Auto Repair Shop Management Software

PulseQueue

Never Miss a Bay Again

PulseQueue automates appointment scheduling for independent auto repair shop owners overwhelmed by missed bookings and empty bays. AI-powered load balancing and real-time SMS reminders optimize calendars, slash no-shows by 40%, and boost bay utilization—freeing managers from manual chaos and driving higher shop revenue through seamless, intelligent scheduling.

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PulseQueue

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 independent auto shop to achieve peak efficiency and delight clients through intelligent, automated scheduling.
Long Term Goal
By 2028, empower 15,000 independent auto repair shops to boost bay utilization by 25% and cut no-shows by 40%, setting the global benchmark for efficient scheduling.
Impact
Reduces appointment no-shows by up to 40% and cuts manual scheduling time by 30% for independent auto repair shops, increasing bay utilization by 25% and directly boosting monthly revenue while alleviating operational stress for owners and managers overwhelmed by inefficient booking processes.

Problem & Solution

Problem Statement
Independent auto repair shop owners lose revenue and productivity to frequent no-shows and chaotic manual scheduling because existing tools lack automation, real-time reminders, and AI-driven load balancing tailored to their unique workflow needs.
Solution Overview
PulseQueue eliminates manual scheduling chaos by automatically syncing with shop calendars and sending real-time SMS reminders to customers, while AI-powered booking fills work bays with the best jobs—slashing no-shows and freeing owners from daily appointment headaches.

Details & Audience

Description
PulseQueue automates appointment scheduling for independent auto repair shops, freeing owners and managers from manual booking headaches. Shops slash no-shows and boost bay utilization with real-time SMS reminders for clients. Unique AI-powered load balancing fills calendars with optimal jobs, maximizing workshop revenue and productivity. Designed for shop owners who demand efficient, effortless scheduling tailored to their business.
Target Audience
Independent auto repair shop owners and managers (30-55) overwhelmed by manual scheduling, prioritizing operational efficiency.
Inspiration
One rainy Tuesday, I watched my friend nervously explain to an angry customer why their car couldn’t be seen—two no-shows and a double booking had left a bay empty, while another overflowed. As he scrambled through paper calendars and texts, I saw not just lost income but mounting stress. That chaos ignited the vision for an intelligent scheduling tool built just for independent shops.

User Personas

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

S

Scaling Scott

- Age 45 with three metropolitan repair shops - MBA in operations management - $2M annual revenue with 15% growth - 20 years automotive industry experience

Background

Started as technician, climbed to regional manager before launching first shop five years ago. Rapid growth caused scheduling chaos and idle bays. Seeks scalable automation to maintain quality as team doubles.

Needs & Pain Points

Needs

1. Guarantee consistent bay utilization across all locations 2. Reduce manual scheduling to free management time 3. Predict peak demand to staff technicians appropriately

Pain Points

1. Idle bays costing thousands every week 2. Overlapping appointments creating technician downtime conflicts 3. Manual schedule updates causing customer frustration

Psychographics

- Embraces rapid growth over cautious stability - Demands data-driven decisions at every turn - Values scalable systems that anticipate demand

Channels

1. LinkedIn professional network 2. Facebook Groups discussion forums 3. Email newsletters monthly digests 4. Automotive trade shows local events 5. Google Search targeted ads

F

Frugal Fiona

- Age 38, single-shop proprietor in suburban town - Vocational auto technician certification - $500K annual revenue on tight margins - Four-person staff team

Background

Family-owned roots taught thrift; invested savings into own workshop three years ago. Tight margins force manual scheduling and constant spreadsheets. Seeks affordable automation for smoother bookings.

Needs & Pain Points

Needs

1. Affordable scheduling with clear pricing and ROI 2. Simplified tools requiring minimal training investment 3. Fast set-up eliminating ongoing consultancy expenses

Pain Points

1. Surprises from hidden software subscription fees 2. Time-consuming manual spreadsheet updates daily 3. Missed appointments when juggling low-tech reminders

Psychographics

- Prioritizes cost savings over premium features - Skeptical of hidden fees, demands transparency - Focuses on practical solutions, avoids over-engineering

Channels

1. Facebook Marketplace local listings 2. YouTube cost-saving tips videos 3. Local newspaper ads community edition 4. Email promotions discount offers 5. Google Ads budget bids

S

Skeptical Sam

- Age 52, veteran one-shop mechanic-turned-owner - High school diploma with 30 years experience - $750K annual revenue and five technicians - Limited exposure to cloud-based tools

Background

Grew roots as apprentice in family garage, built reputation on personal oversight. Previous tech investments failed, causing data loss. Now cautiously explores new solutions.

Needs & Pain Points

Needs

1. Transparent scheduling logic with clear audit trails 2. Reliable fallback to manual scheduling anytime 3. Easy comparison of AI suggestions with personal data

Pain Points

1. Black-box AI triggers uncomfortable distrust 2. Occasional data sync errors break trust 3. Forced AI overrides conflict with experience

Psychographics

- Values personal oversight above automated processes - Distrusts opaque algorithms without clear logic - Prefers proven methods over untested innovations

Channels

1. Industry forums technician discussions 2. DIY repair blogs practical reviews 3. Email newsletters vendor testimonials 4. Local meetups in-person events 5. LinkedIn messages peer endorsements

D

Digital Dana

- Age 30, owner of tech-forward city shop - Bachelor degree in IT management - $1.2M annual revenue with 20% growth - Five-person team comfortable with SaaS

Background

Built career in IT before launching auto shop, championed CRM and diagnostic integrations. Early adopter of cloud systems but struggled with disjointed scheduling tools until discovering AI-driven solutions.

Needs & Pain Points

Needs

1. Deep API integrations with existing software suite 2. Customizable workflows aligning with unique processes 3. Real-time analytics dashboard for performance insights

Pain Points

1. Fragmented systems causing data silos daily 2. Rigid software blocking custom adaptation 3. Slow API responses delaying scheduling updates

Psychographics

- Seeks elegant integrations across all platforms - Loves automating repetitive manual tasks - Prefers cloud-native solutions with open APIs - Driven by data transparency and customization

Channels

1. Slack communities tech-savvy groups 2. GitHub open-source integrations 3. Tech podcasts weekly episodes 4. LinkedIn InMail professional outreach 5. Industry webinars product deep-dives

Product Features

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

Idle Insight Dashboard

Provides a real-time visual map of bay statuses, using color-coding to highlight idle bays instantly. Managers can see which bays are free at a glance, enabling quicker decisions to reassign tasks and maximize utilization.

Requirements

Live Bay Status Feed
"As a shop manager, I want to see live updates of each bay’s status so that I can make immediate operational decisions and reduce idle time."
Description

Implement a continuous data stream that captures and displays the real-time status of each service bay, including occupancy, job stage, and assigned technician. The feed integrates directly with the scheduling engine and job management system to ensure instantaneous updates on the dashboard as bay conditions change.

Acceptance Criteria
Real-Time Occupancy Update
Given a bay status change occurs in the job management system When the status stream sends the update Then the Idle Insight Dashboard reflects the new occupancy state within 2 seconds
Job Stage Indicator Accuracy
Given a technician advances a job stage in the scheduling engine When the update is processed Then the dashboard displays the correct stage color-coded indicator for the affected bay within 3 seconds
Technician Assignment Display
Given a technician is assigned or reassigned to a bay When the assignment is saved in the system Then the dashboard shows the correct technician name and avatar next to the bay in real-time
Handling Data Stream Interruptions
Given a temporary disruption in the data stream When the system reconnects within 5 seconds Then no data updates are missed and the dashboard resumes normal real-time updates without manual refresh
High Volume Update Performance
Given simultaneous status changes in more than 10 bays When the system processes updates Then the dashboard updates all affected bays within 5 seconds without performance degradation
Color-Coded Status Mapping
"As a shop manager, I want bay statuses color-coded on the dashboard so that I can quickly spot idle bays and optimize resource allocation."
Description

Introduce a standardized color scheme to visually differentiate bay states (e.g., green for active, yellow for pending, red for idle). This feature overlays color indicators on the dashboard map, allowing managers to identify idle bays at a glance and prioritize work reassignment.

Acceptance Criteria
Dashboard Bay Status Color Assignment
Given the dashboard is displayed with bay status data loaded, when a bay status equals active, pending, or idle, then the corresponding map indicator color matches green (#00FF00), yellow (#FFFF00), or red (#FF0000) respectively.
Real-Time Status Update Color Change
Given a bay status changes from one state to another, when the change occurs, then the color indicator on the dashboard updates within two seconds to reflect the new status.
Color Legend Display Verification
Given the dashboard is viewed, then a legend is displayed that clearly labels each status color with its corresponding state name, and the legend is visible and legible without scrolling.
High Contrast Color Accessibility
Given a user with color vision deficiency applies WCAG 2.1 AA contrast settings, then each status color indicator and legend entry maintain a contrast ratio of at least 4.5:1 against the background.
Multiple Status State Override Check
Given conflicting status inputs for a bay (e.g., pending and active), when the dashboard processes the input, then the bay displays the color corresponding to the highest priority state (active > pending > idle).
Idle Bay Alert Notifications
"As a shop manager, I want to receive alerts when a bay is idle too long so that I can reassign jobs quickly and maintain productivity."
Description

Configure threshold-based alert rules that trigger notifications when a bay remains idle beyond a predefined duration. Alerts can be delivered via in-app notifications, SMS, or email, prompting managers to take action and assign new tasks promptly.

Acceptance Criteria
In-App Idle Bay Alert Triggered
Given a bay has been idle longer than the configured threshold When the system checks bay statuses Then an in-app notification is generated for the manager within 5 seconds of threshold breach
SMS Idle Bay Alert Triggered
Given a bay remains idle beyond the threshold When alerts via SMS are enabled Then a text message containing bay ID and idle duration is sent to the manager’s registered phone number within 10 seconds
Email Idle Bay Alert Triggered
Given the idle duration exceeds the threshold When email alerts are configured Then an email with bay status and idle time is delivered to the manager’s inbox within 30 seconds
Custom Idle Duration Threshold Configuration
Given the manager accesses alert settings When they set a new idle duration threshold value and save changes Then the system persists the new threshold and applies it on subsequent idle checks
Alert Acknowledgement Logging
Given the manager acknowledges an idle bay alert When the acknowledgment action is taken in-app Then the system logs the timestamp, user ID, and bay ID in the audit trail
Utilization Historical Trends
"As a shop manager, I want historical bay utilization reports so that I can understand usage patterns and plan resources more effectively."
Description

Provide access to historical utilization data and trends for each bay, visualized through graphs and heat maps. This feature enables managers to analyze peak busy periods, identify recurring idle patterns, and make data-driven staffing and scheduling decisions.

Acceptance Criteria
Historical Graph Visualization
Given the shop manager selects a bay and date range, when the system retrieves historical utilization data, then display an interactive line chart showing daily utilization percentages over the period; chart must load within 2 seconds; axes labeled clearly; data points clickable to view exact values.
Peak Hour Heatmap Analysis
Given the shop manager views the utilization heatmap for a selected week, when data is fetched, then display a color-coded matrix indicating average hourly utilization per bay with defined thresholds (green ≥75%, yellow 50–74%, red <50%); heatmap must render within 3 seconds.
Idle Pattern Data Export
Given the shop manager requests an export of historical utilization for a bay and period, when export is triggered, then generate a CSV file containing date, total operating hours, idle hours, and utilization percentage for each day; file download must complete within 5 seconds.
Comparative Trends Between Bays
Given the shop manager selects two or more bays and a date range, when the system loads comparative data, then display overlaid line charts for each bay with distinct colors; include a legend; allow toggling visibility of individual bay series; chart exportable as PNG within 4 seconds.
Historical Data Persistence Verification
Given the shop manager requests utilization data older than 12 months, when data retrieval runs, then return archived data up to 24 months with accuracy matching stored records; response must complete within 4 seconds; data verified against master log.
Custom Filter and Drill-Down Controls
"As a shop manager, I want to filter the dashboard by technician and job type so that I can focus on specific areas of operations."
Description

Offer interactive filters and drill-down capabilities allowing users to refine the dashboard view by technician, vehicle type, job category, and time frame. Filters dynamically update the map to display only relevant bays, aiding targeted decision-making.

Acceptance Criteria
Filter by Technician to Highlight Assigned Bays
Given the Idle Insight Dashboard is displayed When the user selects technician "John Doe" from the technician filter Then only bays assigned to jobs by "John Doe" are displayed on the map, and all other bays are hidden Given the technician filter is applied When the user selects a different technician Then the map updates within 2 seconds to reflect bays for the newly selected technician Given the technician filter is active When the user clears the technician filter Then all bays reappear on the map
Filter by Vehicle Type to View Relevant Bays
Given the Idle Insight Dashboard is displayed When the user selects vehicle type "SUV" from the vehicle type filter Then only bays with jobs classified as "SUV" are shown on the map, and others are hidden Given the vehicle type filter is active When the user applies an additional filter (e.g., technician) Then the map displays bays that satisfy both filters simultaneously within 3 seconds Given the vehicle type filter is active When the user removes the vehicle type filter Then the map returns to displaying bays for all vehicle types
Filter by Job Category for Targeted Bay Status
Given the Idle Insight Dashboard is displayed When the user selects "Engine Repair" in the job category filter Then the map highlights only bays currently handling engine repair tasks Given the job category filter is applied When no bays match the selected job category Then a message "No bays found for the selected job category" is displayed
Filter by Time Frame for Specific Shift Analysis
Given the Idle Insight Dashboard is displayed When the user selects the time frame "8:00 AM - 12:00 PM" in the time frame filter Then only bays with jobs scheduled within that interval are displayed on the map Given the time frame filter is active When the user adjusts the time range to overlap existing bookings Then the map updates within 2 seconds to reflect bays with jobs in the new range
Combined Filters for Multi-Dimensional View
Given the Idle Insight Dashboard is displayed When the user selects technician "Jane Smith", vehicle type "Truck", and job category "Brakes" simultaneously Then only bays matching all three selected criteria are displayed on the map Given combined filters are active When the user resets one of the filters Then the map updates to reflect the remaining active filters within 2 seconds

Custom Idle Rules

Allows shops to set tailored idle thresholds for different bay types, technicians, or times of day. This flexibility ensures alerts align with shop norms, preventing false alarms and focusing attention where it’s needed most.

Requirements

Idle Rule Configuration Interface
"As a shop manager, I want to configure custom idle thresholds for each bay type and technician so that alerts reflect my shop’s operational standards and reduce false alarms."
Description

Provide a dedicated interface within the PulseQueue dashboard that allows shop managers to define, edit, and delete custom idle thresholds. Users can select bay types, individual technicians, or specific time intervals and assign each a minimum idle duration before triggering an alert. The interface includes validation to prevent overlapping rules and offers presets based on common shop layouts, ensuring ease of setup and consistency across different shop profiles.

Acceptance Criteria
Creating a New Idle Rule
Given the manager is on the Idle Rule Configuration Interface and has selected bay type and time interval with a minimum idle duration, when they click Save, then the new idle rule is added to the list with the correct parameters and a success notification is displayed.
Editing an Existing Idle Rule
Given the manager opens an existing idle rule, when they modify the technician selection or idle duration and click Update, then the rule in the list is updated to reflect the changes and a confirmation message appears.
Deleting an Idle Rule
Given the manager views the list of custom idle rules, when they click Delete on a specific rule and confirm the action, then the rule is removed from the list and no longer triggers alerts.
Preventing Overlapping Idle Rules
Given the manager attempts to create or edit a rule that overlaps an existing rule for the same bay or technician and time interval, when they click Save, then the system blocks the action and displays an error message indicating the overlap.
Applying Preset Idle Rules
Given the manager selects a preset configuration from the presets menu, when they click Apply, then the corresponding set of idle rules is populated in the interface and highlighted for review before saving.
Rule Persistence and Retrieval API
"As a system administrator, I want the custom idle rules to be reliably saved and retrieved via API so that the scheduling engine always applies the latest thresholds for each shop."
Description

Implement backend endpoints to store custom idle rules in the database and retrieve them efficiently. The API ensures rules are versioned and tied to the shop profile, supporting rollback and audit logs. It also secures access by enforcing shop-level permissions and includes rate limiting to maintain system performance under high request volumes.

Acceptance Criteria
Save Custom Idle Rule
Given a valid shop ID and custom idle rule payload, when a POST request is made to /api/shops/{shopId}/idle-rules, then the system persists the rule in the database with version set to 1 and ties it to the specified shop profile, and returns HTTP 201 Created with the rule ID in the response body.
Retrieve Custom Idle Rules
Given a shop with existing idle rules, when a GET request is made to /api/shops/{shopId}/idle-rules, then the system returns HTTP 200 OK with a JSON array of all rules for that shop, sorted by version in descending order, including rule details and metadata.
Version Rollback for Idle Rule
Given an existing idle rule with multiple versions, when a POST request is made to /api/shops/{shopId}/idle-rules/{ruleId}/rollback with a target version number, then the system creates a new version identical to the target version, updates the active version pointer, and returns HTTP 200 OK with the new version details.
Audit Log for Idle Rule Changes
Given any create, update, or rollback operation on idle rules, when the operation completes, then the system writes an audit log entry capturing the shop ID, user ID, timestamp, operation type, and change details, and makes logs queryable via /api/shops/{shopId}/audit-logs.
Unauthorized Access Prevention
Given an API request with invalid or unauthorized credentials, when attempting to access any /api/shops/{shopId}/idle-rules endpoint, then the system returns HTTP 403 Forbidden and ensures no rule data is exposed or modified.
Enhanced Idle Monitoring Engine
"As an operations analyst, I want the monitoring engine to apply shop-specific idle rules so that alerts are accurate and reflect individual shop configurations."
Description

Extend the existing idle monitoring engine to consume custom thresholds during runtime. The enhancement applies the appropriate rule set based on bay type, technician assignment, and current time segment. It calculates idle durations in real time, compares against thresholds, and flags bays that exceed allowable idle periods. The engine logs events for analytics and supports horizontal scaling to handle multiple shops concurrently.

Acceptance Criteria
Apply Custom Thresholds by Bay Type
Given custom idle thresholds are configured per bay type, When a bay of a specific type exceeds its threshold by one minute, Then the engine flags an idle alert for that bay type and records the event
Technician-Specific Idle Threshold Application
Given technicians have individual idle thresholds assigned, When a technician’s bay remains idle beyond that technician’s threshold, Then the system generates an idle alert tagged with the technician’s ID
Time-Segment Based Threshold Evaluation
Given different time segments have distinct thresholds configured, When a bay exceeds its threshold during a defined time segment, Then an idle event is triggered and classified under the correct time segment
Real-Time Idle Detection and Alerting
Given the engine processes idle durations continuously, When a bay crosses its configured threshold, Then the engine generates an alert within five seconds and pushes it to both the dashboard and SMS queue
Event Logging for Analytics
Given an idle event is detected, When the event is logged, Then the log entry includes bay ID, technician ID, applied threshold, actual idle duration, timestamp, and is persisted to the analytics store
Contextual Alert Filtering
"As a technician, I want to receive alerts only when bays I’m responsible for exceed my defined idle threshold so that I’m notified about genuine issues without noise."
Description

Develop a filtering mechanism that uses custom idle rules to suppress or trigger alerts. The system sends SMS or in-app notifications only when a bay’s idle time exceeds its configured threshold. Users can adjust alert sensitivity per rule and opt in or out of notifications for specific technicians or time blocks, ensuring that alerts remain relevant and actionable.

Acceptance Criteria
Alert Trigger When Idle Time Exceeds Configured Threshold
Given a bay with a custom idle threshold of 30 minutes, when the bay remains idle for 30 minutes or more, then the system sends an SMS and an in-app alert to the user.
No Alert When Idle Time Is Below Configured Threshold
Given a bay with a custom idle threshold of 45 minutes, when the bay’s idle time is 44 minutes or less, then the system does not send any SMS or in-app notifications.
User Opt-Out for Specific Technician
Given Technician Jane is opted out of notifications, when any bay assigned to Jane exceeds its idle threshold, then the system suppresses SMS and in-app alerts for Jane.
Time Block Notification Suppression
Given notifications are disabled between 10:00 PM and 6:00 AM, when a bay exceeds its idle threshold during that time block, then the system does not send any SMS or in-app alerts.
Alert Sensitivity Adjustment Application
Given alert sensitivity is set to 'Low' for a bay with a 20-minute threshold, when the bay’s idle time reaches 25 minutes, then the system sends an SMS and an in-app alert; if the idle time is between 20 and 24 minutes, no alert is sent.
Time-Based Rule Scheduling
"As a shop manager, I want different idle thresholds for peak and off-peak hours so that alerts align with varying workload demands throughout the day."
Description

Allow shops to define time-bound rule overrides, such as different idle thresholds during peak hours, lunch breaks, or overnight shifts. The system schedules these overrides automatically, switching thresholds at configured times and reverting afterward. It visualizes active time blocks on a calendar view and alerts users when upcoming transitions are about to occur.

Acceptance Criteria
Peak Hours Threshold Override Activation
Given a time-based rule override is configured to start at 17:00 with an idle threshold of 10 minutes; When system clock reaches 17:00; Then the idle threshold is automatically updated to 10 minutes; And a UI banner confirms "Peak hours threshold active"; And the override activation is logged in the system audit trail with timestamp.
Lunch Break Threshold Reversion
Given a lunch break override is configured from 12:00 to 13:00 with an idle threshold of 5 minutes; When system clock reaches 13:00; Then the idle threshold reverts to the default value; And the UI reflects the reverted threshold; And the reversion event is recorded in the audit log.
Overnight Shift Threshold Scheduling
Given an overnight override configured from 22:00 to 06:00 with an idle threshold of 20 minutes; When system clock crosses midnight; Then the override remains active across the date boundary; When system clock reaches 06:00; Then the threshold resets to the standard daytime value; And both activation and reversion are logged.
Visual Calendar Highlight of Active Overrides
Given multiple time-based overrides are configured for the week; When viewing the Time-Based Rule Scheduling calendar; Then each override period is displayed as a colored block spanning its start and end times; And hovering or clicking on a block displays details including threshold value and time range.
Alert Notification for Upcoming Transition
Given a transition (start or end of an override) is scheduled within the next 5 minutes; When system clock is 5 minutes before the transition; Then the system sends an in-app notification and SMS to subscribed users; And the notification includes the transition type, time, and threshold values; And users can acknowledge receipt.

Auto-Fill Suggestion

Analyzes current bookings and waitlisted customers to propose or automatically assign suitable jobs into idle bays. By recommending high-priority or quick-turnaround appointments, it minimizes downtime and drives additional revenue.

Requirements

Idle Bay Availability Detector
"As a shop manager, I want the system to detect idle service bays so that I can maximize bay utilization and reduce downtime."
Description

Continuously monitors the shop’s service bay schedule and detects unoccupied or idle bays in real time. Integrates with the booking database and calendar module to identify gaps where no appointments are scheduled. This detection enables the system to pinpoint downtime opportunities and feed accurate availability data to the auto-fill suggestion engine, optimizing bay utilization and reducing revenue loss from empty slots.

Acceptance Criteria
Continuous Bay Monitoring
Given the system is running during shop operating hours, when no appointment is scheduled for a bay within the next 60 minutes, then the system logs the bay as idle within 1 minute of detection.
Immediate Cancellation Response
Given a customer cancels a scheduled appointment, when the cancellation is recorded in the booking database, then the detector updates the bay status to idle within 30 seconds and pushes availability to the auto-fill engine.
Cross-Module Integration Verification
Given new appointments are added or modified in the calendar module, when synchronization occurs, then the Idle Bay Availability Detector reflects changes in bay occupancy within 2 minutes and no discrepancies exist between calendar and detector data.
Idle Bay Reporting
Given the detector identifies idle bays, when hourly reports are generated, then the report lists all idle bays with start and end times of idle periods and accuracy matches live bay data at 100%.
High-Load Performance
Given peak shop traffic with 50 concurrent bookings, when the detector runs its cycle, then idle bay detection completes within 15 seconds without system errors and CPU usage remains below 75%.
Waitlist Customer Prioritization
"As a shop manager, I want the system to prioritize waitlisted customers based on urgency and history so that high-value jobs are scheduled promptly."
Description

Analyzes the current waitlisted customers by evaluating service urgency, customer loyalty status, historical service duration, and requested booking windows. Integrates with the CRM, waitlist queue, and service history databases to rank customers, ensuring high-value or quick-turnaround jobs are identified first. This prioritization drives targeted scheduling proposals, boosting revenue and customer satisfaction.

Acceptance Criteria
High-Urgency Service Request Prioritization
Given a mix of waitlisted customers with varying urgencies, when the prioritization algorithm runs, then customers with a defined high-urgency flag must occupy the top 10% positions in the ranked list and receive scheduling proposals within 1 hour of addition.
VIP Customer Loyalty Prioritization
Given customers on the waitlist with loyalty status Tier 1 or higher, when the system evaluates loyalty during prioritization, then these VIP customers must be placed in the top 20% of the ranked queue and flagged for immediate scheduling within 24 hours.
Quick-Turnaround Service Slot Recommendation
Given historical service durations in the database, when an idle bay slot appears with at least 60 minutes available, then the system must recommend waitlisted services with average durations ≤60 minutes for at least 80% of those idle slots.
Requested Booking Window Compliance
Given a waitlisted customer’s requested booking window, when the prioritization process assigns a rank, then the proposed appointment for that customer must fall within their requested time window or provide at least two viable alternative slots.
Peak Hour Load Balancing
Given peak business hours defined as 08:00–11:00, when more than 5% of waitlist customers exceed a 6-hour wait, then the system must automatically promote quick-turnaround or high-value services to redistribute load and reduce average wait time below 6 hours.
Auto-Fill Suggestion Generator
"As a shop manager, I want to receive automated suggestions for appointments to fill idle bays so that I can quickly accept the best scheduling options and increase revenue."
Description

Matches detected idle bay slots with prioritized waitlist entries using an AI-powered algorithm that considers load balancing, service duration estimates, required technician skill sets, and shop throughput targets. Generates a ranked list of top suggestions for each idle window, complete with confidence scores and expected revenue impact. This automated engine simplifies decision-making and accelerates booking of optimal appointments.

Acceptance Criteria
Idle Bay Optimization for Quick-Turnaround Jobs
Given an idle bay slot of at least 60 minutes exists, when the generator runs, then it returns the top three waitlist entries with estimated durations ≤60 minutes, ranked by shortest duration, with confidence scores calculated and displayed within 5 seconds.
Load Balancing Across Technicians
Given multiple idle bay slots and a mixed-skill waitlist, when suggestions are generated, then the system distributes appointments evenly across available technicians, ensuring no single technician’s load exceeds 20% above the shop average, with load metrics visible.
Skillset Matching for Specialized Services
Given a waitlist entry requiring a specialized skill, when matching to idle bays, then the suggestion engine only recommends technicians with the required certification, displaying the technician’s skill match and confidence score for each suggestion.
Revenue Impact Projection Display
Given a ranked list of suggestions, when viewing the suggestions, then each entry shows estimated revenue impact based on service fees and expected add-on work, and the total projected revenue uplift is displayed.
Manual Override of Auto-Fill Suggestions
Given auto-fill suggestions are generated, when a manager selects a different waitlist entry manually, then the system records the override decision, updates the schedule accordingly, and logs the action with timestamp and user ID.
Manager Approval Interface
"As a shop manager, I want to review and approve auto-fill suggestions before they are scheduled so that I maintain control over bookings."
Description

Provides an interactive interface within the dashboard where managers can review, accept, decline, or modify auto-fill suggestions before final scheduling. Captures manager feedback and decisions to refine future AI suggestions. Ensures human oversight by allowing manual adjustments to proposed appointments, maintaining scheduling control and flexibility.

