event in the central database within 60 seconds of occurrence.
Data Normalization and Deduplication
Given ingestion of raw event data from different platforms, When data is processed, Then duplicate records are identified and removed, and all metrics are normalized to a common schema with correct timestamp and source attribution.
High-Volume Ingestion Stress Test
Given simulated concurrent ingestion of 10,000 events per minute, When the pipeline is under load, Then ingestion success rate remains above 99% with no data loss or backpressure errors.
Data Latency Monitoring and Alerting
Given the ingestion pipeline is running in production, When end-to-end data latency exceeds 90 seconds, Then an automated alert is sent to the DevOps team and logged in the monitoring dashboard.
Secure API Authentication for Ingestion
Given each podcast platform uses OAuth2 credentials, When the pipeline requests data, Then authentication tokens are validated, refreshed securely, and all API calls use HTTPS with no exposed credentials.
Engagement Metrics Aggregation
"As a podcast host, I want the system to consolidate and normalize different engagement metrics so that I can easily compare the performance of each cross-promotion effort."
Description

Develop a service that processes raw engagement data (listens, shares, follower spikes) and normalizes it into standardized metrics. This transforms heterogeneous platform data into comparable figures, making cross-podcast trends and collaboration impacts readily understandable.

Acceptance Criteria
Multi-Platform Data Ingestion
Given raw payloads from Spotify, Apple Podcasts, and YouTube, when the service receives them, then it must parse, validate, and enqueue each record within 2 seconds without errors.
Handling of Missing Engagement Fields
Given raw engagement entries with missing shares or follower spikes, when data enters the normalization pipeline, then any missing fields are defaulted to zero and a warning message is logged.
Normalization of Engagement Metrics
Given raw metrics for listens, shares, and follower spikes, when normalization is applied, then each metric is converted to a 0-100 scale based on the highest value within the same time window and results must match expected values within ±1%.
Cross-Podcast Engagement Comparison
Given two episodes from different podcasts, when a host requests a comparison report, then the service returns a side-by-side view of normalized listens, shares, and follower spikes for both episodes.
High-Volume Data Processing Performance
Given a batch of 10,000 raw engagement entries, when processed, then the normalization service completes the operation within 5 seconds without failures.
Cross-Podcast Analytics Dashboard
"As an independent podcast host, I want an intuitive dashboard to view cross-podcast engagement trends so that I can quickly assess which collaborations are driving the most impact."
Description

Design an interactive dashboard that visualizes aggregated engagement metrics across podcasts, allowing hosts to drill down by date range, episode, and promotional channel. The dashboard offers charts and tables for quick insights and detailed exploration.

Acceptance Criteria
Filtering Engagement Metrics by Date Range
Given the host selects a valid start and end date on the dashboard When the host applies the date filter Then only engagement metrics (listens, shares, follower spikes) within that range are displayed in all charts and tables.
Drill-Down to Episode Engagement Details
Given the host clicks on a data point representing an episode in any chart When the click event is registered Then the dashboard displays a detailed view showing that episode’s metrics, including breakdown by date and promotional channel.
Filtering by Promotional Channel
Given the host selects one or more promotional channels from the channel filter menu When the channel filter is applied Then the dashboard updates to show engagement metrics only for the selected promotional channels.
Visualization of Aggregated Engagement Metrics
Given the host navigates to the Cross-Podcast Analytics Dashboard When the dashboard loads Then it displays aggregated charts and tables for listens, shares, and follower spikes across all podcasts, and renders all visual elements within 2 seconds.
Exporting Analytics Data
Given the host has applied desired filters on the dashboard When the host clicks the Export button Then a CSV file containing the currently displayed engagement metrics and filter settings is downloaded successfully.
Promotion Impact Visualization
"As a content creator, I want to see visual representations of promotion timelines and listener spikes so that I can understand and improve my co-promotion strategies."
Description

Implement visualization tools such as comparative line graphs and heat maps to display the effect of co-promotion on listener growth and share rates. Hosts can visually correlate promotional activities with spikes, helping them optimize timing and partner selection.

Acceptance Criteria
Viewing Engagement Trends Over Time After Co-Promotion
Given a host has completed a co-promotion campaign When they navigate to the Audience Echo dashboard and select a specific date range Then a line graph displays daily listener counts for the selected podcasts over that range And the graph highlights spikes corresponding to known promotion dates And the displayed listener counts match the underlying data from analytics
Comparing Listener Growth Between Episodes with Different Partners
Given the host selects two episodes featuring different promotion partners When they choose 'Compare Episodes' in the visualization tool Then a comparative line graph is rendered with a distinct color for each episode And hovering over any point shows the exact listener count, date, and partner name And the graph legend clearly identifies each episode by partner
Analyzing Share Rate Heat Map for Promotional Activities
Given the host wants to review share rates over time When they open the heat map visualization and select a month Then each day is represented by a cell colored according to predefined share rate thresholds And a legend explains the color scale from low to high share rates And clicking on a specific cell displays the exact share count and date
Filtering Visualization by Date Range and Podcast Episode
Given the host has multiple episodes and time periods to analyze When they apply filters for a custom date range and one or more episode tags Then the visualization updates to include only data points within the selected filters And all graphs and maps refresh to reflect those filters And no data outside the filters is displayed
Exporting Visualization Reports for Stakeholder Presentations
Given the host needs to share promotional impact data externally When they click the 'Export' button on any visualization Then downloadable PNG and CSV files are generated automatically And the exported files include chart titles, axis labels, legends, and filter details And the CSV contains raw data points matching the visualized information
Collaboration Recommendations Engine
"As a busy podcast host, I want tailored collaboration suggestions based on metrics so that I can plan partnerships that yield the highest engagement."
Description

Create an algorithm that analyzes historical engagement patterns to suggest optimal future collaboration partners and timing. By leveraging past data, the system provides actionable recommendations to maximize reach and growth.

Acceptance Criteria
Historical Engagement-Based Partner Identification
Given the host has three months of historical engagement data for previous collaborations, when the host requests collaboration recommendations, then the engine must suggest partners whose average listener share rate ranks in the top 10% of past collaborators.
Optimal Collaboration Timing Selection
Given the host’s listener activity data showing daily and weekly peaks, when generating timing recommendations, then the engine must identify time windows over the next 30 days that coincide with the top 20% of audience activity periods.
Untapped Audience Segment Partner Suggestion
Given the host’s past collaborations exclude podcasts in high-growth topics (≥15% monthly listener growth), when requesting new partner suggestions, then the engine includes at least one podcast from an untapped high-growth segment.
Adjustment After Underperforming Campaign
Given a recent co-promotion yielded engagement lift below expected thresholds by more than 5%, when recalibrating future recommendations, then the engine must de-weight that partner’s historical engagement metrics by at least 50%.
Recommendation Accuracy Validation
Given the last five recommendations and their actual engagement outcomes, when evaluating recommendation accuracy, then at least 80% of those recommendations must have resulted in a minimum 10% engagement lift compared to baseline episodes.

AutoPitch Generator

Creates tailored co-branded pitch emails and social copy using guest and show data, reducing setup time and ensuring consistent, persuasive messaging for seamless outreach and guest onboarding.

Requirements

Guest Data Extraction
"As a podcast host, I want the AutoPitch generator to pull my guest and show information automatically so that I can generate personalized pitches without manual data entry."
Description

Automatically extract relevant guest details (name, biography, social profiles, past appearances) and show metadata (podcast title, theme, style) from connected data sources. Populate predefined placeholders in pitch and social media templates to ensure data accuracy and reduce manual input, enabling seamless template generation.

Acceptance Criteria
Guest Profile Extraction
Given a connected guest data source, when the extraction process runs, then the system automatically populates the guest's name, biography, social profile URLs, and past appearance list into the corresponding template placeholders with at least 95% accuracy.
Show Metadata Retrieval
Given a linked podcast show account, when metadata extraction is executed, then the system retrieves and populates the podcast title, theme, and style into the designated template fields, matching source data exactly.
Data Source Failover Handling
Given the primary data source is unavailable, when extraction is attempted, then the system seamlessly falls back to the secondary data source and completes data extraction without user intervention or data loss.
Placeholder Population Accuracy
Given a preformatted pitch or social media template, when data is applied, then all placeholders are replaced with the correct guest and show data, with zero orphan placeholders and data consistency across fields.
Performance under Bulk Requests
Given a bulk request of 50 guest data extractions, when the process runs concurrently, then all extractions complete successfully within 30 seconds, maintaining data accuracy and system stability.
Co-branded Template Management
"As a host, I want to customize and store co-branded email and social media templates so that each outreach reflects my brand identity consistently."
Description

Provide a template management interface where hosts can create, edit, and save multiple co-branded email and social media templates. Support brand asset integration, including logos, color schemes, fonts, and signature blocks, to ensure consistent branding across all outreach materials.

Acceptance Criteria
Creating a New Co-branded Template
Given the host is on the Template Management page, when they create a new template by uploading a logo, selecting a color scheme and font, and adding a signature block, then the template is saved and appears in the template list with all selected branding assets intact.
Editing an Existing Co-branded Template
Given the host selects an existing template from the list, when they update the logo, color scheme, font, or signature block and save changes, then the template preview and list view reflect the updated branding assets.
Previewing a Template Before Saving
Given the host is configuring a template, when they click the Preview button, then the system displays an accurate rendition of how the email and social copy will appear with the chosen logos, colors, fonts, and signature.
Organizing and Searching Templates
Given the host has multiple templates saved, when they search or filter by template name, tags, or last modified date, then the system displays only the templates matching the search criteria in descending order of modification date.
Handling Invalid Brand Assets
Given the host uploads an unsupported file type or invalid color code while creating or editing a template, when they attempt to save, then the system rejects the invalid input and displays a clear error message specifying acceptable file formats and color code standards.
Personalized Email Content Generation
"As a host, I want to produce tailored email pitches that address each guest’s background and preferences so that my outreach feels personal and persuasive."
Description

Merge guest and show data into selected email templates, using AI-driven phrasing suggestions to craft personalized introductions, value propositions, and call-to-action statements. Optimize tone and structure to maximize engagement and response rates.

Acceptance Criteria
Generating Personalized Email for New Guest Outreach
Given the host selects a guest and show template When the host initiates email generation Then the system merges guest name, show title, and episode details into the email body without errors And the email preview displays correctly formatted merged data
Providing AI-driven Phrasing Suggestions
Given an email draft with placeholders When the host requests phrasing suggestions Then the system offers at least three alternative phrasings for introduction, value proposition, and call-to-action And each suggestion aligns with show context and guest profile
Optimizing Tone Based on User Preference
Given the host selects a 'Friendly' tone option When generating email content Then all text reflects a friendly tone consistent with predefined style guidelines And no formal or neutral phrasing is present
Applying Different Email Templates
Given the host chooses a 'Formal' or 'Casual' template When generating the email Then the structure, formatting, and placeholder positions correspond exactly to the selected template And the merged content adapts to the template’s design elements
Handling Missing Guest or Show Data
Given required guest or show fields are missing When attempting to generate the email Then the system displays a clear error message specifying which fields are missing And prevents email generation until all required data is provided
Social Copy Generation
"As a host, I want ready-to-post social media blurbs promoting my guest episode so that I can quickly share content across channels without additional writing."
Description

Generate ready-to-publish social media copy snippets formatted for platforms like Twitter, LinkedIn, and Instagram. Leverage episode highlights, guest credentials, and relevant hashtags to create engaging promotional posts that drive audience interest.

Acceptance Criteria
Scenario: Generating Twitter Post During Episode Finalization
Given the episode title, summary, and guest Twitter handle are saved When the host selects “Generate Twitter Copy” for the finalized episode Then the system produces a tweet under 280 characters that includes the episode title, guest handle, two relevant hashtags, and a trackable link.
Scenario: Creating LinkedIn Post with Guest Credentials
Given the guest’s professional credentials and episode highlights are entered When the host clicks “Generate LinkedIn Copy” Then the system outputs a LinkedIn post of 100–300 words featuring the guest’s credentials, key talking points, and at least three industry-relevant hashtags.
Scenario: Producing Instagram Teaser with Hashtags
Given the episode artwork and three bullet-point highlights are available When the host selects “Generate Instagram Copy” Then the system creates a caption under 2,200 characters that includes a call-to-action, three relevant hashtags, and a prompt to listen via a link in bio.
Scenario: Regenerating Copy After Guest Details Update
Given guest details are updated after initial copy generation When the host requests a copy regeneration for any platform Then the system refreshes and displays updated social copy reflecting the new guest information and hashtags.
Scenario: Exporting Social Copy to Marketing Platform
Given generated social copy for multiple platforms is ready When the host selects “Export to Marketing Platform” Then the system formats and delivers the copy via API to the selected marketing tool without manual edits.
Preview and Approval Workflow
"As a podcast producer, I want to review and adjust the generated pitches before sending so that I ensure accuracy and maintain quality."
Description

Implement a preview interface for reviewing generated emails and social media copy. Allow in-line editing, approval or rejection of drafts, and maintain version control with change history tracking to ensure content quality and compliance.

