Food Truck Management SaaS

MenuZap

Serve Fresh Fast, Every Order

MenuZap equips independent food truck owners with a live, mobile dashboard to manage orders, inventory, and menus in real time from any device. Instantly mark items as sold out, eliminate order mistakes, and serve only what’s truly available—keeping lines fast, customers happy, and daily sales on track during even the busiest shifts.

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MenuZap

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 food truck owner to run with the speed, precision, and confidence of a world-class restaurant anywhere.
Long Term Goal
Empower 10,000 food trucks in North America to cut order errors by 50% and boost sales by 20% through real-time mobile operations within four years.
Impact
Reduces food truck order errors by 50% and stockout complaints by 75%, enabling independent owners to serve customers only what's available in real time and increasing daily sales by ensuring every menu update instantly reaches both staff and customers on any device.

Problem & Solution

Problem Statement
Independent food truck owners struggle with order mistakes and frustrated customers because paper menus and costly POS systems can’t update availability in real time, resulting in lost sales and inefficiency during busy shifts.
Solution Overview
MenuZap gives food truck owners a live, mobile dashboard to update menus and inventory in real time, letting them mark items as sold out instantly so customers only order what's actually available—eliminating order mistakes and disappointing lines at the window.

Details & Audience

Description
MenuZap gives food truck owners a simple, all-in-one dashboard to manage orders, inventory, and menus in real time from any device. Independent operators eliminate order errors and sold-out surprises, serving customers only what’s truly available. Live menu updates set MenuZap apart—customers always see and order from your up-to-date menu, keeping lines fast and frustration low.
Target Audience
Independent food truck owners (25-50) frustrated by manual order tracking and craving real-time, mobile simplicity.
Inspiration
One busy Friday night, I watched a food truck owner frantically cross out menu items with a fading Sharpie as impatient customers kept ordering dishes that were already gone. The look of frustration on both sides was unmistakable. In that chaotic moment, I saw how a simple live-updating menu could save owners stress and ensure customers never left disappointed.

User Personas

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

S

Social Seller Sam

- Age 28, male vendor-entrepreneur - Bachelor’s in marketing - 2 years social-media-driven vending - Annual revenue $80k–$120k

Background

He began as a social media manager, then launched his food truck to blend content creation with street food. Early livestream successes taught him the power of real-time updates, shaping his demand for instant menu status.

Needs & Pain Points

Needs

1. Real-time social media menu status updates 2. Seamless livestream integration for selling 3. Instant visual menu availability dashboard

Pain Points

1. Lag between inventory changes and social posts 2. Manual screenshotting slows content creation 3. Inconsistent follower turnout after updates

Psychographics

- Obsessed with real-time audience engagement - Values instant, transparent feedback loops - Loves crafting stories through live content

Channels

1. Instagram Stories – live updates 2. TikTok – short-form videos 3. Facebook Live – community engagement 4. Twitter – quick status tweets 5. YouTube Shorts – promotional clips

A

Allergy Advocate Ava

- Age 32, female, nutrition degree - Former clinical dietitian turned vendor - Specializes in allergy-friendly cuisine - Annual revenue $60k–$90k

Background

She spent five years as a clinical dietitian, then launched her food truck to deliver allergy-safe meals. Early labeling errors fueled her commitment to absolute menu accuracy and cross-contamination prevention.

Needs & Pain Points

Needs

1. Precise allergen labeling for every menu item 2. Real-time tracking of sold-out allergen-free options 3. Integrated nutritional information display

Pain Points

1. Risk of accidental allergen cross-contamination 2. Incomplete ingredient data blocks labeling 3. Customer distrust after past menu mistakes

Psychographics

- Passionate about customer dietary safety - Strictly methodical about detailed ingredient tracking - Driven by food safety standards - Empathetic to customer dietary anxieties

Channels

1. Instagram Posts – allergen highlights 2. Email Newsletters – menu updates 3. Pinterest Boards – recipe inspiration 4. Food Safety Forums – professional insights 5. Website – detailed allergen menus

C

Combo Curator Chris

- Age 35, male, culinary diploma - 5-year independent truck operator - Urban street-food specialist - Annual revenue $120k–$150k

Background

He transitioned from sous-chef to truck owner to explore entrepreneurial creativity. Early combo flops prompted him to seek dynamic menu tools, leading to adoption of real-time inventory-driven bundling.