Acceptance Criteria
Manager Reviews Auto-Fill Suggestions
Given the manager is logged into the dashboard and there are pending auto-fill suggestions, when the suggestions panel loads, then each suggestion displays the job type, customer name, estimated duration, proposed time slot, and actionable buttons for Accept, Decline, or Modify.
Manager Accepts Auto-Fill Suggestion
Given a specific auto-fill suggestion is displayed, when the manager clicks Accept on the suggestion, then the appointment is scheduled in the system at the proposed time and bay, the suggestion is removed from the pending list, and a confirmation notification appears.
Manager Declines Auto-Fill Suggestion
Given a specific auto-fill suggestion is displayed, when the manager clicks Decline on the suggestion, then the suggestion is removed from the pending list, no appointment is scheduled, and an optional feedback input appears for the manager to provide a reason.
Manager Modifies Auto-Fill Suggestion
Given a specific auto-fill suggestion is displayed, when the manager clicks Modify, then an editable form pre-populated with the suggestion details appears, and upon saving changes, the appointment is scheduled with the updated details, and a confirmation notification appears.
Manager Provides Feedback for Declined or Modified Suggestions
Given the manager has declined or modified a suggestion, when prompted for feedback, then the manager can submit feedback which is stored and associated with the original suggestion in the system.
Automated Confirmation & Notification
"As a customer, I want to receive instant appointment confirmations and reminders when my service is scheduled so that I can plan accordingly and avoid missing my slot."
Description

Automatically updates the scheduling calendar upon manager approval or auto-approval based on policy and triggers real-time SMS notifications to customers with appointment details and reminder messages. Integrates with the messaging service and calendar sync module to ensure consistency across systems. This automation reduces no-shows, enhances customer experience, and keeps the schedule current.

Acceptance Criteria
Manager-Triggered Confirmation
Given a manager manually approves an appointment in the scheduling dashboard When the approval is confirmed by the system Then the appointment is added to the scheduling calendar and an SMS confirmation with appointment details is sent to the customer
Auto-Approval Based on Policy
Given a new booking that satisfies the auto-approval policy (e.g., trusted customer or low-risk service) When the system processes the booking Then the appointment is automatically approved, added to the calendar, and an SMS notification is sent without any manager intervention
Real-Time SMS Notification Dispatch
Given an approved appointment (manual or auto) When the system triggers the SMS notification Then the message is delivered to the customer’s phone within 5 seconds and delivery confirmation is received from the messaging service
Calendar Sync Consistency
Given an updated appointment status or time When the calendar sync module runs Then the primary scheduling calendar and all integrated external calendars reflect the same appointment details within 1 minute
Scheduled SMS Reminder Delivery
Given an upcoming appointment 24 hours away When the system’s reminder scheduler triggers Then an SMS reminder containing appointment date, time, and location is sent to the customer exactly 24 hours before the appointment

Escalation Path

Implements a multi-tier notification system that escalates idle alerts over time—from in-app notifications to SMS and email reminders. This guarantees that persistent idle periods receive proper attention until resolved.

Requirements

Idle Period Detection
"As a shop manager, I want the system to automatically detect when a bay has been idle for too long so that I can reassign or optimize bookings without manual oversight."
Description

Implement a monitoring system that continuously tracks appointment statuses and identifies idle periods when bays remain unused for a configurable threshold. This component must integrate with the existing scheduling engine, leveraging real-time calendar data to detect inactivity and raise the initial tier of alerts.

Acceptance Criteria
Idle Bay Exceeds Configured Threshold
Given a bay remains unused for longer than the configured threshold, when the monitoring system evaluates calendar data, then an idle period alert is generated within 1 minute of the threshold breach.
Threshold Configuration Update Applied
Given an administrator updates the idle period threshold, when the new threshold is saved, then the monitoring system applies the updated threshold to subsequent idle evaluations within 5 minutes.
Integration with Scheduling Engine
Given the scheduling engine updates appointment statuses in real time, when a bay booking is confirmed or ends, then the monitoring system reflects the change within 30 seconds.
Initial Alert Notification Sent
Given an idle period is detected, when an initial alert is triggered, then an in-app notification is sent to the assigned manager’s dashboard and appears within 2 minutes.
No False Positives During Back-to-Back Appointments
Given back-to-back appointments in a bay, when one appointment ends within 1 minute and the next begins, then no idle period alert is generated.
Notification Tier Configuration
"As an administrator, I want to customize escalation channels and timings so that alerts align with our shop’s communication policies and urgency levels."
Description

Develop an interface allowing administrators to configure multiple alert tiers, specifying channels (in-app, SMS, email), escalation intervals, recipients, and message templates. This ensures flexibility in tailoring escalation paths to the shop’s operational requirements and communication preferences.

Acceptance Criteria
Add Alert Tier
Given the administrator is on the Notification Tier Configuration page When the administrator clicks 'Add Tier' and fills in the tier name, selects channels, sets recipients, defines escalation interval, and chooses a message template Then the new alert tier is saved, displayed in the tier list with correct settings, and persists after page refresh
Edit Alert Tier
Given an existing alert tier is listed When the administrator selects the tier and updates channels, escalation interval, recipients or message template then saves changes Then the tier list reflects updated settings and changes persist after logout and login
Delete Alert Tier
Given one or more alert tiers exist When the administrator selects a tier and clicks 'Delete' and confirms the action Then the tier is removed from the list and no longer triggers notifications
Configure Escalation Interval
Given the administrator is configuring a tier When the administrator sets an escalation interval below minimum or above maximum allowed values Then the interface displays a validation error and prevents saving until a valid interval is entered
Select Notification Channels
Given the administrator configures channels for a tier When the administrator selects or deselects in-app, SMS, and email options Then the selected channels are accurately saved and notifications are sent only via those channels during escalation
Set Message Template
Given the administrator is defining message templates for a tier When the administrator enters template text with placeholders for shop name, alert details, and tier level and previews the message Then the preview correctly replaces placeholders with sample data and the template saves without errors
Notification Dispatch Engine
"As a system operator, I want notifications to reliably dispatch across selected channels with automatic retries so that no critical alerts are lost."
Description

Build a robust engine responsible for sending notifications through the configured channels. It should handle queueing, channel-specific formatting, retry logic for failed deliveries, and logging for audit and troubleshooting purposes.

Acceptance Criteria
Queued Notification Processing
Given a new notification is created in the system When the dispatch engine runs Then the notification is placed into the queue with correct timestamp, channel metadata, and unique identifier
Channel-Specific Formatting
Given a notification targeting SMS, email, or in-app channel When the engine formats the message Then the content uses the correct channel template, personalizes all placeholders, and adheres to channel-specific constraints (e.g., SMS character limit)
Retry Logic on Failure
Given a notification delivery failure due to network or server error When the engine attempts delivery Then it retries up to 3 times using exponential backoff and records each retry attempt
Notification Logging and Auditing
Given any notification dispatch attempt When processing completes Then the engine logs a record with timestamp, channel, recipient ID, delivery status, and error details for audit and troubleshooting
High Volume Throttling
Given a surge of notifications exceeding the configured rate limit When the engine dispatches messages Then it enforces per-channel rate limits, queues excess messages, and processes them once capacity frees up
Escalation Timing Rules
"As a shop owner, I want alert escalations to follow defined timing rules so that I receive reminders at sensible intervals without overwhelming my staff."
Description

Define and implement rules governing the timing between escalation tiers, including base thresholds, exponential backoffs, and maximum escalation limits. This ensures alerts are paced appropriately to avoid spamming users while maintaining urgency for unresolved issues.

Acceptance Criteria
Initial Idle Alert Escalation Timing
Given a repair bay remains idle for the base threshold time (e.g., 15 minutes), when the threshold is reached, then the system must send an in-app idle alert to the assigned manager within 1 minute.
Exponential Backoff Interval Verification
Given the base idle alert has been sent, when the bay continues idle past subsequent intervals, then the system must send escalated notifications (SMS, then email) at doubled intervals (e.g., 30, 60, 120 minutes) up to the maximum limit.
Maximum Escalation Limit Enforcement
Given multiple escalations have been sent, when the escalation count reaches the configured maximum (e.g., 4 alerts), then the system must stop further notifications and log a “Maximum Escalation Reached” event.
Acknowledgement Resets Escalation Timer
Given a manager acknowledges an idle alert via any channel, when the acknowledgement is recorded, then the escalation timer must reset to the base threshold and suppress further alerts for the current idle period.
High-Priority Bay Escalation Adjustment
Given a bay is marked as high priority, when idle alerts are initiated, then the system must apply a reduced base threshold (e.g., 10 minutes) and halved exponential backoff intervals compared to standard bays.
User Acknowledgement Tracking
"As a technician, I want to acknowledge received alerts so that the system stops sending further notifications once I’m addressing the issue."
Description

Create functionality to track when recipients acknowledge or dismiss alerts, halting further escalations for that idle event. This includes recording acknowledgment timestamps, user identifiers, and integrating with the dashboard to display resolution status.

Acceptance Criteria
User Acknowledges Alert via In-App Notification
Given an idle event alert is sent and displayed in the in-app notification center, when the user taps “Acknowledge”, then the system records an acknowledgment timestamp and user identifier, stops any further escalations for that idle event, and updates the alert status to “Acknowledged” in the dashboard.
User Dismisses Alert via SMS Link
Given an idle event alert escalated via SMS containing a dismissal link, when the user clicks “Dismiss” in the SMS, then the system captures the dismissal timestamp and user phone number, halts all further notifications for that event, and marks the event as “Dismissed” on the dashboard.
Acknowledgment Displayed in Dashboard
Given an alert has been acknowledged or dismissed, when a manager views the dashboard, then the alert record displays the correct resolution status, timestamp, and user identifier, and no further escalations are scheduled.
Duplicate Acknowledgment Prevention
Given an alert has already been acknowledged, when the same user or another user attempts to acknowledge or dismiss that alert again, then the system prevents duplicate acknowledgment entries and displays a notification indicating the event has already been resolved.
Failed Acknowledgment Logging
Given a network or server error occurs during acknowledgment, when the user tries to acknowledge or dismiss the alert, then the system logs the failure event, retries the operation up to three times, and if the issue persists, flags the alert for manual review and notifies the operations team.

Waitlist Reachout

Integrates with the shop’s customer database to automatically send targeted SMS or email offers to waitlisted customers when a bay becomes idle. This feature boosts fill rates by providing instant rebooking options.

Requirements

Database Synchronization
"As a shop manager, I want the system to automatically sync waitlist entries and bay statuses so that I always have up-to-date information without manual updates."
Description

Ensure seamless integration between PulseQueue and the shop’s customer database to access and update waitlist statuses in real time. This includes bi-directional data flow for customer contact details, appointment history, and bay availability, with robust error handling to maintain data integrity and prevent synchronization delays.

Acceptance Criteria
Real-time Waitlist Status Update
Given a customer is added to the waitlist in the shop database, when PulseQueue synchronization runs, then the new waitlist entry is reflected in PulseQueue within 30 seconds; and given a customer is removed from the waitlist in PulseQueue, the change propagates back to the shop database within 30 seconds.
Bi-directional Contact Detail Sync
Given a customer's contact details are updated in PulseQueue, when the sync process completes, then the shop database contact details match exactly; and given contact details are updated in the shop database, the updates appear in PulseQueue unchanged within 30 seconds.
Appointment History Consistency Check
Given existing appointment history records in both systems, when a synchronization occurs, then all records for the past 12 months are identical in PulseQueue and the shop database with no missing or duplicated entries.
Bay Availability Synchronization
Given a bay status (available or occupied) changes in the shop’s system, when the synchronization runs, then PulseQueue reflects the updated status within 15 seconds to ensure accurate scheduling.
Error Handling on Sync Failure
Given a network or database error during synchronization, when the error occurs, then the system logs the error with timestamp and context, retries synchronization up to 3 times automatically, and sends an alert notification to the system administrator.
Idle Bay Detection
"As a service advisor, I want the system to detect and notify me when a bay goes idle so that I can quickly offer it to waiting customers."
Description

Implement a monitoring mechanism that continuously evaluates bay utilization and flags idle bays as soon as they become available. The system must support configurable thresholds (e.g., idle time of 5 minutes) and trigger events that drive the waitlist reach-out workflow.

Acceptance Criteria
Idle Bay Threshold Reached
Given a repair bay has been unoccupied for a continuous period equal to the configured idle threshold, when the threshold is exceeded, then the system must flag the bay as idle and publish an idleBayDetected event to the message queue within 10 seconds.
Configurable Threshold Update
When an administrator updates the idle time threshold value in system settings, then the new threshold must be applied immediately to all subsequent bay utilization evaluations without requiring a system restart.
Real-time Idle Bay Event Triggered
Given active monitoring of multiple bays, when any bay becomes idle, then the system must trigger the waitlist reach-out workflow, sending a notification event containing the bay ID and timestamp within 5 seconds of detection.
Handling False Idle Signals
Given transient sensor interruptions shorter than the configured idle threshold, when occupancy signals resume before the threshold is reached, then the system must not flag the bay as idle.
Concurrent Bay Monitoring Under Load
When monitoring up to 50 bays simultaneously under peak usage, then the system must detect idle bays and emit events for each within the defined SLAs without performance degradation or missed detections.
Automated SMS/Email Dispatcher
"As a customer on the waitlist, I want to receive an immediate SMS or email offer when a bay opens so that I can rebook quickly and secure a slot."
Description

Develop an engine to send targeted SMS or email offers to waitlisted customers when a bay becomes idle. The dispatcher should handle template management, scheduling, retry logic for failed deliveries, and integrate with third-party messaging providers to ensure high deliverability.

Acceptance Criteria
Idle Bay Availability Trigger
Given a bay is marked idle in the system, when the dispatcher engine detects the idle state, then it must query the waitlist, select up to 3 customers by FIFO priority, and initiate offer messages to them within 30 seconds.
Offer Template Management
Given multiple offer templates exist for different services, when creating or editing templates, then the system must allow selecting service type, drafting message content with placeholders ([CustomerName], [BayType], [EstimatedStartTime]), and saving the template for future dispatch.
Message Scheduling
Given a target waitlisted customer and selected template, when dispatch is triggered, then the system must schedule the SMS or email respecting shop business hours (08:00–18:00), enforce a send rate limit of 5 messages per minute, and queue additional messages until limits reset.
Retry Logic on Delivery Failure
Given a message fails to deliver (provider callback error or timeout), when the failure is detected, then the engine must retry up to 3 times using exponential backoff intervals of 2, 4, and 8 minutes, log each attempt’s outcome, and mark the message as undeliverable after the final failed retry.
Delivery Confirmation Logging
Given a message is successfully delivered, when a delivery confirmation is received from the provider, then the system must log the timestamp, provider message ID, delivery status in the job record, and update the customer’s communication history.
Third-Party Provider Fallback
Given integration with multiple messaging providers, when the primary provider returns an error or is unresponsive for over 1 minute, then the dispatcher must automatically reroute the message through a secondary provider and raise an alert if neither provider succeeds.
Offer Personalization Engine
"As a repeat customer, I want offers that reflect my service history and preferences so that the proposition feels relevant and encourages me to rebook."
Description

Create a personalization layer that customizes offers based on customer profile, service history, and estimated repair duration. The engine should support dynamic content insertion (e.g., customer name, discount codes) and apply business rules to maximize acceptance rates.

Acceptance Criteria
Trigger Personalized Offer to Waitlisted Customer
Given a bay becomes idle and a customer is on the waitlist, when the personalization engine processes the waitlist, then an SMS or email offer is generated within 5 seconds, addressed with the customer's name and containing a valid rebooking link and discount code.
Dynamic Content Insertion Verification
Given a customer with profile data including name and service history, when generating an offer, then the offer message must include placeholders correctly replaced with customer name, last service date, recommended service type, and unique discount code.
Business Rule Compliance for Discount Codes
Given business rules specifying discount parameters, when generating discount codes, then codes must not exceed the maximum allowed discount percentage, must expire within 7 days, and must be unique per customer and per service.
Service History-Based Offer Customization
Given a customer's service history indicates prior brake service over 6 months ago, when the engine customizes offers, then the system offers a brake inspection discount and mentions the last service date in the message body.
Multi-Channel Offer Delivery
Given a customer's preferred communication channel is email or SMS, when sending the personalized offer, then the system delivers the message via the correct channel within 10 seconds of bay availability.
Edge Case: Missing Profile Data
Given a customer record missing certain profile fields, when generating an offer, then the system uses default placeholders or omits optional dynamic fields and logs a warning without failing the offer dispatch.
Response Tracking & Analytics
"As a shop owner, I want to see analytics on how many customers accept waitlist offers so that I can assess the feature’s effectiveness and improve scheduling efficiency."
Description

Implement tracking capabilities to capture customer responses, click-through rates, and booking conversions from waitlist offers. Provide a dashboard with real-time analytics and reports to measure campaign performance and optimize messaging strategies.

Acceptance Criteria
Idle Bay Triggered Waitlist Notification
Given an idle bay event and an existing waitlist with at least one customer, When the bay becomes idle, Then the system sends an SMS or email offer to the top five customers on the waitlist within 30 seconds.
Customer Response Tracking
Given a customer has received a waitlist offer, When the customer clicks the booking link or replies with a predefined keyword, Then the system logs the click-through or response event with customer ID and timestamp.
Booking Conversion Logging
Given a customer follows a waitlist offer link, When the customer completes a booking, Then the system associates the successful booking with the original offer ID and marks the offer as converted in the analytics database.
Real-Time Analytics Dashboard Update
Given any new response or booking event, When the event is recorded, Then the analytics dashboard updates response rate, click-through rate, and conversion rate metrics within five seconds.
Campaign Performance Report Generation
Given a manager requests a weekly campaign performance report, When the report is generated, Then the system exports a CSV or PDF containing total offers sent, response count, click-through count, conversion count, and rates, aggregated correctly for the selected week.
Compliance & Opt-Out Management
"As a compliance officer, I want customers to have a clear way to opt out of waitlist notifications so that we stay compliant with communication regulations."
Description

Incorporate features to manage customer communication preferences, including easy opt-out links in messages and adherence to SMS/email regulations. Ensure that do-not-contact lists are respected and updated in real time.

Acceptance Criteria
Opt-Out Link Presence
Given a waitlist reachout message is generated for a customer When the message content is assembled for sending via SMS or email Then the message includes a clear, visible, and functional opt-out link or keyword that allows the customer to unsubscribe
Opt-Out Processing and Confirmation
Given a customer clicks the opt-out link or sends the predefined keyword (e.g., STOP) When the system receives the opt-out request Then the customer’s communication preference is updated to do-not-contact and a confirmation message is sent acknowledging the unsubscription
Real-Time Do-Not-Contact Enforcement
Given a customer is added to the do-not-contact list When a waitlist reachout message is about to be sent Then the system checks the do-not-contact list in real time and blocks any messages to that customer
Regulatory Compliance Content
Given legal requirements for SMS and email communications When composing a waitlist reachout message Then the message includes the shop’s identification, sender information, compliance statements, and an opt-out mechanism in line with SMS and email regulations
Unsubscribe Audit Trail Logging
Given an opt-out or do-not-contact action is performed by a customer When the action is processed by the system Then an immutable audit log entry is created recording the customer ID, timestamp, communication channel, and action type

Idle Trend Forecast

Uses historical scheduling data to predict likely idle periods and recommend optimal timing for promotions or resource adjustments. By forecasting dips in bay usage, managers can proactively plan staffing and marketing efforts.

Requirements

Data Collection and Preprocessing
"As a system administrator, I want the scheduling data to be automatically aggregated and cleaned so that the idle trend forecasting engine has reliable and accurate input data for analysis."
Description

Automatically aggregate historical scheduling data from booking systems and SMS logs, clean and normalize the data by handling missing values and outliers, and store it in a time-series optimized datastore for efficient analysis and model training.

Acceptance Criteria
Historical Data Aggregation
Given that PulseQueue is connected to booking systems and SMS logs, when the data collection process runs, then all booking records and SMS logs from the past 24 months are fetched without errors.
Missing Value Handling
Given aggregated scheduling data with missing fields, when preprocessing runs, then missing values are imputed using median for numerical fields and 'Unknown' for categorical fields, and no nulls remain.
Outlier Detection and Treatment
Given scheduling entries with extreme duration values, when preprocessing runs, then outliers beyond 3 standard deviations are identified and capped at the 99th percentile, and a report of detected outliers is generated.
Time-Series Datastore Integration
Given preprocessed data, when data is loaded into the time-series optimized datastore, then ingestion completes within SLAs (under 5 minutes) and all data points are queryable by timestamp.
Data Integrity Verification
Given preprocessed time-series data stored, when querying random samples, then retrieved records match source data transformations with no discrepancies in timestamps and values.
Idle Period Detection Algorithm
"As a shop manager, I want the system to predict upcoming idle periods based on historical data so that I can proactively plan marketing or staffing actions."
Description

Implement a machine learning pipeline that analyzes preprocessed historical usage data to identify patterns of idle periods, incorporating time-based features such as day of week, seasonality, and holidays, and output predicted idle slots with confidence scores.

Acceptance Criteria
Data Ingestion Validation
Given historical usage data is available in the data lake When the pipeline ingests data Then the system successfully loads all records without errors and generates an ingestion summary report
Feature Engineering Accuracy
Given preprocessed data When feature generation runs Then day-of-week, seasonality, and holiday indicators are correctly computed for every record with at least 98% accuracy
Model Training Performance
Given the training dataset When model training completes Then the algorithm achieves a minimum of 85% accuracy on the validation set and logs all performance metrics
Prediction Output Format
Given new historical usage inputs When predictions are requested Then the system returns a JSON list of predicted idle slots with start_time, end_time, and confidence_score between 0 and 1
Holiday and Seasonality Handling
Given a request for a known holiday period When generating predictions Then the algorithm adjusts idle period forecasts based on holiday indicators, showing at least a 10% variation from non-holiday baseline
Forecast Visualization Dashboard
"As a shop manager, I want to view upcoming predicted idle periods on an interactive dashboard so that I can quickly assess availability and make scheduling decisions."
Description

Develop an interactive dashboard displaying predicted idle periods through visualizations like line graphs for utilization trends and a calendar view highlighting low-usage slots, with filters for date ranges and bay types, and support for data export.

Acceptance Criteria
Date Range Filter Application
Given the Forecast Visualization Dashboard is open, When the user selects a start and end date via the date picker, Then the line graph and calendar view update to display only data within the selected date range.
Bay Type Filter Selection
Given the Forecast Visualization Dashboard is open, When the user selects one or more bay types from the bay type filter dropdown, Then all visualizations refresh to include only data for the chosen bay types.
Idle Period Line Graph Rendering
Given predicted idle period data is available, When the dashboard loads, Then the line graph plots each day's predicted bay utilization percentage and visually highlights days below the idle threshold.
Calendar View Highlighting
Given predicted idle period data for the selected timeframe, When the calendar view is displayed, Then low-usage slots are distinctly colored, and hovering over any slot shows a tooltip with date, time, and predicted utilization.
Data Export Functionality
Given the user needs to share idle trend data, When the user clicks the export button and chooses CSV or PDF, Then the dashboard generates and downloads a file containing the current date range, bay types, and predicted utilization values in the chosen format.
Promotion Recommendation Engine
"As a marketing coordinator, I want the system to recommend promotional strategies for predicted idle periods so that I can increase bookings during low-demand times."
Description

Create a recommendation engine that leverages predicted idle periods to suggest tailored promotional strategies, such as discounts or service bundles, and integrate with SMS/email systems to schedule and send these promotions at optimal times.

Acceptance Criteria
Generate Idle Period Predictions
Given the system has at least six months of historical appointment data When the recommendation engine runs its forecast Then it produces a list of predicted idle periods for the next seven days with confidence scores above 80%
Recommend Tailored Promotions
Given predicted idle periods are available When the engine analyzes bay utilization and customer segments Then it generates at least three distinct promotion strategies (e.g., discounts, service bundles) for each idle period
Schedule Promotions for Delivery
Given the manager has approved a set of promotions When the engine schedules delivery Then it automatically queues SMS and email messages at optimal send times aligned with the start of each idle period
Manager Approval Workflow
Given promotion recommendations are generated When the manager views the recommendations Then they can approve, modify, or reject each recommendation and receive confirmation of their action
Track Promotion Performance
Given promotions have been sent When the idle period passes Then the system logs message delivery status and tracks conversion metrics (booking rate, revenue uplift) against baseline usage
Idle Alert Notification System
"As a shop manager, I want to receive timely notifications about upcoming idle periods so that I can take immediate action to fill those slots."
Description

Build a notification system that sends real-time alerts via SMS or in-app messages to managers ahead of predicted idle periods, including actionable recommendations for staffing adjustments or marketing actions.

Acceptance Criteria
SMS Alert for Imminent Idle Period
Given the system predicts an idle bay period at least 2 hours in advance, when the idle time window is confirmed, then an SMS alert containing the predicted idle interval and a recommended staffing adjustment must be sent to the manager’s mobile number within 5 minutes of prediction.
In-App Notification with Staffing Recommendation
Given the manager is logged into the PulseQueue app and a predicted idle period is within the next 4 hours, when the forecast is generated, then the app must display a notification with the idle time slot and an actionable staffing recommendation (e.g., call in technician, reschedule jobs).
Promotion Suggestion Alert
Given the system forecasts a low utilization period tomorrow, when marketing parameters are configured, then an alert must be sent (SMS or in-app) including a recommended promotion (e.g., 10% off oil change between 2–4pm) and a direct link to create the promotion in the app.
Manager Acknowledgement and Follow-Up
Given an alert has been delivered, when the manager taps ‘Acknowledge’ in the SMS link or in-app notification, then the system must log the acknowledgement, update the alert status to ‘Acknowledged’ in the dashboard, and send a confirmation message within 1 minute.
Notification Delivery Monitoring
Given alerts are dispatched via SMS and in-app channels, when the system attempts delivery, then it must log success or failure for each channel and retry failed SMS deliveries up to 2 times at 5-minute intervals.

SmartScheduler

AI-driven reminder timing that learns each customer’s responsiveness and sends SMS alerts at the optimal moment—boosting open rates and slashing no-shows further by aligning with individual behaviors.

Requirements

Behavioral Data Collection
"As a shop manager, I want the system to track each customer's past response behaviors so that the AI can learn optimal times to send reminders and reduce no-shows."
Description

The system must capture and store detailed customer interaction data, including response times to SMS reminders, engagement patterns across different times of day, and no-show occurrences. This data will feed into the AI-driven scheduler to enable personalized reminder timing. It integrates with existing messaging logs and customer records, ensuring seamless data flow and minimal performance impact.

Acceptance Criteria
Customer SMS Response Tracking
Given an SMS reminder is sent to a customer When the customer replies Then the system logs the reminder timestamp, response timestamp, and calculates response time with at least 1-second accuracy
Engagement Pattern Recording
Given varying times of day for SMS reminders When reminders are sent at each hour interval Then the system records customer interactions and timestamps across all time slots for at least 90% of sent messages
No-Show Event Logging
Given an appointment slot has ended without a customer check-in When the no-show threshold time passes Then the system logs a no-show event and associates it with the customer record with no data loss
Data Integration Verification
Given existing messaging logs and customer records When new interaction data is captured Then the system automatically integrates and updates records without errors in 100% of tested cases
Performance Impact Assessment
Given the behavioral data collection module is active When processing peak messaging volumes Then the system maintains performance under 5% CPU and memory overhead compared to baseline
Response Pattern Analysis
"As a system administrator, I want the AI to analyze customer response trends so that reminder times are tailored to each individual's habits and improve open rates."
Description

Implement an AI module that analyzes collected behavioral data to identify individual customer response patterns. The module should detect time-of-day preferences, typical reaction delays, and engagement frequency, generating a personalized response profile for each customer. This analysis will form the basis for dynamic reminder scheduling.

Acceptance Criteria
Evening Response Pattern Detection
Given at least 30 days of SMS interaction data, When the AI module analyzes customer response timestamps, Then it correctly identifies if ≥60% of responses occur between 18:00 and 21:00 and tags the customer profile with 'Evening Preferred'
Weekend Engagement Analysis
Given SMS interactions spanning two consecutive weekends, When the module processes response dates, Then it identifies if ≥50% of responses occur on Saturday or Sunday and updates the profile with 'Weekend Responder'
Rapid Responder Identification
Given response time data for a minimum of 20 messages, When the module calculates the average response delay, Then it tags customers with an average delay ≤5 minutes as 'Rapid Responder'
Delayed Responder Detection
Given response time data for a minimum of 20 messages, When the module calculates the average response delay, Then it tags customers with an average delay ≥120 minutes as 'Delayed Responder'
Peak Hour Preference Identification
Given message timestamps collected over 15 days, When the module segments responses into hourly buckets, Then it identifies the hour with the highest response frequency and assigns it as the customer's 'Peak Hour Preference'
Infrequent Engagement Profiling
Given interaction data for at least 90 days, When the module evaluates response frequency per week, Then it flags customers with ≤1 response per week as 'Infrequent Engager'
Reminder Timing Optimization Engine
"As an auto shop owner, I want the scheduler to automatically pick the best time to send reminders for each customer so that reminder open rates increase and no-shows decrease."
Description

Develop the core optimization engine that uses machine learning algorithms to determine the optimal moment to send SMS reminders. The engine must consider individual response profiles, appointment urgency, and shop operating hours. It should recalculate timing recommendations in real-time as new behavioral data is received.