Acceptance Criteria
Draft Email Preview Interface
Given a generated email draft is available, When the user navigates to the preview interface, Then the email content is displayed in its final formatted state with co-branding elements visible.
In-line Editing of Generated Copy
Given the user is in the preview mode, When the user edits text directly within the draft, Then changes are saved in real-time without losing formatting or co-branding styles.
Approval Workflow for Email Drafts
Given a draft is finalized, When the user clicks 'Approve', Then the draft status updates to 'Approved' and is locked from further edits until a new version is created.
Version Control and Change History
Given multiple edits have been made to a draft, When the user views the version history, Then all previous versions are listed with timestamps, editor names, and diff highlights for each change.
Rejection and Feedback Loop
Given a draft is deemed unsatisfactory, When the user clicks 'Reject' and enters feedback, Then the draft status updates to 'Rejected', feedback is recorded, and the original author is notified with the comments.

AdFit Matchmaker

Uses AI to analyze guest demographics, episode topics, and audience segments to recommend the best-fitting sponsors for each episode, ensuring ads resonate with listeners and maximize sponsorship value.

Requirements

Sponsor Data Ingestion
"As a podcast host, I want to import and sync sponsor profiles automatically so that I always work with the latest sponsor information when selecting ad partners."
Description

Implement a robust ingestion pipeline to import and normalize sponsor data, including company profiles, demographics, industry categories, budgets, and contact details via API integrations and CSV uploads. Ensure data consistency, validation, and real-time synchronization with the ChirpFlow database to maintain up-to-date sponsor profiles for matching.

Acceptance Criteria
API Sponsor Data Retrieval
Given valid sponsor API credentials, when the ingestion service calls the sponsor API endpoint, then it retrieves all sponsor records and logs the ingestion with a 200 OK response.
CSV Sponsor Data Upload
Given a correctly formatted CSV file uploaded via the UI, when the user submits the file, then the system parses, ingests, and stores all sponsor records without errors and displays a success message.
Sponsor Data Normalization and Validation
Given raw sponsor data from API or CSV sources, when the ingestion pipeline processes the data, then it enforces required fields, normalizes industry categories to predefined taxonomies, formats budgets as numeric values, and rejects or flags invalid records with logged errors.
Real-time Database Synchronization
Given updated sponsor data in source systems, when changes occur, then the ingestion pipeline synchronizes updates to the ChirpFlow database within 5 seconds, ensuring all sponsor profiles reflect the latest information.
Duplicate Sponsor Detection
Given incoming sponsor records, when the pipeline processes them, then it identifies duplicates based on company name and contact email, merges new data into existing profiles, and flags potential duplicates for manual review without creating redundant records.
Audience Segment Profiling
"As a podcast host, I want clear audience segment profiles so that I can match sponsors whose products resonate with my listeners."
Description

Develop audience segment profiling by analyzing listener data, engagement metrics, and demographic information from past episodes. Integrate with existing ChirpFlow analytics to categorize listeners into meaningful segments, enabling targeted sponsor matching based on audience interests and behaviors.

Acceptance Criteria
Nightly Data Aggregation
System processes 100% of new listener records within 1 hour of scheduled run and integrates them into existing audience segments.
Automated Segment Generation
System categorizes listeners into at least five segments based on demographics, engagement, and listening history, with each segment containing at least 500 listeners.
Sponsor Recommendation Accuracy
Recommendations match sponsors with audience segments at a relevance score of at least 0.8 for 90% of test cases.
Segment Editing and Validation
When hosts adjust segment definitions, the system reprocesses data within 5 minutes and updates segment membership in real-time.
Reporting Dashboard Integration
Segment profiling data is accurately displayed on the ChirpFlow analytics dashboard, with segment counts and key metrics matching backend data within a 2% variance.
AI Matchmaking Engine
"As a podcast host, I want AI-generated sponsor recommendations so that I can quickly identify the most relevant and valuable sponsors for my episodes."
Description

Create an AI-powered matchmaking engine that processes sponsor profiles, guest demographics, episode topics, and audience segments to calculate compatibility scores. Leverage machine learning algorithms to rank and recommend the best-fit sponsors for each episode, continuously refining recommendations based on host feedback and performance data.

Acceptance Criteria
Matching sponsors for a new podcast episode
Given a new episode with guest demographics and episode topics, when the AI Matchmaking Engine is invoked, then it returns a ranked list of at least five sponsors with compatibility scores between 0.0 and 1.0, sorted in descending order.
Refining recommendations based on host feedback
Given host feedback indicating a sponsored ad underperformed, when the feedback is submitted, then the engine adjusts the compatibility model and applies a minimum 10% change in future score rankings for that sponsor category.
Initial sponsor compatibility scoring
Given a set of sponsor profiles and audience segment data, when the matchmaking process runs for the first time, then each sponsor receives a compatibility score within 24 hours, and no score is null or out of range.
Adaptive learning after performance data ingestion
Given historical performance metrics from previous episodes, when the engine ingests new performance data, then it updates model parameters and demonstrates at least a 5% increase in average click-through rate predictions.
Handling episodes with no matching sponsors
Given an episode whose topics and demographics yield no high-compatibility matches, when the matchmaking engine completes processing, then it returns an empty recommendation list and a notification stating “No suitable sponsors found.”
Recommendation Review Interface
"As a podcast host, I want an interactive interface to review and give feedback on sponsor matches so that I can refine future recommendations according to my preferences."
Description

Design and build an intuitive UI within ChirpFlow for hosts to review recommended sponsors, view detailed match score breakdowns, accept or reject suggestions, and provide feedback. Ensure the interface supports bulk actions, filtering, and sorting to streamline decision-making.

Acceptance Criteria
Viewing Sponsor Recommendations
Given the host is on the AdFit Matchmaker page, When the host opens the Recommendation Review Interface, Then the interface displays a list of recommended sponsors with sponsor names, logos, match scores, and key match attributes for each recommendation.
Reviewing Match Score Breakdown
Given a recommended sponsor is selected, When the host clicks on the match score breakdown option, Then a detailed view shows individual score components including audience alignment, topic relevance, and demographic match with numeric values and visual indicators.
Accepting or Rejecting Recommendations
Given a list of recommendations, When the host clicks 'Accept' or 'Reject' for a sponsor, Then the system updates the recommendation status, moves accepted sponsors to a confirmed list, and logs rejected sponsors in feedback records.
Providing Feedback on Recommendations
Given a recommended sponsor, When the host chooses to provide feedback, Then the interface displays a feedback form with predefined reasons and an open text field, and upon submission stores feedback and updates the recommendation status to 'Reviewed'.
Bulk Actions on Multiple Recommendations
Given multiple recommendations are displayed, When the host selects several recommendations and chooses a bulk action (accept or reject), Then the system applies the chosen action to all selected items and provides a summary confirmation.
Filtering and Sorting Recommendations
Given the recommendations list, When the host applies filters (e.g., match score threshold, demographic segment) or sorting (e.g., highest to lowest score, alphabetical sponsor name), Then the list updates dynamically to reflect the selected filter and sort criteria.
Sponsorship Performance Analytics
"As a podcast host, I want to track how my sponsors perform in terms of listener engagement and revenue so that I can optimize future sponsorship choices."
Description

Implement detailed performance analytics reporting for placed sponsors, tracking metrics such as impressions, click-through rates, conversion estimates, and revenue impact. Integrate reports into ChirpFlow dashboards and enable exporting to CSV or PDF for stakeholder review and sponsor negotiation.

Acceptance Criteria
Accessing Sponsorship Analytics Dashboard
Given a host with placed sponsors accesses the Sponsorship Performance Analytics section on the ChirpFlow dashboard, When the dashboard loads, Then impressions, click-through rates, conversion estimates, and revenue impact metrics are displayed in separate, clearly labeled widgets.
Exporting Performance Reports to CSV
Given a host viewing sponsorship performance analytics, When the host clicks the "Export to CSV" button, Then a CSV file containing all displayed metrics, date stamps, and episode identifiers is downloaded to the user's device.
Exporting Performance Reports to PDF
Given a host viewing sponsorship performance analytics, When the host selects the "Export to PDF" option, Then a PDF report is generated that includes charts, tables, and summary statistics matching the on-screen data.
Filtering Analytics by Date Range
Given a host on the analytics dashboard, When the host selects a custom date range filter, Then all metrics update to reflect data only within the selected date range.
Estimating Revenue Impact
Given displayed impressions and click-through rates, When the system applies the configured sponsorship rate card, Then the revenue impact estimate is calculated and presented alongside raw metrics.

AutoSlot Creator

Automatically inserts customized ad slots into episode prep packets based on sponsor priorities and episode length, saving hosts time and guaranteeing prime placement for maximum listener engagement.

Requirements

Dynamic Slot Placement
"As a podcast host, I want the system to automatically choose the best positions in my episode for ad slots so that ads integrate smoothly without disrupting listener experience."
Description

Automatically analyzes episode duration, content structure, and sponsor priorities to determine optimal ad insertion points. Ensures that ad slots are placed at natural breaks in the conversation to maintain listener engagement while maximizing sponsor visibility. Integrates seamlessly into the prep packet generation workflow and adapts to varying episode lengths and formats.

Acceptance Criteria
Standard Interview Episode Analysis
Given an uploaded 30–45 minute interview episode, when the Dynamic Slot Placement runs analysis, then it inserts a pre-roll within the first 2 minutes and a mid-roll at the first natural break post-second segment.
Short-Form Episode Handling
Given an uploaded episode under 20 minutes, when the algorithm scans for ad insertion points, then it adds exactly one mid-roll at the longest detected pause exceeding two seconds and ensures no interruption of active speech.
Long-Form Episode Segmentation
Given an uploaded episode over 60 minutes, when the system evaluates episode duration and structure, then it places two mid-rolls at approximately 25% and 75% of the total runtime aligned with segment transitions.
Multi-Sponsor Prioritization
Given multiple sponsors with assigned priority levels, when ad slots are being generated, then the highest-priority sponsor’s slot appears within the first 5 minutes and lower-priority sponsors are placed at subsequent natural breaks.
Dynamic Break Detection in Conversational Flow
Given any episode format, when the content-scanning engine detects consecutive silence or transition markers exceeding two seconds, then an ad slot is placed at that point, ensuring it aligns with conversational pauses.
Sponsor Priority Mapping
"As a sponsorship manager, I want higher-tier sponsors to be placed in prime ad slots so that they receive maximum exposure and fulfill our contractual agreements."
Description

Maps sponsor tier levels and contract terms to slot prominence, guaranteeing that higher-tier sponsors receive premium placement in the prep packets. Automatically adjusts slot order based on sponsor priority settings, ensuring contractual obligations are met and sponsors receive the attention level they expect.

Acceptance Criteria
High-Tier Sponsor Prominence in Short Episodes
Given an episode length under 15 minutes and a Gold-tier sponsor, when generating the prep packet, then the Gold-tier sponsor ad slot appears first in the ad slots section; and the ad slot duration matches the sponsor's contracted time.
Multi-Sponsor Slot Reordering
Given multiple sponsors with different tier levels, when the admin updates sponsor priority settings, then the system reorders ad slots in the prep packet in real time according to updated tiers; and the new order persists across future packet generations.
Minimum Visibility for Bronze-Tier Sponsors
Given a Bronze-tier sponsor with a contractual guarantee of one ad slot, when generating a prep packet, then the Bronze-tier sponsor receives exactly one ad slot placed after all Platinum- and Gold-tier slots.
Contractual Slot Frequency Enforcement
Given a sponsor contract specifying two slots per episode, when generating the prep packet, then the system includes exactly two ad slots for that sponsor; and no additional slots are assigned beyond the contractual limit.
Emergency Sponsor Swap Handling
Given a last-minute cancellation of a Platinum-tier sponsor and replacement with a Silver-tier sponsor, when updating the episode prep packet, then the Silver-tier slot occupies the former Platinum slot position; and all lower-tier slots shift down one rank.
Custom Slot Formatting
"As a podcast host, I want to customize how ad slots appear in my prep packets so that they align with my show's branding and sponsor guidelines."
Description

Provides configurable templates for ad slot presentation within prep packets, allowing hosts to apply custom branding, sponsor messaging, and call-to-action elements. Supports multiple formatting styles and dynamically inserts sponsor logos and taglines to create professional, cohesive prep documents.

Acceptance Criteria
Template Selection Formatting
Given the host has selected template 'A' in the formatting settings; When generating the prep packet; Then the ad slots follow template 'A' including correct fonts, colors, spacing, and placeholder positions.
Sponsor Logo Insertion
Given a sponsor has a logo and tagline uploaded; When the prep packet is generated; Then the sponsor's logo appears at the specified dimensions and position, and the tagline text displays using the template’s font and style.
Custom CTA Styling
Given the host inputs custom call-to-action text and style options; When the host previews the ad slot; Then the CTA displays with the specified font size, color, weight, and hyperlink formatting.
Multiple Style Rendering
Given the host switches among 'inline', 'sidebar', and 'banner' styles; When applying each style; Then the ad slots render correctly in the preview and exported packet matching the selected style’s layout.
Real-time Format Preview
Given the host modifies formatting options in the editor; When viewing the real-time preview pane; Then all changes (fonts, colors, images) update immediately and match the final exported document.
Slot Preview and Approval
"As a podcast host, I want to preview and approve ad slot placements before sending prep packets so that I maintain control over ad positioning and timing."
Description

Offers an interactive preview interface where hosts can review auto-generated ad slots, adjust timing or order, and approve placements before finalizing the prep packet. Ensures hosts maintain editorial control and can make last-minute changes without manual packet edits.