Needs & Pain Points

Needs

1. Dynamic combo creation reflecting live inventory 2. Clear sell-through metrics for bundle components 3. Automated price suggestions based on bundle data

Pain Points

1. Tracking bundle availability is manual and error-prone 2. Unsold combos eat into profits 3. Complex price updates across multiple combos

Psychographics

- Deeply strategic about bundle profitability - Boldly experimentative with menu offerings - Thrives on precise data-driven decisions - Optimizes for customer perceived value

Channels

1. LinkedIn Groups – culinary entrepreneurship 2. Food Blogs – business strategies 3. Instagram Ads – targeted promotions 4. Email Marketing – bundle campaigns 5. MenuZap App – advanced analytics

P

Peak Performer Piper

- Age 29, female, hospitality diploma - Former restaurant shift lead - Operates in dense urban centers - Annual revenue $200k+

Background

She cut her teeth managing high-volume restaurant shifts before starting her own truck. Early service bottlenecks drove her to seek tools that guarantee uninterrupted order flow.

Needs & Pain Points

Needs

1. Order confirmations under five seconds 2. Automated sold-out alerts during peak rushes 3. Simplified batch processing interface

Pain Points

1. Service bottlenecks cause long lines 2. Manual menu toggles slow order flow 3. Order mistakes escalate under noisy conditions

Psychographics

- Thrives under extreme high-pressure service - Values absolute flawless operational efficiency - Adapts quickly to rapid changes

Channels

1. Slack – team coordination 2. MenuZap Dashboard – live operations 3. SMS Alerts – urgent notifications 4. WhatsApp Groups – staff chat 5. Local Vendor Forums – peer advice

S

Sustainability Seeker Sophia

- Age 38, female, environmental studies degree - Organic-focused food truck owner - Operates in eco-conscious markets - Annual revenue $100k–$130k

Background

She transitioned from nonprofit sustainability work to running an eco-friendly truck. Early overstock losses drove her to demand precise waste forecasting tools.

Needs & Pain Points

Needs

1. Detailed waste tracking per menu item 2. Accurate demand forecasting reports 3. Local supplier integration options

Pain Points

1. Unpredictable spoilage rates undermine planning 2. Overstocked perishables lead to waste 3. Syncing with small growers is difficult

Psychographics

- Committed to absolute zero-waste operations - Values totally transparent supply chains - Fiercely passionate about environmental stewardship

Channels

1. Eco-Friendly Blogs – sourcing tips 2. Instagram – sustainability stories 3. Vendor Networks – local sourcing 4. Email Alerts – waste reports 5. Farmers Market Apps – supplier connections

Product Features

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

Auto Rebalance

Automatically shifts surplus inventory from trucks with excess stock to those running low, ensuring each location stays optimally supplied without manual intervention. Reduces stockouts, minimizes waste, and balances resources across your fleet in real time.

Requirements

Real-time Inventory Monitoring
"As a food truck operator, I want real-time visibility into my current inventory levels so that I can see which items are available and when stock is running low."
Description

Continuously collect and update inventory levels from each food truck via the mobile dashboard, ensuring that stock data is synchronized in real time. This functionality provides up-to-the-second visibility into item availability, supports accurate rebalancing decisions, and integrates seamlessly with existing inventory management modules.

Acceptance Criteria
Real-Time Stock Level Update Frequency
Given any inventory transaction occurs on a truck When the transaction is completed Then the updated stock level appears on the mobile dashboard within 2 seconds of the change
Dashboard Inventory Accuracy Validation
Given a physical inventory count is performed randomly on a truck When the count is compared to the dashboard data Then the dashboard’s reported inventory must match the physical count with no more than ±1 unit variance 100% of the time
Offline Sync Recovery
Given a food truck experiences network disconnection When the network is restored Then all offline inventory transactions are synchronized and the dashboard inventory is updated correctly within 5 seconds
High-Volume Order Impact on Updates
Given multiple orders (e.g., 100 orders) are placed within a 5-second window When the orders are processed Then each item’s inventory is updated on the dashboard accurately with no lost or duplicated updates and within the defined real-time threshold
User Notification on Critical Stock Threshold
Given an item's stock level falls below the predefined critical threshold When the dashboard receives the update Then the system highlights the item in red and displays an alert notification to the user within 1 second
Surplus Detection Algorithm
"As an operations manager, I want the system to detect when a truck has excess stock compared to demand so that I can reallocate resources efficiently."
Description

Implement an intelligent algorithm that analyzes inventory data across the fleet to identify trucks with excess stock relative to demand. The algorithm calculates optimal transfer quantities, prioritizes items according to spoilage risk and sales velocity, and integrates with the inventory monitoring system for continuous evaluation.