Acceptance Criteria
Determining Initial Reminder Timing
Given a new appointment is scheduled, when the engine processes the appointment data, then it calculates an optimal SMS send time based on default customer response profiles and ensures it's within shop operating hours.
Real-time Timing Recalculation
Given updated customer behavior data is received, when the engine ingests the new data, then it recalculates and provides an updated SMS send time recommendation within 5 seconds of data receipt.
Handling Urgent Appointments
Given an appointment marked as urgent, when the engine calculates the reminder timing, then it prioritizes urgency by scheduling the SMS no later than 2 hours before the appointment start time while still optimizing for customer responsiveness.
Operating Hours Compliance
Given the calculated send time falls outside of shop operating hours, when the engine finalizes the recommendation, then it adjusts the send time to the nearest valid time slot within the next operating window.
Model Performance Validation
Given historical reminder send times and customer response rates, when running performance evaluation, then the optimization engine achieves at least a 20% reduction in average time-to-open compared to baseline timings.
SMS Dispatch Integration
"As a user, I want reminders to be sent automatically at the times determined by the AI so that I receive notifications when I'm most likely to see them."
Description

Integrate the timing optimization engine with the SMS gateway to schedule and send reminders at calculated optimal times. Ensure reliable delivery, retry logic for failures, and logging of dispatch events. The integration should provide extensibility for future support of additional messaging channels.

Acceptance Criteria
Optimal Timing SMS Dispatch
Given the timing optimization engine calculates an optimal send timestamp for a customer reminder When the system’s scheduler reaches the calculated timestamp Then the SMS gateway receives a send request within 1 second of the timestamp and returns a 200 OK response
Failed Delivery Retry Logic
Given an SMS dispatch attempt returns a transient error code (e.g., network timeout or 5xx response) When the error is received Then the integration retries the dispatch up to 3 times with exponential backoff and marks the message as failed only after all retries fail
Dispatch Event Logging
Given each SMS send request and gateway response When a dispatch event occurs (success or failure) Then the system logs an event record including timestamp, customer ID, message ID, status code, and error message (if any) to the central logging store
Gateway Extensibility for Additional Channels
Given the system architecture supports multiple messaging channels When a new channel adapter (e.g., email or push notification) is added Then the SMS dispatch integration layer remains unchanged and the new adapter can be registered and invoked using the same scheduling interface
High Volume Dispatch Performance
Given a batch of 10,000 optimized reminders to send within a one-hour window When the scheduler triggers all send requests Then the integration processes at least 95% of the dispatch requests within 5 minutes without exceeding average API latency of 200ms per request
Admin Dashboard Controls
"As a shop manager, I want a dashboard interface to review and adjust reminder timing rules and see performance metrics so that I can fine-tune the system and track its impact."
Description

Extend the PulseQueue dashboard to include controls for SmartScheduler settings, such as the ability to override AI-suggested times, set default reminder windows, and view analytics on reminder performance. Provide visualizations of engagement trends and no-show reductions driven by SmartScheduler.

Acceptance Criteria
Override AI Suggested Reminder Time
Given an admin selects an existing appointment, when they input a custom reminder time and save, then the reminder is scheduled at the overridden time instead of the AI-suggested time.
Set Default Reminder Window
Given an admin sets a default reminder window of 24 hours, when a new appointment is created, then the reminder is scheduled 24 hours before the appointment unless manually overridden.
View Engagement Trend Visualization
When an admin views the SmartScheduler analytics page and selects a date range, then a chart displays daily reminder open rates and engagement trends for that period.
No-Show Reduction Data Accuracy
Given historical no-show data and SmartScheduler activation, when analytics are generated, then the dashboard accurately displays the percentage reduction in no-shows compared to the baseline data.
Persisted Custom Settings Across Sessions
Given an admin configures override and default settings, when they log out and log back in, then all custom settings persist and are reflected in the dashboard controls.

InstaReschedule

One-tap rebooking embedded in the SMS that opens a pre-filled calendar interface—allowing customers to effortlessly adjust appointment times without calls or emails, reducing friction and freeing up staff.

Requirements

SMS Reschedule Link Generation
"As a customer, I want a secure reschedule link in my SMS reminder so that I can modify my appointment time with a single tap, without calling or emailing the shop."
Description

Automatically generate and embed a unique, secure reschedule link in every appointment reminder SMS that directs customers to the rescheduling interface. This link must include a time-bound authentication token, prevent unauthorized access, and ensure seamless redirection to the pre-filled calendar view without additional login steps. The system should handle link expiration and provide fallback messaging when links become invalid.

Acceptance Criteria
Unique Secure Link Generation
Given an appointment reminder SMS is sent When the system generates the reschedule link Then each link is unique per appointment uses HTTPS and includes a time-bound authentication token
Time-Bound Token Expiration
Given a generated reschedule link has passed its validity period When a customer clicks the link Then the system rejects access and displays an expiration message with instructions to request a new link
Unauthorized Access Prevention
Given a modified or forged reschedule link When a customer attempts access Then the system detects invalid token and denies entry to the rescheduling interface
Seamless Redirection to Pre-Filled Calendar
Given a valid reschedule link When a customer clicks the link Then the customer is automatically redirected to a calendar view pre-filled with their original appointment details without additional login
Fallback Messaging for Invalid Link
Given an invalid or expired reschedule link When a customer clicks the link Then the system sends fallback SMS with instructions on how to obtain a new link or contact the shop
Pre-filled Calendar Interface
"As a customer, I want the calendar to show my existing booking and available slots so that I can quickly choose a new time without re-entering information."
Description

Display a calendar interface that is automatically populated with the customer’s current appointment details and highlights available time slots based on real-time data. The interface should allow one-tap selection of a new slot, visually distinguish past and unavailable times, and adapt responsively to mobile devices. Changes in selection should immediately update the appointment preview before confirmation.

Acceptance Criteria
Mobile Launch with Pre-Filled Details
Given the customer taps the one-tap reschedule link in the SMS on their mobile device, when the calendar interface loads, then the customer’s current appointment date, time, and service details must be auto-populated and all available time slots for the next 30 days are displayed with past and unavailable slots visibly greyed out.
Attempt to Select Unavailable Time Slot
Given the calendar shows past or fully booked slots as unavailable, when the customer taps any greyed-out slot, then the selection must be blocked and a tooltip or inline message “Slot unavailable. Please select another time.” must appear.
Successful New Slot Selection and Preview Update
Given available slots are displayed, when the customer taps a new desired time slot, then that slot is highlighted, the appointment preview updates instantly to reflect the new date and time, and the “Confirm Reschedule” button becomes enabled.
Responsive Interface Across Devices
Given the customer accesses the reschedule interface on desktop or mobile, when the screen is resized or the device orientation changes, then the calendar layout must adapt dynamically to the viewport, ensuring dates, slots, and buttons remain fully visible and usable.
Real-Time Data Fetch Failure Handling
Given the system fetches real-time availability data on load, when the data request fails or times out, then the interface must display an error message with a “Retry” option, preserve any pre-filled appointment details, and allow the customer to attempt reloading without data loss.
Real-Time Availability Sync
"As a customer, I want to see up-to-date availability so that I can select a valid timeslot and avoid conflicts with other bookings."
Description

Implement a back-end service that queries the scheduling database in real time to fetch current bay availability and prevent double-bookings. The service should push updates to the calendar interface instantly when another user books or cancels an appointment. It must support high concurrency and maintain performance under peak loads to ensure accurate slot display.

Acceptance Criteria
Preventing Double-Booking Under Concurrent Requests
Given multiple users attempt to book the same bay at the same time, When the back-end service processes concurrent booking requests, Then only the first valid request is confirmed and subsequent requests receive a ‘Slot Unavailable’ response within 200ms.
Instant Availability Update on Appointment Booking
Given a user confirms a new appointment, When the booking is saved in the database, Then the updated availability is pushed to all active calendar interfaces within 1 second.
Real-Time Slot Availability During High Traffic
Given a peak load of 500 requests per minute, When the service handles availability queries, Then 95% of responses return current slot data within 300ms without errors.
Synchronized Cancellation Reflection
Given a user cancels an existing appointment, When the cancellation is committed to the database, Then freed slots are immediately visible to all clients and can be booked by other users within 500ms.
Performance Under Peak Load
Given system peak conditions with 1000 concurrent users, When availability sync operations occur, Then overall CPU usage remains below 70% and response times average under 400ms.
Secure Authentication Token
"As a system administrator, I want reschedule links to use expiring authentication tokens so that only authenticated customers can modify appointments, reducing unauthorized changes."
Description

Generate a cryptographically secure, time-limited token embedded in the SMS link to verify the customer’s identity and appointment ownership. Tokens must expire after a configurable duration, be single-use, and be validated by the back-end before displaying the reschedule interface. Invalid or expired tokens should redirect users to a help page with instructions.

Acceptance Criteria
Valid Token Usage Scenario
Given a customer receives an SMS link containing a secure token and the token is valid and unused, when the customer clicks the link, then the backend validates the token, marks it as used, and displays the reschedule interface.
Token Expiry Scenario
Given a token has surpassed its configurable expiration duration, when a customer clicks the SMS link, then the backend rejects the token and redirects the user to the help page with expiration instructions.
Single-Use Token Enforcement Scenario
Given a token has already been used to access the reschedule interface, when the customer attempts to use the same link again, then the backend rejects the token and displays an error directing them to request a new link.
Invalid Token Handling Scenario
Given a customer modifies or uses a tampered token in the SMS link, when the link is accessed, then the backend detects the invalid token signature and redirects the user to the help page with troubleshooting steps.
Configurable Expiration Duration Scenario
Given a shop manager updates the token expiration setting, when new SMS links are generated after the change, then tokens expire according to the newly configured duration.
Confirmation and Notification Handling
"As a customer, I want to receive a confirmation of my rescheduled appointment so that I know the change was processed and I have the correct details."
Description

Upon successful rescheduling, automatically send confirmation notifications via SMS and email containing the updated appointment details, including date, time, service type, and shop information. The system should also notify shop staff through their existing dashboard or preferred channel. Notifications must be reliable and sent within seconds of confirmation.

Acceptance Criteria
SMS Confirmation Delivery
Given a customer reschedules an appointment, when the reschedule is confirmed, then an SMS with the updated appointment date, time, service type, and shop information is sent within 5 seconds and SMS delivery status is recorded as delivered.
Email Confirmation Delivery
Given a customer reschedules an appointment, when the reschedule is confirmed, then an email with the updated appointment date, time, service type, and shop information is sent within 5 seconds and email delivery status is recorded as delivered.
Staff Dashboard Notification
Given a customer reschedules an appointment, when the reschedule is confirmed, then a notification containing updated appointment details appears instantly in the shop staff dashboard.
Alternate Channel Notification
Given a customer reschedules an appointment and has a preferred channel set, when the reschedule is confirmed, then a notification with updated appointment details is sent via the selected channel within 5 seconds.
Notification Retry on Failure
Given a notification attempt fails, when the system detects a delivery failure, then it automatically retries sending the notification up to three times within the next minute.
Reschedule Analytics and Reporting
"As a shop manager, I want insights into rescheduling patterns so that I can optimize appointment policies and reduce no-show rates."
Description

Track all rescheduling events and capture metadata such as time of request, original vs. new slot, device type, and customer demographics. Provide an analytics dashboard for shop managers to view trends in rescheduling frequency, peak reschedule periods, and post-reschedule no-show rates. Enable export of reports for further analysis.

Acceptance Criteria
Rescheduling Event Logging
Given a customer confirms an appointment change via InstaReschedule When the system processes the new booking Then an entry is created in the rescheduling events log
Metadata Capture on Reschedule
Given an appointment is rescheduled When the change is recorded Then the system captures and stores time of request, original slot, new slot, device type, and customer demographic data
Analytics Dashboard Trend Visualization
Given the shop manager accesses the Reschedule Analytics Dashboard When data is loaded Then weekly and monthly trend charts for rescheduling frequency are displayed correctly
Peak Reschedule Period Identification
Given the dashboard has reschedule data When the manager views the heatmap Then the system highlights hours with the highest rescheduling counts
Report Export Functionality
Given the manager selects a date range and fields on the analytics dashboard When the export button is clicked Then a CSV or PDF file containing all reschedule events and metadata is generated and downloadable

OmniChannel Ping

Seamlessly escalates undelivered or unanswered SMS reminders to alternative channels like email or WhatsApp—ensuring every customer receives their appointment notice through their preferred medium.

Requirements

Channel Preference Detection
"As an auto shop manager, I want the system to detect each customer's preferred contact channel so that reminders are sent via the medium they are most likely to respond to."
Description

A system that automatically identifies each customer's preferred communication channel by analyzing their historical interactions and explicitly stated preferences, ensuring that reminders are sent via the most effective medium. Integrates with the customer profile service to store and update channel preferences, enhances engagement by delivering messages on the channels customers are most responsive to, reduces undelivered notifications, and improves appointment adherence.

Acceptance Criteria
Initial Preference Capture at Signup
Given a new customer completes signup and selects a preferred channel When the profile is created Then the selected channel is persisted in the customer profile service and retrievable via API
Manual Preference Update by Support Agent
Given a support agent updates a customer’s channel preference in the profile UI When the change is saved Then the new preference is stored in the profile service and confirmation is displayed to the agent
Automated Historical Interaction Analysis
Given existing customer message logs When the system analyzes historical interaction data Then it infers the most responsive channel and updates the customer profile service with the detected preference
Real-time Interaction Preference Update
Given a customer replies on an alternative channel When the system receives the first reply Then it updates the customer’s channel preference in the profile service within one minute
Channel Selection for Reminder Dispatch
Given a scheduled appointment reminder When the dispatch process runs Then it retrieves the customer’s preferred channel from the profile service and sends the reminder via that channel
Multi-Channel Escalation Logic
"As an auto shop manager, I want failed SMS reminders to be automatically escalated to email and then WhatsApp so that I can be confident customers receive their appointment notifications."
Description

Definition and implementation of rules that escalate undelivered or unanswered reminders from SMS to alternate channels in a prioritized order (e.g., email, then WhatsApp), with configurable retry intervals and maximum attempts. Ensures timely delivery of appointment notifications by seamlessly switching channels when a message fails, integrates with the notification engine to monitor delivery statuses, and logs escalation paths for audit and reporting.

Acceptance Criteria
SMS Undelivered Escalates to Email
Given an SMS reminder fails delivery with a non-transient error, When the system detects the failure, Then it must wait the configured retry interval and send the appointment reminder via the customer's email address and record the email delivery status.
Email Undelivered Escalates to WhatsApp
Given an email reminder fails delivery after maximum retry attempts, When the system detects the email failure, Then it must escalate by sending the appointment reminder via WhatsApp within the configured retry interval and update the notification status accordingly.
Unanswered SMS Escalates to Email
Given an SMS reminder is successfully delivered but receives no customer acknowledgment within the configured timeout period, When the timeout expires, Then the system must escalate by sending the reminder via email and log the escalation event with timestamps and channel details.
Max Attempts Enforcement Stops Escalation
Given a notification has been escalated and the total number of attempts across all channels reaches the configured maximum, When the next escalation is due, Then the system must cease further escalation attempts and log the final failure status for auditing.
Audit Logging of Escalation Path
Given any escalation event occurs, When each channel attempt is initiated, Then the system must log the channel name, attempt timestamp, retry count, and delivery status to the audit log for reporting purposes.
Channel Template Management
"As a marketing coordinator, I want to manage reminder templates for SMS, email, and WhatsApp within one interface so that messages remain consistent and personalized."
Description

A management interface for creating, editing, and organizing message templates for each communication channel, supporting personalization tokens, localization, and compliance with channel-specific formatting requirements. Enables marketing and operations teams to maintain consistent branding and message clarity across SMS, email, and WhatsApp reminders, and ensures adaptability to different customer segments and locales.

Acceptance Criteria
Create SMS Template with Tokens and Localization
Given an admin navigates to the Create Template page and selects SMS channel When they enter a template name, message body including valid personalization tokens, and select English locale Then the system validates token syntax, saves the template under SMS channel, and makes it available in the SMS template list.
Edit WhatsApp Template for Channel-Specific Formatting
Given an existing WhatsApp template is selected for editing When the admin modifies the message content to meet WhatsApp's formatting rules (e.g., no more than 4096 characters, valid hyperlink syntax) Then the system highlights any formatting violations, enforces compliance, and allows saving only when the template meets channel requirements.
Organize Email Templates by Customer Segment and Locale
Given the admin views the template management dashboard When they filter templates by email channel, customer segment, or locale Then the system displays only matching templates sorted by name and indicates segment and locale associations.
Preview Template Across Channels
Given an admin selects a template and clicks Preview When they choose a channel (SMS, Email, WhatsApp) Then the system renders a simulated message with actual token values replaced by sample data, applies channel-specific rendering rules, and displays errors if any.
Archive Unused Templates to Maintain Consistency
Given a template has not been used in any campaign or scheduled message for six months When the admin selects the archive action Then the system marks the template as archived, removes it from standard lists, and logs the archive action with timestamp and user ID.
Delivery Status Tracking
"As a shop owner, I want to see the delivery status of my appointment reminders across all channels so that I can quickly identify and address any issues."
Description

A tracking mechanism that captures and displays the delivery status of reminders across all channels in real time, including metrics such as sent, delivered, read, bounced, and replied. Integrates with channel APIs to ingest status callbacks, aggregates data in the dashboard, and alerts shop managers to failed or unconfirmed reminders for timely manual intervention if needed.

Acceptance Criteria
Real-Time Status Update Display
Given a reminder is sent through any channel, when the channel API returns a status callback, then the dashboard updates the reminder’s status to the new state (sent, delivered, read, bounced, or replied) within 5 seconds.
Comprehensive Delivery Metrics Aggregation
Given multiple reminders are processed, when viewing the dashboard metrics, then the total counts for sent, delivered, read, bounced, and replied reminders accurately reflect the data ingested from all channel APIs for the selected time period.
Failed Reminder Alert to Manager
Given a reminder’s status changes to bounced or undelivered, when this status is recorded, then the system generates an on-screen alert for the shop manager and sends an automated notification (email or SMS) to the manager within 1 minute.
Multi-Channel Status Tracking Integrity
Given reminders sent via SMS, email, and WhatsApp, when querying the delivery status endpoint, then each reminder record includes channel identifier and its current status, ensuring no channel data is missing or misattributed.
Historical Status Data Reporting
Given reminders over the past 30 days, when the manager requests a report, then the system returns a downloadable report that includes each reminder’s timestamp, channel, and status history for the selected date range.
Fallback Channel Analytics
"As a product manager, I want analytics on how each channel performs and which escalation sequences yield the best results so that I can optimize our notification strategy."
Description

An analytics module that aggregates and analyzes channel performance data to identify the most effective escalation paths and optimize default channel priorities. Provides reports and visualizations on open rates, response rates, and conversion rates by channel sequence, helping product managers refine escalation rules and improve overall notification success rates.

Acceptance Criteria
Monthly Performance Report Generation
Given a completed month, when the product manager requests the channel performance report, then the system aggregates open rate, response rate, and conversion rate by escalation path within 2 minutes, generates interactive charts on the dashboard, and provides downloadable CSV and PDF outputs.
Real-time Escalation Path Analysis
When accessing the real-time analytics dashboard, the product manager sees live aggregated open, response, and conversion rates for each escalation sequence updated at least every minute with data latency under 60 seconds.
Custom Time Range Analytics
Given a user-selected custom date range, when the filter is applied, then the system recalculates and displays open, response, and conversion rates for that period within 30 seconds, matching values in the raw event logs.
Visualization Export Functionality
When the user exports the displayed analytics, then the system offers PNG, PDF, and CSV formats that accurately reflect the current charts and tables with correct labels, legends, and axis scales.
Performance Alert Configuration
Given configured performance thresholds for open, response, and conversion rates, when any metric drops below its threshold, then the system automatically sends an email alert to designated product managers within five minutes.

Reward Nudge

Integrates personalized incentive codes or limited-time discounts into reminder messages—motivating customers to confirm or rebook quickly, boosting loyalty and filling open slots.

Requirements

Incentive Code Generation
"As an auto shop owner, I want the system to automatically generate unique incentive codes for each appointment reminder so that I can motivate customers to confirm or rebook without manual code creation."
Description

Automatically generate unique, single-use incentive codes or discount vouchers tailored for each customer to include in SMS reminders. This functionality ensures each reminder carries a personalized offer, prevents code reuse, and tracks offer assignment for analytics and auditing.

Acceptance Criteria
Unique Code Generation for SMS Reminders
Given an appointment reminder is queued for SMS dispatch, when the system prepares the reminder, then it generates a unique, single-use incentive code formatted as an 8-character uppercase alphanumeric string and associates it with the reminder.
Single-Use Validation on Redemption
Given an incentive code has been issued, when a customer attempts to redeem the code, then the system verifies the code has not been used before and marks it as redeemed upon successful validation.
Code Formatting and Uniqueness Enforcement
Given simultaneous code generation requests, when the system processes them, then each generated code must conform to the pattern ^[A-Z0-9]{8}$ and no two codes may be identical.
Customer-Specific Code Assignment
Given reminders are generated for different customers, when the incentive codes are created, then each customer must receive a distinct code that is not reused across any other customer or reminder.
Analytics Tracking of Code Usage
Given codes are generated and sent, when the system logs events, then each log entry includes the timestamp, customer ID, code value, issuance status, and redemption status for reporting and auditing.
Personalized Discount Assignment
"As a returning customer, I want to receive a discount offer based on my service history so that I feel valued and am more likely to confirm my next appointment."
Description

Leverage customer data and booking history to assign relevant discount levels or reward offers. This ensures the incentives resonate with individual customer segments and maximizes uptake by aligning offers with past behavior and preferences.

Acceptance Criteria
New Customer Discount Allocation
Given a customer with no previous bookings, when the system evaluates discount assignments, then it assigns a default 15% introductory discount code in the reminder message.
Frequent High-Spend Customer Reward
Given a customer with over five bookings in the last year totaling more than $1,000, when generating their reminder, then the system assigns a premium 20% discount code tailored to their service history.
Reactivation Discount for Inactive Customers
Given a customer with no bookings in the past six months, when preparing a reminder, then the system assigns a 25% reactivation discount code with an expiration of 7 days.
Cancellation Follow-Up Incentive
Given a customer who cancels a scheduled appointment, when sending a follow-up reminder, then the system provides a 10% discount code specific to their last service type and urges rebooking within 7 days.
VIP Tier Upgrade Offer
Given a customer who qualifies for VIP status through cumulative spending, when issuing a reminder, then the system includes a VIP-exclusive 30% discount code and acknowledges their tier upgrade.
Time-Limited Offer Scheduler
"As a customer receiving a reminder, I want the discount code to show an expiration date so that I feel motivated to confirm my appointment quickly before the offer lapses."
Description

Enable configuration of expiration windows for incentive codes within reminder messages. Administrators can set start and end times for each offer, enforce countdowns, and trigger automated notifications as deadline approaches to create urgency.

Acceptance Criteria
Admin Configures Time-Limited Offer Window
Given I am an administrator on the Time-Limited Offer Scheduler page When I enter valid start and end times for a new incentive code and save the configuration Then the offer appears in the scheduler list with the correct start and end timestamps
Front-End Displays Countdown in SMS Reminder
Given a customer has received an SMS reminder containing a time-limited incentive code When the current time is between the offer's start and end times Then the SMS message dynamically displays a countdown timer showing the remaining time until expiration
Automatic Notification Triggers Near Expiration
Given an offer is within one hour of its configured end time When the remaining time threshold (e.g., 60 minutes) is reached Then the system automatically sends a follow-up SMS message alerting the customer of the impending deadline
Validation Prevents Invalid Time Ranges
Given I attempt to configure an offer with an end time earlier than its start time When I submit the offer configuration form Then the system displays a clear validation error and prevents saving until the time range is corrected
Expired Offers Are Disabled and Unusable
Given the current time has passed the configured end time of an offer When a customer attempts to apply the expired incentive code Then the system rejects the code usage with a message indicating the offer has expired and no discount is applied
SMS Template Customization
"As a shop manager, I want to customize the SMS reminder template with my branding, discount code, and expiration date so that messages align with our shop’s identity and promotional strategies."
Description

Provide a user-friendly interface for customizing SMS templates to include dynamic fields for incentive codes, expiration details, and personalized messages. This empowers shops to maintain brand voice and tailor messaging per campaign or customer segment.

Acceptance Criteria
Valentine Campaign Template Setup
Given a manager opens the SMS template editor and selects the Valentine’s Day campaign, When they insert dynamic fields for customer name, incentive code, and expiration date, Then the placeholders {{customer_name}}, {{incentive_code}}, and {{expiration_date}} appear correctly formatted in the template.
Template Preview Validation
Given the manager clicks preview for a drafted SMS template with sample customer data, When the preview modal displays, Then each dynamic placeholder is replaced with sample data and the message reflects the shop’s brand voice.
Template Application to Campaign
Given a saved custom template, When the manager applies it to a new promotional campaign targeting a specific customer segment, Then the selected template populates the SMS preview and is queued for release to that segment.
Template Editing Propagation
Given an existing SMS template is edited to update the incentive code and expiration date, When the manager saves changes, Then all future uses of the template—including scheduled messages—reflect the updated fields and version history records the edit.
Dynamic Field Resolution in Send Test
Given a test SMS is sent using a template containing dynamic fields, When the manager receives the test message on their phone, Then the SMS displays actual incentive code and expiration date values from the test data and includes a working link to the promotional landing page.
Offer Redemption Tracking Dashboard
"As a shop manager, I want to see real-time statistics on how many incentive codes have been redeemed so that I can assess the campaign’s effectiveness and adjust future offers accordingly."
Description

Implement a dashboard to monitor incentive code usage, redemption rates, and impact on booking confirmations. Display metrics such as codes sent, redeemed, and resulting fill rates to help managers optimize future offers and measure ROI.

Acceptance Criteria
Redemption Overview Display
Given the manager accesses the Offer Redemption Tracking Dashboard, when the dashboard loads, then metrics for codes sent, codes redeemed, and resulting fill rate are displayed within 2 seconds.
Date Range Filtering
Given the manager selects a custom date range and applies the filter, when the filter is confirmed, then the dashboard updates to display only the codes sent, redeemed, and fill rates within that specified period.
Data Export Functionality
Given the manager clicks the export button, when the export is confirmed, then a CSV file containing columns for dates, codes sent, codes redeemed, redemption rate, and fill rate is generated and downloaded within 3 seconds.
Real-Time Redemption Updates
Given a customer redeems an incentive code, when the redemption is processed, then the dashboard reflects the updated redemption count and adjusted fill rate within 60 seconds.
Redemption vs Fill Rate Comparison Chart
Given the dashboard displays time-series data, when the manager views the comparison chart, then a line chart shows redemption rate and booking fill rate over the selected period with clear legends and hover tooltips for each data point.

Performance Pulse

Comprehensive analytics dashboard tracking reminder delivery, open and click-through rates, rebooking conversions, and no-show trends—empowering managers to fine-tune messaging strategies and maximize effectiveness.

Requirements

Real-time Data Aggregation
"As a shop manager, I want real-time aggregation of reminder metrics so that I can monitor campaign effectiveness instantly."
Description

Continuously collects and processes reminder delivery, open, click-through, rebooking conversion, and no-show data in real-time, ensuring the analytics dashboard reflects the most current performance metrics. Integrates seamlessly with the scheduling engine and SMS delivery system to provide a unified, up-to-the-minute view of all campaign activities and outcomes.