Acceptance Criteria
Host Reviews Auto-Generated Ad Slots
Given an episode prep packet with auto-generated ad slots, when the host opens the Slot Preview interface, then all ad slots display with correct start times, durations, and sponsor details.
Host Adjusts Ad Slot Timing
Given the host is in the Slot Preview interface, when the host modifies an ad slot’s start time or duration, then the preview updates immediately and prevents overlaps or exceeding the episode length.
Host Reorders Ad Slots
Given the host is in the Slot Preview interface, when the host moves an ad slot to a new position, then the system persists the new order in the preview and underlying prep packet.
Host Approves Final Ad Slot Configuration
Given the host has reviewed and adjusted all ad slots, when the host clicks the Approve button, then the system locks the slots, marks the prep packet as finalized, and sends a confirmation notification.
Sponsor Priority Validation in Slot Preview
Given multiple sponsors with assigned priority levels, when generating or previewing ad slots, then ad slots appear ordered by priority and display priority labels.
Performance Analytics Integration
"As a podcast host, I want to see how each ad slot performed with listeners so that I can optimize placement for future episodes and provide sponsors with detailed performance reports."
Description

Collects and aggregates listener engagement metrics for each ad slot post-publish and integrates the data into sponsor reports. Provides hosts and sponsors with insights on ad performance, click-through rates, and listener drop-off to inform future placement strategies and demonstrate ROI.

Acceptance Criteria
Post-Publish Engagement Data Collection
Given an episode has been published with ad slots, when listener engagement events occur within 7 days post-publish, then the system captures and stores metrics including impressions, clicks, and listener drop-off timestamps for each ad slot.
Sponsor Report Data Integration
Given captured ad engagement metrics, when a sponsor requests their monthly report, then the system aggregates metrics per sponsor and includes them in a downloadable report within 5 seconds.
Click-Through Rate Calculation
Given stored impression and click events for an ad slot, when the report is generated, then the system calculates CTR as (total clicks / total impressions) × 100 and displays it with two decimal precision.
Listener Drop-Off Analysis
Given the timeline of listener sessions, when drop-off events occur within an ad slot, then the system calculates the percentage of listeners who dropped off during the slot and flags any slot with > 25% drop-off.
Dashboard Update for Hosts
Given new ad performance data, when a host accesses the episode dashboard, then the ad section displays updated metrics (impressions, clicks, CTR, drop-off rate) in both tabular and graphical format within 2 seconds.

Dynamic Rate Card

Generates real-time sponsorship pricing recommendations by combining audience metrics, guest influence scores, and market trends, empowering hosts to set competitive rates and increase revenue.

Requirements

Real-Time Data Aggregation
"As a podcast host, I want real-time aggregation of audience, guest, and market data so that I can make sponsorship pricing decisions based on the most current insights."
Description

Automatically collect and unify audience metrics, guest influence scores, and sponsorship market prices into a single data repository in real time, ensuring that pricing recommendations always reflect the latest information.

Acceptance Criteria
Audience Metrics Ingestion Scenario
Given the system receives a new audience metric event from the metrics API When the event arrives Then it is stored in the real-time data repository within 2 seconds
Guest Influence Score Update Scenario
Given a guest influence score update is published by the influence scoring service When the update is streamed Then the latest score is reflected in the unified repository without duplication
Sponsorship Market Price Integration Scenario
Given the market price feed publishes new sponsorship rates When the feed is consumed in real time Then the data repository is updated with current market prices and timestamped accordingly
Unified Data Repository Synchronization Scenario
Given simultaneous inputs from audience, influence, and market services When all streams are processed Then the repository presents a single consolidated record for each sponsorship recommendation within 3 seconds
Real-Time Data Consistency Under Load Scenario
Given the system processes 10,000 data events per minute When the load threshold is reached Then no events are lost or delayed beyond the SLA of 5 seconds
Audience Metric Integration
"As a podcast host, I want my listener demographics and engagement metrics integrated into the rate card so that sponsorship rates align with my audience’s value."
Description

Integrate with analytics platforms (e.g., Chartable, Podtrac) to pull listener counts, engagement rates, and demographic breakdowns, enabling the rate card to factor in detailed audience behavior and value.

Acceptance Criteria
Listener Count Retrieval from Chartable
Given the host initiates a rate card update, When the system sends a request to Chartable API with valid credentials, Then the system receives a non-null integer representing daily unique listeners within 10 seconds.
Engagement Rate Fetching from Podtrac
Given the host views sponsorship pricing, When the system queries Podtrac for engagement metrics over the past 30 days, Then the system retrieves percentage values for likes, shares, and average listen duration and displays them in the rate calculation.
Demographic Breakdown Aggregation
Given the analytics APIs return segmented audience data, When the system receives age and regional breakdowns, Then it stores each segment in the rate card database and calculates a weighted demographic value factor.
Fallback Handling on API Failure
Given an API timeout or 5xx error occurs during metric retrieval, When the system cannot fetch live data, Then it logs the error, notifies the host via UI, and applies the last known metrics for rate recommendations.
Secure Storage of Retrieved Metrics
Given audience metrics are fetched from external platforms, When storing data, Then all metrics are encrypted at rest, API tokens are secured in environment variables, and access logs record each retrieval event.
Market Trend Analysis Dashboard
"As a podcast host, I want to see pricing trends for similar shows so that I can adjust my sponsorship rates to remain competitive in the market."
Description

Provide an interactive dashboard that visualizes market pricing trends for similar podcasts, highlighting fluctuations over time and comparative benchmarks to guide hosts in setting competitive rates.

Acceptance Criteria
Interactive Trend Chart Access
Given the host navigates to the Market Trend Analysis Dashboard, when they select the 'Trend Chart' view, then an interactive line chart displaying monthly average sponsorship rates of at least 10 similar podcasts over the past 12 months loads within 2 seconds and allows hovering to display exact rate values.
Date Range Filtering
Given the host views the dashboard, when they apply a start and end date filter, then the chart and benchmarks update to reflect pricing trends and comparative data only within the selected date range, and display a 'No Data' message if no data exists.
Benchmark Comparison Display
Given the host selects a specific podcast benchmark, when they choose up to three podcasts to compare, then the dashboard displays side-by-side trend lines with distinct colors and a legend, updating in real-time.
Real-time Data Refresh
Given the dashboard is open, when new market data becomes available, then the dashboard automatically refreshes within 60 seconds and visually indicates updated data points with a brief highlight animation.
Insight Tooltip Guidance
Given the host hovers over any chart element or benchmark label, then a tooltip appears within 300ms explaining the data point, including timestamp, average rate, and comparison to overall market average, adhering to branding guidelines.
Customizable Pricing Model
"As a podcast host, I want to customize how sponsorship rates are calculated so that I can align recommendations with my preferred pricing strategy."
Description

Allow hosts to choose from tiered or custom pricing formulas (e.g., CPM, flat fee, performance-based) and adjust weightings for audience size, guest influence, and market conditions to tailor rate recommendations to their strategy.

Acceptance Criteria
Selecting CPM Pricing Formula
Given the host is on the Custom Pricing Model page, when they select the CPM formula, then the system shall calculate sponsorship rates as (CPM rate) × (audience size ÷ 1,000) using current audience metrics.
Configuring Tiered Pricing
Given the host chooses the Tiered Pricing option, when they define pricing tiers and associated audience thresholds, then the system shall display the correct rate for each tier and preview the total sponsorship price correctly.
Adjusting Audience Size Weighting
Given the host views weighting controls, when they adjust the audience size slider or input a custom percentage, then the system shall recalculate and display the updated rate recommendation in real time reflecting the new weighting.
Modifying Guest Influence Weighting
Given the host accesses weighting settings, when they change the guest influence score weighting, then the rate recommendation shall update dynamically to reflect the influence score impact on pricing.
Saving Custom Pricing Formula
Given the host has customized pricing formula parameters, when they click ‘Save Custom Model’, then the system shall persist the custom formula, make it selectable in future sessions, and apply it to generate rate recommendations.
Rate Recommendation API
"As a sponsor platform developer, I want an API to fetch up-to-date sponsorship rates so that I can integrate my platform with ChirpFlow’s dynamic rate card."
Description

Expose a secure API endpoint that returns real-time sponsorship price suggestions for external integrations, enabling guests, sponsors, or third-party tools to programmatically retrieve rate recommendations.

Acceptance Criteria
Valid Rate Recommendation Request
Given a valid authenticated request with correct parameters When the client invokes GET /api/rate-recommendation with valid API key and parameters Then the API returns HTTP 200 And the response body contains a JSON with "recommended_rate" field greater than 0 And the response includes "currency", "confidence_score", and "timestamp" fields
Authentication Failure
Given an invalid or missing API key When invoking GET /api/rate-recommendation Then the API returns HTTP 401 And the response body contains error code "INVALID_API_KEY" and descriptive message
Invalid Input Handling
Given a request with missing required parameters or invalid parameter types When invoking GET /api/rate-recommendation Then the API returns HTTP 400 And the response body contains error code "INVALID_REQUEST" with details of missing or invalid parameters
High Load Performance
Given 1000 concurrent valid requests When invoking GET /api/rate-recommendation Then 99% of responses are returned within 500ms And no requests return HTTP 5xx errors
Data Freshness Validation
Given a rate recommendation request at any time When the API returns a response Then the "timestamp" field value is within the last 5 minutes

Sponsor Pitch Builder

Creates tailored pitch decks and email templates for each sponsor opportunity using guest and show data, streamlining outreach and boosting conversion rates through personalized proposals.

Requirements

Guest and Show Data Integration
"As a podcast host, I want the sponsor pitch builder to pull guest and show data automatically so that I can create personalized pitches without manually compiling information."
Description

Automatically aggregates and normalizes relevant guest profiles and episode metadata from ChirpFlow’s database, ensuring accurate and up-to-date information is available for pitch creation. Provides a unified data layer that can be queried to personalize pitch decks and email templates, reducing manual data gathering and errors.

Acceptance Criteria
Aggregating Guest Profiles
Given a host initiates pitch creation When the system retrieves guest profiles Then it aggregates all specified guest attributes (name, biography, social media links) into the unified data layer within 5 seconds
Normalizing Episode Metadata
Given multiple episodes exist with varying metadata formats When the system processes episode data Then all metadata fields (title, date, duration, topics) are converted to a standardized format matching the data model
Querying Unified Data Layer
Given the user requests personalized pitch content When the system queries the unified data layer Then it returns the correct guest and episode data matching the query parameters with 100% accuracy
Handling Missing or Incomplete Data
Given a guest profile or episode record has missing fields When the system aggregates data Then it flags incomplete records and logs an alert without causing system errors
Real-Time Data Updates
Given a guest profile or episode metadata is updated in the database When the change occurs Then the unified data layer reflects the update within 2 seconds
Template Customization Engine
"As a podcast host, I want to customize the layout and style of my sponsor pitch so that it aligns with my show’s branding and the sponsor’s requirements."
Description

Build an interface and backend service that enables users to customize pitch deck and email template layouts, styles, and content blocks. Supports drag-and-drop functionality, preset themes, and brand asset uploads, ensuring each sponsor proposal aligns with the host's branding and sponsor expectations.

Acceptance Criteria
Brand Asset Upload and Application
Given a user has brand assets (logo, colors, fonts) uploaded, when the user selects assets from the asset library, then the selected assets are applied correctly to the pitch deck and email template preview.
Content Block Drag-and-Drop Layout
Given a user is editing a template, when the user drags a content block into the layout editor, then the block snaps into position and the template updates to reflect the new block order immediately.
Preset Theme Selection and Preview
Given a range of preset themes in the template engine, when the user selects a theme, then the preview pane updates to show the deck and email template in the selected theme within two seconds.
Save and Reuse Customized Template
Given a user has customized a template, when the user clicks 'Save As Template,' then the system stores the template under the user's library and lists it for future use.
Export Email Template with Tokens
Given an email template with personalization tokens, when the user exports the template, then the exported file includes all tokens intact and is compatible with common email platforms (e.g., Mailchimp, SendGrid).
Personalization Token Insertion
"As a podcast host, I want to automatically insert sponsor-specific details into my pitch templates so that each proposal feels personalized and relevant."
Description

Allow dynamic insertion of personalization tokens (e.g., sponsor name, targeted metrics, previous guest quotes) into templates. Ensures each pitch is tailored to the sponsor by replacing tokens with actual data during generation, improving relevance and conversion rates.