Acceptance Criteria
Post-Peak Surplus Identification
Given inventory data updated every 15 minutes, when actual stock for an item exceeds forecasted demand by 25% or more over the next two-hour window in the last three intervals, then the algorithm must flag that item as surplus.
Spoilage Risk Prioritization
Given perishable items with shelf-life metadata and current age, when surplus is detected, then items with spoilage risk scores above 80% must be prioritized for transfer before lower-risk items.
Low Inventory Alert and Transfer Initiation
Given a truck’s stock level falls below its predefined reorder threshold for any item, when the next inventory evaluation occurs, then the algorithm must generate transfer suggestions from trucks with surplus within five minutes of threshold breach.
Optimal Transfer Quantity Calculation
Given flagged surplus and low-inventory items, when calculating transfer quantities, the algorithm must propose amounts that balance both trucks within a 10% deviation of their target inventory levels while respecting vehicle capacity and current sales velocity.
Real-Time Continuous Monitoring
Given the fleet’s inventory is evaluated at five-minute intervals, when new stock data arrives, then surplus detection and transfer suggestion updates must complete within one minute to ensure near real-time responsiveness.
Transfer Request Scheduling
"As a logistics coordinator, I want the system to automatically schedule inventory transfers at off-peak times so that trucks can rebalance stock without disrupting service."
Description

Create a scheduling component that generates and manages inventory transfer requests between trucks at appropriate times. The system should optimize transfer windows based on route proximity and peak service hours, and automatically notify drivers of pending transfers to minimize service disruption.

Acceptance Criteria
Off-Peak Optimal Transfer Scheduling
Given Truck A inventory for Item X falls below reorder threshold and Truck B inventory for Item X exceeds surplus threshold When current time is identified as an off-peak period and route distance between trucks is within predefined proximity limit Then the system schedules a transfer request within the next available off-peak window and records the scheduled time in the dashboard
Driver Notification Dispatch
Given a transfer request is successfully scheduled When the scheduled departure time for transfer is 30 minutes away Then the system sends a push notification to the assigned driver’s mobile app containing transfer details (items, quantity, origin, destination, departure time)
Peak Service Hour Avoidance
Given peak service hours are defined (e.g., 11:00–14:00) When the optimal transfer window calculated falls within peak hours Then the system defers scheduling to the nearest adjacent off-peak window and logs the adjustment reason
Transfer Window Conflict Resolution
Given two or more transfer requests are scheduled for the same truck with overlapping windows When the system detects the overlap Then it automatically adjusts one request to the next viable off-peak slot or flags the conflict for dispatcher review
Manual Scheduling Override
Given an automatic transfer request exists When a dispatcher manually updates the transfer departure time or route Then the system applies the override, updates the schedule in real time, and notifies the driver of the changes
Admin Override Controls
"As an admin user, I want to manually override the automatic transfer suggestions so that I can accommodate special events or forecasted demand."
Description

Develop an interface allowing managers to manually adjust or override automatic rebalancing suggestions. Features include modifying transfer quantities, cancelling or postponing transfers, and inputting special event or forecast data to refine the automatic decisions, ensuring full operational flexibility.

Acceptance Criteria
Adjust Transfer Quantity Manually
Given an auto-rebalance suggestion is displayed, when the manager inputs a custom transfer quantity and saves, then the dashboard updates to reflect the new quantity and persists the override in the transfer plan.
Cancel Suggested Transfer
Given a pending transfer exists, when the manager clicks 'Cancel Transfer' and confirms the action, then the transfer is removed from the schedule and no inventory movement occurs for that suggestion.
Postpone Scheduled Transfer
Given a scheduled transfer in the upcoming hour, when the manager selects 'Postpone Transfer' and chooses a new date/time, then the transfer is rescheduled accordingly and the updated schedule is displayed.
Input Special Event Forecast Data
Given there is a special event date in the future, when the manager enters event forecast data into the override interface and submits, then the rebalancing algorithm recalculates suggestions based on the new forecast and updates displayed recommendations.
Override with Manual Forecast Data
Given the manager inputs manual demand forecast data for a specific truck, when the override is applied, then the system recalculates and displays updated auto-rebalance suggestions that incorporate the manual forecast.
Notification and Alerts
"As a truck operator, I want to receive alerts when a transfer is initiated or completed so that I can prepare for incoming or outgoing deliveries."
Description