Acceptance Criteria
Live Reminder Delivery Tracking
Given an SMS reminder is sent through the SMS delivery system, When the SMS gateway confirms delivery, Then the delivery event is logged and displayed on the analytics dashboard within 2 seconds.
Real-time Open and Click Monitoring
Given a delivered SMS contains a tracking link, When the recipient opens the message or clicks the link, Then the open or click-through event is recorded and updated on the dashboard within 5 seconds.
Rebooking Conversion Recording
Given a customer initiates a rebooking via the reminder message, When the customer completes the rescheduling process, Then the rebooking conversion metric on the dashboard is updated within 3 seconds.
No-show Event Aggregation
Given an appointment reaches its scheduled time without check-in, When the scheduling engine flags a no-show, Then the no-show count is incremented and reflected on the dashboard in real-time.
Unified Data Synchronization
Given simultaneous event streams from the scheduling engine and SMS delivery system, When both streams emit events for reminders and responses, Then the analytics dashboard consolidates and displays all events within 5 seconds without duplicates or missing data.
Customizable Dashboard Widgets
"As a shop manager, I want to customize my analytics dashboard so that I can focus on the metrics most relevant to my decision-making."
Description

Allows users to select, arrange, and configure individual dashboard components—such as charts for delivery rates, tables for click-through data, and gauges for no-show trends—tailoring the analytics view to their specific needs. Widgets support drag-and-drop layout changes, time range filters, and metric thresholds for personalized insights.

Acceptance Criteria
Widget Selection and Addition
Given the user is on the dashboard customization panel, when they open the widget library then they can view available widgets; when they select a widget and click 'Add' then the widget appears in the dashboard layout.
Drag-and-Drop Layout Customization
Given the dashboard contains multiple widgets, when the user drags a widget to a new location and drops it then the widget updates its position; and the layout persists after page reload.
Time Range Filter Application
Given a widget supports time range filtering, when the user selects a start and end date then the widget data refreshes to reflect metrics within that range; and the selected range displays on the widget header.
Metric Threshold Configuration
Given a widget displays metric trends, when the user sets a threshold value and clicks 'Save' then the widget highlights data points exceeding the threshold; and a visual alert icon appears.
Widget Removal and Reset to Default
Given a customized dashboard, when the user removes a widget or clicks 'Reset to Default' then the dashboard reverts to the default widget set and layout.
Trend Analysis and Forecasting
"As a shop manager, I want trend analysis and forecasting of reminder outcomes so that I can proactively adjust strategies to reduce no-shows."
Description

Analyzes historical reminder performance and appointment data to identify patterns in open rates, no-show occurrences, and rebooking conversions. Uses statistical models to project future performance trends, enabling managers to anticipate scheduling bottlenecks, optimize message timing, and plan staffing levels accordingly.

Acceptance Criteria
Historical Data Ingestion Validation
Given at least 12 months of historical reminder and appointment data is available When the system ingests the data for analysis Then all records for open rates, no-show occurrences, and rebooking conversions are imported without omission or duplication And data integrity checks confirm 100% match between source and stored records
Trend Visualization Accuracy
Given historical performance data has been processed When the trend charts are displayed in the dashboard Then open rate, no-show rate, and rebooking conversion trends correctly reflect the input data within a ±1% margin of error And chart interactions (hover, zoom) display accurate metric values
Forecast Generation Reliability
Given historical performance patterns are available When the system generates a 30-day performance forecast Then the forecasted open rate, no-show rate, and conversion values are produced using the configured statistical model And model confidence intervals are calculated and displayed for each forecasted metric
Scheduling Bottleneck Alert Timing
Given forecasted no-show and booking patterns indicate potential bottlenecks When a threshold (e.g., >20% no-show rate) is breached Then the system sends an alert to the manager via the dashboard and optional SMS within 5 minutes of forecast completion
Staffing Level Recommendation Precision
Given forecasted appointment volume and no-show rates When the system calculates recommended staffing levels Then the recommendations adjust staffing counts by role (technician, service advisor) within ±1 staff member accuracy And include an explanation of the calculation basis in the dashboard
Automated Alert Generation
"As a shop manager, I want automated alerts for significant performance changes so that I can respond quickly to issues."
Description

Monitors key performance indicators and triggers automated alerts when predefined thresholds are met—such as a sudden drop in open rates or spike in no-shows. Alerts are delivered via SMS, email, or in-app notifications, guiding managers to investigate and tweak messaging strategies in a timely manner.

Acceptance Criteria
Open Rate Drop Alert Scenario
Given the open rate falls below 20% over a rolling 24-hour period When the system evaluates KPI thresholds Then an automated alert must be generated and sent via SMS, email, and in-app notification within 5 minutes
No-Show Spike Alert Scenario
Given the no-show rate increases by more than 10% compared to the previous week When the system detects the spike Then an alert with historical and current no-show metrics must be dispatched to the manager through all configured channels
Threshold Boundary Verification Scenario
Given a KPI value equals exactly the configured threshold When the monitoring process runs Then the system must trigger the corresponding alert to verify boundary conditions
Notification Delivery Failure Scenario
Given an alert fails to send via any channel When delivery confirmation is not received within 2 minutes Then the system retries delivery up to 3 times and logs the failure for administrative review
Alert Acknowledgment Tracking Scenario
Given an alert is delivered When the manager views or interacts with the notification Then the system must record an acknowledgment timestamp and update the alert status to ‘Acknowledged’ in the dashboard
Data Export and Integration
"As a shop manager, I want to export and integrate my analytics data so that I can perform advanced reporting and share insights with stakeholders."
Description

Provides functionality to export analytics data in common formats (CSV, JSON) and offers API endpoints for seamless integration with third-party BI tools and reporting platforms. Ensures data is structured, documented, and versioned to support external analysis and long-term record keeping.

Acceptance Criteria
CSV Data Export for Monthly Reports
Given a user selects a date range and 'CSV' format and clicks 'Export', when the export job completes, then a downloadable CSV file is provided containing headers matching the data schema and rows corresponding to analytics records within the date range.
JSON Data Export via API Endpoint
Given an authenticated API client requests analytics data in JSON via the /api/v1/analytics/export endpoint with valid date range parameters, when the request is processed, then the API returns HTTP 200 and a JSON payload conforming to the documented schema and containing analytics records for the requested range.
Versioned Schema Documentation Retrieval
Given a user accesses the API schema endpoint with a specified version parameter, when the request is made, then the system returns the schema documentation including field names, data types, and version identifier in JSON format.
Performance Testing on Large Dataset Export
Given the analytics dataset exceeds 100,000 records and a user initiates a CSV export, when the export process runs, then it completes within 2 minutes without timing out and generates a file that can be downloaded successfully.
Third-Party BI Tool Data Compatibility
Given a third-party BI tool requests data via the API, when it retrieves the JSON export, then the tool successfully imports the data without schema errors, confirming compatibility with at least two named BI platforms (e.g., Tableau, Power BI).

VIP Priority

Automatically flags high-value or repeat customers for elevated reminder treatment—combining priority SMS timing with personalized follow-up prompts to protect key relationships and enhance satisfaction.

Requirements

VIP Customer Identification
"As a shop manager, I want the system to identify high-value customers automatically so that I can ensure they receive priority scheduling and reminders."
Description

Automatically flag high-value or repeat customers based on configurable metrics such as total spend and visit frequency. Integrate these flags with the scheduling engine to ensure that identified VIPs receive elevated reminder treatment, protecting key relationships and optimizing resource allocation.

Acceptance Criteria
Flagging VIP Customers at Checkout
Given a customer completes a service booking and their total spend exceeds the VIP spend threshold or their visit frequency exceeds the VIP frequency threshold, when the booking is confirmed, then the system automatically applies a VIP flag to the customer’s profile.
Configurable VIP Metrics Setup
Given an admin accesses the VIP settings page, when they input and save new spend and frequency threshold values, then the system persists those values and displays a confirmation message.
Integration of VIP Flag with Scheduling Engine
Given a customer profile flagged as VIP, when the customer books a new appointment, then the scheduling engine schedules priority SMS reminders at elevated timing and attaches personalized follow-up prompts.
Bulk Flagging Existing Customer Database
Given the overnight batch job runs, when it processes all existing customer records against the current VIP thresholds, then it flags all qualifying customers, unflags those no longer meeting criteria, and logs a summary of changes.
Review and Override VIP Flags
Given a manager views the list of VIP-flagged customers, when they manually add or remove a VIP flag on a customer record, then the override is saved immediately and reflected in all future scheduling and reminder logic.
Priority SMS Timing Engine
"As a VIP customer, I want to receive reminders at optimized times so that I don't miss my appointment and feel valued."
Description

Implement an advanced timing engine that adjusts SMS reminder schedules specifically for VIP customers. Support configurable priority windows (e.g., 48 hrs, 24 hrs, 2 hrs before appointment) and integrate with the existing SMS gateway to dispatch messages at optimized times, reducing no-shows among top clients.

Acceptance Criteria
Configurable Priority Window Setup
Given an admin user sets VIP SMS timing windows to 48 hours, 24 hours, and 2 hours before an appointment, When the configuration is saved, Then the system persists the priority windows settings and displays a confirmation.
Schedule SMS Dispatch Within Priority Windows
Given a VIP customer’s appointment is scheduled, When the system clock reaches each configured priority window (48h, 24h, 2h) before the appointment, Then an SMS reminder is queued for dispatch at that specific time.
SMS Gateway Integration for Priority Messages
Given a queued VIP SMS reminder, When the dispatch time arrives, Then the system invokes the existing SMS gateway API, receives a 200 OK response, and updates the reminder status to “Sent.”
Fallback Mechanism on SMS Dispatch Failure
Given an SMS gateway error or timeout during VIP reminder dispatch, When the initial send attempt fails, Then the system retries up to three times with exponential backoff and logs the final failure if all retries are unsuccessful.
No-Show Reduction Monitoring for VIP Reminders
Given a period of VIP SMS reminders using priority timing, When comparing no-show rates for VIP customers before and after implementation, Then the system reports at least a 40% reduction in VIP no-shows over a 30-day sample.
Personalized Follow-up Prompts
"As a shop manager, I want personalized follow-up prompts for VIP customers so that I can maintain strong relationships through tailored communication."
Description

Generate dynamic follow-up messages for VIP customers that include personalized content such as customer name, past service details, and recommended next steps. Leverage template-driven messaging integrated with customer records to boost engagement and reinforce service relationships.

Acceptance Criteria
VIP Follow-up Message Generation Scenario
Given a VIP customer record exists with name and service history, when the system generates a follow-up prompt, then the message includes the customer's first name and the date of their last service.
Personalized Service History Inclusion Scenario
Given a VIP customer's past services are stored, when creating a follow-up prompt, then at least one relevant past service detail is referenced in the message.
Recommended Next Steps Scenario
When generating a follow-up prompt for a VIP customer, then the system includes a clear recommended next step based on the customer's last service type.
Template-driven Dynamic Field Population Scenario
Given multiple message templates exist, when selecting a template for a VIP follow-up, then all dynamic fields (e.g., {CustomerName}, {ServiceType}, {NextStep}) are correctly populated with no remaining placeholders.
Real-time Follow-up Dispatch Timing Scenario
Given a VIP follow-up prompt is generated, when determining dispatch timing, then the message is scheduled and sent within the configurable VIP priority window.
VIP Tag Management
"As a shop manager, I want to manually tag or untag VIP customers so that I can correct any automated misclassifications and maintain an accurate VIP list."
Description

Provide a user interface for shop managers to manually assign, edit, or remove VIP tags on customer profiles. Ensure real-time synchronization with the customer database and scheduling engine to maintain accurate VIP rosters and allow manual overrides when needed.

Acceptance Criteria
Assign VIP Tag to Customer Profile
Given a shop manager is viewing a customer profile, When the manager selects 'Add VIP Tag' and clicks 'Save', Then the VIP tag appears in the profile UI and persists in the database.
Edit VIP Tag on Existing Customer Profile
Given a customer profile already has a VIP tag, When the manager updates the VIP tag details and clicks 'Update', Then the new VIP tag details are displayed immediately and stored in the database.
Remove VIP Tag from Customer Profile
Given a customer profile has an existing VIP tag, When the manager clicks 'Remove VIP Tag' and confirms, Then the VIP tag is removed from the profile UI and deleted from the database.
Real-Time Synchronization with Database and Scheduling Engine
Given any VIP tag change is saved, When the change is processed, Then the customer database and scheduling engine reflect the update within 2 seconds and future appointment reminders use the correct VIP status.
Manual VIP Tag Override During Appointment Scheduling
Given a manager is booking an appointment for a customer, When the manager toggles the VIP tag option on the scheduling screen and saves, Then the appointment is saved with the updated VIP status and the reminder workflow adjusts accordingly.
VIP Analytics Dashboard
"As a shop owner, I want an analytics dashboard for VIP customer interactions so that I can measure the impact of priority reminders on engagement and revenue."
Description

Develop a dashboard module that displays key performance metrics for VIP customers, including no-show rates, SMS response rates, and revenue impact. Include visual charts and data export capabilities to help shop owners measure the ROI of VIP priority reminders and inform future scheduling strategies.

Acceptance Criteria
Dashboard Loads VIP Metrics
Given the shop owner accesses the VIP Analytics Dashboard When the page loads Then the no-show rate, SMS response rate, and revenue impact for VIP customers are displayed and updated within 3 seconds
Filter VIP Data by Date Range
Given the shop owner selects a custom date range When the filter is applied Then the dashboard metrics update to show no-show rate, SMS response rate, and revenue impact only for VIP appointments within the selected dates
Export VIP Metrics to CSV
Given the shop owner clicks the export button When CSV format is chosen Then a file named "VIP_Metrics_<start>_<end>.csv" downloads containing columns for Customer ID, Appointment Date, No-Show, SMS Response, and Revenue Impact
Visualize Trends in Chart View
Given the VIP Analytics Dashboard is displayed When viewing the charts section Then the line chart shows weekly no-show and SMS response rate trends and the bar chart shows monthly revenue impact without missing data points
Validate Revenue Impact Calculation
Given the dashboard calculates revenue impact When the system aggregates VIP appointment data Then the displayed revenue impact equals the sum of fees from completed VIP appointments multiplied by the configured premium factor

Dynamic Discount Engine

Automatically calculates and applies optimal discount levels based on real-time bay idleness, customer value, and booking urgency. This ensures every offer balances margin protection with high fill rates, maximizing revenue while quickly turning empty slots into confirmed appointments.

Requirements

Real-time Bay Utilization Monitor
"As a shop manager, I want real-time visibility into bay utilization so that discount offers reflect current availability and maximize fill rates."
Description

Ingest live data from shop management tools to monitor bay occupancy and idle time, updating every minute. Provide accurate, up-to-date metrics on bay idleness that the discount engine can access to calculate optimal discount levels in response to real-world availability.

Acceptance Criteria
Live Data Ingestion Scenario
Given the shop management tool emits bay occupancy and idle time data every 30 seconds, when the system ingests incoming data, then it must process and update bay utilization metrics within 60 seconds.
Dashboard Update Scenario
Given real-time occupancy data is ingested, when metrics are updated, then the dashboard must refresh within 60 seconds, displaying occupancy and idle time values matching source data within a 2% tolerance.
Data Interruption Alert Scenario
Given the expected data feed interval is 60 seconds, when no data is received for more than 120 seconds, then the system must trigger an alert via email and log an incident with timestamp and shop identifier.
API Performance Scenario
Given the shop management API integration, when the system requests bay data, then 95% of API calls must complete within 500ms over any 1-hour period.
Data Accuracy Validation Scenario
Given the system records ingested bay utilization metrics, when data points are stored, then stored values must exactly match the source tool’s reported occupancy status and idle duration, verified through unit and integration tests.
Customer Value Scoring
"As a marketing analyst, I want customer value scores computed automatically so that high-value customers receive tailored discounts that protect margins."
Description

Calculate a dynamic customer value score based on historical spend, service frequency, and loyalty status by integrating with the CRM database. This score feeds into the discount engine to prioritize high-value customers and adjust discount levels to balance margin protection with customer retention.

Acceptance Criteria
High-Value Customer Score Calculation
Given a customer with total historical spend of $5000 and frequency of 12 visits, When the scoring service runs, Then the system calculates a value score ≥ 90 based on the defined weighting rules.
Frequent Customer Frequency Weighting
Given a customer with 6 service visits in the past 6 months, When the scoring algorithm processes frequency data, Then the customer frequency factor contributes at least 20% to the overall score.
Loyalty Status Integration
Given a customer marked as 'Gold' loyalty in the CRM, When the score is computed, Then the loyalty status multiplier of 1.2 is applied correctly to the base score.
Real-Time Score Update on CRM Data Change
Given a customer's spend increases by $200, When the CRM record is updated, Then the new value score is recalculated within 1 minute and updated in the discount engine.
Score Storage and Availability for Discount Engine
Given the computed customer value score, When the score is stored, Then it is retrievable via the discount engine API within 2 seconds for use in discount calculation.
Urgency-Based Discount Calculation
"As a shop owner, I want discounts to automatically increase as the booking window gets shorter so that last-minute slots are more likely to be booked."
Description

Implement an algorithm that adjusts discount percentages according to the time remaining until the appointment window, escalating discounts as the slot time approaches. Ensure the algorithm respects minimum margin thresholds and maximum discount caps to prevent revenue loss.

Acceptance Criteria
High-Urgency Slot Discount Increase
Given a bay is unbooked and the appointment start time is within 2 hours, When the discount algorithm runs, Then the calculated discount increases by at least 5% above the standard rate and does not exceed the maximum cap.
Margin Threshold Enforcement
Given any appointment time-to-start, When the urgency-based discount is computed, Then the final price must maintain a minimum margin of 20% above the shop’s cost.
Maximum Discount Cap
Given the time-to-appointment is under 30 minutes, When applying the urgency-based discount, Then the discount percentage must never exceed the 50% maximum limit.
Real-Time Discount Recalculation
Given a slot’s time-to-appointment crosses a predefined threshold (e.g., from 3h to 2h), When the algorithm triggers, Then the discount is recalculated and updated in the user interface within 5 seconds.
Booking Integration with Applied Discount
Given a customer confirms a booking with the calculated urgency discount, When the booking is saved, Then the discounted price is accurately recorded in the booking record and displayed in the confirmation message.
Discount Configuration Dashboard
"As an operations manager, I want a configuration dashboard so that I can fine-tune discount rules without developer intervention."
Description

Provide an administrative dashboard to configure all discount parameters, including minimum margin requirements, maximum discount limits, time-based discount curves, and override rules. The dashboard should offer real-time previews of how changes affect discount calculations.

Acceptance Criteria
Minimum Margin Requirement Update
Given the admin sets the minimum margin to 20%, when saving the configuration, then all subsequent discount calculations must not propose discounts below 20%.
Maximum Discount Limit Enforcement
Given the admin sets the maximum discount limit to 50%, when saving the configuration, then the engine never applies discounts above 50% in any booking scenario.
Time-Based Discount Curve Preview
Given the admin configures a time-based discount curve, when selecting any time slot in the dashboard, then the preview graph updates to display the exact discount percentage for that slot according to the curve.
Override Rule Configuration
Given the admin creates an override rule for VIP customers, when simulating a VIP booking, then the system applies the override discount and ignores the base discount curve.
Real-Time Calculation Preview Performance
Given the admin updates any discount parameter, when changes are saved, then the real-time preview reflects the updated discount calculation within 2 seconds and matches the backend output.
Automated Discount Notification
"As a customer, I want to receive a discounted appointment offer via SMS so that I can immediately confirm without having to call the shop."
Description

Automatically apply calculated discounts to the booking interface and trigger SMS or email notifications to customers featuring the discounted offer. Update appointment records with discount details and ensure seamless integration between notification services and the scheduling system.

Acceptance Criteria
Discount Applied at Booking Interface
Given a calculated discount exists for a selected bay, when a customer accesses the booking interface, then the interface displays the discounted price instead of the standard price; the discount label clearly shows both the percentage and the final price; the displayed discount updates in real time if bay idleness or booking urgency changes before confirmation
Notification Trigger on Discount Calculation
Given a discount is applied to a pending booking, when the system confirms the discount calculation, then an event is dispatched to the messaging service with the customer contact, discount amount, and booking details; no duplicate events are generated for the same booking
SMS Notification Delivery Verification
Given an SMS notification is triggered, when the messaging service processes the notification, then the customer receives the SMS within 2 minutes; the SMS content matches the approved template including discount details and booking information; the system logs the delivery status as 'Delivered' or provides an error code if delivery fails
Email Notification Content Accuracy
Given an email notification is triggered, when the email is sent, then the email content includes the correct discount percentage, final price, and booking slot information; the email subject is 'Your Discounted Appointment Confirmation'; the email passes HTML validation with no broken links or missing images
Appointment Record Update with Discount Details
Given a discount application event completes, when the appointment is created or updated, then the appointment record includes fields for discount percentage, discount amount, and original price; discount details are visible in the admin UI; audit logs capture the timestamp and source of the discount update

Tiered Waitlist Rewards

Segments waitlisted customers into loyalty tiers and urgency levels, delivering personalized discount offers that resonate with each group. By tailoring incentives to customer history and shop priorities, it boosts acceptance rates and deepens customer loyalty.

Requirements

Waitlist Tier Segmentation
"As a shop manager, I want to automatically segment waitlisted customers into loyalty tiers so that I can offer appropriate reward incentives that reflect each customer’s value."
Description

Automatically classify waitlisted customers into loyalty tiers (e.g., Bronze, Silver, Gold) based on their historical spending, visit frequency, and service ratings. This segmentation integrates with the customer relationship management (CRM) database to ensure real-time updates as customer profiles evolve. By categorizing customers according to their loyalty status, the system enables targeted incentive strategies that align with the shop’s retention goals and maximize reward efficiency.

Acceptance Criteria
New Customer Waitlist Enrollment
Given a customer with no prior purchase history is added to the waitlist, When the system runs tier segmentation, Then the customer is automatically assigned to the Bronze loyalty tier.
High-Spending Customer Tier Assignment
Given a waitlisted customer with total spend over $2,000 in the past 12 months, When tier segmentation executes, Then the customer is classified into the Gold loyalty tier.
Frequent Visitor Tier Assignment
Given a waitlisted customer with more than five visits in the last six months, When tier segmentation runs, Then the customer is assigned to the Silver loyalty tier.
Real-Time Tier Update on Profile Change
Given a customer's cumulative spend crosses a tier threshold in the CRM, When the CRM record is updated, Then the system updates the customer's waitlist tier within five minutes.
CRM Integration Data Sync
Given new transaction data in the CRM, When the CRM sync occurs, Then the waitlist tier segmentation reflects the updated data without errors and within the defined sync window.
Urgency Level Assignment
"As a shop manager, I want the system to assign urgency levels to waitlisted appointments so that high-priority customers are offered openings first and lead times are minimized."
Description

Determine and assign urgency levels to each waitlisted appointment request using factors such as requested service date, current bay availability, and average job duration. The system calculates a priority score that influences the order in which customers are offered openings. By distinguishing between low-, medium-, and high-urgency requests, the shop can optimize capacity utilization and reduce lead times for critical repairs.

Acceptance Criteria
High Urgency Request with Limited Bay Availability
Given a customer requests service within 24 hours and available bays are below the defined threshold, when the system calculates the priority score, then it assigns a High urgency level with a score above 80.
Medium Urgency Request for Standard Service Slot
Given a customer requests service 2 to 3 days out and bay availability is adequate, when the system calculates the priority score, then it assigns a Medium urgency level with a score between 50 and 80.
Low Urgency Request for Future Booking
Given a customer requests service more than 3 days in advance, when the system calculates the priority score, then it assigns a Low urgency level with a score below 50.
Dynamic Urgency Recalculation on Bay Availability Update
When bay availability changes by one or more bays, then the system automatically recalculates the urgency levels and priority scores for all waitlisted requests with service dates within the next 48 hours.
Priority Queue Ordering based on Urgency Levels
Given multiple waitlisted requests, when generating the offer list, then the system orders customers first by High urgency, then Medium, then Low, and within each tier by descending priority score.
Personalized Discount Engine
"As a pricing strategist, I want discounts tailored to customer tier and urgency so that acceptance rates increase without compromising shop margins."
Description

Generate customized discount offers by combining loyalty tier, urgency level, and current shop capacity, while ensuring compliance with predefined margin rules. Discounts are calculated dynamically using business-defined algorithms to balance customer incentives and profitability. Integration with the pricing module provides real-time rate adjustments and safeguards against over-discounting.

Acceptance Criteria
Calculating Discount Based on Loyalty Tier and Urgency
Given a waitlisted customer with a defined loyalty tier and urgency level, when the engine generates a discount, then the discount percentage must match the predefined values for that tier and urgency combination.
Adjusting Discount According to Shop Capacity
Given the shop’s current bay utilization rate, when capacity falls below the threshold, then the engine must increase the discount within allowed bounds; when capacity is above the threshold, then the discount must not exceed the base rate for that tier and urgency.
Ensuring Compliance with Margin Rules
Given the calculated discount, when applied to the standard service price, then the resulting margin must not drop below the minimum margin defined in the margin rules.
Real-Time Integration with Pricing Module
Given a real-time pricing update from the pricing module, when the discount engine receives it, then it must recalculate any pending discount offers within 500ms and reflect the new pricing in the generated offer message.
Preventing Over-Discounting Safeguards
Given margin rules and shop capacity constraints, when a calculated discount exceeds allowable limits, then the system must cap the discount at the maximum allowed value and log a warning event.
SMS Discount Notification
"As a customer, I want to receive personalized SMS offers when an earlier appointment opens up so that I can quickly secure a discounted service slot."
Description

Automatically send SMS notifications containing personalized discount offers and secure booking links to waitlisted customers when an appropriate slot becomes available. The notification system supports message scheduling, retry logic for delivery failures, and tracking of click-through and redemption rates. This feature ensures timely communication and simplifies the acceptance process.

Acceptance Criteria
Waitlist Slot Available Notification
Given a waitlisted customer reaches the top of the queue and an appropriate service slot becomes available, when the system detects the availability, then an SMS with the customer’s personalized discount offer and a secure booking link is sent within 1 minute.
Scheduled SMS Dispatch
Given the auto repair shop’s defined notification schedule, when a message is due to be sent outside business hours or during peak times, then the system queues the SMS and dispatches it at the next scheduled window without manual intervention.
Retry Logic on Delivery Failure
Given an attempt to send an SMS notification fails due to network or carrier issues, when no delivery confirmation is received within 5 minutes, then the system automatically retries sending up to 3 times with exponential backoff intervals.
Click-through Tracking
Given an SMS notification is successfully delivered, when the customer clicks the secure booking link, then the system logs the click event against the customer record and updates the click-through rate metric within the analytics dashboard in real time.
Discount Redemption Confirmation
Given a customer books an appointment using the secure link and applies the discount code, when the booking is confirmed, then the system marks the discount as redeemed, updates the customer’s loyalty tier if applicable, and logs the redemption in reporting within 2 minutes.
Analytics Dashboard for Waitlist Rewards
"As a shop owner, I want to view analytics on waitlist reward performance so that I can optimize incentive strategies and improve overall shop profitability."
Description

Provide a comprehensive dashboard that displays key performance metrics—such as offer acceptance rates by tier, revenue generated from waitlist incentives, and reduction in no-shows—through interactive charts and exportable reports. This dashboard integrates with the analytics engine and supports date-range filters, cohort analysis, and scenario simulations to inform strategic adjustments.

Acceptance Criteria
Date-Range Filter Application
Given a user selects a start and end date, When the dashboard applies the filter, Then all displayed metrics (offer acceptance rates, revenue generated, no-show reduction) update to reflect data only within the chosen date range.
Interactive Chart Rendering
Given the dashboard is loaded, When metrics are displayed as charts, Then each chart renders within 2 seconds and shows correct data points with interactive tooltips on hover.
Exportable Reports Generation
Given a user applies filters on the dashboard, When the user exports the report, Then the system generates a CSV and PDF containing all filtered metrics and retains the applied date range, tier, and cohort selections.
Cohort Analysis Drill-Down
Given a user selects a specific customer tier cohort, When the cohort filter is applied, Then the dashboard displays acceptance rates and revenue trends over time for that cohort only.
Scenario Simulation Projection
Given a user inputs hypothetical incentive levels and customer volumes, When the simulation is run, Then the system generates projected impact on acceptance rates and revenue in an interactive chart.

Flash Slot Scheduler

Provides a visual interface for managers to mark upcoming time windows as "Flash Slots," triggering immediate discount campaigns. This makes it easy to plan, launch, and monitor multiple dash periods throughout the day, ensuring consistent bay utilization.

Requirements

Flash Slot Creation Interface
"As a shop manager, I want to visually select and mark time windows as Flash Slots so that I can quickly launch targeted discount campaigns to fill empty bays."
Description

Provide a drag-and-drop calendar interface where managers can select time windows and designate them as Flash Slots, automatically applying discount rules and notifying the scheduler.