Acceptance Criteria
Standard Sponsor Pitch Generation
Given a sponsor profile with complete data when the user generates a pitch for the sponsor then all personalization tokens (sponsor name, targeted metrics, previous guest quotes) are replaced with corresponding sponsor and show data and no tokens remain unfilled
Pitch Generation with Missing Sponsor Data
Given a sponsor profile missing optional fields when the user generates a pitch then the system substitutes default values or omits optional sections gracefully and completes generation without errors
Bulk Pitch Generation Process
Given a list of multiple sponsors when the user initiates bulk pitch generation then the system produces individual pitch decks and email templates for each sponsor with correctly replaced tokens and no cross-contamination of data
Preview of Generated Pitch
Given a prepared template when the user clicks the preview button then the system displays the pitch with all tokens replaced accurately and the preview content matches the final generated output
Dynamic Token Validation
Given a template containing undefined or misspelled tokens when the user generates or previews a pitch then the system flags the invalid tokens, highlights them in the interface, and prevents submission until corrected
Automated Email Campaign Workflow
"As a podcast host, I want to schedule and send pitch emails directly from the platform so that I can streamline my outreach process and manage follow-ups automatically."
Description

Enable users to schedule and send pitch emails in bulk or individually directly from the ChirpFlow platform. The workflow includes email list management, scheduling, A/B testing support, and automated follow-up sequences based on open and reply rates.

Acceptance Criteria
Bulk Email Scheduling
Given the user has selected multiple contacts and a pre-built email template, when they schedule the campaign for a future date and time, then all emails are queued and sent at the specified time without errors.
Individual Email Sending
Given the user composes or selects an email template and enters a single recipient, when they click “Send Now,” then the email is delivered immediately with correct sender details and no delivery failures.
A/B Testing Campaign Setup
Given the user defines two email variants and a target segment, when they schedule the A/B test campaign, then the system sends variant A to 50% and variant B to 50% of the segment, tracks open and reply rates for both, and displays the results in the dashboard after the test period.
Automated Follow-Up Sequence
Given the user configures a follow-up rule to trigger based on no reply within 3 days of the initial send, when the timing condition is met for opened but unreplied emails, then the system automatically sends the specified follow-up template to those contacts.
Email List Import and Segmentation
Given the user uploads a CSV file with valid contact data, when the import completes, then the system creates a new contact list without duplicates, applies correct tags based on import fields, and makes the list available for campaign scheduling.
Pitch Performance Analytics
"As a podcast host, I want to see analytics on my pitch outreach performance so that I can optimize my approach and improve sponsor conversion rates."
Description

Provide a dashboard that tracks key metrics such as open rates, click-through rates, response rates, and conversion outcomes for each sponsorship pitch. Empower hosts to adjust strategies based on real-time data and identify high-performing templates.

Acceptance Criteria
Dashboard displays pitch metrics on page load
Given the host navigates to the Pitch Performance Analytics dashboard When the dashboard loads Then the system displays open rates, click-through rates, response rates, and conversion outcomes for all pitches in the default date range
User filters metrics by custom date range
Given the host is on the Pitch Performance Analytics dashboard When they select a valid start and end date Then the dashboard updates to show metrics only for pitches sent within the selected date range
User compares performance between templates
Given the host selects two or more pitch templates for comparison When they initiate the comparison Then the dashboard displays a side-by-side view of open rates, click-through rates, response rates, and conversion outcomes for each selected template
Host receives real-time updates for new pitch interactions
Given a new email open, click, or response occurs for any sent pitch When the event is recorded Then the dashboard automatically refreshes or shows a notification within 60 seconds to reflect the updated metric
User exports pitch performance report
Given the host chooses to export the current view of pitch performance When they select the export option and specify a file format (CSV or PDF) Then the system generates and downloads a file containing all displayed metrics, date range, and template comparison details

Alignment Insights

Provides detailed reports on sponsor-guest-theme compatibility, highlighting shared values, audience overlaps, and content synergies to guide hosts in selecting partnerships that enhance listener trust and engagement.

Requirements

Value Alignment Scoring
"As a podcast host, I want a clear numeric score that indicates how well a sponsor's values align with my guest's messaging so that I can choose partnerships that resonate authentically with my audience."
Description

The system calculates a compatibility score between sponsors and guests based on shared core values, brand ethics, and messaging tone. It leverages natural language processing to analyze sponsor campaign materials and guest profile content, producing a clear, normalized score that helps hosts prioritize high-integrity partnerships. This feature integrates into the Alignment Insights dashboard, providing transparency around the scoring algorithm and allowing hosts to drill down into factors influencing the score.

Acceptance Criteria
Score Calculation for Sponsor-Guest Value Alignment
Given sponsor campaign materials and guest profile data are available, when the system runs the NLP analysis, then it generates a compatibility score between 0 and 100 with no errors.
Normalization of Compatibility Score
Given a raw compatibility output from the NLP algorithm, when the system normalizes scores, then the final compatibility score is scaled and formatted as an integer between 0 and 100.
Visibility of Score Factors Breakdown
Given a computed compatibility score, when the host requests details, then the system displays a breakdown of core values, brand ethics, and messaging tone matches with corresponding weights and explanations.
Integration into Alignment Insights Dashboard
Given a sponsor-guest pairing exists, when the host accesses the Alignment Insights dashboard, then the compatibility score appears adjacent to the pairing listing and updates in real time.
Drill-Down into Scoring Components
Given the host clicks the compatibility score indicator, when the drill-down view opens, then the system presents a detailed report showing each scoring factor, match percentage, and source excerpts used in the analysis.
Audience Overlap Analysis
"As a podcast host, I want to see how much my guest's audience overlaps with a potential sponsor's target demographic so that I can predict engagement and ad effectiveness."
Description

Identify and quantify the intersection between sponsor target demographics and guest listener profiles using historical engagement data and third-party analytics. The feature presents percentage overlaps across age groups, interests, geographic regions, and engagement metrics. It integrates visual aids and filter controls, enabling hosts to segment audience data and uncover high-potential sponsorship matches that drive listener engagement and ad performance.

Acceptance Criteria
Age Group Overlap Visualization
Given the host selects a sponsor and a guest profile, when the system computes age group overlaps, then the system displays overlap percentages for predefined age brackets (18-24, 25-34, 35-44, 45-54, 55+) with numerical precision to the nearest 1% and renders a corresponding bar chart.
Interest Segment Filtering
Given the host filters by specific interest categories, when the filter is applied, then the system lists only those audience segments where sponsor and guest share at least a 10% overlap and updates the visual display within 2 seconds.
Geographic Region Analysis
Given the host selects one or more geographic regions, when the selection is confirmed, then the system calculates and displays overlap percentages by region on an interactive map, with clickable tooltips showing region name and percentage data accurate to 1 decimal place.
Engagement Metric Comparison
Given the host chooses to compare engagement metrics, when the comparison view is requested, then the system presents a side-by-side comparison of guest listen rates versus sponsor ad click-through rates, including a calculated correlation coefficient and a summary insight statement.
Filter Controls Reset Functionality
Given the host has applied multiple filters and sorting options, when the reset button is clicked, then all filters revert to their default states and the full audience overlap dataset is redisplayed within 1 second.
CSV Export of Overlap Data
Given the host clicks the export button, when the export is initiated, then the system generates and downloads a CSV file containing all displayed overlap metrics with column headers matching the UI labels and data values consistent with the displayed numbers.
Content Synergy Visualization
"As a podcast host, I want visual maps highlighting thematic synergies between my guest's topics and a sponsor's campaign themes so that I can craft more compelling sponsorship segments."
Description

Provide interactive charts and heat maps that map thematic overlap between sponsor campaign keywords and guest episode topics. Users can explore clusters of related themes, view co-occurrence frequencies, and adjust weightings to emphasize content areas most relevant to their show. This visual tool enhances understanding of topic alignment, helping hosts craft more cohesive sponsorship segments and narrative integrations.

Acceptance Criteria
Viewing Thematic Overlap Dashboard
Given the host navigates to the Content Synergy Visualization page When sponsor keywords and guest topics data are loaded Then an interactive heat map displays co-occurrence frequencies between campaign keywords and episode topics
Adjusting Keyword Weightings
Given the user applies a custom weighting slider to a specific keyword When the slider value changes Then all related chart cluster intensities and co-occurrence frequencies update in real time reflecting the new weighting
Exploring Topic Clusters
Given the host clicks on a thematic cluster in the interactive chart When the cluster is selected Then a detailed list of associated keywords and guest episode topics appears alongside the chart
Filtering Co-occurrence Frequencies
Given the user sets a minimum co-occurrence frequency filter When the filter threshold is applied Then only theme overlaps meeting or exceeding the threshold are displayed on both charts and heat maps
Exporting Visualization Data
Given the host chooses to export the current view When the host clicks the export button Then a CSV file is downloaded containing raw co-occurrence counts, weighted scores, and cluster metadata matching the displayed visualization
Real-time Compatibility Alerts
"As a podcast host, I want instant alerts when a selected sponsor and guest pairing has exceptionally high or low compatibility so that I can take timely action."
Description

When hosts browse potential sponsor opportunities or prepare for upcoming guest bookings, the dashboard proactively issues real-time alerts indicating exceptionally high or low compatibility scores. Alerts include recommendations to confirm, refine, or reconsider partnerships, with context on contributing factors. This ensures hosts can make informed decisions quickly and adjust workflows before booking confirmations.

Acceptance Criteria
Browsing Sponsors with High Compatibility
Given a host browses potential sponsors and a sponsor’s compatibility score is 85 or above, when the dashboard loads, then a “High Compatibility” real-time alert must appear within 2 seconds, display a green badge, and include a “Confirm Partnership” recommendation.
Browsing Sponsors with Low Compatibility
Given a host browses potential sponsors and a sponsor’s compatibility score is 40 or below, when the dashboard loads, then a “Low Compatibility” real-time alert must appear within 2 seconds, display a red badge, and include a “Reconsider Partnership” recommendation.
Reviewing Alert Recommendations
Given a compatibility alert is displayed, when the host clicks the alert, then three actionable recommendations—Confirm, Refine Criteria, Reconsider—must be listed as selectable options and link to their respective workflows.
Viewing Alert Contextual Details
Given a compatibility alert is displayed, when the host expands the alert details, then the system must list the top three contributing factors—audience overlap percentage, shared value alignment score, theme synergy score—with source data.
Interacting with Compatibility Alerts in Workflow
Given a host interacts with a compatibility alert by selecting a recommendation, when the selection is confirmed, then the system must record the choice, update the booking interface to reflect the decision, and log the action in the host’s activity history.
Customizable Report Export
"As a podcast host, I want to export a branded report of sponsor-guest compatibility to share with sponsors and my production team so that we have a professional document supporting our partnership decisions."
Description

Enable hosts to export comprehensive sponsor-guest compatibility reports in multiple formats (PDF, CSV). Exports include branded headers, customizable color schemes, and selective inclusion of metrics or visualizations. Reports can be shared with sponsors, production teams, or stakeholders to support partnership discussions and provide professional documentation of alignment insights.

Acceptance Criteria
Export report as PDF with branded header
Given a host selects the PDF format, when exporting the sponsor-guest compatibility report, then the generated PDF includes the host’s customizable branded header, all selected metrics, and maintains layout consistency across pages.
Export report as CSV with selected metrics
Given a host selects the CSV format and chooses specific metrics, when exporting the report, then the CSV file includes only the chosen metric columns with correct headers, uses comma delimiters, escapes special characters, and opens successfully in standard spreadsheet applications.
Customize report color scheme
Given a host customizes the report’s color scheme from available theme options, when exporting in any format, then the header, footer, and data visualizations in the exported report reflect the selected color codes accurately without defaulting to standard colors.
Selective inclusion of metrics and visualizations
Given a host marks specific visualizations and metrics to include or exclude in the report settings, when exporting, then the exported file contains only the marked items and excludes unselected ones, preserving visual integrity for the included charts.
Share exported report with stakeholders
Given a host downloads and sends the exported report to sponsors or team members, when the recipient opens the file in a supported viewer, then the report displays correctly with no missing elements, and the file size does not exceed 10MB for PDFs and 5MB for CSVs.

Sponsorship Dashboard

Offers a centralized view of all active and potential sponsor relationships, tracking campaign performance, revenue forecasts, and upcoming ad commitments to keep monetization efforts organized and transparent.

Requirements

Campaign Overview Panel
"As a podcast host, I want a centralized overview of all sponsorship campaigns so that I can quickly assess the status and details of each partnership without navigating multiple pages."
Description

Provide a consolidated dashboard panel that displays all active and potential sponsorship campaigns with key details such as sponsor name, campaign status, start and end dates, and key performance indicators. This panel should integrate seamlessly within the Sponsorship Dashboard to give hosts immediate visibility into ongoing and upcoming sponsorship activities.

Acceptance Criteria
Viewing Active and Potential Campaigns
Given the host is on the Sponsorship Dashboard, when they access the Campaign Overview Panel, then it lists all active and potential campaigns with sponsor name, campaign status, and start and end dates.
Filtering Campaigns by Status
Given multiple campaigns exist, when the host selects a status filter (Active, Potential, Completed), then only campaigns matching the selected status are displayed.
Viewing Campaign KPI Details
Given an active campaign is selected, when the host clicks on the campaign row, then key performance indicators (e.g., impressions, clicks, revenue forecast) are displayed within the panel.
Date Range Display Accuracy
Given campaigns have defined start and end dates, when the panel loads, then date ranges are formatted as MM/DD/YYYY and accurately reflect each campaign’s timeline.
Seamless Integration within Sponsorship Dashboard
Given the Sponsorship Dashboard layout, when the Campaign Overview Panel renders, then it adheres to the dashboard’s style guide, is responsive across devices, and does not overlap or obscure other UI elements.
Performance Metrics Visualization
"As a podcast host, I want to see visual representations of sponsorship performance metrics so that I can understand trends and report results to sponsors effectively."
Description

Implement interactive charts and graphs that visualize sponsorship performance metrics, including impressions, clicks, conversions, and revenue generated. Users should be able to filter data by time period and campaign to analyze sponsor performance trends and make informed decisions.

Acceptance Criteria
Time Period Filtering
Given the user opens the dashboard, When the user selects a predefined time period or custom date range, Then all performance metrics visualizations update to reflect data only within the selected period.
Campaign Filter and Comparison
Given the user selects one or multiple campaigns from the campaign list, When the selection is applied, Then the visualizations update to display metrics exclusively for the selected campaigns and allow side-by-side comparison.
Data Export Functionality
Given the user clicks the 'Export Data' button, When the export format (CSV or PDF) is chosen, Then the system generates and downloads a file containing the currently filtered metrics and chart data.
Real-Time Data Updates
Given new performance data is available in the system, When the user views the dashboard, Then the charts refresh automatically every 5 minutes or upon manual refresh and display the latest metrics without requiring a page reload.
Device Responsiveness
Given the user accesses the sponsorship dashboard on desktop, tablet, or mobile, When the user interacts with charts (e.g., filter, hover for tooltips), Then the layout adapts to the screen size and interactions remain fully functional.
Revenue Forecast Calculator
"As a podcast host, I want to forecast potential sponsorship revenue so that I can budget and plan future content and marketing strategies."
Description

Develop a forecasting tool that projects expected revenue based on scheduled ad slots, historical performance data, and pending sponsor commitments. The calculator should allow users to adjust parameters and instantly update forecasts to plan monetization strategies.

Acceptance Criteria
Forecast Generation with Scheduled Ad Slots
Given the user has scheduled ad slots for an upcoming episode, when they run the revenue forecast calculator, then the tool projects the total expected revenue by summing the rates for each scheduled ad slot.
Forecast Incorporating Historical Performance Data
Given at least three months of historical ad performance data is available, when the calculator runs a forecast, then it adjusts projections by applying average fill rates and revenue per slot derived from historical data.
Forecast Including Pending Sponsor Commitments
Given there are pending sponsor commitments with defined slot counts and rates, when the forecast is generated, then those pending commitments are included in the revenue projection and displayed separately from confirmed slots.
Real-time Forecast Update on Parameter Adjustment
Given the user modifies forecast parameters (e.g., slot rates, number of slots, fill rate assumptions), when they apply changes, then the revenue forecast updates instantly without a full page reload and reflects the new inputs.
Export and Save Revenue Forecast
Given the user views a completed forecast, when they choose to export or save, then the forecast can be downloaded as a CSV or PDF file containing input parameters, breakdowns, and total projected revenue.
Upcoming Ad Commitments Timeline
"As a podcast host, I want a timeline of upcoming ad commitments so that I can prepare episodes and track upcoming sponsorship obligations."
Description

Create a timeline view that displays upcoming ad commitments, including dates, time slots, and sponsor details. This feature should help hosts visualize and organize their ad delivery schedule, ensuring timely fulfillment of sponsor agreements.

Acceptance Criteria
Viewing Upcoming Ad Commitments
Given the host opens the Upcoming Ad Commitments Timeline, when there are ad commitments scheduled within the next 30 days, then each commitment is displayed in chronological order with date, time slot, and sponsor name visible.
Filtering Commitments by Sponsor
Given multiple sponsors have commitments, when the host selects a sponsor filter in the timeline view, then only commitments associated with that sponsor are shown and the filter can be cleared to restore all commitments.
Marking Commitments as Completed
Given a commitment has passed, when the host marks the commitment as completed in the timeline, then the commitment status updates to “Completed,” is visually distinguished, and no longer appears in the upcoming list.
Responsive Timeline Layout
Given the host accesses the timeline on desktop, tablet, or mobile, when the viewport size changes, then the timeline adjusts its layout to remain readable and scrollable without losing data or functionality.
Viewing Commitment Details
Given the host clicks on an upcoming commitment in the timeline, when the detail panel opens, then it displays full sponsor details, ad content requirements, and links to edit or reschedule the commitment.
Sponsor Relationship Management
"As a podcast host, I want to manage sponsor details and communication history so that I can maintain strong relationships and meet contractual obligations efficiently."
Description

Add a management interface for sponsor contacts and agreements, allowing hosts to store sponsor information, contract details, renewal dates, and communication history. This should integrate with the dashboard to streamline sponsor interactions and maintain transparency.

Acceptance Criteria
Adding a New Sponsor Contact
Given the host is on the Sponsor Relationship Management interface When the host enters a sponsor’s name, contact details, contract start and end dates, and clicks "Save" Then the new sponsor appears in the sponsor list with all entered information accurately displayed
Updating Sponsor Contract Details
Given an existing sponsor is listed in the management interface When the host updates contract terms or renewal dates and clicks "Update" Then the changes are persisted and reflected in both the sponsor list and Sponsorship Dashboard
Automated Renewal Date Reminder
Given a sponsor’s contract renewal date is within 30 days When the host views the Sponsorship Dashboard Then the system displays a renewal alert badge next to the sponsor and sends an email reminder to the host
Recording Sponsor Communication
Given the host selects a sponsor and clicks "Add Communication Record" When the host enters the date, channel, notes, and clicks "Save" Then the communication entry appears in the sponsor’s communication history sorted by date
Viewing Sponsor Details in Dashboard
Given the host is on the Sponsorship Dashboard When the host clicks on a sponsor’s name Then a detail panel opens showing the sponsor’s contact info, contract details, renewal date, and communication history

Performance Forecast

Leverages historical guest metrics, listening trends, and seasonal variables to project an episode’s expected download count and engagement rate, empowering hosts to prioritize high-impact bookings.

Requirements

Historical Data Collection
"As a podcast host, I want the system to collect and store historical guest metrics, listening trends, and seasonal factors so that forecast calculations are based on accurate and complete data."
Description

Implement a module to automatically gather and normalize guest performance metrics (downloads, engagement rate), listening trends, and seasonal data from internal logs and third-party analytics, ensuring the Forecast Engine has comprehensive and up-to-date inputs.

Acceptance Criteria
Scheduled Data Pull from Internal Logs
Given the system clock reaches the configured pull schedule When the data collection module runs Then it retrieves guest download counts and engagement rates from internal logs for the past 24 hours and stores them in the raw data repository
Third-Party Analytics Data Sync
Given valid API credentials for a third-party analytics service When the data ingestion process starts Then the system fetches latest listening trend data for all active episodes, respects rate limits, and logs any missing or malformed records
Seasonal Trend Data Update
Given the system is within a new calendar quarter When seasonal variables update triggers fire Then seasonal weighting factors are downloaded from the seasonal data provider and integrated into the forecast input dataset
Normalization of Performance Metrics
Given raw engagement rates and download counts are ingested When the normalization routine executes Then metrics are scaled to a consistent range and stored with timestamps, ensuring uniform units across all data sources
Error Handling for Data Collection Failures
Given any data retrieval or normalization step fails When an exception occurs Then the system retries up to three times, logs the error with context, and raises an alert if all retries fail
Forecast Calculation Engine
"As a podcast host, I want the system to calculate expected download counts and engagement rates for upcoming episodes so that I can prioritize guests most likely to drive audience growth."
Description

Develop a statistical engine leveraging machine learning models and time-series analysis to project future episode download counts and engagement rates based on aggregated historical data and seasonal variables.

Acceptance Criteria
Baseline Download Forecast Accuracy
Given historical download data for at least 12 past episodes, when the engine generates a forecast for the next episode, then the predicted download count must be within ±10% of actual downloads for 90% of episodes in a held-out validation set.
Seasonal Trend Adjustment
Given known seasonal variables (e.g., month, holiday indicators), when generating forecasts, then the model must adjust predictions to reflect seasonality, reducing seasonal residual error by at least 15% compared to a model without seasonal inputs.
Engagement Rate Projection Consistency
Given historical engagement metrics (e.g., average listen duration, drop-off rate), when forecasting engagement rates, then the predicted engagement rate must achieve a correlation coefficient (R) ≥ 0.8 with actual engagement rates in the test dataset.
Model Retraining Trigger
Given receipt of new episode performance data crossing the retraining threshold (e.g., after 100 new data points or on a monthly schedule), when the threshold is met, then the system must automatically trigger model retraining and record a retraining event log with timestamp and version.
Forecast Visualization Integration
Given forecast results from the calculation engine, when a host accesses the forecast dashboard, then the system displays forecasted download counts and engagement rates with 95% confidence intervals and comparative historical averages.
Forecast Visualization Dashboard
"As a podcast host, I want to view forecast results in a visual dashboard so that I can quickly interpret potential episode performance and make informed booking decisions."
Description

Design and implement a dashboard component that displays forecasted metrics with charts and tables, enabling hosts to compare predicted performance across different episodes and guests.

Acceptance Criteria
Dashboard Initialization and Data Loading
Given the host navigates to the Forecast Visualization Dashboard, when the page loads, then a loading spinner appears within 1 second. Given the page load is initiated, then all forecasted metrics display within 5 seconds without layout shifts. Given the data is loading, then placeholder charts and tables are shown until actual data is rendered.
Comparative Episode Forecast Display
Given the host selects multiple episodes for comparison, when viewing the dashboard, then each episode’s forecasted download count and engagement rate are displayed as distinct bars or lines in a combined chart. Given forecast values are displayed, then hovering over each data point shows a tooltip with precise numeric values and episode titles.
Guest Performance Drill-down
Given the host clicks on a guest’s name in the forecast table, when the click event occurs, then a modal or side panel opens showing that guest’s historical forecast vs actual performance chart. Given the performance chart is displayed, then it includes both download count and engagement rate trends for at least the past five episodes.
Responsive Layout on Different Screen Sizes
Given the host resizes the browser window to a width less than 768px, when viewing the dashboard, then all charts stack vertically and remain fully visible without horizontal scrolling. Given the host views the dashboard on tablet or mobile, then tables support horizontal scrolling and maintain column headers visible at the top.
Data Refresh and Error Handling
Given new forecast data is available from the API, when the host clicks the refresh button, then all chart and table data updates within 3 seconds. Given an API failure occurs during refresh, when the host attempts to refresh, then a user-friendly error message displays and the previous data remains visible.
Booking Priority Suggestions
"As a podcast host, I want the system to suggest guest bookings ranked by forecasted performance so that I can focus on scheduling guests who will maximize my show's reach."
Description

Create an integration within the guest management workflow that ranks and suggests high-impact bookings based on forecasted performance, highlighting top candidates in the scheduling interface.

Acceptance Criteria
Highlight Top High-Impact Guests on Scheduling Interface
Given the host opens the scheduling interface with forecast data available, when the guest list loads, then the top 3 guests with the highest projected downloads are highlighted with a gold border and displayed at the top of the list.
Sort Guests by Projected Engagement Rate
Given multiple guests in the scheduling queue, when the host selects “Sort by Engagement Rate,” then guests are ordered descending by forecasted engagement percentage.
Filter Guests Above Download Threshold
Given the host defines a minimum download threshold, when the filter is applied, then only guests with forecasted downloads greater than or equal to the threshold appear in the list.
Dynamic Suggestions Update Upon Guest Addition
Given a new guest profile with historical metrics is added, when the guest list refreshes, then the system recalculates and re-ranks the top suggestions to include the new guest.
Seasonal Adjustment Applied to Forecasts
Given seasonal multipliers are defined for each month, when generating performance forecasts, then the projected download counts reflect seasonality adjustments within a 5% variance of expected seasonal uplift or decline.
Forecast Customization Settings
"As a podcast host, I want to customize the weightings of variables in the forecast model so that predictions align with my specific audience behavior and content goals."
Description

Provide a settings interface allowing hosts to adjust the weight of different variables (historical metrics, seasonality factors, model sensitivity) to tailor forecasts to their unique audience and content strategy.

Acceptance Criteria
Adjust Historical Metrics Weight
Given the host is on the Forecast Customization Settings page When the host moves the slider for historical guest performance weight to a new value and clicks 'Save' Then the system stores the updated weight and recalculates the forecast preview using the new weight
Modify Seasonality Factors
Given the host accesses seasonality settings When the host enters custom start and end dates for a seasonal period and assigns a multiplier value Then the system validates the dates and multiplier, saves the seasonality factor, and updates the forecast accordingly
Change Model Sensitivity
Given the host chooses a model sensitivity option (e.g., Low, Medium, High) When the host selects an option and saves Then the forecast algorithm adjusts its variance thresholds and displays a confirmation message
Reset to Default Settings
Given the host has made custom adjustments to any forecast settings When the host clicks the 'Reset to Defaults' button and confirms Then all weights and settings return to the system default values and any applied changes are cleared
Persistent User Preferences
Given the host has previously saved custom forecast settings When the host revisits the Forecast Customization Settings page Then the page loads the host's saved settings and displays them accurately in each control

Guest Scorecard

Generates a comprehensive rating for each potential guest based on past episode performance, social media reach, and audience overlap—simplifying guest selection with a single, objective metric.