Acceptance Criteria
Drag-and-Drop Time Window Selection
Given the manager is viewing the Flash Slot Scheduler calendar interface When the manager drags over a specific time window Then the selected time window is highlighted and the 'Mark as Flash Slot' option is displayed.
Automatic Discount Rule Application
Given a time window is marked as a Flash Slot When the manager confirms the selection Then the system automatically applies the pre-configured discount rules to that slot and updates the pricing in the calendar.
Immediate Scheduler Notification
Given a Flash Slot is successfully created When the manager saves the slot Then the scheduler receives a real-time SMS and in-app notification containing the slot details.
Prevent Overlapping Flash Slots
Given existing Flash Slots on the calendar When the manager attempts to create a new Flash Slot that overlaps Then the system prevents creation and displays an error message indicating the overlap conflict.
Visual Identification of Flash Slots
Given one or more Flash Slots have been created When the manager views the calendar Then each Flash Slot is displayed in a distinct color and shows a tooltip with discount and timing information on hover.
Discount Rule Configuration
"As a shop manager, I want to configure discount rules for Flash Slots based on service types and time constraints so that I can control promotion margins and target specific services."
Description

Enable managers to define discount parameters for Flash Slots, including discount percentage ranges, service categories, and time-based constraints, ensuring promotions align with business goals and maximize revenue.

Acceptance Criteria
Define Discount Percentage Range
Given the manager selects a Flash Slot, when they enter a discount percentage range between 5% and 50%, then the system accepts and saves the values. Given the manager enters a discount percentage less than 0% or greater than 100%, then a validation error “Discount must be between 0% and 100%” appears.
Specify Service Categories for Discounts
Given a list of service categories is displayed, when the manager selects one or more categories, then only the selected categories are included in the discount rule. Given no category is selected, when saving, then the system shows error “Please select at least one service category”.
Set Time-Based Constraints for Flash Slots
Given the manager sets start and end times for a Flash Slot, when the times are within business hours, then the rule is accepted. Given the end time is before the start time, then a validation error “End time must be after start time” displays.
Validation of Discount Rules on Flash Slot Creation
Given a Flash Slot is scheduled with a configured discount rule, when the slot is created, then the discount settings apply to all appointments within the slot. Given the discount rule has overlapping time constraints with another rule, then the system warns of conflict.
Error Handling for Invalid Discount Configurations
Given the manager attempts to save a discount rule with missing required fields, then the system prevents saving and highlights missing fields. Given a system error occurs while saving, then the manager sees a generic error message and can retry.
Real-time Slot Availability Sync
"As a shop manager, I want to see current bay availability in real time while creating Flash Slots so that I can avoid scheduling conflicts and optimize utilization."
Description

Integrate with the scheduling engine to fetch up-to-the-minute bay utilization and display real-time availability during Flash Slot creation, preventing overbooking and ensuring accurate campaign targeting.

Acceptance Criteria
Flash Slot Creation Reflects Real-Time Availability
Given a manager navigates to create a Flash Slot, when the creation form loads, then the system displays available bay time windows updated within the last 5 seconds and prevents selection of any time window that is no longer free.
Prevention of Overbooking During Slot Selection
Given two managers attempt to select the same bay time window simultaneously, when the first manager confirms the slot, then the second manager’s view updates within 2 seconds to mark the slot as unavailable and prevent confirmation.
Error Handling on Sync Failure
Given the scheduling engine API fails to provide updated availability data, when the manager attempts to load or refresh the availability, then the system displays a clear error message 'Unable to fetch real-time availability' and disables the 'Create Slot' button until data can be successfully retrieved.
Automatic Availability Refresh During Slot Configuration
Given the manager is on the Flash Slot creation page for more than 1 minute, when 1 minute of idle time elapses, then the system automatically refreshes and updates bay availability data without requiring a manual refresh.
Automated SMS Campaign Trigger
"As a shop manager, I want SMS notifications triggered when Flash Slots go live so that customers receive timely alerts and I increase booking conversions."
Description

Upon Flash Slot activation, automatically send personalized SMS notifications to customers on the waitlist or matching criteria, informing them of limited-time discounts and providing direct booking links.

Acceptance Criteria
Flash Slot Activation SMS Trigger
Given a manager activates a Flash Slot in the scheduler interface When activation is confirmed Then within 1 minute the system retrieves all waitlist and matching-criteria customers, generates personalized SMS messages containing the flash discount and unique booking links, and enqueues them for delivery
Waitlist Notification Dispatch
Given there are customers on the waitlist for the activated service type When a Flash Slot is launched Then the system sends SMS notifications to the top priority customers, ensures delivery within 2 minutes, and logs the delivery status for each recipient
Personalized SMS Content Validation
Given customer profile data is available When assembling the SMS message Then the template auto-populates the customer’s name, vehicle model, flash discount details, slot time, and a trackable booking link, ensures message length ≤160 characters, and includes UTM parameters for campaign tracking
Invalid Phone Number Handling
Given the customer list includes invalid or malformed phone numbers When SMS sending attempts fail due to invalid numbers Then the system logs the failure reason, marks the number as invalid, retries once using a fallback format within 5 minutes, and generates an alert for the admin if the retry fails
SMS Delivery Acknowledgement and Retry
Given an SMS gateway transient error occurs When the initial send attempt fails Then the system retries up to three times at 1-minute intervals, logs each attempt, and if all retries fail, flags the campaign status as failed and notifies the operations team
Flash Slot Performance Analytics
"As a shop manager, I want to view analytics for my Flash Slot campaigns so that I can measure their performance and refine future promotions."
Description

Offer a dashboard with key metrics for each Flash Slot campaign, including booking rate, redemption rate, revenue impact, and bay utilization improvement, allowing managers to assess effectiveness and iterate promotions.

Acceptance Criteria
Booking Rate Metric Accuracy Verification
Given a completed Flash Slot campaign with X available slots and Y confirmed bookings, when the dashboard calculates the booking rate, then it shall display (Y/X)*100% rounded to one decimal place and match the value returned by the analytics service.
Redemption Rate Trend Visualization
Given multiple Flash Slot campaigns run over a selected date range, when the manager views the Redemption Rate metric, then the dashboard shall render a trend line chart showing percentage redeemed for each campaign with hover tooltips displaying exact values.
Revenue Impact Calculation
Given actual revenue figures for the period before and during a Flash Slot campaign, when the dashboard computes revenue impact, then it shall display both the absolute revenue difference and the percentage change compared to the prior period.
Bay Utilization Improvement Display
Given baseline bay utilization and utilization data captured during a Flash Slot, when viewing Flash Slot analytics, then the dashboard shall display the percentage improvement in bay utilization and flag campaigns that achieve at least 10% improvement.
Dashboard Response Time Under Load
Given up to 100 concurrent users accessing the Flash Slot Performance Analytics dashboard, when loading any metric panel, then the dashboard shall fully render the content within 2 seconds.

Countdown Campaign

Enhances SMS offers with embedded live countdown timers and real-time slot availability indicators. The urgency-driven messaging encourages faster customer action, slashing decision time and filling empty bays within minutes.

Requirements

Real-time Countdown Timer Embedding
"As a shop manager, I want customers to see a live countdown timer in their SMS offers so that they feel a sense of urgency and book appointments quickly."
Description

Implement the ability to embed a live countdown timer within SMS offers. The timer displays the remaining time until the offer expires, updates in real time across different devices, and integrates seamlessly with the messaging system to drive urgency. It should render correctly on major mobile clients and adapt to user time zones, ensuring accurate countdowns for all recipients.

Acceptance Criteria
Timer Initialization on SMS Receipt
Given a user receives an SMS with an embedded countdown timer, When the user opens the SMS within 60 seconds of receipt, Then the countdown timer initializes and displays the correct remaining time until offer expiration.
Real-Time Countdown Accuracy Across Timezones
Given users in different time zones receive the same SMS offer, When each user views the countdown timer, Then the timer reflects the identical global expiration moment adjusted correctly to each user’s local time zone.
Responsive Rendering on Major Mobile Clients
Given users open the SMS on supported mobile clients (iOS Messages, Android default SMS, popular third-party apps), When the countdown timer is displayed, Then it renders without visual distortion, maintains legibility, and refreshes in real time on iOS 15+, Android 11+, and top third-party SMS apps.
Graceful Fallback in Unsupported Clients
Given an SMS client that does not support dynamic countdown timers, When the user opens the message, Then a static image of the countdown and the textual expiration timestamp are displayed in place of a live timer.
Seamless Integration with SMS Campaign Workflow
Given an SMS campaign scheduled with embedded timers, When the messaging system dispatches the offer, Then the messages are delivered without delay and timers begin countdown within 5 seconds of the SMS being opened by recipients.
Dynamic Slot Availability Indicator
"As a customer, I want to see available appointment slots directly in the SMS so that I can choose a time without navigating away or calling the shop."
Description

Develop a dynamic slot availability indicator that shows real-time open appointment slots within SMS messages. This feature queries the scheduling engine for current bay availability and reflects changes instantly, preventing overbooking and improving transparency. It enhances customer trust by showing only viable time slots and encourages rapid decision-making.

Acceptance Criteria
Customer views available slots in SMS
Given a customer opens the SMS offer link When the system queries the scheduling engine Then only slots with real-time availability are displayed, each showing the current available bay count retrieved within the last 5 seconds
Slot selection updates availability in real-time
Given a customer is viewing available slots When another booking changes a slot’s availability Then the displayed availability count updates within 5 seconds without requiring a manual refresh
Prevents overbooking under concurrent requests
Given two customers attempt to book the same slot concurrently When both booking requests are submitted Then only the first request is confirmed and the second customer receives a 'slot unavailable' notification
Handles fully booked slots gracefully
Given all appointment slots are fully booked When a customer opens the SMS link Then the SMS displays 'No slots available' instead of showing slot listings
Fallback when scheduling engine is unreachable
Given the scheduling engine is unreachable When a customer opens the SMS link Then the system displays a maintenance message and disables booking actions
SMS Template Customization with Timers
"As a shop manager, I want to customize SMS templates with countdown timers and my shop branding so that messages align with our marketing style and feel personalized to recipients."
Description

Provide a user interface for customizing SMS templates to include countdown timers, slot indicators, and personalized branding. Shop managers should be able to select template layouts, adjust countdown duration, and preview messages before sending. Templates should support placeholders for customer names, service types, and unique offer codes.

Acceptance Criteria
Template Layout Selection
Given the shop manager is on the SMS template customization page and sees multiple layout options, When the manager selects a layout and clicks save, Then the chosen layout is applied and persists when reopening the template.
Countdown Timer Configuration
Given the manager accesses the countdown timer settings, When the manager sets a duration (e.g., 48 hours) and saves, Then the preview displays a live countdown timer reflecting the exact duration configured.
Placeholder Population
Given the manager inserts placeholders for customer name, service type, and offer code, When generating a preview with sample data (e.g., John Doe, Oil Change, SUMMER21), Then the preview text replaces placeholders correctly with the sample values.
Branding Customization
Given the manager uploads a logo and selects brand colors, When viewing the template preview, Then the uploaded logo and selected brand colors are rendered accurately.
Slot Availability Indicator Integration
Given the manager includes a slot availability indicator in the template, When previewing with real-time data showing 3 open slots, Then the preview displays "Only 3 slots left!" and updates if availability changes.
Automated Trigger Based on Vacancy
"As a shop manager, I want the system to automatically send countdown campaign SMS when a bay opens up so that I can quickly fill unexpected openings without manual intervention."
Description

Create an automated rule engine that triggers countdown campaign SMS when specific appointment bays become unfilled or when cancellation occurs. The system should monitor bay status in real time and dispatch targeted SMS with embedded timers to relevant customer segments based on predefined criteria like service history or location.

Acceptance Criteria
Single Bay Vacancy Trigger
Given a single service bay status changes to 'vacant' When the system detects the vacancy within 30 seconds Then an SMS countdown campaign is sent to the top 10 local customers within 1 minute of detection
Multiple Bay Vacancy Threshold
Given three or more service bays become unfilled simultaneously When the third bay status is recorded as 'vacant' Then a bulk countdown SMS is dispatched to the 'high-value' customer segment within 2 minutes
Cancellation-Induced Vacancy Trigger
Given a customer cancels an appointment less than 24 hours before the slot When cancellation is confirmed in the system Then an SMS countdown campaign is sent to eligible nearby customers matching service type within 1 minute
Customer Segmentation Targeting
Given a vacancy trigger occurs When selecting recipients Then only customers with matching service history and active SMS opt-in status are targeted and at least 95% of recipients meet these criteria
Real-Time SMS Dispatch Verification
Given a countdown campaign is triggered When SMS messages are sent Then 100% include the correct live countdown timer and availability indicator and delivery success rate is at least 90%
Analytics Dashboard for Countdown Campaigns
"As a shop manager, I want to view detailed analytics on my countdown campaigns so that I can measure effectiveness and optimize future offers."
Description

Design and implement an analytics dashboard within PulseQueue to monitor the performance of countdown campaigns. The dashboard should display metrics such as open rates, click-through rates on slot indicators, conversion rates, average time to booking after SMS, and revenue uplift. It should support filtering by date range, shop location, and service type.

Acceptance Criteria
Real-Time Metric Display
Given the user opens the analytics dashboard, when the page loads then open rates, click-through rates, conversion rates, average time to booking after SMS, and revenue uplift metrics are displayed and updated within 5 seconds.
Filter by Date Range
Given the user sets a start and end date on the date-picker, when the filter is applied then the dashboard only shows metrics for countdown campaigns sent within the selected date range.
Shop Location Drill-Down
Given multiple shop locations in the system, when the user selects a specific location then all displayed metrics update to reflect only campaigns run at that location.
Service Type Comparison
Given different service types are available, when the user selects one or more service types from the filter, then click-through rates and conversion rates recalculate and display for those selected services only.
Revenue Uplift Calculation
Given historical baseline revenue data, when the dashboard displays revenue uplift then it calculates the percentage increase compared to baseline and shows the result in both chart and numeric formats.

One-Tap Booking

Embeds a single-click confirmation button directly in the SMS offer, automatically finalizing the discounted slot and syncing it to the customer’s calendar. This frictionless experience reduces drop-offs and accelerates conversion.

Requirements

SMS Confirmation Button
"As a customer receiving a discounted slot offer via SMS, I want to tap a ‘Confirm Booking’ button so that my appointment is instantly reserved without additional steps."
Description

Embed a dynamic ‘Confirm Booking’ button within the SMS offer message that, when tapped by the recipient, triggers an API call to reserve the discounted appointment slot. The button should render correctly across major SMS clients and handle user interactions gracefully, providing visual feedback. This feature reduces friction by eliminating the need for manual replies and accelerates conversion by offering a single-tap booking experience.

Acceptance Criteria
User Taps Confirm Booking on Android Messaging App
Given the user receives an SMS with the confirm booking button on an Android device, when the user taps the button, then the system must call the booking API, reserve the slot, display an in-message confirmation banner, and add the appointment to the user’s Google Calendar within 60 seconds.
User Taps Confirm Booking on iOS Messages
Given the user receives an SMS with the confirm booking button in the iOS Messages app, when the user taps the button, then the system must call the booking API, reserve the slot, display a native success alert, and add the appointment to the user’s Apple Calendar within 60 seconds.
SMS Client Without Native Button Support
Given the user’s SMS client does not render interactive buttons, when the user views the message, then a fallback URL link must be displayed, and tapping the link must open the booking page in a browser, call the booking API, and show a confirmation screen.
Handling API Failures on Confirmation Tap
Given the user taps the confirm booking button and the booking API returns an error or times out, when the error occurs, then the user must see an error message with a retry option, and no booking must be recorded.
Visual Feedback and Idempotency on Multiple Taps
Given the user taps the confirm booking button multiple times before receiving a response, when duplicate taps occur, then only one API call must be processed, and subsequent taps must show a loading indicator or disabled button until completion.
Calendar Entry Accuracy Verification
Given a successful booking via the confirm button, when the appointment is synced to the user’s calendar, then the event details must match the reserved slot (date, time, shop name, and service type) with no discrepancies.
Real-time Calendar Sync
"As a shop manager, I want confirmed bookings to sync to our calendar automatically so that I don’t have to manually update schedules."
Description

Automatically synchronize confirmed bookings to both the customer’s personal calendar (Google Calendar, iCal, Outlook) and the shop’s internal scheduling system in real time. The integration should use standard calendar APIs and webhooks to ensure consistency across platforms, preventing double bookings and manual entry errors.

Acceptance Criteria
Customer Calendar Sync Success
Given a booking is confirmed via one-tap SMS When the system invokes the customer's calendar API (Google Calendar, iCal, or Outlook) Then the event is created on the customer's calendar with correct date, time, title, and location And a successful sync entry is logged in the system audit log.
Shop Internal Calendar Sync Success
Given a confirmed booking exists When the system sends booking data to the shop's internal scheduling API Then the booking appears in the shop's calendar with matching details within 2 seconds And no duplicate entries are created.
API Failure Handling
Given a calendar API request returns an error or times out When the sync attempt fails Then the system retries the sync up to 3 times with exponential backoff And logs the failure notification in the admin dashboard for manual review.
Duplicate Booking Prevention
Given a booking request for a customer or time slot already present When the sync process runs Then the system detects existing events by unique identifier And prevents creation of duplicates by updating the existing event details instead.
Authentication Token Refresh
Given an expired OAuth token for a calendar service When the sync process attempts an API call Then the system automatically refreshes the token And proceeds with event creation without manual intervention.
Discount Slot Allocation Engine
"As a shop manager, I want the system to suggest discounted appointment slots automatically so that empty bays are filled efficiently."
Description

Implement logic to dynamically generate discounted appointment slots based on current bay utilization, technician availability, and shop operating hours. The engine should calculate optimal discount levels to maximize fill rates and automatically include these slots in outbound SMS campaigns.

Acceptance Criteria
Optimal Discount Calculation During Peak Hours
Given bay utilization is 80% or higher, when generating discounted slots, then the engine calculates a discount between 15% and 30% proportional to utilization to target a 40% fill rate increase.
Technician Availability-Based Slot Generation
Given technician schedules for the next 7 days, when the engine runs slot allocation, then only create slots where at least one technician is available for the full estimated service duration.
Operating Hours Compliance
Given shop operating hours are defined, when generating slots, then ensure no slot starts before opening time or ends after closing time and respects lunch breaks.
SMS Campaign Slot Inclusion
Given new discounted slots have been generated, when preparing the outbound SMS campaign, then include all newly created discounted slots in the campaign payload with valid time, date, and discount information.
Dynamic Load Balancing Across Bays
Given varying bay utilizations across the day, when generating discounted slots, then distribute discounted appointments across underutilized bays to balance load and optimize utilization.
Confirmation Notifications
"As a customer, I want to receive a confirmation SMS so that I’m assured my booking is finalized and can view the details immediately."
Description

After a user confirms a slot via the one-tap button, send a confirmation SMS receipt to the customer and an internal notification to the shop manager or front-desk system. Notifications should include appointment details, discount applied, and a link to reschedule or cancel if needed.

Acceptance Criteria
SMS Confirmation Sent to Customer
Given a user taps the one-tap confirmation button in the SMS offer, When the system processes the confirmation, Then an SMS receipt is sent to the customer’s phone number containing appointment date, time, and service type.
Internal Notification Sent to Manager
Given a slot confirmation is received, When the booking is finalized, Then an internal notification is delivered to the shop manager’s front-desk system with customer name, appointment details, and discount applied.
SMS Contains Appointment and Discount Details
Given the confirmation SMS is dispatched, Then the message body clearly lists appointment date, appointment time, service type, and the exact discount amount or code applied.
Reschedule and Cancel Links are Functional
Given the customer receives the confirmation SMS, When the customer clicks the reschedule link, Then they are directed to a pre-populated rescheduling interface; And when they click the cancel link, Then they see a cancellation confirmation prompt.
Notifications Logged in Shop System
Given the confirmation process completes, Then both the outbound SMS and internal notification events are recorded in the system audit log with timestamps, customer details, and appointment metadata.
One-Tap Booking Analytics
"As a product owner, I want analytics on one-tap booking usage so that I can assess feature effectiveness and optimize future campaigns."
Description

Capture key metrics for one-tap booking interactions—including button click-through rates, successful bookings, conversion time, and no-show reductions—and display them in the PulseQueue analytics dashboard. Provide filters by date range, discount level, and shop location to enable performance monitoring.

Acceptance Criteria
Metrics Capture on Click
Given a user receives an SMS with a one-tap booking button When the user clicks the button Then the system records the click timestamp and increments the click-through count
Successful Booking Recording
Given a user completes a one-tap booking When the booking is confirmed Then the system logs the booking event and updates the total bookings metric
Conversion Time Calculation
Given recorded timestamps for SMS delivery and booking confirmation When calculating conversion time Then the dashboard displays the average and individual conversion times accurately
No-Show Reduction Tracking
Given booking records with attendance status When comparing no-show rates pre- and post-one-tap implementation Then the dashboard shows the percentage reduction in no-shows for the selected period
Date Range Filtering
Given a selected date range filter When applied on the analytics dashboard Then all displayed metrics update to reflect only interactions within that date range
Discount Level Filtering
Given a selected discount level filter When applied on the analytics dashboard Then metrics displayed correspond only to bookings made under that discount level
Shop Location Filtering
Given a selected shop location filter When applied on the analytics dashboard Then metrics displayed correspond only to the chosen shop's data

Deal Performance Analytics

Delivers a dedicated dashboard reporting on discount dash metrics—conversion rates, revenue uplift, average response time, and ROI. Shops can quickly identify top-performing strategies, refine discount thresholds, and optimize future campaigns.

Requirements

Data Integration Pipeline
"As a shop manager, I want the system to automatically ingest and consolidate campaign data across channels so that I can trust that the analytics dashboard reflects all relevant metrics without manual data preparation."
Description

Ingest and consolidate raw data from multiple sources—including booking systems, payment gateways, and SMS reminders—into a unified dataset, applying validation, normalization, and archival processes to ensure the dashboard reflects accurate, up-to-date metrics.

Acceptance Criteria
Booking System Data Ingestion
Given new booking records exist in the source system When the data integration pipeline executes Then all booking records are ingested into the unified dataset within 5 minutes without errors
Payment Gateway Data Validation
Given payment transactions are provided by the gateway API When the pipeline processes payment records Then only transactions with valid status codes are stored And any invalid or duplicate transactions are logged for review
SMS Reminder Data Sync
Given SMS reminder logs are generated daily When the pipeline fetches SMS data Then all reminder records sent that day are consolidated into the dataset And delivery status and timestamps are accurately recorded
Data Normalization Across Sources
Given varied field formats across booking, payment, and SMS data When the pipeline normalizes incoming records Then dates are standardized to ISO8601 format And numeric fields (e.g., amount, duration) are converted to uniform units
Historical Data Archival
Given data older than 12 months exists in the active dataset When the archival process runs monthly Then records older than 12 months are moved to the archive store And archive integrity is verified with checksum validation
Real-Time Conversion Tracking
"As a marketing coordinator, I want to see conversion rates update in real time so that I can quickly adjust promotions based on performance."
Description

Capture and process discount interaction events in near real time, calculating conversion rates immediately as customers respond to offers, and updating visual metrics on the dashboard with minimal latency.

Acceptance Criteria
Real-Time Offer Acceptance Update
Given a customer accepts a discount offer via SMS When the system captures the interaction event Then the conversion rate metric on the dashboard is updated within 2 seconds
High-Volume Event Processing
Given 1000 discount interactions occur concurrently When the system processes incoming events Then all conversion rate calculations complete successfully and metrics display without error
Ingestion Error Retry Mechanism
Given an incoming interaction event fails due to network issues When retry logic is invoked Then the event is successfully ingested and conversion rate metrics update within 5 seconds or an alert is generated
Conversion Rate Period Comparison
Given the dashboard displays current conversion rates When a user views the analytics section Then the system compares the last 24-hour conversion rate to the previous 24-hour period and shows the percentage change
Processing Latency Alert
Given continuous event processing When end-to-end processing time exceeds 3 seconds Then the system logs a latency warning and sends a notification to administrators
Revenue Uplift Analysis
"As a shop owner, I want to understand how much additional revenue each discount campaign generates so that I can justify marketing spend and optimize future offers."
Description

Compute revenue uplift by comparing campaign-period revenue against established baselines, breaking down results by campaign, discount tier, and time period to reveal the true incremental financial impact of each promotion.

Acceptance Criteria
Comparing Campaign Period Revenue to Baseline
Given a campaign with recorded revenue and a defined baseline, when the system runs revenue uplift analysis, then the displayed uplift equals campaign revenue minus baseline revenue for the selected period.
Breaking Down Revenue Uplift by Discount Tier
Given multiple discount tiers used in a campaign, when the system generates uplift reports, then each tier's revenue uplift is individually calculated and displayed in the breakdown table.
Analyzing Time Period Revenue Impact
Given a specified time period filter, when the user selects the filter in the dashboard, then the system recalculates and displays revenue uplift for that period only.
Validating Incremental Revenue Calculations
Given sample datasets with known revenue values, when the analysis algorithm runs, then the calculated incremental revenue matches the precomputed expected values within a 1% tolerance.
Assessing Campaign-Level ROI
Given campaign cost data and revenue uplift results, when ROI is computed, then the system displays ROI as (revenue uplift - cost)/cost with an accuracy of two decimal points.
Discount Threshold Optimization Engine
"As a shop owner, I want the system to recommend the most effective discount thresholds so that I can maximize both conversion rates and profit margins."
Description

Analyze historical conversion, margin, and ROI data to identify optimal discount levels; generate dynamic recommendations for adjusting thresholds to maximize both customer uptake and overall profitability.

Acceptance Criteria
Historical Data Ingestion Completed
Given the system has access to the historical dataset, when data ingestion runs, then 100% of conversion, margin, and ROI records for the past 12 months are imported without errors and schema compliance is validated.
Optimal Discount Level Computation
Given validated historical data, when the optimization engine executes, then it calculates a discount level that maximizes projected ROI while ensuring conversion uplift of at least 10%, and completes computation within two minutes.
Recommendation Display to Manager
Given optimized discount recommendations are available, when the manager opens the dashboard, then they see the recommended discount level, expected conversion increase, and ROI impact displayed accurately within 5% of computed values.
Threshold Adjustment Application
Given the manager accepts or modifies the recommended threshold, when they confirm their choice, then the system updates the active discount threshold immediately, logs the change with timestamp and user ID, and displays a success confirmation.
Performance Monitoring Post-Implementation
Given an updated discount threshold is live, when seven days elapse, then the system generates a performance report comparing actual conversion rate, margin, and ROI against projections, highlighting variances.
ROI Reporting Dashboard
"As a shop manager, I want a clear ROI report for each campaign so that I can decide which strategies are most cost-effective."
Description

Present comprehensive campaign ROI metrics—including cost of discounts, revenue gains, and net profit—in interactive charts and tables, enabling users to compare performance across campaigns and time frames easily.

Acceptance Criteria
Initial Dashboard Data Load
Given the user navigates to the ROI Reporting Dashboard, when the page loads, then total discount costs, revenue gains, and net profit are displayed correctly within 5 seconds.
Date Range Filter Application
Given the user selects a custom date range and applies the filter, then all dashboard charts and tables update to show metrics exclusively for the chosen period.
Campaign Comparison View
Given the user selects multiple campaigns for comparison, when comparison mode is activated, then the dashboard presents side-by-side ROI metrics for each selected campaign.
Interactive Chart Drill-down
Given the user clicks on any chart segment, when drill-down is triggered, then detailed campaign metrics appear in a tooltip or subview without a full page reload.
Exportable Report Generation
Given the user clicks the export button and chooses CSV or PDF, then the system generates and downloads a file containing the displayed ROI metrics and comparisons.

InstantVoice Sync

Transcribe and update job statuses in real time through voice commands, eliminating manual data entry and ensuring the scheduler always reflects the latest progress instantly.

Requirements

Voice Command Recognition Module
"As a service advisor, I want to initiate job status updates through simple voice commands so that I can keep my hands on tasks and reduce time spent on manual data entry."
Description

Capture and process live audio input from users via mobile or desktop interfaces, accurately detecting the start and end of voice commands, filtering background noise using advanced algorithms, and converting speech to text in real time with sub-500ms latency. Integrate with device microphones and support wake-word activation to ensure seamless activation and continuous listening without manual intervention.