Requirements

Data Aggregation Module
"As a podcast host, I want the system to automatically gather and update guest performance, social media reach, and audience overlap data so that I can rely on accurate information without manual data collection."
Description

Automatically collect and normalize guest-related data from past episode performance metrics, social media APIs (e.g., Twitter, Instagram), and audience analytics platforms. This module schedules regular data fetches, handles API rate limits, and ensures data integrity through validation and error handling, providing a reliable, up-to-date dataset for score calculations.

Acceptance Criteria
Initial Data Import for Past Episodes
Given valid credentials for the podcast database, when the data aggregation module is triggered for the first time, then it retrieves and stores performance metrics for all past episodes without errors and logs any missing entries.
Scheduled Daily Fetch from Social Media APIs
Given the system schedule is active, when 02:00 UTC arrives, then the module fetches the latest follower counts from Twitter and Instagram for each guest, completing within 15 minutes with zero API errors.
API Rate Limit Handling under Peak Load
Given API rate limits are reached during a fetch, when the module receives a rate-limit response, then it pauses further requests, waits for the retry-after interval, and resumes fetching seamlessly without data loss.
Data Validation and Error Logging
Given incoming data from source APIs, when the module processes each record, then it validates fields against the schema, discards invalid records, and logs validation errors to the error tracking system.
Normalization of Diverse Data Formats
Given raw data from different sources (CSV, JSON, XML), when the module ingests inputs, then it normalizes all data to the unified schema, ensuring consistent field names, data types, and formats.
Score Computation Engine
"As a podcast host, I want the system to compute a unified score for each potential guest based on configurable metrics so that I can quickly compare and prioritize guests without analyzing multiple data points."
Description

Implement an algorithm that weights and normalizes aggregated metrics—such as download counts, engagement rates, and follower overlap—into a single, objective guest score. The engine should support dynamic weighting, threshold checks, and real-time recalculation when new data arrives, ensuring consistent and transparent scoring.

Acceptance Criteria
Initial Score Calculation
Given aggregated metrics for a guest are available, when the Score Computation Engine runs the calculation, then it returns a normalized score between 0 and 100 that accurately reflects the weighted metrics.
Dynamic Weight Adjustment
Given updated weight parameters are submitted by the administrator, when the engine applies the new weights, then all existing guest scores are recalculated in real time and updated in the system without manual intervention.
Threshold Check Enforcement
Given defined minimum threshold values for engagement rate and follower overlap, when a guest’s metrics fall below any threshold, then the engine flags the guest as 'Below Threshold' and excludes them from the recommended guest list.
Real-Time Data Ingestion
Given new performance metrics are ingested (e.g., recent download counts, social media updates), when the ingestion completes, then the engine triggers an automatic score recalculation within 5 seconds and reflects the updated score in the dashboard.
Scoring Transparency and Audit Log
Given a score computation or update event occurs, when the engine processes this event, then it logs an audit entry with timestamp, raw input metrics, applied weights, computed score, and user responsible for the change.
Scorecard Dashboard
"As a podcast host, I want a dashboard that shows guest scores and underlying metrics so that I can visually identify the best candidates and streamline the invitation process."
Description

Design and build a user-friendly dashboard displaying guest scores alongside key contributing metrics. The interface should allow sorting, filtering, and searching, with visual indicators for high-impact guests. It integrates seamlessly with the booking workflow, enabling hosts to select and invite top-scoring guests directly from the dashboard.

Acceptance Criteria
Dashboard Access and Data Retrieval
Given a host navigates to the Scorecard Dashboard, When the dashboard is requested, Then all guest scores and contributing metrics are displayed within 3 seconds.
Sorting by Guest Score
Given the dashboard is displayed, When the host clicks the 'Score' column header, Then the guest list is sorted in descending order by score.
Filtering by Metric Threshold
Given the dashboard is displayed, When the host applies a filter for 'social media reach > 10000', Then only guests with social media reach above 10,000 are shown.
Search for Guest Name
Given the dashboard is displayed, When the host enters a guest’s name into the search field and submits, Then the dashboard displays only guests whose names match the search term.
Invite Top-Scoring Guest
Given a guest with a score >= 80 is listed, When the host clicks the 'Invite' button next to that guest, Then the booking workflow modal opens with the guest’s information pre-populated.
Customizable Weighting Settings
"As a podcast host, I want to customize how much each metric influences the guest score so that the scoring reflects my priorities and target audience preferences."
Description

Provide a settings panel where users can adjust the weight assigned to each metric—such as social reach, past episode downloads, and audience overlap—to tailor the scoring algorithm to their specific goals. Changes should trigger on-the-fly recalculations and persist across sessions, offering full customization of the guest scoring criteria.

Acceptance Criteria
Real-time Recalculation upon Weight Adjustment
Given the user changes any metric weight on the settings panel, when the slider or input is adjusted, then the system recalculates all guest scorecards within 2 seconds reflecting the new weights without requiring a page refresh.
Persisting Customized Weights Across Sessions
Given the user has adjusted metric weights and saved the settings, when the user logs out and then logs back in, then the previously configured weights are loaded and applied to guest scorecards.
Validation of Weight Input Values
Given the user attempts to set a metric weight to a negative value or a value greater than 100, when the user inputs the invalid value and tries to save, then an inline error message appears specifying the valid range and the invalid input is rejected.
Automatic Saving of Weight Adjustments
Given the user modifies any metric weight on the panel, when the input field loses focus, then the updated weight value is automatically saved, and a confirmation message is displayed.
UI Indicator for Custom Weights Applied
Given the user has customized one or more metric weights, when viewing the settings panel, then each modified metric shows a “customized” badge and the “Reset to Default” button becomes enabled.
Export and Sharing Functionality
"As a podcast host, I want to export or share guest scorecards with my team so that we can collaboratively review and decide on booking priorities."
Description

Enable hosts to export guest scorecards as CSV or PDF and generate shareable links for collaboration with team members or co-hosts. Exports should include raw metrics, final scores, and applied weights, while shared links respect user permissions and update dynamically when data changes.

Acceptance Criteria
Export Guest Scorecard as CSV
Given a host views a completed guest scorecard, When the host selects “Export to CSV”, Then the system generates a CSV file that includes columns for each raw metric, final guest score, and applied weight, and initiates a download within 3 seconds.
Export Guest Scorecard as PDF
Given a host views a completed guest scorecard, When the host selects “Export to PDF”, Then the system generates a PDF document with branded header, raw metrics table, final score section, and applied weights footer, and prompts a download or print dialog within 5 seconds.
Generate Shareable Scorecard Link
Given a host requests to share a guest scorecard, When the host clicks “Generate Shareable Link”, Then the system creates a unique URL that grants read-only access to the scorecard and displays the access level in the host’s share settings.
Permission Control on Shared Links
Given a host configures permissions for a shareable link, When the host selects “Edit” permissions, Then recipients accessing the link can add comments but cannot modify raw metrics, final scores, or applied weights, and the host can revoke or change permissions at any time.
Dynamic Update of Shared Scorecards
Given a guest scorecard is shared via link, When underlying guest metrics or weights are updated, Then the shared view reloads or refreshes automatically within 60 seconds to reflect the latest data without requiring a new link.

Trend Tracker

Analyzes listener behavior and topic popularity over time to identify emerging content themes, enabling hosts to tailor episode subjects and guest expertise for maximum audience interest.

Requirements

Data Collection Pipeline
"As a podcast host, I want the system to automatically gather and consolidate listener interaction data across platforms so that I have complete and accurate data for trend analysis."
Description

Establish a robust pipeline that collects, cleans, and aggregates listener behavior data (e.g., plays, skips, completion rates) and topic metadata from integrated podcast platforms and social media channels. This pipeline ensures real-time data ingestion, normalization, and storage in a centralized data warehouse, enabling accurate and timely trend analysis.

Acceptance Criteria
Real-Time Ingestion from Podcast Platforms
Given the pipeline is connected to a supported podcast platform API, When a new listener event occurs, Then the event data is ingested into the staging area within 5 seconds with a 99% success rate.
Accurate Data Normalization
Given raw listener behavior data with varying timestamp formats and missing fields, When processed by the normalization module, Then all timestamps are converted to ISO 8601, missing fields are populated with defaults, and data conforms to the schema with a 100% validation pass.
Centralized Data Storage
Given normalized data batches, When loaded into the data warehouse, Then each batch is fully persisted in the target tables with no record loss and table row counts match staging counts.
Social Media Data Integration
Given messages from integrated social media channels, When ingested, Then mentions, likes, and shares metrics are extracted and stored alongside listener behavior records within 10 minutes of occurrence.
High-Volume Data Scalability
Given a spike of 10,000 events per minute, When the pipeline processes events for 10 minutes, Then it maintains at least 95% throughput with no errors and average processing latency under 10 seconds.
Trend Analysis Engine
"As a podcast host, I want the system to analyze listener behavior and topic popularity over time so that I can identify emerging content themes for my show."
Description

Develop an analytical engine that applies statistical algorithms and machine learning models to the collected dataset to detect patterns, calculate topic popularity scores, and identify emerging themes. The engine should support customizable time windows, weighting parameters, and anomaly detection to deliver relevant and actionable insights.

Acceptance Criteria
Custom Time Window Analysis
Given the host selects a custom time window of 30 days, when the engine runs the analysis, then it returns a list of topics with popularity scores as numerical values between 0 and 100, ordered descending, within 5 seconds of the request.
Weighted Parameter Adjustment
Given the host configures weighting parameters to apply a 2:1 ratio for listens versus shares, when the engine recalculates scores, then the resulting popularity scores reflect the specified weighting, validated against baseline data in automated tests.
Anomaly Detection Alerting
Given anomaly detection is enabled, when the engine identifies a topic with a 200% spike in mentions within a 24-hour period, then it flags the topic as anomalous and generates an alert in the dashboard within 60 seconds.
Historical Trend Comparison
Given the host requests a comparison between two consecutive 7-day periods, when the engine processes the request, then it provides the percent change in popularity for each topic, highlighting those with at least ±10% variation.
Emerging Theme Identification
Given the engine analyzes listener behavior over the past 90 days, when emerging theme detection runs, then it identifies the top 5 topics with consistent upward trends and outputs a report with supporting metrics such as growth rate and average mentions per week.
Visualization Dashboard
"As a podcast host, I want a dashboard that visualizes trending topics and listener metrics so that I can easily interpret and act on the insights."
Description

Create an interactive UI component within ChirpFlow that displays time-series charts, heatmaps, and trend lines for topic popularity and listener engagement metrics. The dashboard should allow hosts to filter by date range, audience segment, and content categories, with tooltips and drill-down capabilities for deeper analysis.

Acceptance Criteria
Date Range Filtering
Given the user is on the visualization dashboard When the user selects a start and end date Then all charts and heatmaps update to display data only within the selected date range
Audience Segment Filtering
Given the dashboard is displaying metrics When the user applies an audience segment filter Then all visual components refresh to show metrics exclusively for the chosen segment
Tooltip Information Display
Given a data point is displayed on a chart When the user hovers over the data point Then a tooltip appears showing the date, topic name, and exact engagement value
Drill-down Data Exploration
Given a trend line visualizing topic popularity When the user clicks a specific data point on the trend line Then detailed underlying records (episode title, date, metrics) are displayed in a breakdown view
Dashboard Performance Load Time
Given the user navigates to the visualization dashboard When the page loads Then all interactive charts and filters must render and be fully operational within 2 seconds
Alert and Recommendation System
"As a podcast host, I want to receive alerts and content recommendations when new trends emerge so that I can adapt episode topics promptly."
Description

Implement a rules-based and ML-powered notification system that monitors trend analysis outputs and sends real-time alerts via email, in-app notifications, or Slack when significant topic shifts or spikes are detected. Additionally, generate personalized content recommendations to guide hosts in selecting future episode subjects and guests.

Acceptance Criteria
Email Alert for Significant Topic Spike
Given the trend analysis detects a ≥20% increase in topic mentions over a 7-day window, when the threshold is crossed, then an email is sent to the host within 5 minutes containing the topic name, spike percentage, and a dashboard link; no duplicate emails are sent for the same spike event.
In-App Notification for Emerging Trend
Given a new trend emerges with a relevance score ≥0.8, when the user accesses the app, then an in-app notification appears within 2 minutes with a badge and clicking it navigates to a detailed trend page displaying a chart and recommended episode topics.
Slack Notification for Weekly Trend Summary
Given the weekly summary schedule triggers at Monday 09:00, when executed, then a formatted message summarizing the top 3 emerging topics with metrics and recommendation links is posted to the configured Slack channel within 10 minutes; failures are logged and retried twice.
Personalized Content Recommendations Email
Given trend analysis results and user preferences, when analysis completes, then an email with the top 5 recommended episode subjects and guest profiles ranked by relevance (score ≥0.7) is delivered to the host within 1 hour, including supporting data for each recommendation.
Notification Failure Handling and Escalation
Given a notification delivery error occurs, when the system fails to send an email or Slack message, then it retries up to 3 times with exponential backoff, logs each failure, and if still unsuccessful, raises an in-app alert and escalates to the admin within 15 minutes.
Report Export and Sharing
"As a podcast host or team member, I want to export trend reports to share with collaborators so that we can align on future episode planning and strategy."
Description

Enable users to generate exportable trend reports in PDF and CSV formats, including key metrics, visual summaries, and recommended action items. Provide sharing options with customizable branding and permission settings to streamline collaboration with co-hosts, producers, and sponsors.

Acceptance Criteria
Generating PDF Trend Report
The generated PDF report includes user-selected date range, key metrics, visual charts, and recommended action items; The PDF file downloads within 5 seconds; The report layout adheres to the active branding template and page size settings
Exporting CSV Trend Data
The CSV export contains all trend data rows matching the selected filters (date range, topics); Column headers match the metric names in the UI; The CSV file downloads within 5 seconds and opens without errors in spreadsheet software
Customizing Report Branding
User can upload or select a branding template and preview it before export; The exported PDF and CSV include the correct logo, color scheme, and footer text; Branding changes are saved and applied automatically on subsequent report exports
Setting Sharing Permissions
User can set view-only or edit permissions for each collaborator before sharing; Permission settings are enforced—view-only users cannot download or modify the report; Changes to permissions are reflected immediately and notified to collaborators
Collaborating with External Stakeholders
User can generate a shareable link that expires after a configurable time period; Stakeholders accessing the link can view the report in-browser without authentication if allowed; Download and print options respect the link’s permission settings

Opportunity Radar

Highlights high-potential guest-host pairings by matching performance forecasts with podcast theme alignment, streamlining outreach to guests likely to drive exceptional engagement.

Requirements

Performance Forecast Engine
"As a podcast host, I want to see predicted engagement scores for potential guests so that I can prioritize outreach to those most likely to boost my show’s performance."
Description

Implement a forecasting engine that analyzes past guest performance metrics—including listener engagement, social reach, and episode feedback—to predict potential success scores for new guest-host pairings. This engine integrates with the existing podcast analytics API, applies machine learning models for trend identification, and updates forecasts in near real-time to ensure recommendations reflect the latest data.

Acceptance Criteria
Initial Forecast Generation
Given a guest with historical performance metrics retrieved from the analytics API When the engine processes the guest data Then it generates a success score between 0 and 100 within 30 seconds and stores it in the forecasts database
Real-time Data Update Impact
Given new listener engagement, social reach, or episode feedback data arrives via the analytics API When the forecasting engine receives the updated data Then it recalculates the forecast score within 5 minutes and archives the previous score version for audit
Theme Alignment Scoring
Given a host's podcast theme tags and a guest's topic keywords When the engine evaluates pairing suitability Then it calculates a theme alignment score and includes only guest-host pairs with an alignment score >= 70% in the high-potential list
Batch Forecast Processing
Given a batch request of up to 1000 guests When the engine processes the batch Then it completes forecasting for all guests within 10 minutes with an error rate below 1%
Forecast Accuracy Validation
Given a dataset of past episodes with both predicted and actual performance metrics When running the accuracy validation job Then the engine's predictions achieve a mean absolute error (MAE) of <=10 points on a 0-100 scale
Theme Alignment Scoring
"As a podcast host, I want recommendations based on thematic alignment so that conversations feel coherent and relevant to my show’s audience."
Description

Develop a scoring system that assesses the thematic fit between a podcast’s topic areas and a guest’s expertise or content focus. This feature leverages natural language processing on episode transcripts, guest bios, and external content to compute alignment scores, ensuring suggested pairings resonate with the host’s brand and audience interests.

Acceptance Criteria
Viewing Theme Alignment Score for Prospective Guest
Given a host selects a prospective guest profile, when the system analyzes the guest’s bio and recent content, then it displays a theme alignment score between 0 and 100, updated within 5 seconds.
Filtering Guests by Theme Alignment Score
Given the host sets a minimum alignment threshold in the dashboard, when the filter is applied, then only guests with scores equal to or above the threshold are listed, and the list updates in under 3 seconds.
Recalculating Alignment Score on Transcript Update
Given new episode transcripts are uploaded, when the system reprocesses the transcript, then it recalculates and updates the guest’s theme alignment score automatically within 10 minutes.
Exporting Guest Alignment Scores
Given the host exports the guest suggestion list, when the export completes, then the CSV includes a column for theme alignment scores matching the dashboard values and is downloadable without errors.
Notification for High Alignment Matches
Given a guest’s alignment score exceeds a predefined high-score threshold, when the score is generated, then the host receives an in-app notification and email alert within 1 minute.
Opportunity Dashboard Interface
"As a podcast host, I want a clear interface to explore top guest opportunities so that I can quickly identify and organize potential guests for outreach."
Description

Create an interactive dashboard within ChirpFlow where hosts can view, filter, and sort high-potential guest-host pairings. The dashboard displays forecast scores, alignment ratings, and key metrics; supports search and dynamic filtering by category, date added, and score thresholds; and allows hosts to save favorites or mark guests for outreach.

Acceptance Criteria
Dashboard Initial Load
Given the host opens the Opportunity Dashboard, when the dashboard finishes loading, then a list of high-potential guest-host pairings is displayed with forecast scores, alignment ratings, and key metrics within 3 seconds.
Search for Guest by Name
Given the host enters a guest’s name in the search bar, when they submit the query, then matching guest-host pairings are filtered and displayed immediately.
Filter by Date Added
Given the host selects a date range filter, when they apply the filter, then only pairings added within the selected dates are shown on the dashboard.
Sort by Forecast Score
Given the host clicks the forecast score column header, when they choose ascending or descending order, then the guest-host pairings are resorted accordingly within 2 seconds.
Save Favorite Guest
Given the host clicks the star icon next to a guest’s pairing, when they confirm the action, then the pairing is added to their Favorites list and visually marked with a filled star.
Dynamic Score Threshold Filtering
Given the host adjusts the minimum forecast score slider, when they set a threshold, then only pairings with scores equal to or above the threshold are displayed in real time.
Automated Outreach Recommendations
"As a podcast host, I want ChirpFlow to suggest outreach messaging and timing so that I can increase response rates and reduce the effort of crafting invitations."
Description

Add a recommendation engine that generates personalized outreach templates and schedules optimized contact times based on guest availability patterns and past response rates. This includes suggested email copy, social media DM scripts, and best-time-to-send analytics, all accessible directly from the Opportunity Radar.

Acceptance Criteria
Personalized Email Template Generation
1. System auto-generates an email template populated with guest’s name, expertise, and episode topic 2. Template includes placeholders for host personalization 3. Generated copy adheres to saved brand voice guidelines (≥95% match) 4. Template is editable within the UI before sending
Social Media DM Script Generation
1. System provides a social media DM script tailored to platform (e.g., Twitter, LinkedIn) 2. Script includes guest-specific details and episode context 3. Script follows brand voice guidelines (≥95% match) 4. Editable fields allow host adjustments before sending
Best-Time-to-Send Analytics Display
1. System analyzes≥30 days of past guest response data 2. Displays top 3 hourly windows ranked by reply rate 3. Analytics chart is interactive and shows time in guest’s local timezone 4. Recommendations update dynamically when filters change
Scheduling Optimization Suggestion
1. System suggests optimal contact times based on guest availability patterns and past response rates 2. Suggestion accounts for guest’s time zone and typical work hours 3. Suggestion accuracy is within±30 minutes of historical peak response time 4. Suggested times are presented as clickable options in the UI
Opportunity Radar Integration
1. Outreach recommendations (email templates, DM scripts, send times) are accessible via a single click on the Opportunity Radar interface 2. Recommendations load within 2 seconds of user request 3. UI displays all recommendation types in a consolidated view 4. User can initiate outreach from within the Radar without navigating away
Real-time Notification System
"As a podcast host, I want to receive timely alerts when new top guest matches appear so that I can act quickly and secure bookings before opportunities lapse."
Description

Implement a notification system that alerts hosts when new high-potential pairings emerge or when forecast updates change a guest’s opportunity score beyond a defined threshold. Notifications can be delivered via email, in-app banners, and Slack integrations, ensuring hosts stay informed of time-sensitive matches.

Acceptance Criteria
Email Notification for New High-Potential Pairing
Given a new guest-host pairing with an opportunity score above the defined threshold, when the pairing is created, then an email with guest details and opportunity score is sent to the host within 5 minutes.
In-App Banner Alert for Score Threshold Breach
Given an existing pairing’s opportunity score increases or decreases beyond the set threshold, when the score update is processed, then an in-app banner appears on the host dashboard within 2 minutes displaying the guest name, new score, and recommended action.
Slack Channel Notification for Score Updates
Given the host has linked a Slack workspace and subscribed to notifications, when any guest’s opportunity score crosses the defined threshold, then a formatted Slack message with guest name, score change, and link to the pairing details is posted to the designated channel within 5 minutes.
Real-Time Notification Preference Configuration
Given a host accesses notification settings, when they enable or disable email, in-app, or Slack notifications, then the system saves preferences and applies them immediately, reflected in subsequent notifications.
Notification Delivery Error Handling
Given the system fails to send a notification via email, in-app, or Slack, when the retry logic is triggered, then the system retries delivery up to three times and logs the failure; if all retries fail, then an alert is sent to the system administrator within 10 minutes.

Seasonal Insights

Provides data-driven guidance on the optimal timing for episode releases and guest bookings by correlating past performance spikes with calendar events and industry trends.

Requirements

Event Correlation Engine
"As a podcast host, I want the system to automatically correlate past performance peaks with calendar events and trending topics so that I can understand which timings yield the highest listener engagement."
Description

Develop a data processing engine that analyzes historical episode performance metrics alongside calendar events and industry trend indicators. The engine should identify statistically significant performance spikes and map them to relevant dates, holidays, or trending topics. It will power recommendation features by providing a backend service that continuously ingests, normalizes, and correlates time-series data from listening platforms, social media trends, and external event calendars.

Acceptance Criteria
Data Ingestion and Normalization
Given new time-series data from listening platforms and social media feeds, when processed by the engine, then data is ingested without errors, missing timestamps are backfilled using linear interpolation, and all metrics conform to the unified schema validated against a predefined data dictionary.
Performance Spike Detection
Given normalized performance metrics over the past year, when running statistical analysis, then the engine identifies spikes exceeding two standard deviations from the moving average with a false positive rate below 5%.
Event Mapping Accuracy
Given identified performance spikes, when mapping to calendar events and trend indicators, then at least 90% of spikes are correctly associated with relevant dates, as verified by manual audit against a known events list.
Real-Time Trend Correlation
Given incoming social media trend scores and external event feeds, when processed in real-time, then the engine updates correlation scores within 15 minutes of data arrival with a per-update latency below 30 seconds.
Recommendation Generation Integration
Given correlated spike-event data, when generating release timing recommendations, then the API returns the top three dates with the highest predicted performance uplift for each podcast within 200 milliseconds, formatted according to the recommendation schema.
Release Timing Recommendations
"As a podcast host, I want to receive data-driven recommendations for the best release dates so that I can schedule episodes when they are most likely to reach a large audience."
Description

Implement an algorithm that generates optimal episode release dates based on the outputs of the Event Correlation Engine. This feature should offer ranked suggestions for release timing, highlighting dates with predicted high listener interest. Recommendations will include confidence scores, historical context, and brief rationales, and will be accessible from the Shore Insights section within ChirpFlow’s dashboard.

Acceptance Criteria
Display Ranked Release Date Suggestions
Given the user is in the Shore Insights section, when they view the Release Timing Recommendations panel, then they see a list of at least 3 release date suggestions sorted in descending order by confidence score.
Include Confidence Scores
Given the list of suggested release dates is displayed, then each suggestion shows a numerical confidence score between 0% and 100% reflecting predicted listener interest.
Show Historical Context and Rationales
Given each release date suggestion, then it includes a brief rationale and at least one historical performance datapoint explaining the recommendation.
Responsive Filtering by Date Range
Given the user applies a custom date range filter, when the filter is set, then the recommended release dates update to include only suggestions within the selected date range.
Performance of Recommendation Generation
When the user accesses the Shore Insights section, then the release timing recommendations are generated and fully displayed within 3 seconds.
Guest Booking Insights Dashboard
"As a podcast host, I want to see a dashboard that suggests when I should book guests based on past episode performance and guest schedules so that I maximize the impact of each guest appearance."
Description

Create a visual dashboard that displays guest booking recommendations by mapping peak audience engagement periods against guest availability windows. The dashboard will present interactive timelines showing suggested booking dates, historical guest performance, and recommended lead times for invitations. Integration with the Insights module ensures hosts can plan guest outreach alongside release scheduling.

Acceptance Criteria
Peak Engagement Suggestion
Given the host selects a date range on the Guest Booking Insights Dashboard, when the data is processed, then the dashboard highlights the top three audience engagement peaks within that period and displays corresponding calendar dates for optimal guest booking.
Interactive Timeline Filters
Given the host adjusts timeline filters for date range and engagement thresholds, when changes are applied, then the interactive timeline updates in real time to reflect only those dates matching the selected engagement levels and guest availability windows.
Historical Guest Performance Display
Given the host clicks on a suggested booking date, when the system retrieves associated data, then the dashboard displays historical guest performance metrics—such as average downloads and listener ratings—for guests previously booked during similar engagement peaks.
Lead Time Recommendation Accuracy
Given the host views recommended lead times for invitation send dates, when reviewing a suggested booking slot, then the dashboard calculates and displays the optimal invitation send date based on at least 80% alignment with historical booking lead times.
Insights Integration Sync
Given updates are made in the Seasonal Insights release schedule, when the host opens the Guest Booking Insights Dashboard, then the dashboard automatically syncs and displays the latest release schedule changes without requiring a manual page refresh.
Calendar Integration and Alerts
"As a podcast host, I want recommendations to sync directly to my calendar and receive timely alerts so that I never miss an optimal release or booking opportunity."
Description

Provide two-way integration with popular calendar platforms (Google Calendar, Outlook) to automatically sync recommended release and booking dates. The system will push alert notifications and reminders to hosts about upcoming suggested slots, ensuring that high-potential dates aren’t missed. Configuration options will allow users to adjust notification channels and frequencies.