Acceptance Criteria
Wake-Word Activation Deployment
Given the application is running in the foreground or background, When the user says the configured wake word 'Hey PulseQueue', Then the system begins capturing audio input within 100ms and transitions to active listening mode.
Background Noise Filtering
Given ambient background noise up to 60dB, When the user issues a voice command, Then the system filters out noise and achieves at least 90% word accuracy in the transcribed text.
Voice Command Boundary Detection
Given a user voice command preceded and followed by at least 0.5 seconds of silence, When the user finishes speaking, Then the system correctly identifies the speech start and end times and delivers the complete transcription.
Real-Time Transcription Latency
Given a voice command of up to 10 words, When the user completes speaking, Then the converted text is displayed in the UI within 500 milliseconds of speech end.
Device Microphone Integration
Given the user grants microphone permission, When the application initiates voice capture, Then the system successfully accesses the device microphone and streams audio without errors.
Real-Time Transcription Engine
"As a technician, I want my spoken job progress reports to be transcribed instantly so that the scheduler reflects the latest status without manual typing."
Description

Convert captured audio streams into text instantaneously using AI-powered speech-to-text models optimized for automotive terminology. Ensure at least 95% accuracy for common shop phrases, insert punctuation automatically, support speaker diarization for multi-user scenarios, and stream transcription results to the status update pipeline with minimal delay.

Acceptance Criteria
Single-User Voice Update Scenario
Given a single mechanic issues a job status update via voice command, when the audio is captured, then the transcription engine converts speech to text with at least 95% accuracy for predefined shop phrases.
Multi-Speaker Diarization Scenario
Given two or more users speak during a session, when the audio is processed, then the system must correctly assign speaker labels with at least 90% diarization accuracy.
Noisy Shop Environment Scenario
Given ambient shop noise up to 70 dB, when audio is streamed to the transcription engine, then the system maintains at least 95% transcription accuracy for common shop terminology.
Automatic Punctuation Insertion Scenario
Given a continuous spoken sentence requiring punctuation, when transcription output is generated, then the engine inserts commas, periods, and question marks correctly in at least 98% of instances.
Real-Time Streaming Delay Scenario
Given a live audio stream, when transcription results are transmitted to the status update pipeline, then the end-to-end latency does not exceed 500 milliseconds.
Job Status Mapping Service
"As a scheduler, I want spoken updates to automatically map to the correct job status so that the appointment board remains accurate."
Description

Interpret transcribed text to identify job identifiers and statuses, applying natural language understanding to parse commands such as “Job 123: testing complete.” Map parsed commands to internal status codes (e.g., In Testing to Testing Complete), trigger secure database updates, validate recognition confidence levels above 80%, handle ambiguous inputs with fallback prompts, and log all changes for audit and rollback purposes.

Acceptance Criteria
Valid Command Parsing and Update
Given a voice command 'Job 123: testing complete' with recognition confidence ≥80%, when the system parses the transcript, then it maps the status to 'Testing Complete' and updates the database record for job 123 successfully.
Low Confidence Command Handling
Given a voice command 'Job 456: assemble parts' with recognition confidence <80%, when the system assesses the confidence level, then it rejects the update and issues a fallback prompt requesting the user to repeat or confirm the command.
Ambiguous Input Fallback Prompt
Given a voice command 'Job 789: complete' that could map to multiple internal statuses, when the system cannot unambiguously determine the target status, then it triggers a clarifying prompt listing possible status options.
Database Update and Logging
Given a successfully parsed command with valid job ID and status, when the system applies the update, then it performs the database transaction within a secure context, logs the timestamp, job ID, old status, new status, and user interaction details, and ensures rollback on failure.
Idempotent Status Update
Given the same valid voice command received twice for an unchanged status, when the system processes the second request, then it recognizes no status change is needed, returns an acknowledgment without duplicating log entries, and maintains data integrity.
Audit Log Recording
Given any successful status update, when the system completes the database transaction, then it writes an immutable audit record containing the job ID, previous status, updated status, confidence score, timestamp, and source identifier.
Voice Feedback and Error Handling
"As a service manager, I want the system to confirm my voice commands or ask for clarification if uncertain so that I can trust the updates are correct."
Description

Provide immediate audible or visual feedback confirming successful command execution or indicating errors. Utilize text-to-speech and on-screen notifications to read back updated statuses, prompt users for clarification when recognition confidence is low, allow quick correction via follow-up commands, and ensure workflows remain uninterrupted by gracefully handling misrecognitions.

Acceptance Criteria
Successful Voice Command Confirmation
Given a user issues a valid voice command, when the system recognizes the command with confidence above 90%, then the job status is updated accordingly, an audible confirmation is played via text-to-speech within 2 seconds, and the same confirmation message is displayed on-screen.
Low Confidence Recognition Prompt
Given a user issues a voice command recognized with confidence between 60% and 90%, when the system processes the command, then it should prompt the user with a clarification question via TTS within 3 seconds and display the question on-screen until a yes/no response is received.
Error Correction via Follow-up Command
Given the system has requested clarification after low-confidence recognition, when the user provides a follow-up voice command within 5 seconds, then the system updates the job status to the corrected value, confirms the update audibly and visually, and proceeds with the workflow.
On-screen Notification for Misrecognition
Given the system recognizes a command with confidence below 60% and no clarification response is received within 5 seconds, then an error notification is displayed on-screen stating “Command not recognized. Please try again.” and an alert tone is played.
Continuous Workflow Despite Errors
Given any misrecognition or error in voice input, when the error is detected, then the system logs the failed attempt, maintains the current workflow state without interruption, and immediately allows the user to issue new voice commands.
Multi-Language Command Support
"As a bilingual technician, I want to use the voice sync feature in my preferred language so that I can update job statuses comfortably."
Description

Support voice commands in at least English and Spanish to accommodate diverse shop staff. Automatically detect the selected language from user profile settings, apply appropriate speech recognition and transcription models per language, and allow seamless switching without manual reconfiguration. Provide localized documentation and training materials for each supported language.

Acceptance Criteria
English Voice Command Transcription
Given user’s profile language is set to English, when user speaks a valid voice command in English (e.g., "Set job status to in progress"), then the system must transcribe the command with at least 95% accuracy and update the job status accordingly.
Spanish Voice Command Transcription
Given user’s profile language is set to Spanish, when user speaks a valid voice command in Spanish (e.g., "Actualizar estado a completado"), then the system must transcribe the command with at least 95% accuracy and update the job status accordingly.
Seamless Language Switching
Given user changes preferred language in their profile from English to Spanish, when the next voice command is issued in Spanish, then the system must automatically apply the Spanish speech recognition model without any manual reconfiguration.
Access Localized Documentation
Given user’s profile language is set to English or Spanish, when user requests help or opens training materials, then the system must display the documentation in the selected language within 1 second.
Unsupported Language Handling
Given user’s profile language is set to an unsupported language, when user issues a voice command, then the system must display an error notification indicating support for English and Spanish only and prompt the user to switch to a supported language.

GuidedPrompt

Provide context-aware voice prompts that guide technicians to capture structured updates—such as time logs, parts used, and next steps—ensuring completeness and consistency in every job report.

Requirements

Voice Recognition Accuracy
"As a technician, I want the system to accurately transcribe my spoken updates so that I can efficiently record job details without manual corrections."
Description

Integrate a high-fidelity speech-to-text engine that accurately captures technician voice inputs with noise-reduction filters and domain-specific vocabulary for automotive terminology. This requirement ensures minimal transcription errors, seamless hands-free data entry, and compatibility with existing job report frameworks in PulseQueue. It will improve data integrity, reduce manual correction overhead, and enhance technician adoption by providing reliable voice-driven interactions.

Acceptance Criteria
Background Noise Handling
Given the shop environment with noise levels up to 85 dB, when a technician speaks a standard voice prompt, then the speech-to-text engine transcribes the input with at least 95% word accuracy.
Automotive Terminology Recognition
When a technician uses domain-specific terms (e.g., engine knock, torque converter) during voice input, then the engine correctly transcribes these terms with 98% accuracy or higher.
Real-Time Transcription Latency
Given continuous voice input from a technician, when speech ends, then the transcription appears in the GuidedPrompt interface within 2 seconds.
Hands-Free Operation Compatibility
When a technician initiates a voice session without interacting with the device (hands-free), then the system captures and transcribes continuous speech for up to 5 minutes without interruption.
Integration with Job Report Framework
Given the transcribed text, when the speech-to-text engine outputs the content, then it populates the corresponding fields in the job report template without formatting errors and matches the spoken content exactly.
Contextual Trigger Mechanism
"As a technician, I want the system to prompt me at the right time based on my current task so that I don’t miss recording critical job information."
Description

Develop a context-aware engine that analyzes real-time job metadata—such as repair type, bay occupancy, and technician location—to trigger relevant voice prompts at appropriate workflow milestones. This component integrates with the appointment scheduler and job status modules in PulseQueue, ensuring prompts are delivered exactly when needed to capture timely updates and prevent data omissions.

Acceptance Criteria
Job Start Voice Prompt Trigger
Given a technician starts a new repair job When the job status changes to 'In Progress' Then the system delivers a voice prompt requesting the initial time log and confirmation of repair type.
Parts Usage Prompt Trigger
Given a technician scans or enters a part into the job record When the part addition is confirmed Then the system issues a voice prompt requesting the quantity used and part number validation.
Completion Milestone Prompt
Given a repair sub-task is marked complete When the job status updates to 'Sub-task Completed' Then the system delivers a voice prompt asking for next steps and estimated remaining time for the overall repair.
Bay Occupancy Change Prompt
Given bay occupancy drops below 50% and remains unchanged for 5 minutes When the system detects the idle state Then it issues a voice prompt reminding the technician to update job status or request a new assignment.
Technician Location-Based Prompt
Given the technician arrives at the designated inspection area When GPS or RFID confirms location entry Then the system triggers a voice prompt requesting completion of the inspection checklist and any observations.
Structured Update Capture
"As a technician, I want step-by-step voice guidance for entering job details so that my reports are complete and uniformly structured."
Description

Design and implement guided voice prompts that lead technicians through standardized fields for time logs, parts used, labor steps, and next actions. The prompts should enforce data validation rules and populate structured fields in the job report database. This requirement guarantees completeness, consistency, and ease of reporting across all service jobs in PulseQueue.

Acceptance Criteria
Technician Initiates Voice Prompt Session
Given a technician has selected a specific job in the mobile app, When they tap 'Start GuidedPrompt', Then the system begins the first voice prompt for 'Job Start Time' and displays the structured field for input.
Time Log Validation
Given the technician responds with start and end times, When the system captures the times, Then it validates the format (HH:MM) and ensures end time is after start time before storing them.
Parts Auto-Complete Suggestion
Given the technician speaks a part name, When the system recognizes the speech, Then it provides auto-complete suggestions from the parts inventory list and requires selection of a valid part before proceeding.
Guided Labor Step Capture
Given the technician is prompted for 'Labor Steps', When they speak each step, Then the system records up to five discrete steps and populates separate structured fields for each step.
Next Action Confirmation
Given all required fields (time logs, parts used, labor steps, next action) are populated and validated, When the technician confirms 'Finish Report', Then the report is saved to the job report database and a success notification is displayed.
Real-time Prompt Feedback
"As a technician, I want instant feedback on my voice entries so that I can correct mistakes immediately and ensure report accuracy."
Description

Implement a feedback loop that validates technician responses on-the-fly, providing corrective or confirmatory voice messages if entries are missing, ambiguous, or out of expected ranges. This mechanism should integrate with the update capture module to immediately highlight errors and suggest alternatives, improving data accuracy and reducing post-job review overhead.

Acceptance Criteria
Missing Part Usage Entry
Given a technician completes a job report without specifying parts used When the system detects the missing entry Then the system issues a corrective voice prompt requesting the missing part information immediately
Ambiguous Time Log Entry
Given a technician provides an unclear time log (e.g., ’around noon’) When the system receives the ambiguous input Then it asks a follow-up voice question for a precise start or end time using a 24-hour format
Out-of-Range Next Step Input
Given a technician’s stated next step falls outside the predefined list of allowed steps When the system recognizes the out-of-range entry Then it suggests the closest valid alternatives and prompts the technician to confirm or select one
Valid Technician Response Confirmation
Given a technician provides a complete and valid entry for parts, time logs, and next steps When the system verifies all data fields match expected formats and ranges Then it issues a confirmatory voice message acknowledging successful capture of the update
Integration with Update Capture Module
Given the real-time feedback loop is invoked during the job update process When the system routes corrected or confirmed entries into the update capture module Then the module stores the validated data without errors and logs the correction events for audit
Prompt Template Customization
"As a shop manager, I want to customize voice prompt templates so that the guided prompts align with our specific service procedures."
Description

Create an administrative interface allowing shop managers to define, customize, and categorize voice prompt templates based on service type, vehicle make, or technician preference. Templates should support variable placeholders and conditional logic, enabling adaptive prompts within the PulseQueue system. This feature empowers shops to tailor workflows and ensure relevancy for diverse repair scenarios.

Acceptance Criteria
Admin Creates New Prompt Template
Given the shop manager navigates to the Prompt Template Customization interface When they select a service type, enter template text with at least one valid variable placeholder, and click Save Then the system stores the new template, lists it in the templates table, and confirms successful creation
Admin Defines Conditional Logic
Given the shop manager adds a conditional block for vehicle make within a template When they preview the template for different makes Then the system displays the correct prompt text for each applicable make and hides inapplicable content
Admin Categorizes and Filters Templates
Given multiple templates tagged by service type, vehicle make, and technician preference exist When the shop manager applies a filter for a specific category Then only templates matching the selected category criteria are displayed
Technician Receives Context-Aware Prompt
Given a technician starts a job for a specified service type and vehicle make When the system retrieves the associated template Then the voice prompt includes populated variables (e.g., customer name, vehicle VIN) and respects defined conditionals
Validation of Variable Placeholders
Given the shop manager attempts to save a template containing undefined or malformed placeholders When they click Save Then the system blocks saving, highlights invalid placeholders, and displays an error message explaining required format

SmartTerm Correction

Leverage AI-driven lexicons to automatically recognize, standardize, and correct shop-specific terminology, part numbers, and technician names, significantly reducing transcription errors.

Requirements

Terminology Recognition Engine
"As a service scheduler, I want the system to automatically recognize shop-specific terms in bookings so that I spend less time manually correcting transcription errors."
Description

Develop a core engine that leverages natural language processing to identify and match shop-specific terms such as part numbers, technician names, and service codes within incoming text. The engine must support context-aware parsing, handle variations and synonyms, integrate seamlessly with the existing PulseQueue data model, and expose APIs for other modules.

Acceptance Criteria
Recognition of Shop-Specific Terms in Incoming Service Requests
Given a service request text containing various shop-specific terms, when the terminology engine processes the text, then it should identify and standardize each term based on the shop's lexicon with at least 95% accuracy and log any unmapped terms for manual review.
Handling Synonyms and Term Variations in Job Notes
Given job notes containing synonyms or term variations, when processed by the engine, then all synonyms must map to the standardized lexicon term with a precision of 90% or higher and suggest possible matches for any new variations based on a Levenshtein distance threshold of 2.
Seamless API Integration with Scheduling Module
Given a scheduling module request sent to the /parse-terms endpoint, when the engine responds, then the JSON response must include an array of identified terms, their standardized values, and confidence scores of at least 0.8, all returned within 200ms for 95% of requests under normal load.
Context-Aware Parsing for Technician Assignment
Given a service description containing technician names among other text, when the engine parses the description, then it should extract and normalize the technician’s canonical full name with 98% accuracy, resolving variations (e.g., 'Mike' to 'Michael') and flagging ambiguous matches for review.
Error Logging and Feedback Loop for Lexicon Improvement
When the engine processes text, then it must log any false-positive and false-negative term identifications with timestamps accessible via API; when a user corrects an unmapped term in the UI, the lexicon should update automatically and reduce the same error occurrence by at least 50% in subsequent test runs.
AI Lexicon Integration
"As a system administrator, I want the AI lexicon to automatically incorporate new parts and shop terminology so that recognition accuracy remains consistently high."
Description

Integrate external and custom AI-driven lexicon services to enrich the engine’s vocabulary with domain-specific terminology. The integration must allow real-time updates of lexicon entries, support multiple source connections, ensure low-latency access during processing, and include fallback mechanisms for missing terms with version control for lexicon changes.

Acceptance Criteria
Real-time Lexicon Lookup During Transcription
Given a transcription input containing shop-specific terminology, when processed by the AI engine, then each term is identified and replaced with the standardized lexicon entry within 100ms per term.
Batch Upload of Custom Lexicon Entries
Given a user uploads a CSV file of custom lexicon entries, when the upload completes, then all entries are parsed, validated, and available for real-time processing within 5 minutes with a confirmation message.
Fallback Mechanism for Unknown Terms
Given a term not found in primary lexicon sources or custom entries, when processed, then the system consults a secondary fallback lexicon and, if still missing, flags the term for manual review while completing the transcription without error.
Lexicon Version Control and Rollback
Given a new lexicon version is published, when the version update is applied, then the system retains the previous version and allows rollback to any prior version within 10 minutes via the administrative interface.
High-Throughput Multi-Source Lexicon Access
Given 1000 concurrent transcription requests across multiple lexicon sources, when processed, then the average lookup latency remains below 100ms per request and no requests time out.
Real-time Correction Suggestion UI
"As a service advisor, I want inline correction suggestions during data entry so that I can quickly confirm or adjust terms without interrupting my workflow."
Description

Design and implement a user interface component within the appointment scheduling workflow that highlights detected term discrepancies and offers inline correction suggestions. The UI should allow users to accept, reject, or modify suggestions with a single click, display confidence scores, provide keyboard shortcuts, and maintain consistency with PulseQueue’s design system across desktop and mobile layouts.

Acceptance Criteria
Desktop Typo Highlighting
Given a user enters a term with a recognized discrepancy in the desktop scheduling UI, when the term loses focus, then the UI highlights the term in red and displays an inline suggestion with a confidence score of 75% or higher.
Accept Suggestion via Click
Given an inline suggestion is displayed next to a highlighted term, when the user clicks the 'Accept' button, then the original term is replaced by the suggested correction and the highlight is removed.
Reject Suggestion via Keyboard Shortcut
Given an inline suggestion is focused, when the user presses the 'Esc' key, then the suggestion is dismissed, the highlight is removed, and the original term remains unchanged.
Manual Term Modification
Given an inline suggestion is displayed for a highlighted term, when the user manually edits the term and presses 'Enter', then the new term is saved, the suggestion box closes, and no error is displayed.
Mobile Confidence Display
Given the scheduling UI is accessed on a mobile device, when a term discrepancy is detected, then an inline suggestion appears below the term showing the corrected term and its confidence score, and tapping the suggestion reveals 'Accept' and 'Reject' buttons.
Admin Terminology Customization
"As a shop manager, I want to customize the terminology list for my shop so that the system accurately reflects our unique naming conventions."
Description

Create an administrative interface enabling shop managers to add, edit, or remove custom terms and synonyms specific to their business. The interface must support bulk CSV import of terminology, offer search and filtering capabilities, enforce validation rules for term formats, track change history, and apply updates immediately to the recognition engine.

Acceptance Criteria
Add Custom Term via Interface
Given an authenticated shop manager on the Terminology Customization page When the manager enters a valid new term and its synonym, clicks “Save,” and the format passes validation rules Then the new term and synonym appear in the term list, the change is recorded in audit history, and the recognition engine immediately uses the updated lexicon
Edit Existing Custom Term
Given a shop manager viewing an existing custom term in the list When the manager clicks “Edit,” updates the term or synonym to a new valid value, and confirms the change Then the updated term replaces the old entry in the list, the change is tracked in the audit log with timestamp and user ID, and the recognition engine applies the new term immediately
Delete Custom Term
Given a shop manager on the terminology list page with one or more terms available When the manager selects a term, clicks “Delete,” and confirms the action Then the term is removed from the list, the deletion is recorded in the change history, and the term is no longer recognized by the engine
Bulk CSV Import of Terms
Given a shop manager on the Terminology Customization page with a CSV file containing valid term and synonym pairs When the manager uploads the file, reviews any validation errors presented, and confirms the import Then all valid entries are added or updated in bulk, invalid rows are reported with error details, changes are logged in history, and the recognition engine reflects the new terms immediately
Search and Filter Terms
Given a shop manager on the term list page with dozens of custom entries When the manager enters a search keyword or selects filter criteria (e.g., date added, term status) Then the list displays only terms matching the search or filter, pagination responds correctly, and search performance returns results within one second
Validation of Term Format
Given a shop manager submitting a new or edited term When the term contains unsupported characters, duplicates an existing term, or exceeds the character limit Then the interface prevents saving, highlights the invalid field with a clear error message, and logs the validation failure in system logs
Change History Tracking
Given a shop manager reviewing the terminology audit log When the manager selects a term and requests its history Then the system displays a chronological list of all create, update, and delete actions with user, timestamp, and before/after values, supporting pagination and export to CSV
Correction Logging and Reporting
"As a data analyst, I want detailed logs of every correction and override so that I can monitor system performance and identify areas for improvement."
Description

Implement a logging system that captures all automatic corrections, user overrides, and term modifications for auditing and performance analysis. The system must record timestamps, user identifiers, original and corrected values, and confidence scores, and provide exportable reports in CSV or PDF formats accessible via the PulseQueue analytics dashboard.

Acceptance Criteria
Automatic Correction Logging During Entry
1. System records timestamp, user ID, original value, corrected value, and confidence score for each automatic correction. 2. Log entry is persisted in the correction_logs database table. 3. Logged entries are retrievable via the analytics dashboard within 5 seconds of occurrence.
User Override Correction Logging
1. When a user overrides or rejects an AI-suggested correction, system logs the timestamp, user ID, original suggested value, and user-entered override value. 2. Log entry includes a flag indicating an override action and stores confidence score of the original suggestion. 3. Override logs are accessible in the analytics correction report.
Term Modification Change Audit
1. Upon manual addition, modification, or deletion of a lexicon term, system logs timestamp, user ID, original term entry, and the new term entry. 2. Audit log entries are stored in a lexicon_audit table with an action type field (add, modify, delete). 3. Audit logs are included in exportable reports.
CSV Export of Correction Logs
1. Analytics dashboard provides a CSV export option for correction_logs. 2. Exported CSV includes columns: timestamp, user ID, original value, corrected value, confidence score, action type. 3. CSV file downloads within 10 seconds and validates against CSV schema.
PDF Export of Correction Logs
1. Analytics dashboard provides a PDF export option for correction_logs. 2. PDF report displays a table with formatted columns: timestamp, user ID, original value, corrected value, confidence score, action type. 3. PDF file generation completes within 15 seconds and is correctly formatted for printing.

Offline Resync

Allow technicians to record voice updates even without network coverage and automatically synchronize them with the central scheduler once connectivity is restored, ensuring no data is lost.

Requirements

Offline Voice Capture
"As a technician, I want to record appointment updates via voice even when I’m in a no-service area so that I don’t lose critical scheduling information."
Description

Technicians can record and store voice updates locally on their device when network coverage is unavailable. These voice recordings are persisted securely in an encrypted local cache, ensuring each entry is timestamped and tagged with the relevant appointment ID. Once the device regains connectivity, the app automatically detects network availability and uploads all pending recordings to the central scheduler without user intervention. This functionality ensures no data loss and maintains accurate scheduling records.

Acceptance Criteria
Technician Records Voice Update Offline
Given the technician is in an area without network coverage, When they record a voice update for an appointment, Then the recording is saved locally in the encrypted cache on the device.
Offline Recordings Are Securely Stored
Given a locally saved voice recording, When attempting to access the file from storage, Then the recording must be encrypted at rest and inaccessible without proper decryption credentials.
Automatic Upload Upon Network Restoration
Given the device regains network connectivity, When pending recordings exist in the local cache, Then the app automatically uploads all pending recordings to the central scheduler without any user intervention.
Recordings Maintain Accurate Metadata
Given a recording session has completed offline, When the recording is stored, Then it is tagged with the correct appointment ID and timestamped in ISO 8601 format.
No Duplicate Uploads of Recordings
Given a recording was previously uploaded successfully, When the device reconnects to the network again, Then the app must not upload the same recording more than once.
Failed Uploads Are Retried And Logged
Given an upload attempt fails due to server error or connectivity issues, When the app detects the failure, Then it logs the error details and retries the upload every 5 minutes until it succeeds.
Connectivity Monitoring
"As a technician, I want the app to automatically detect when I’m back online and sync my pending updates so that I don’t have to remember to do it manually."
Description

The app continuously monitors network status and triggers an automatic synchronization process when stable connectivity is re-established. It differentiates between transient and sustained connectivity, queuing recordings during outages and initiating bulk or incremental uploads once a reliable connection is detected. This ensures timely data transfer and minimizes manual syncing requirements.

Acceptance Criteria
Transient Connectivity Drop Scenario
Given the technician is recording voice updates when the network drops for less than 30 seconds, the app must continue recording locally without interruption and automatically queue the data for synchronization once connectivity is re-established
Sustained Outage Queuing Scenario
When the network is unavailable for more than 30 seconds, all voice recordings must be stored securely in local storage and clearly marked as pending sync in the UI
Automatic Bulk Synchronization Scenario
Given stable connectivity is detected after an outage longer than 2 minutes, the app must initiate a bulk upload of all queued recordings within 10 seconds and display progress to the user
Incremental Upload on Reconnection Scenario
When intermittent connectivity is detected, the app must perform incremental uploads of recordings in the queue without retrying already synced data and resume remaining uploads until the queue is empty
Sync Resume after App Restart Scenario
If the app is closed or crashes before pending recordings are synced, upon next launch with a stable connection, the app must automatically resume synchronization from where it left off and confirm completion to the user
Secure Local Storage
"As a technician, I want my offline recordings to be stored securely on my device so that sensitive customer information remains protected."
Description

Voice recordings captured offline are encrypted at rest using industry-standard algorithms and stored in a sandboxed area of the device. Access controls ensure only the app can read and write these files. Metadata, including timestamps and appointment references, is stored alongside recordings to maintain integrity and provide context for later synchronization.

Acceptance Criteria
Encrypt Voice Recording Offline
Given a technician initiates a voice recording without network coverage, When the recording is saved locally, Then the audio file is encrypted at rest using AES-256 and stored within the app’s sandbox.
Enforce App-Only Access to Local Files
Given any external application or process attempts to read or write the locally stored recordings, When the access request is made, Then the OS denies the operation and no unencrypted data is exposed.
Store Metadata with Recording
Given a voice recording is completed offline, When the recording is saved, Then timestamp and appointment reference metadata are stored alongside the encrypted file in a structured format and retrievable by the app.
Prevent Data Loss on Device Restart
Given the device powers off or restarts during offline recording sessions, When the app is relaunched, Then all previously encrypted recordings and their metadata remain intact in the sandbox and accessible by the app.
Sync Encrypted Recordings Upon Reconnection
Given the device regains network connectivity, When the app triggers offline data synchronization, Then recordings and metadata are decrypted in-memory, transferred securely to the central scheduler, verified for integrity, and local copies flagged as synced.
Conflict Detection and Resolution
"As a shop manager, I want the system to detect and resolve any conflicts between offline and online updates so that the schedule remains accurate and consistent."
Description

When syncing, the system compares offline recordings with existing appointment entries to detect conflicts such as overlapping updates or mismatched timestamps. It applies a set of predefined rules—like keeping the latest timestamp or prompting the user when necessary—to resolve discrepancies. This prevents data corruption and ensures the final schedule reflects the most accurate information.

Acceptance Criteria
Overlapping Update Detection
Given an offline voice update for an appointment that overlaps with an existing appointment in the same bay, When synchronization occurs, Then the system flags the conflict and logs it without overwriting either entry.
Timestamp Mismatch Handling
Given an offline recording timestamp is earlier than the corresponding server entry’s timestamp, When synchronization occurs, Then the system discards the offline update and retains the server version.
Automatic Latest-Timestamp Resolution
Given an offline recording timestamp is later than the corresponding server entry’s timestamp, When synchronization occurs, Then the system automatically applies the offline update to the server without user intervention.
User Prompt for Ambiguous Conflicts
Given a conflict where both offline and server timestamps are identical or rules cannot determine precedence, When synchronization occurs, Then the system prompts the user to select which version to keep before applying changes.
Bulk Sync Multiple Conflict Management
Given multiple offline recordings that each conflict with different server entries during a single sync session, When synchronization occurs, Then the system processes each conflict in sequence, applies automatic resolutions where possible, prompts the user for ambiguous conflicts, and generates a summary report of all actions taken.
Sync Status Feedback
"As a technician, I want to see the status of my pending and completed uploads so that I know whether my offline recordings have been successfully synchronized."
Description

The app provides real-time feedback on the synchronization process, displaying statuses such as 'Pending Upload', 'Uploading', 'Upload Successful', and 'Upload Failed'. Users can view a log of recent sync activities and manually retry failed uploads. This transparency helps technicians and managers stay informed about the state of their data.