Acceptance Criteria
Sync Recommended Dates to Google Calendar
Given a host has connected their Google Calendar When the system generates a recommended release date Then the date and time appear in the host's Google Calendar within 5 minutes
Sync Recommended Dates to Outlook Calendar
Given a host has connected their Outlook Calendar When the system generates a recommended booking date Then the slot is added to the host's Outlook Calendar with correct title and description
Host Adjusts Notification Settings
Given the host navigates to notification settings When they change alert frequency or channel Then all subsequent reminders follow the updated configuration immediately
Host Receives Reminder via Email
Given a recommended slot is 24 hours away When the alert trigger fires Then an email reminder is sent to the host's registered address with date, time, and link to reschedule
System Handles Failed Calendar Sync
Given a calendar sync attempt fails due to network error When retry logic executes Then the system retries up to 3 times and logs an error if still unsuccessful
Trend Analytics and Reporting
"As a podcast host, I want comprehensive reports on seasonal and trend-based performance so that I can plan future episodes around proven audience interests."
Description

Develop a reporting module that visualizes long-term trends in listener engagement, seasonal fluctuations, and topic popularity. Reports will include charts for monthly, quarterly, and yearly comparisons, with exportable PDF and CSV formats. These insights help hosts identify recurring performance patterns and make strategic content planning decisions.

Acceptance Criteria
Monthly Engagement Trends Chart Display
Given a host with at least 12 months of episode data When the host selects the 'Monthly View' in the Trend Analytics module Then the system displays a line chart showing listener engagement for each of the past 12 months with labeled axes and interactive tooltips
Quarterly Engagement Fluctuation Comparison
Given a host with at least 4 quarters of historical data When the host switches to 'Quarterly View' in the Trend Analytics module Then the system renders a bar chart comparing average engagement metrics across each quarter of the selected year
Yearly Topic Popularity Overview
Given a host has tagged each episode with topic metadata When the host views the 'Yearly Topic Popularity' report Then the system generates a pie or donut chart showing the percentage share of listener engagement per topic over the past year
Export Trend Report to PDF
Given a host has generated any trend report (monthly, quarterly, or yearly) When the host clicks the 'Export as PDF' button Then the system downloads a PDF file containing the chart, title, date range, and summary insights matching the on-screen report
Export Trend Data to CSV
Given a host has generated any trend report When the host clicks the 'Export as CSV' button Then the system downloads a CSV file with raw numerical data for the selected time frame and metrics matching the chart values
Correlate Seasonal Events with Engagement Peaks
Given a host has event annotations for episodes (holidays, industry events) When the host enables 'Seasonal Correlation' in the report settings Then the system overlays markers on the trend chart at corresponding dates and highlights any engagement spikes within a seven-day window
Customizable Recommendation Filters
"As a podcast host, I want to customize recommendation criteria (e.g., topic genre or audience age group) so that the suggested timings and bookings align precisely with my show’s niche and audience profile."
Description

Enable users to refine timing and booking recommendations through filters such as genre, audience demographics, episode format, and past guest performance scores. The system will dynamically adjust suggestions based on selected criteria, allowing hosts to tailor outcomes to their unique show style and listener base.

Acceptance Criteria
Filter by Genre
Given the host selects “Technology” in the genre filter, When the host applies the filter to the recommendation engine, Then only timing suggestions and guest booking recommendations tagged with “Technology” are displayed.
Filter by Audience Demographics
Given the host chooses audience age 18–34 and location North America, When the host requests optimized booking times, Then the system returns recommendations based solely on past performance data for that demographic segment.
Filter by Episode Format
Given the host opts for “Interview” format in the format filter, When recommendations are generated, Then only guest suggestions and release windows matching the interview format’s historical engagement metrics appear.
Filter by Past Guest Performance Score
Given the host sets a minimum guest performance score of 80%, When filtering recommendations, Then the system excludes any guest or slot with an average performance score below 80%.
Combine Multiple Filters for Tailored Suggestions
Given the host applies genre “Health,” audience location “Europe,” and minimum performance score 75%, When generating recommendations, Then the system provides only those suggestions meeting all three criteria simultaneously.

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ChirpFlow Unveils No-Show Ninja to Slash Podcast Guest No-Shows by 80%

Imagined Press Article

City, State – ChirpFlow, the leading podcast guest management platform for independent creators, today announced the launch of No-Show Ninja, an AI-driven feature designed to eliminate up to 80% of guest no-shows and keep hosts on schedule. Podcast hosts have long grappled with the frustration of last-minute cancellations and unconfirmed guests. Missed appointments not only disrupt production workflows but also undermine listener trust and revenue potential. No-Show Ninja leverages advanced machine learning and automated scheduling intelligence to deliver personalized reminders, dynamic rescheduling, and seamless calendar updates that ensure every guest arrives prepared and on time. “With No-Show Ninja, we’re addressing one of the biggest pain points in podcast production,” said Alex Turner, CEO of ChirpFlow. “Our mission is to empower independent hosts to focus on creativity and content, not administrative headaches. By reducing no-shows by up to 80%, we help creators reclaim hours each week and maintain a consistent release schedule.” Key features of No-Show Ninja include: • AI-Optimized Reminders: Guests receive targeted alerts via email, SMS, and in-app notifications at 24 hours, one hour, and ten minutes before the recording session. Notification timing, channel selection, and messaging style adapt to each guest’s historical responsiveness for maximum engagement. • Auto-Reschedule Intelligence: If a guest misses their slot, No-Show Ninja automatically proposes the next available time based on host availability and guest preferences. This Auto Slot Filler capability keeps calendars full and recording momentum high—without manual intervention. • Smart Waitlist Integration: Leaders from previous inquiry lists and past guests are ranked by relevance and engagement metrics, then invited instantly whenever a slot opens. This ensures downtime is minimized and high-quality replacements are always on standby. • Dashboard Insights: A real-time analytics dashboard tracks reminder delivery rates, guest confirmations, and last-minute cancellations. Actionable recommendations help hosts refine reminder cadence and communication channels over time. Early adopters report dramatic improvements. “Before No-Show Ninja, I would lose nearly one in five guests at the last minute,” said Emily Rivera, host of The Balanced Life Podcast. “Now, cancellations are almost unheard of. The AI reminders feel personal, and the auto-reschedule feature saved me so many hours of back-and-forth.” No-Show Ninja is available today to all ChirpFlow subscribers at no additional cost. Existing workflows automatically incorporate the feature, and hosts can customize reminder templates and rescheduling rules through the platform’s intuitive settings menu. About ChirpFlow ChirpFlow streamlines podcast guest management for independent hosts by automating scheduling, episode tracking, and guest preparation. Founded in 2022, ChirpFlow serves thousands of creators—from solo hosts to network producers—helping them save time, reduce no-shows, and deliver polished content every week. The platform’s branded prep packets, AI-driven workflows, and integrated analytics empower hosts to maintain professional standards without breaking the bank. Media Contact: Sarah Kapoor Director of Communications, ChirpFlow press@chirpflow.com +1 (415) 555-0198

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ChirpFlow Launches CrossCast Connect to Ignite Collaborative Podcast Growth

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City, State – ChirpFlow, the premier podcast guest management solution, today announced the general availability of CrossCast Connect, a groundbreaking feature set that automates cross-show collaborations and amplifies audience reach across multiple podcasts. As podcast networks and independent hosts increasingly seek strategic partnerships and guest crossovers, managing joint promotions and shared content has grown more complex. CrossCast Connect solves this challenge with a centralized collaboration dashboard, automated co-promotion scheduling, and AI-driven guest matching—making it effortless for creators to expand their listener base and increase engagement. “Podcasters thrive on community and shared enthusiasm,” said Maya Li, Chief Product Officer at ChirpFlow. “CrossCast Connect unlocks the power of collaboration by removing administrative barriers. Instead of juggling spreadsheets and multiple inboxes, hosts can coordinate cross-show promotions, co-branded prep materials, and joint marketing campaigns in just a few clicks.” Highlights of CrossCast Connect include: • SynergyMatch AI: Analyzes podcast themes, audience demographics, and listening patterns to suggest optimal cross-promotion partners. Hosts receive ranked guest-host pairings that promise the highest co-listenership and mutual growth potential. • CoPromo Scheduler: Automates the timing and distribution of shared promotional assets—email blasts, social posts, and show mentions—across participating podcasts. Once partners approve the campaign, CoPromo Scheduler handles delivery, tracking, and performance reporting. • Shared Media Vault: A secure, cloud-based repository for co-branded graphics, audio clips, logos, and social templates. Team members and external collaborators access up-to-date assets, ensuring each promotion aligns with brand guidelines. • Collaboration Dashboard: A unified workspace where hosts track active cross-promotion campaigns, upcoming timelines, task assignments, and engagement metrics. Real-time status updates and customizable notifications keep every team member aligned and accountable. Early trials of CrossCast Connect delivered impressive results. “We saw a 40% boost in listens when we coordinated episode swaps with two network partners,” said Jonathan Miles, Network Manager at Apex Podcasts. “The automated workflows and tracking tools saved us hours of coordination time, and the audience data confirmed that cross-promotion was a win-win for everyone.” CrossCast Connect is included in ChirpFlow’s Pro and Enterprise plans, with enhanced reporting features available in the Enterprise tier. Hosts can upgrade or start a free trial today to experience next-level collaboration capabilities. About ChirpFlow ChirpFlow is a full-featured podcast guest management platform that automates scheduling, episode coordination, and guest preparation for creators of all sizes. By combining powerful AI features with user-friendly design, ChirpFlow helps hosts and producers deliver professional-grade content on time, every time. Media Contact: Sarah Kapoor Director of Communications, ChirpFlow press@chirpflow.com +1 (415) 555-0198

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ChirpFlow Introduces SponsorSync to Automate Podcast Sponsorship and Boost Revenue

Imagined Press Article

City, State – ChirpFlow, the trusted partner for podcast guest management, today announced the launch of SponsorSync, an innovative sponsorship automation suite that matches podcasters with ideal advertisers, streamlines ad insertion, and maximizes revenue potential. Securing and managing sponsors has become one of the most time-consuming tasks for independent hosts and network producers alike. SponsorSync combines AI-driven guest and audience insights with automated ad placement tools to simplify sponsorship workflows, ensuring hosts spend less time on administration and more time on creating compelling content. “SponsorSync is a game-changer for monetization,” said Alex Turner, CEO of ChirpFlow. “We recognize that hosts want fair compensation for their creative work, but negotiating sponsor deals and handling ad logistics can be overwhelming. SponsorSync automates the entire process—from prospect identification to rate recommendations and ad slot scheduling—so creators can focus on delivering value to both their audience and sponsors.” Key capabilities of SponsorSync include: • AdFit Matchmaker: Leverages AI to analyze guest profiles, episode themes, and audience demographics to recommend sponsors whose messaging aligns with listener interests. Matchmaker presents hosts with a ranked list of high-potential sponsors. • Dynamic Rate Card: Generates real-time sponsorship pricing based on audience metrics, guest influence scores, and current market trends. Hosts receive data-backed rate recommendations, ensuring competitive and transparent pricing. • AutoSlot Creator: Automatically inserts customized ad slots into each episode’s prep packet, factoring in sponsor priorities, desired exposure, and episode length. Integrated calendar invites and delivery notifications keep sponsors informed every step of the way. • Sponsor Pitch Builder: Produces tailored pitch decks and email templates using guest bios, prior performance data, and show highlights. Hosts can personalize each outreach in minutes, accelerating deal cycles and improving conversion rates. • Sponsorship Dashboard: A centralized view of active and potential sponsor relationships, complete with performance analytics, revenue forecasts, and upcoming commitments. Customizable reports allow hosts to track ROI and refine sponsorship strategies over time. During beta testing, participants increased sponsorship revenue by an average of 35% within the first month. “SponsorSync identified new brand opportunities we never considered and handled the outreach seamlessly,” said Brand-Building Ben, host of The Weekly Sponsor Spotlight. “We closed three new partnerships in two weeks—something that used to take me months.” SponsorSync is available now as an add-on to all ChirpFlow subscription plans. For a limited time, new and existing customers can unlock a free 30-day trial to experience SponsorSync’s full capabilities. About ChirpFlow Founded in 2022, ChirpFlow delivers comprehensive podcast guest management solutions—including scheduling, prep packet generation, and advanced analytics—to help creators of all sizes optimize workflows and grow their shows. From independent hosts to large networks, ChirpFlow’s suite of AI-driven features empowers users to save time, reduce no-shows, and maximize revenue opportunities. Media Contact: Sarah Kapoor Director of Communications, ChirpFlow press@chirpflow.com +1 (415) 555-0198

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