Acceptance Criteria
Offline Voice Update Pending Upload
Given a technician records a voice update without network coverage When the app detects no connectivity Then the update appears in the sync interface with status 'Pending Upload'
Connectivity Restoration Triggers Sync
Given there are one or more items marked 'Pending Upload' When network connectivity is restored Then the app automatically initiates upload, showing status 'Uploading' and upon completion updating to 'Upload Successful' within 30 seconds
Manual Retry of Failed Uploads
Given an item’s sync status is 'Upload Failed' When the user selects the 'Retry' option for that item Then the app re-attempts the upload and updates the status to 'Upload Successful' on success
Sync Activity Log Visibility
Given the technician opens the sync activity log Then the app displays the 10 most recent sync events in chronological order with timestamp, item type, and final status
Real-Time Status Indicator Display
Given the technician views any recorded item Then the app displays a colored status badge: gray for 'Pending Upload', blue for 'Uploading', green for 'Upload Successful', or red for 'Upload Failed'

Hands-Free Hub

Integrate with Bluetooth headsets or wearable devices to enable fully hands-free voice updates, empowering technicians to update job progress without stopping work or removing protective gear.

Requirements

Device Pairing & Connection Management
"As a technician, I want to pair my Bluetooth headset with PulseQueue so that I can operate hands-free without manual device switching."
Description

Enable technicians to seamlessly discover, pair, and manage Bluetooth headsets and compatible wearable devices within PulseQueue. The system should support dynamic scanning for nearby devices, secure pairing protocols, and a user-friendly interface for connecting or disconnecting devices. It must maintain stable connections, handle reconnections automatically, and provide visual cues on connection status.

Acceptance Criteria
Bluetooth Device Discovery
Given the technician navigates to the device pairing screen When the system performs a scan for nearby Bluetooth devices Then all discoverable headsets and wearables within range are listed with signal strength indicators
Secure Device Pairing
Given the technician selects a device from the available list When the technician initiates pairing Then the system completes a secure pairing handshake and stores the device credentials in encrypted form
Connection Status Visualization
Given one or more devices are paired When a device connects or disconnects Then the interface displays distinct visual cues (e.g., a green icon for connected, a gray icon for disconnected) next to the device name
Automatic Reconnection
Given a previously paired device goes out of range and then returns When the device comes back into range Then the system automatically reconnects to the device within 5 seconds without manual intervention
Manual Device Management
Given multiple devices are paired When the technician chooses to disconnect or remove a device Then the system prompts for confirmation and upon approval disconnects or unpairs the device and clears its credentials
Voice Activation & Command Processing
"As a technician, I want to invoke voice commands so that I can update job status without touching the interface."
Description

Implement voice activation capabilities to detect predefined wake words (e.g., “Hey Pulse”) and convert spoken phrases into actionable commands. The system should use AI-driven speech recognition optimized for noisy workshop environments, ensuring accurate interpretation of technician instructions. Integration with the core scheduling engine should allow direct mapping of voice inputs to system functions.

Acceptance Criteria
Noisy Workshop Job Status Update
Given ambient noise levels up to 85 dB, When the technician utters the wake word “Hey Pulse” followed by “update job 123 status to complete”, Then the system recognizes the wake word and accurately transcribes the command at least 95% of the time and updates the job status in the scheduling engine within 2 seconds.
Hands-Free Schedule Overview
Given the technician is wearing a Bluetooth headset, When the technician says “Hey Pulse, what’s my schedule for today?”, Then the system responds with the list of appointments for the day, reading them back within 3 seconds with at least 98% word accuracy.
Voice Cancellation of Appointment
Given a scheduled appointment exists, When the technician says “Hey Pulse, cancel appointment 456”, Then the system confirms the command by asking “Are you sure you want to cancel appointment 456?”, processes the cancellation upon confirmation, removes the appointment from the schedule within 2 seconds, and sends a cancellation notification via SMS.
Ambiguous Command Handling
Given the system receives a command that could match multiple actions, When the technician issues an ambiguous command (e.g., “Hey Pulse, update job”), Then the system prompts for clarification by asking a follow-up question within 1 second, and correctly executes the clarified command after receiving the response.
Post-Command Voice Confirmation
Given a valid command has been executed, When the system completes the requested action, Then it provides a verbal confirmation via the headset stating “Job status updated successfully” (or appropriate message) within 1 second and logs the confirmation in the system audit trail.
Real-Time Job Progress Updates via Voice
"As a technician, I want to update job progress hands-free so that I can maintain workflow continuity without removing my protective gear."
Description

Allow technicians to verbally update job milestones—such as start, pause, resume, and complete—directly through their Bluetooth headsets. The system should confirm successful updates in real time within the technician’s calendar and the shop manager’s dashboard, ensuring accurate load balancing and minimizing manual data entry.

Acceptance Criteria
Voice Command Recognition at Job Start
Given a technician wearing a connected Bluetooth headset issues the voice command 'Start job', when the system accurately recognizes the command, then the job status is updated to 'In Progress' on the technician’s calendar within 2 seconds.
Voice Command Recognition for Pause and Resume
Given a technician says 'Pause job' or 'Resume job', when the system processes the command correctly, then the job status is updated accordingly on both the technician’s calendar and the manager’s dashboard within 2 seconds.
Confirmation Feedback via Headset
Given a voice command is recognized and processed, when the job status is updated, then the system provides immediate audio feedback through the headset confirming the new status with a clear verbal message.
Dashboard Update Real-Time Sync
Given any voice-triggered job status change, when the update is applied, then the shop manager’s dashboard reflects the change within 3 seconds, ensuring accurate load balancing visibility.
Error Handling for Unrecognized Commands
Given a technician issues an unrecognized or unclear voice command, when the system cannot process the command, then it prompts the technician to repeat the command clearly and logs the failed recognition event for review.
Audio Feedback & Error Handling
"As a technician, I want audible confirmation and error prompts so that I know my voice commands were processed correctly or if I need to repeat them."
Description

Provide immediate auditory feedback for technician commands, including confirmations (e.g., beeps or spoken acknowledgments) and error prompts. In case of unrecognized or failed commands, the system should prompt the technician to retry or offer guidance. All feedback must be clear, concise, and optimized for workshop noise levels.

Acceptance Criteria
Valid Command Confirmation
Given a technician issues a supported voice command, when the system recognizes it with confidence ≥ 80%, then within 1 second the system emits a single beep followed by a spoken acknowledgment stating the executed command.
Unrecognized Command Prompt
Given a technician issues an unsupported or unclear command, when speech recognition confidence < 50% or no match is found, then within 2 seconds the system emits a double-tone error beep and plays a voice prompt saying “Command not recognized, please repeat,” then re-enters listening mode.
Ambient Noise Handling
Given background noise exceeds 75 dB in the workshop, when the system detects noise above threshold during command listening, then it immediately plays a voice prompt saying “Environment too noisy, please pause or move closer,” and pauses listening until noise drops below threshold.
Critical Action Confirmation
Given a technician issues a critical command (e.g., complete job), when recognized, then the system asks “Are you sure you want to complete the job?” and waits up to 5 seconds for a confirmatory “Yes” before executing; a negative or no response cancels the action.
Feedback Volume Optimization
Given the technician is in a high-noise environment and initial feedback volume is insufficient for clarity, when feedback volume < 70 dB, then the system automatically increases feedback volume in 2 dB increments up to a maximum of 85 dB until the technician issues a “Confirm” command or the limit is reached.
Compatibility Certification & Testing
"As a product manager, I want to ensure compatibility with various devices so that technicians have a seamless hands-free experience regardless of their hardware choice."
Description

Establish a compatibility matrix and perform rigorous testing of the Hands-Free Hub with major Bluetooth headset brands, wearable devices, and supported operating systems. Document certification processes and compatibility guidelines to ensure consistent performance across devices, minimizing connectivity issues.

Acceptance Criteria
Pairing with iOS Bluetooth Headset
Given a supported iOS device and a Bluetooth headset in pairing mode When the user selects the headset from the PulseQueue app’s Bluetooth settings Then the headset pairs within 10 seconds and remains connected after app restart
Pairing with Android Bluetooth Headset
Given a supported Android device and a Bluetooth headset in pairing mode When the user initiates pairing from the PulseQueue app’s Bluetooth menu Then the headset pairs within 10 seconds and retains connection after device reboot
Voice Update Using Connected Headset
Given a connected Bluetooth headset When a technician issues a voice command to update job status Then the system records and reflects the updated job status without requiring manual input
Auto-Reconnection after Signal Loss
Given an active Bluetooth connection that experiences signal drop When the headset returns within range Then the PulseQueue app automatically reconnects within 5 seconds without user intervention
Compatibility with Wearable Device
Given a supported wearable device and PulseQueue app installed When the technician enables voice updates via wearable Then the device pairs successfully and processes voice commands with accuracy above 95%

Gap Spotlight

Analyzes the past week’s booking and utilization data to pinpoint specific time slots, bays, or service categories where revenue opportunities were missed. Prioritizes gaps by potential uplift and provides concise summaries so shop owners know exactly where to focus marketing or scheduling efforts.

Requirements

Weekly Data Aggregation
"As a shop manager, I want the system to automatically gather and harmonize last week’s booking and utilization data so that I can trust the analysis without manual data collection."
Description

Implement a data aggregation engine that automatically collects and consolidates booking and utilization data from all bays, time slots, and service categories over the past week. This module should integrate with existing scheduling databases and real-time logs to ensure completeness and accuracy. The system must normalize disparate data formats, handle missing values, and store the aggregated dataset for subsequent analysis. Benefits include a unified data view, reduced manual data wrangling, and a foundation for reliable gap analysis.

Acceptance Criteria
Automatic Data Extraction
Given access to all scheduling databases and real-time logs, when the weekly aggregation process runs, then booking and utilization records for every bay, time slot, and service category over the past seven days are collected without omissions.
Missing Value Handling
Given input records containing null or missing fields, when normalization is applied, then missing values are either imputed using predefined rules or marked and logged, ensuring no record causes the aggregation to fail.
Data Format Normalization
Given data inputs in varied formats (CSV, JSON, SQL), when processed by the aggregation engine, then all fields are converted to the unified schema with correct data types and formats.
Aggregated Dataset Storage
Given successful consolidation of weekly data, when storing the aggregated dataset, then the system persists it in the designated storage location with a timestamp, version metadata, and retention policy.
Integration Logging and Monitoring
Given the aggregation workflow execution, when any error or exception occurs, then detailed logs are generated and real-time alerts are sent to administrators within 5 minutes.
Gap Identification Algorithm
"As a shop owner, I want the system to intelligently identify when and where my bays are underutilized so I can take action to fill those gaps and increase revenue."
Description

Develop a sophisticated algorithm that scans the aggregated data to pinpoint time slots, bays, and service categories where actual utilization falls below expected thresholds. The algorithm must account for seasonality, historical averages, and booking patterns to accurately detect underutilized segments. It should output a list of identified gaps along with metadata such as gap duration, bay ID, service type, and frequency. This functionality is crucial for revealing missed revenue opportunities otherwise hidden in raw data.

Acceptance Criteria
Identify Underutilized Time Slots
Given aggregated historical booking and utilization data for the past 4 weeks, when the Gap Identification Algorithm executes, then it outputs all time slots where utilization is below 70% of the historical average.
Account for Seasonality
Given data spanning multiple seasons, when the algorithm processes the data, then it adjusts expected utilization thresholds to reflect seasonal patterns before identifying gaps.
Detect Underutilized Service Categories
Given categorized service type usage data, when the algorithm evaluates each category, then it lists service categories with actual bookings at least 30% below expected thresholds.
Generate Gap Metadata
Given identified underutilized segments, when the algorithm compiles the output, then it includes gap duration, bay ID, service type, and frequency for each detected gap.
Prioritize Gaps by Potential Revenue Uplift
Given multiple detected gaps, when the algorithm ranks them, then it orders the gaps by estimated potential revenue uplift descending, based on average service price and gap duration.
Revenue Uplift Prioritization
"As a shop owner, I want the system to prioritize underutilized slots by potential revenue uplift so that I focus my marketing on the most profitable opportunities."
Description

Implement a prioritization module that ranks identified gaps based on their potential revenue uplift. This requires calculating expected revenue for each gap by combining average service prices, historical conversion rates, and slot availability. The module should then sort gaps in descending order of uplift potential, highlighting the most lucrative opportunities first. This prioritization ensures that shop owners focus marketing and scheduling efforts on gaps that promise the highest financial return.

Acceptance Criteria
Calculate Expected Revenue for Each Gap
Given weekly booking and utilization data with average service prices and historical conversion rates, When the prioritization module processes a gap, Then it computes expected revenue as average service price × available slots × conversion rate.
Sort Gaps by Uplift Potential
Given a list of gaps with computed expected revenue, When the module sorts the gaps, Then they are ordered in descending order of expected revenue uplift.
Highlight Top N Opportunities in UI
Given a sorted gaps list, When the user opens the Gap Spotlight dashboard, Then the top 5 gaps are displayed prominently with their uplift values ranked highest to lowest.
Handle Missing Historical Data Gracefully
Given a gap with missing conversion rate or price data, When generating revenue uplift, Then the module applies default values and logs a warning without failing the process.
Validate Data Accuracy Using Test Dataset
Given a test dataset with known expected revenue values, When the prioritization module runs, Then computed revenue uplift matches expected values within ±1% tolerance.
Concise Summary Dashboard
"As a shop manager, I want a clear dashboard summarizing the most critical scheduling gaps so I can quickly understand where to focus my efforts."
Description

Design and develop a user interface component that displays a concise summary of the top-priority gaps for the week. The dashboard should present key metrics such as time slot, bay, service category, potential uplift, and historical utilization percentage using clear visual elements (e.g., cards, charts, and tables). It should support filtering by date, bay, and service type, and allow users to drill down into detailed reports. This feature empowers shop managers to quickly grasp missed opportunities and decide on next steps.

Acceptance Criteria
Weekly Gap Summary Overview
Given the user visits the Concise Summary Dashboard on Mondays, When the dashboard loads, Then it displays the top 5 gaps for the past week sorted by potential uplift with time slot, bay, service category, uplift amount formatted as currency, and historical utilization percentage.
Filtering Gaps by Date, Bay, and Service Type
Given the dashboard is loaded, When the user selects a date range, a specific bay, and a service type, Then the dashboard displays only the gaps matching all selected filters. When the user clicks 'Reset Filters', Then all filters clear and the full list of gaps reappears.
Drilling Down into Detailed Reports
Given the user clicks on a gap card for a specific time slot and service, When the detailed report view opens, Then it shows daily slot utilization, revenue trend charts, and an export CSV button filtered to that gap's parameters.
Visual Representation of Potential Uplift
Given the dashboard displays potential uplift data, When rendering the bar chart, Then each bar’s length accurately reflects the uplift amount, axes and legend are labeled, and hovering over a bar shows a tooltip with the exact uplift amount.
Responsive Layout on Mobile and Tablet
Given the user accesses the dashboard on tablet or mobile devices, When the viewport width changes, Then cards stack vertically on mobile, filters collapse into a single dropdown menu, and no visual elements overflow or overlap.
Targeted Marketing Recommendations
"As a marketing coordinator, I want actionable marketing recommendations based on scheduling gaps so I can engage customers effectively and boost bookings."
Description

Develop a recommendation engine that suggests targeted marketing actions based on the identified and prioritized gaps. For each high-priority gap, the system should propose specific marketing strategies (e.g., SMS promotions, email campaigns, discount offers) tailored to the gap’s timing, service category, and customer segmentation. Recommendations should include suggested messaging templates and send times to maximize response rates. Integrating this with the existing SMS/reminder system ensures seamless execution.

Acceptance Criteria
Promotion for Underutilized Morning Slots
Given a high-priority gap in morning booking slots, when the recommendation engine runs, then it generates an SMS promotion including a templated message, targeted customer segment, and a suggested send time of 6 AM local time, and writes the recommendation to the SMS queue
Email Campaign for Low-Demand Service Category
Given a service category with low utilization identified in the past week, when generating recommendations, then the system provides an email campaign strategy including subject line, body template, customer segmentation filter, and recommended send date, and the output is exportable as a CSV
Discount Offer for Specific Bay Empty Windows
Given one or more time windows where a specific repair bay was idle for more than four hours, when processing gaps, then the recommendation engine suggests a discount offer template, specifies discount percentage, time validity, and target customer segment, and schedules it in the SMS system
SMS Promotion for Customer Segment
Given a customer segment defined by service history and booking frequency, when recommending marketing actions for a high-priority gap, then the system generates an SMS template including personalized fields (e.g., name, last service), recommended send time, and auto-scheduling in the reminder system
Integration with SMS/Reminder System
Given any generated marketing recommendation, when selecting 'Send Now' or 'Schedule', then the system must transmit the message via the existing SMS/reminder API, confirm successful delivery status codes, and log the transaction in the campaign history

Schedule Optimizer

Leverages AI-driven analysis to recommend precise adjustments to upcoming schedules—such as shifting high-demand services to peak hours or reallocating technician slots—to close identified revenue gaps. Users can apply suggestions directly to the calendar, reducing guesswork and boosting bay utilization.

Requirements

Historical Data Analysis
"As a shop manager, I want the system to analyze historical appointment and utilization data so that the AI recommendations are based on accurate insights into past performance."
Description

Implement a system that ingests and processes past scheduling, service, and utilization data to identify trends and patterns. This module will cleanse, normalize, and aggregate data to provide a reliable foundation for demand forecasting and schedule optimization. The analysis will enable the AI to understand peak hours, service durations, and technician performance over time.

Acceptance Criteria
Data Ingestion Completeness
Given historical scheduling, service, and utilization data sources are provided, When the ingestion module executes, Then all records from each source for the specified period are imported with no missing entries.
Data Cleansing Accuracy
Given ingested raw data, When the cleansing process runs, Then invalid or duplicate entries are identified and corrected or removed, achieving a data quality error rate below 1%.
Data Normalization Consistency
Given cleansed data with varying formats and units, When normalization rules are applied, Then all date/times adhere to ISO 8601 format, units are standardized, and no discrepancies remain.
Trend Pattern Identification
Given normalized historical data over at least 12 months, When the analysis module executes pattern detection, Then peak hours, average service durations, and technician utilization patterns are identified with an accuracy of at least 95% against baseline benchmarks.
Aggregated Data Reporting
Given analyzed trends, When generating the aggregated data summary, Then the system produces reports that include total services per hour, average job duration per service type, and technician performance metrics, and exports these in CSV and JSON formats without errors.
Demand Forecast Module
"As a scheduler, I want accurate demand predictions for upcoming days so that I can allocate bays and technicians proactively to meet expected workloads."
Description

Develop an AI-driven forecasting engine that uses historical data and external factors (e.g., seasonality, local events) to predict future service demand by time slot and service type. The module will provide probability distributions and confidence levels for each forecasted interval to guide schedule adjustments.

Acceptance Criteria
Hourly Forecast Generation
Given the system has at least 6 months of historical service data; When the user requests a 7-day hourly demand forecast; Then the system generates a forecast for every hour of each day with associated probability distributions and confidence levels; And the forecast is returned within 5 seconds without missing time slots.
Service Type Demand Accuracy Check
Given historical breakdown of service types by time slot; When the forecast is generated; Then the forecasted service type percentages for each time slot reflect actual historical proportions within a ±10% error margin; And the total of all service type percentage allocations per slot equals 100%.
External Events Impact Detection
Given a known external event on a specific date; When the forecast is created; Then the demand forecast for affected time slots adjusts by at least 15% compared to baseline; And the forecast highlights event-driven adjustments with confidence levels of at least 80%.
Forecast Confidence Level Validation
Given all forecasted time slots have associated confidence metrics; When the forecast is displayed; Then every time slot shows a confidence level above 50%; And slots below the threshold trigger a warning notification to the user.
Historical Data Integration
Given new historical data import for the prior day; When the system ingests the data; Then the data is fully available for forecasting within 10 minutes; And no records are omitted or duplicated in the dataset.
Recommendation Generation Engine
"As a shop owner, I want prioritized scheduling suggestions so that I can easily apply the highest-impact changes and maximize bay utilization."
Description

Create an AI component that evaluates current schedules against forecasted demand to generate actionable recommendations. Suggestions may include shifting high-demand services to underutilized slots, reassigning technician workloads, and bundling complementary tasks. Recommendations will be ranked by projected revenue impact.

Acceptance Criteria
High-Demand Time Slot Adjustment
Given the AI engine processes the current schedule and demand forecast, When underutilized slots coincide with peak demand services, Then the engine should recommend shifting those services to the identified slots with an estimated revenue increase.
Technician Workload Rebalancing
Given multiple technicians with uneven workloads for the upcoming week, When the engine evaluates skill sets and availability, Then it should propose reassignments that equalize workloads within a 10% variance.
Service Bundling Recommendation
Given customers often book complementary services separately, When the engine identifies frequently paired services in historical data, Then it should suggest service bundles that reduce booking steps by at least 20%.
Revenue Impact Ranking Display
Given the engine generates multiple schedule adjustment suggestions, When suggestions are presented to the user, Then each recommendation must be ranked by projected revenue impact and displayed in descending order.
Direct Application of AI Suggestions
Given a user selects one or more AI recommendations, When the user confirms application, Then the system must update the calendar accordingly and log the change in the audit trail.
Interactive Schedule Adjustment UI
"As a service manager, I want an intuitive interface to preview and apply optimization suggestions so that I can implement adjustments quickly without leaving the scheduling screen."
Description

Design and build a user interface widget within the calendar view that displays AI-generated recommendations. The UI should allow one-click application of suggestions, drag-and-drop adjustments, and manual overrides. Real-time feedback on the estimated revenue or utilization gains should be provided as changes are made.

Acceptance Criteria
One-Click Application of AI Suggestions
Given the user sees AI-generated recommendations in the schedule widget When the user clicks the 'Apply' button for a recommendation Then the suggested adjustment is applied to the calendar within 2 seconds And the UI highlights the updated slot
Drag-and-Drop Adjustment with Real-Time Feedback
Given the user drags a suggested appointment slot to a new time When the drag operation is completed Then the system recalculates and displays the updated estimated revenue uplift and bay utilization percentage in real time
Manual Override Post-Suggestion
Given an applied AI suggestion in the calendar When the user manually edits appointment details Then the system accepts the override without errors And updates revenue and utilization projections accordingly
Viewing Real-Time Revenue Impact
Given any schedule adjustment action performed When the action is applied Then the estimated revenue delta is displayed within the adjustment UI with latency under 500ms
Conflict Resolution for Overlapping Adjustments
Given two appointments overlap as a result of an adjustment When the user attempts to apply the conflicting change Then the system displays a clear alert message And prevents the overlap while suggesting alternate available time slots
Optimization Performance Dashboard
"As a business owner, I want to monitor the impact of schedule optimizations so that I can validate ROI and refine AI recommendations based on real results."
Description

Implement a dashboard that tracks the before-and-after metrics of applied schedule optimizations, including changes in bay utilization, revenue increase, and no-show reduction. The dashboard will visualize trends over time and allow filtering by technician, service type, and date range.

Acceptance Criteria
Bay Utilization Trend Analysis
Given a schedule optimization is applied and at least 7 days of pre- and post-optimization data exist When the user navigates to the Bay Utilization Trend section of the dashboard Then a line chart displays daily bay utilization percentages for both periods, clearly labeled as "Before Optimization" and "After Optimization"
Revenue Impact Filtering by Service Type
Given optimization results include revenue metrics categorized by service type When the user selects a specific service type from the filter dropdown Then the dashboard updates to display revenue before and after optimization exclusively for the chosen service type
No-Show Reduction Over Time
Given the system has recorded no-show counts for appointments When the user views the No-Show Reduction section Then a bar graph compares weekly no-show counts before and after optimization, with axes and legends correctly labeled
Technician-Specific Optimization Overview
Given multiple technicians’ data is available When the user selects a technician from the technician filter Then the dashboard refreshes all displayed metrics (bay utilization, revenue, no-show counts) to reflect only data for the selected technician
Date Range Comparison
Given the user inputs a custom start and end date When the date range filter is applied Then all dashboard metrics (bay utilization, revenue increase, no-show reduction) are recalculated and displayed strictly within the specified date range

What-If Simulator

Lets users experiment with different scheduling scenarios—like adding extra slots, adjusting service durations, or running targeted promotions—and immediately view projected revenue impacts. Empowers managers to make confident, data-backed decisions without disrupting live operations.

Requirements

Scenario Configuration Builder
"As a shop manager, I want to configure custom scheduling scenarios by adjusting slots, durations, and promotions so that I can explore different scheduling strategies safely."
Description

Enables users to define custom scheduling scenarios by adjusting parameters such as number of time slots, service durations, promotion attributes, and resource allocations. The builder integrates seamlessly with the existing scheduling engine, allowing parameters to be saved, edited, and reused. It provides validation to ensure logical parameter values and prevent invalid configurations, ensuring users can easily set up experiments without impacting live schedules.

Acceptance Criteria
Valid Parameter Entry
Given the user accesses the Scenario Configuration Builder, when they input valid values for time slots, service durations, promotions, and resources within accepted ranges, then the system accepts the inputs and enables the 'Save' button.
Configuration Persistence
Given the user has created and saved a scenario, when they navigate away and return later, then the previously saved scenario parameters are displayed correctly and can be loaded.
Parameter Validation Feedback
Given the user enters an invalid parameter (e.g., negative duration or overlapping time slots), when they attempt to save, then the system displays a clear error message indicating the invalid field and prevents saving.
Seamless Integration with Scheduling Engine
Given the user saves a new scenario, when they run the simulation, then the scenario parameters are correctly applied to the scheduling engine and simulation results update accordingly.
Reusable Scenario Editing
Given the user selects an existing scenario, when they modify one or more parameters and save, then the system updates the scenario with the new parameters and retains version history.
Real-Time Revenue Projection Engine
"As a shop manager, I want to see instant revenue projections based on my scenario settings so that I can make informed scheduling decisions quickly."
Description

Core computational module that processes input scenario parameters through predictive models to instantly estimate key metrics such as projected revenue, bay utilization rate, and no-show impact. It handles large datasets efficiently and updates projections within seconds. The engine leverages historical booking and revenue data for accurate forecasting and integrates with the scenario builder.

Acceptance Criteria
Parameter Adjustment Instantaneous Update
Given the user changes one or more scenario parameters When the user submits the changes Then the engine recalculates and displays updated revenue, bay utilization, and no-show impact within 2 seconds.
Large Dataset Processing Under Load
Given a historical dataset of at least 100,000 booking records When the engine processes the dataset for projection Then the calculation completes successfully without errors within 5 seconds and uses no more than 80% CPU utilization on a standard instance.
Historical Data Integration Validation
Given the availability of at least 6 months of historical booking and revenue data When the projection engine runs Then it incorporates weighted averages of the last six months to generate forecasts.
Accuracy Against Benchmark Scenarios
Given a set of predefined test scenarios with known revenue outcomes When the engine computes projections for these scenarios Then its results deviate by no more than ±5% from the benchmark values.
API Response Time Compliance
Given any valid input request to the projection API When the request is received Then the API responds with a full projection result in under 2 seconds at least 95% of the time.
Interactive Visualization Dashboard
"As a shop manager, I want to view simulation results in interactive charts and heatmaps so that I can easily interpret the data and insights."
Description

Presents simulation results through interactive charts and heatmaps showing revenue over time, utilization graphs, and no-show risk indicators. Users can hover for details, filter time ranges, and toggle between metrics. The dashboard integrates into the PulseQueue UI with consistent styling and supports responsive design for tablet use.

Acceptance Criteria
Real-time Revenue Trend Exploration
Given the simulator has generated revenue projections, when the user hovers over the revenue trend line for any date, then a tooltip displays the date, projected revenue, percentage change from the previous period, and confidence interval.
Bay Utilization Heatmap Analysis
Given the simulation results include bay utilization data, when the user views the heatmap and selects a time range filter, then the heatmap updates to reflect utilization percentages for each bay within the specified range, with color intensity matching utilization levels.
No-show Risk Indicator Spotlight
Given the simulator calculates no-show probabilities, when the user toggles the no-show risk layer on the dashboard, then risk indicators (e.g., colored icons) appear on the timeline chart at slots where no-show probability exceeds the threshold, and hovering shows slot time and risk percentage.
Metric Toggle and Comparison
Given multiple metrics are available (revenue, utilization, no-show rate), when the user toggles between metrics or selects multiple metrics, then the dashboard displays the corresponding charts side by side or overlaid, and updates legends and axis labels accordingly.
Responsive Tablet Interaction
Given the dashboard is accessed on a tablet device, when the user interacts with charts (hover, tap, pinch-to-zoom), then all interactive elements respond correctly, layouts adjust for screen orientation, and no horizontal scrolling is required.
Side-by-Side Scenario Comparison
"As a shop manager, I want to compare multiple scheduling scenarios side by side so that I can choose the best option."
Description

Allows users to compare multiple saved scenarios by displaying their metrics side by side in a comparative table and synchronized visualizations. Users can select up to four scenarios, label them, and highlight the best-performing one. This feature supports exporting comparisons for team review.

Acceptance Criteria
Scenario Selection
Given the user has at least two saved scenarios, when they open the comparison interface, then they can select a minimum of two and a maximum of four scenarios, and the UI prevents selecting more than four.
Scenario Labeling
Given one or more scenarios are selected, when the user edits a scenario label, then the updated label appears immediately in both the comparison table and synchronized visualizations.
Comparative Table Display
Given scenarios are selected, when the comparison view loads, then the system displays a table listing each scenario side by side with metrics for projected revenue, bay utilization, and no-show rates, with each column correctly aligned.
Best Scenario Highlight
Given multiple scenarios are displayed, when the user enables auto-highlight or clicks the highlight control, then the system visually distinguishes the top-performing scenario based on projected revenue using a distinct color or badge.
Comparison Export
Given the comparison view is populated, when the user clicks the export button, then the system generates and downloads a PDF or CSV file containing the labeled scenarios, side-by-side metrics, and highlighted best performer.
Exportable Simulation Reports
"As a shop manager, I want to export simulation reports so that I can share insights with my team and stakeholders."
Description

Enables users to generate and download detailed simulation reports in PDF and CSV formats, including parameter settings, projection graphs, and comparative analysis. Reports are branded with shop identity and include date, scenario descriptions, and an executive summary to ensure easy sharing with stakeholders.

Acceptance Criteria
PDF Report Generation with Shop Branding
Given the user has completed a simulation and selected the "Export PDF" option When the system generates the report Then the PDF includes the shop’s logo, name, address, export date, scenario description, parameter settings table, projection graphs, comparative analysis, and an executive summary
CSV Report Download with Parameter Settings
Given the user has completed a simulation and selected the "Export CSV" option When the system generates the report Then the CSV file contains columns for each simulation parameter, timestamp, scenario identifier, and all raw projection data
Accuracy of Projection Graphs in Exported PDF
Given a completed simulation with known output values When the user views the exported PDF Then projection graphs in the PDF match the on-screen graphs exactly, including axis labels, data points, and scales
Executive Summary Content Verification
Given the simulation report is prepared for export When the user opens the exported PDF or reviews the CSV summary section Then the executive summary includes total projected revenue, variance from baseline, key performance indicators, and a concise narrative of parameter adjustments
Inclusion of Scenario Descriptions and Dates
Given one or more simulations have been run When the user exports any report format Then the report header displays the scenario name, detailed description, and the export date in ISO 8601 format

QuickExport

Generates polished, ready-to-share reports with a single click. Choose from customizable formats (PDF, Excel, CSV) to send to stakeholders, lenders, or marketing teams. Eliminates manual report preparation and ensures everyone has up-to-date insights.

Requirements

Export Format Selection
"As a shop manager, I want to select the desired export format (PDF, Excel, or CSV) so that I can share reports in the format best suited for my stakeholders."
Description

Enable users to choose from multiple export formats (PDF, Excel, CSV) when generating reports. The system will present format options in the QuickExport interface, apply consistent styling, and ensure exported files adhere to format-specific standards. This feature streamlines report delivery, accommodates diverse stakeholder preferences, and eliminates manual file conversions.

Acceptance Criteria
Format Option Visibility
When user opens the QuickExport interface, the export format dropdown lists PDF, Excel, and CSV; each option is selectable; default selection is PDF.
PDF Export Generation
Given user selects PDF and initiates export, when the process completes, then the downloaded file has a .pdf extension, opens without errors, contains all report content, and applies consistent styling (fonts, logos, headers).
Excel Export Generation
Given user selects Excel and initiates export, when the process completes, then the downloaded file has a .xlsx extension, includes all data columns, preserves cell formatting (bold headers, date and currency formats), and contains no empty sheets.
CSV Export Generation
Given user selects CSV and initiates export, when the process completes, then the downloaded file has a .csv extension, uses commas as delimiters, encloses fields containing commas in quotes, handles line breaks correctly, and is encoded in UTF-8.
Bulk Export Queueing
Given user queues multiple reports for export in different formats, when the queue is processed, then each report is exported in its selected format, a notification displays success or failure for each item, and valid exports complete without errors.
Custom Report Templates
"As a marketing coordinator, I want to create and save custom report templates so that I can quickly generate branded reports without repetitive setup."
Description

Provide a template configuration system allowing users to customize report layouts, including header/footer text, company logos, date ranges, and column selections. Templates can be saved and reused, ensuring brand consistency and reducing setup time for recurring reports. Integration with PulseQueue’s style guide ensures a polished, professional appearance.

Acceptance Criteria
Creating a New Custom Template
Given a user navigates to the template configuration page When they enter header and footer text, upload a company logo, select a date range and choose report columns Then the system saves the template and displays it in the saved templates list with correct settings and preview
Editing an Existing Template
Given a user selects a saved template from the list When they update header text, change the logo, modify column selections or adjust date ranges Then the system saves changes and updates the template preview to reflect the modifications
Applying a Saved Template During Export
Given a user initiates a report export When they choose a saved custom template from the export options Then the generated PDF, Excel or CSV report matches the template’s layout, includes the correct header/footer text, logo, date range and columns
Deleting a Saved Template
Given a user views the list of saved templates When they select a template and confirm deletion Then the template is removed from the list and is no longer available for report exports
Validating Template Against Style Guide
Given a user configures or edits a template When they save the template Then the system validates font, color, spacing, and logo placement against PulseQueue’s style guide and prevents saving if any element is non-compliant
Scheduled Auto-Exports
"As a shop owner, I want reports to be automatically generated and emailed every week so that I don't have to remember to export and send them manually."
Description

Implement scheduling capabilities for automatic report generation and delivery. Users can define frequency (daily, weekly, monthly), target formats, and recipient lists. The system will automatically generate and distribute reports via email or shared link, reducing manual effort and ensuring stakeholders receive timely insights.

Acceptance Criteria
Daily Export for Shop Manager
Given a shop manager schedules a daily report export in PDF format to a specified email list, when the schedule triggers at 00:00, then the system generates the PDF report and emails it to all listed recipients.
Weekly Excel Report with Multiple Recipients
Given a user sets up a weekly export for Excel format every Monday at 08:00 with multiple email recipients, when the scheduled time occurs, then the system produces the Excel file and delivers it to each specified email address.
Monthly CSV Shared Link Generation
Given an administrator configures a monthly CSV export on the first day at 09:00 with shared link delivery, when the schedule executes, then the system creates the CSV report, generates a unique secure link, and sends the link to recipients.
Modify Existing Schedule
Given a user edits an existing export schedule to change frequency and recipient list, when the user saves the changes, then the system updates the schedule, validates inputs, and displays a confirmation message.
Error Handling for Invalid Email Addresses
Given a user enters an invalid email address in the recipient field, when the user attempts to save the schedule, then the system validates the email list, displays an error message for the invalid address, and prevents saving until corrected.
Data Filters and Sorting
"As a financial analyst, I want to filter report data by service type and date so that I can focus on the metrics most relevant to my analysis."
Description

Allow users to apply filters (date range, service type, technician) and sorting options directly within QuickExport before exporting. Filtered and sorted data ensures recipients receive only relevant information, improving clarity and decision-making. Filters persist across sessions for user convenience.

Acceptance Criteria
Apply Date Range Filter
Given the user selects a valid start date and end date within the export dialog, when the user clicks 'Export', then the generated report includes only records with service dates on or after the start date and on or before the end date, and if the start date is after the end date, an error message is displayed and export is blocked.
Filter by Service Type
Given the user selects one or more service types from the filter dropdown, when the user initiates export, then the exported file contains only entries matching the selected service types and excludes all others.
Sort by Technician Name
Given the user enables sorting by technician name and chooses ascending or descending order, when the export is generated, then the report rows are ordered correctly by technician name in the chosen sequence.
Combined Filters and Sorting
Given the user applies a date range filter, selects service types, and sets a sort order, when export is executed, then the resulting report reflects all filters simultaneously and the data is sorted according to the specified criteria.
Persisting Filters Across Sessions
Given the user applies filters and logging out of the application, when the user logs back in and navigates to QuickExport, then the previously applied filters are automatically reapplied and visible in the filter panel.
One-Click Share Link
"As an auto repair shop manager, I want to generate a secure share link in one click so that I can instantly share reports with my team without attaching large files."
Description

Generate a unique, secure shareable link or direct email delivery for exported reports with a single click. Users can specify recipients and access permissions (view-only or editable). The feature simplifies report distribution, safeguards data, and tracks link access for audit purposes.

Acceptance Criteria
One-Click Link Generation
Given the user is on the exported reports page When the user clicks the "Generate Share Link" button Then a unique, secure shareable link is generated, displayed, and copied to the clipboard
Access Permission Assignment
Given the user opens the share dialog When the user selects "View-Only" or "Editable" permission Then the generated link enforces the selected access permission correctly
Direct Email Delivery
Given the user has entered one or more valid recipient email addresses When the user clicks "Send via Email" Then each recipient receives an email containing the report link and an indication of the assigned permissions
Secure Link Expiration
Given the user generates a shareable link When the link reaches its configured expiration time Then accessing the link displays an expiration notice and prevents report access
Link Access Tracking
Given a recipient clicks the shared link When the link is accessed Then an audit record is created capturing timestamp, recipient identifier, and IP address

Trend Tracker

Visualizes key performance indicators—revenue per bay, utilization rates, no-show trends—on intuitive graphs and heatmaps. Enables users to spot long-term patterns and seasonality effects to inform strategic planning and targeted promotions.

Requirements

Data Aggregation Engine
"As a shop manager, I want consolidated performance data aggregated from all scheduling and booking activities so that I can have a single source of truth for tracking trends."
Description

Develop a centralized engine to collect and normalize scheduling, transaction, and appointment data from various sources within PulseQueue. This engine will ensure data consistency, handle real-time updates, and support historical data retention for trend analysis, providing a reliable foundation for all visualizations and KPI computations.

Acceptance Criteria
Real-Time Data Ingestion Functionality
Given a scheduling update from any connected source when the update is emitted then the Data Aggregation Engine ingests and stores the record within 2 seconds and makes it available for downstream processing
Data Normalization Accuracy
Given raw scheduling, transaction, and appointment records with source-specific formats when processed by the engine then each record is transformed to match the unified schema with 100% field mapping accuracy and no data loss
Historical Data Retrieval Capability
Given a user requests aggregated data for any date range within the past 24 months when the query is executed then the engine returns the complete dataset within 5 seconds and preserves original timestamps
Data Consistency Under Load
Given continuous concurrent updates from up to 500 simultaneous source connections during peak hours when processed then the engine maintains ACID properties, ensuring no duplicate or missing records
Source System Failure Recovery
Given an upstream data source outage when connectivity is restored then the engine automatically backfills missed records without manual intervention and logs reconciliation results
KPI Calculation Module
"As a shop manager, I want accurate KPI calculations for revenue, utilization, and no-shows so that I can trust the insights generated by the Trend Tracker."
Description

Implement a robust calculation module that processes aggregated data to compute key performance indicators such as revenue per bay, bay utilization rates, and no-show percentages. This component must support configurable time intervals and handle edge cases like partial appointments to deliver accurate and timely metrics.

Acceptance Criteria
Monthly Revenue per Bay Calculation
Given aggregated appointment and transaction data for a calendar month When the KPI Calculation Module processes this data Then it calculates revenue per bay by summing appointment fees per bay, divides by the number of days in the month, and outputs values matching expected benchmarks within 0.1%
Daily Utilization Rate with Partial Appointments
Given appointment schedules with start and end times, including partial-day bookings When the module computes daily utilization Then it calculates total occupied bay time divided by total available bay time and returns utilization rates to two decimal places, matching manual calculations within 0.1%
No-show Percentage for Configurable Intervals
Given appointment records flagged as no-show and total scheduled appointments for a user-selected interval When the KPI module processes the data Then it calculates no-show percentage by dividing no-show count by total scheduled appointments multiplied by 100, returning results within 0.1% of expected values
Edge Case Handling for Overlaps and Cancellations
Given overlapping appointments and cancellation records within the data set When the module aggregates KPIs Then it excludes canceled appointments, counts overlapping times only once in utilization, and produces correct revenue, utilization, and no-show metrics
Custom Time Interval Adjustment
Given a user-defined time interval (e.g., weekly, quarterly) When the KPI Calculation Module executes Then it filters appointment data strictly within interval boundaries and calculates revenue, utilization, and no-show metrics accurately for that interval
Interactive Graph Visualizations
"As a shop manager, I want to interact with graphs and drill down into specific metrics so that I can identify patterns and anomalies across different time periods."
Description

Create dynamic, interactive chart components (line, bar, and area charts) to display KPIs over selectable date ranges. Features should include hover tooltips, zooming, filtering by shop location or bay, and toggling individual metrics on and off, enabling users to explore data-driven insights directly within the dashboard.

Acceptance Criteria
Revenue per Bay Date Range Selection
Given the user selects a custom start and end date, When the date range is applied, Then the line chart updates to show daily revenue per bay within that range.
Hover Tooltip Display
Given the user hovers over a data point on any chart, Then a tooltip appears showing the exact value, date, and metric name.
Chart Zoom Functionality
Given the user selects a time span via drag or zoom controls, Then the chart zooms in to that period and updates axes accordingly.
Shop Location Filtering
Given the user selects one or multiple shop locations from the filter menu, Then the charts refresh to display data only for the selected locations.
Metric Toggle Control
Given the user toggles a metric's visibility in the legend, Then the corresponding data series shows or hides on the chart in real time.
Heatmap Visualization Module
"As a shop manager, I want to view heatmaps of bay utilization and no-show occurrences so that I can quickly identify busy periods and optimize my scheduling strategy."
Description

Design and integrate heatmap visualizations to showcase utilization and no-show patterns across days of the week and times of day. The module should allow custom thresholds, color scales, and overlay annotations to help users pinpoint peak demand windows and underutilized slots at a glance.

Acceptance Criteria
Default Heatmap Display for Weekly Utilization
Given the user navigates to the Heatmap Visualization Module with no custom filters applied When the module loads Then a heatmap displaying utilization rates for each day of the current week and each hourly time slot must render using the default color scale And each heatmap cell must show the correct utilization percentage in a tooltip on hover And the default color scale must meet WCAG 2.1 AA contrast standards
Custom Threshold Highlighting
Given the user sets a low utilization threshold to 20% and a high utilization threshold to 80% When the user applies these thresholds Then all heatmap cells with utilization below 20% use the low-threshold color And all cells with utilization above 80% use the high-threshold color And intermediate values use the gradient color scale
Overlay Annotation for Peak Demand Windows
Given the user enables peak demand annotations When peak demand periods are detected based on utilization data Then the heatmap displays an annotation marker over the corresponding time slot cells labeled 'Peak Demand' And clicking the annotation shows exact time, date, and utilization percentage
Date Range Filtering for Heatmap Data
Given the user selects a custom start date of 2025-05-01 and end date of 2025-05-31 When the user applies the date range filter Then the heatmap updates to display only data within the specified date range And all utilization values outside the range are excluded from the visualization
Export Heatmap as Image and CSV
Given the user clicks the 'Export' button When the dropdown appears Then selecting 'Export as PNG' triggers download of the currently displayed heatmap as a PNG image And selecting 'Export as CSV' triggers download of a CSV file containing date, time slot, and utilization for each cell displayed
Trend Export and Reporting
"As a shop manager, I want to export KPI reports and raw data so that I can share insights with my team and incorporate them into strategic planning sessions."
Description

Enable export functionality for both visual charts and underlying data. Users should be able to download PDF reports with embedded graphs and CSV files containing raw KPI values and timestamps. Include customizable report templates and scheduling options for regular automated report delivery.

Acceptance Criteria
Raw Data CSV Export
Given the user selects a date range and clicks “Download CSV” on the Trend Export page, when the export process completes, then a CSV file containing raw KPI values and precise timestamps for the selected range is downloaded and named “trend_export_<YYYYMMDD_HHMMSS>.csv”
Embedded Graph PDF Report
Given the user chooses “Export to PDF” and selects desired KPIs and time period, when the PDF is generated, then the report includes high-resolution charts with titles, legends, and axis labels, and is downloaded as “trend_report_<YYYYMMDD>.pdf”
Custom Report Template Creation
Given the user accesses the template settings and configures header, footer, selected KPIs, and layout, when the user saves the template, then the template appears in the list of available report templates and can be selected for future exports
Scheduled Report Delivery
Given the user schedules a report with chosen template, frequency, and recipient emails, when the schedule is active, then system sends the correctly formatted report via email at the specified intervals and logs delivery status
Bulk Export Performance
Given the user requests exports for a large date range or multiple KPIs in one operation, when the export is initiated, then the system completes and delivers the CSV or PDF file within 60 seconds under normal server load conditions

Product Ideas

Innovative concepts that could enhance this product's value proposition.

BayBlink Alerts

Automatically ping managers when bays sit idle over 10 minutes, boosting utilization by filling gaps instantly.

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NoShow Zap

Send personalized SMS two hours before appointments with instant rebook links, slashing no-shows by up to 50%.

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Discount Dash Slots

Offer time-limited discounted slots to waitlisted customers via SMS, filling empty bays within minutes.

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TechTrack Pro

Enable technicians to update job progress via voice-to-text on mobile, syncing live with the scheduler.

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Revenue Radar

Deliver weekly AI-driven reports highlighting revenue gaps and schedule tweaks, with one-click export.

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Press Coverage

Imagined press coverage for this groundbreaking product concept.

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PulseQueue Unveils AI-Powered Scheduling to Slash No-Shows and Boost Auto Shop Revenue

Imagined Press Article

City, State – 2025 marks a turning point for independent auto repair shop owners grappling with empty bays, missed bookings and unreliable manual scheduling. Today, PulseQueue, the leading AI-driven appointment management platform, officially launches its full suite of intelligent scheduling tools—automating calendar optimization, reducing no-shows by 40%, and maximizing bay utilization to drive higher shop revenue. In an industry where every open bay represents lost income, PulseQueue’s advanced machine learning engine analyzes shop capacity, technician workloads and historical appointment patterns to automatically balance repair schedules and fill idle slots with minimal intervention. Real-time SMS reminders learn each customer’s responsiveness, ensuring messages arrive at the optimal moment and cut no-shows by almost half. Busy managers and owner-operators can now free themselves from manual calendar juggling, stay focused on repairs and deliver a superior customer experience. “Independent shops have been underserved by one-size-fits-all scheduling tools,” said Jordan Lee, CEO of PulseQueue. “We built an intelligent system that adapts to each shop’s unique workflow, technician skill levels and customer behaviors. Instead of chasing no-shows and scrambling to fill gaps, managers can rely on AI to handle the heavy lifting and keep bays running at peak efficiency.” Key highlights of the PulseQueue launch include: • AI-Powered Load Balancing: The core engine distributes appointments across technicians and bays, taking into account individual skill sets, estimated service times and priority customers. Busy shops can avoid overloading top performers while ensuring every technician contributes effectively. • Real-Time SMS Reminder Network: SmartScheduler analyzes customers’ historical reply and click-through patterns to pinpoint the ideal reminder window. Combined with InstaReschedule’s one-tap booking links embedded in messages, rebooking friction drops to near zero. • Automated Waitlist Reach-Out: When unexpected cancellations or service delays occur, PulseQueue identifies high-value waitlisted customers and sends targeted text or email offers, keeping bays full even during last-minute disruptions. • Comprehensive Analytics and Reporting: The Idle Insight Dashboard and Performance Pulse analytics provide actionable snapshots of bay utilization, no-show trends and reminder performance. Managers can export custom reports for financial planning, staff meetings or lender presentations. • Flexible Escalation Paths: If idle bays linger beyond predefined thresholds, alerts escalate from in-app notifications to SMS or email—guaranteeing critical issues get addressed before they impact revenue. James Hernandez, owner-operator of SpeedWorks Auto in Denver, has already participated in a closed beta. “PulseQueue transformed our scheduling overnight. We cut no-shows by more than 45 percent, and idle bays are a thing of the past. The system even suggested same-day service slots to customers on our waitlist, which boosted our daily revenue by 12 percent. It’s like having a dedicated operations manager 24/7.” PulseQueue’s flexible pricing model scales with shop growth—ensuring even cost-conscious independent owners can benefit from enterprise-grade scheduling innovations. Early adopters receive onboarding support, hands-on training and access to PulseQueue’s integration partners, including leading shop management systems and CRM platforms. Looking ahead, PulseQueue plans to introduce advanced features such as dynamic discount engines that automatically generate optimized offers based on real-time idleness and customer value, as well as AI-driven “What-If” scenario simulators for proactive capacity planning. The company is committed to fostering a thriving community of garage professionals dedicated to operational excellence. About PulseQueue PulseQueue is a Silicon Valley–based technology company transforming appointment scheduling for independent auto repair shops. Its AI-powered platform automates load balancing, customer communications and analytics to maximize bay utilization, minimize no-shows and drive sustainable revenue growth. Media Contact: Samantha Nguyen Public Relations Manager, PulseQueue Phone: (555) 123-4567 Email: pr@pulsequeue.ai Website: www.pulsequeue.ai

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PulseQueue Debuts Idle Insight Dashboard to Maximize Bay Utilization in Auto Repair Shops

Imagined Press Article

San Francisco, CA – June 8, 2025 – PulseQueue today announced the official release of its Idle Insight Dashboard, a real-time visual tool designed to help independent auto repair shops instantly identify and eliminate unused bay time. This new feature delivers color-coded status maps, custom alerts and automated filling suggestions—transforming how shops monitor and optimize daily operations. Repair shop managers know that every minute a bay sits idle is lost revenue. Yet manual tracking and reactive decision-making often leave gaps in the schedule and revenue on the table. The Idle Insight Dashboard addresses this challenge by providing at-a-glance visibility into bay status, technician workloads, and upcoming appointments. Powered by PulseQueue’s AI engine, the dashboard pinpoints idle periods as they occur and recommends actionable next steps to fill open slots. “Idle Insight is a game-changer for shops that want to proactively manage capacity and boost profitability,” said Priya Desai, VP of Product at PulseQueue. “By highlighting underutilized bays in real time and coupling alerts with automated suggestions, managers can make faster decisions and tap into revenue opportunities that were previously invisible.” Key capabilities of the Idle Insight Dashboard include: 1. Real-Time Bay Status Visualization: A sleek interface displays each service bay in color-coded segments—green for active, yellow for approaching thresholds, and red for idle. Managers can immediately see which bays require attention. 2. Custom Idle Rules: Shops can define individual thresholds for each bay type or technician based on service complexity and historical data. This personalization prevents false alarms and ensures notifications remain relevant to unique shop workflows. 3. Auto-Fill Suggestions: When a bay transitions to idle, PulseQueue’s AI reviews waitlisted customers and quick-turn service options, then proposes or auto-assigns suitable appointments. This reduces downtime and drives incremental revenue. 4. Escalation Path Notifications: Alerts escalate from in-app pop-ups to SMS and email reminders if idle periods persist. Shop owners and managers can adjust escalation settings to match their operational preferences. 5. Waitlist Reach-Out Integration: If AI suggestions require confirmation from customers on the waitlist, the system automatically sends targeted SMS or email offers—capturing appointments within minutes of a gap opening. Beta users report significant improvements in bay utilization and revenue. “Before Idle Insight, we often didn’t realize a technician had downtime until the end of the day,” said Elena Martinez, shop manager at ProFix Auto in Austin. “Now, I get real-time alerts and can fill open slots almost instantly. In our first week, we increased bay utilization by 22 percent and saw a 10 percent lift in daily revenue.” PulseQueue offers the Idle Insight Dashboard as part of its core scheduling platform, with seamless integration into existing shop management systems. The feature is available to all PulseQueue subscribers at no additional cost until August 1, 2025, after which it will be included in the Professional and Enterprise plans. About PulseQueue PulseQueue is an AI-driven appointment scheduling solution built for independent auto repair shops. Its suite of intelligent tools automates appointment distribution, customer communications, and performance analytics—helping shops reduce no-shows, optimize bay usage and improve operational efficiency. For media inquiries, please contact: Alex Chen Director of Communications, PulseQueue Phone: (555) 987-6543 Email: media@pulsequeue.ai Website: www.pulsequeue.ai

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PulseQueue Introduces TechTrack Pro Voice Integration for Seamless Technician Updates

Imagined Press Article

Los Angeles, CA – June 8, 2025 – PulseQueue, the industry’s leading AI-driven scheduling platform for independent auto repair shops, today launched TechTrack Pro, an advanced voice integration suite that enables technicians to update job statuses hands-free—drastically reducing administrative burden and improving real-time accuracy of shop schedules. In busy repair environments, technicians often halt their work to manually log progress, record parts usage and update anticipated completion times. These interruptions slow down service delivery and increase the likelihood of scheduling errors. TechTrack Pro eliminates manual entry through a combination of voice-to-text transcription, context-aware prompts and offline recording—ensuring the central scheduler always reflects the latest job data without disrupting the technician’s workflow. “Techs are the heart of every auto repair operation,” said Maria Gomez, Chief Technology Officer at PulseQueue. “With TechTrack Pro, we’re empowering them to stay focused on repairs while our AI handles real-time data capture. The result is a more accurate schedule, fewer surprises for managers and customers, and a smoother overall experience for everyone involved.” TechTrack Pro’s core components include: • InstantVoice Sync: Technicians speak status updates directly into their mobile device or hands-free headset. The system transcribes updates—such as parts used, time logs and next steps—and instantly updates the central scheduler. • GuidedPrompt Workflow: Context-aware voice prompts walk technicians through structured updates, ensuring critical information is captured completely and consistently. For example, after logging a repair milestone, GuidedPrompt might ask for estimated time to completion. • SmartTerm Correction: PulseQueue’s proprietary AI lexicon recognizes shop-specific terminology, part numbers and technician names—automatically standardizing text entries and reducing errors. • Offline Resync: In areas of limited connectivity, TechTrack Pro stores voice recordings locally and automatically synchronizes them once network coverage returns—delivering uninterrupted updates without data loss. • Hands-Free Hub Integration: For maximum safety and convenience, TechTrack Pro connects with Bluetooth headsets and wearable devices—enabling fully hands-free operation, even when technicians are working under vehicles or handling hazardous components. Early adopters have seen dramatic improvements in data accuracy and operational flow. “TechTrack Pro has revolutionized our bay communication,” said Tyler Nguyen, lead technician at Precision Auto Care in Seattle. “I no longer have to find a free moment to type updates into a tablet. I speak my progress and move right back to the work. Our schedule is more reliable, and managers can plan staffing and bay assignments with confidence.” The launch of TechTrack Pro further solidifies PulseQueue’s mission to deliver end-to-end automation for auto repair shops—combining powerful scheduling algorithms, intelligent customer reminders and now frictionless technician reporting. Next on the roadmap are feature enhancements that will leverage voice data to automatically trigger down-time offers via the Discount Dash Slots and integrate scheduling insights with third-party parts ordering systems. About PulseQueue PulseQueue is a San Francisco-based software company dedicated to transforming appointment and workflow management for independent auto repair shops. By harnessing AI-driven load balancing, real-time communication and voice integration, PulseQueue helps shops eliminate inefficiencies, reduce no-shows and maximize revenue. Media Contact: Rachel Dawson Communications Lead, PulseQueue Phone: (555) 246-8100 Email: press@pulsequeue.ai Website: www.pulsequeue.ai

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