Implement a notification system that sends real-time alerts to truck operators and managers when transfers are scheduled, executed, or fail. Alerts should be delivered via in-app messages, push notifications, or SMS, and include details on items, quantities, and timing to ensure all stakeholders stay informed.

Acceptance Criteria
Scheduled Transfer Notification
Given a transfer is scheduled via the Auto Rebalance module, when the schedule is confirmed, then an alert must be sent within 30 seconds via in-app message, push notification, and SMS containing item name, quantity, origin truck, destination truck, and scheduled transfer time.
Successful Transfer Notification
Given a transfer completes successfully, when the inventory arrives at the destination, then an alert must be delivered within 30 seconds via in-app message and push notification (with SMS fallback) detailing item name, quantity moved, departure time, and arrival time.
Failed Transfer Notification
Given a transfer fails, when the system logs a transfer error, then an alert must be sent within 1 minute via in-app message and SMS including item name, quantity attempted, scheduled time, and specific failure reason.
Notification Delivery Method Fallback
Given the primary notification channel fails, when a push notification or in-app message is not delivered within 30 seconds, then an SMS fallback must be triggered and delivered within 1 minute containing the full transfer details.
Notification Content Completeness
Given any transfer-related notification is sent, when the message is constructed, then it must include all required fields (item names, quantities, origin, destination, and timestamp) with no missing or null values.

Smart Threshold Alerts

Sets customizable low-stock triggers for each ingredient or menu item and sends instant alerts when levels dip below your preferred threshold. Proactively alerts you before shortages occur, giving you time to restock or rebalance.

Requirements

Threshold Configuration Interface
"As a food truck owner, I want to configure customizable low-stock thresholds for each menu item so that I can proactively manage inventory and avoid running out of popular items during service."
Description

Develop an intuitive interface within the MenuZap dashboard that allows food truck owners to set and customize low-stock triggers for each ingredient and menu item. The interface will provide input fields for defining threshold values, options for unit measurements, and bulk-edit capabilities. It will integrate with existing inventory data to display current stock levels and recommended thresholds based on historical usage patterns. The solution will ensure seamless navigation, validation of input values to prevent configuration errors, and immediate reflection of changes across the system.

Acceptance Criteria
Single Item Threshold Configuration
Given a food truck owner views an individual menu item's threshold settings, when they enter a valid numeric threshold value and click 'Save', then the system stores the new threshold, updates the displayed current stock level with the threshold marker, and persists the change across page reloads.
Bulk Threshold Editing
Given a user selects multiple ingredients or menu items from the inventory list, when they input a common threshold value and apply the bulk update, then the system updates each selected item's threshold, displays a success confirmation, and reflects the changes in the inventory dashboard.
Unit Measurement Selection
Given an owner configures a threshold for an ingredient available in multiple units, when they select a unit of measurement from the dropdown and save, then the system converts the threshold to the base unit, stores both the unit type and value, and displays the threshold in the selected unit consistently throughout the interface.
Validation for Invalid Threshold Values
Given a user enters an invalid threshold value such as negative numbers, zero, or non-numeric characters, when they attempt to save, then the system blocks the save action and shows an inline error message explaining valid input requirements.
Historical Usage Recommended Threshold Display
Given the owner opens the threshold configuration interface for an ingredient, when the historical usage data has been processed, then the system displays a recommended threshold value based on the past 30 days of usage, marked as 'Recommended' next to the input field.
Threshold Change Reflection in Alerts
Given a threshold is updated and saved, when the system next evaluates stock levels against thresholds, then any resulting low-stock alerts are immediately recalculated and visible in the Alerts section, matching the new thresholds.
Real-time Inventory Monitoring
"As a food truck operator, I want the system to monitor stock levels in real time so that I can receive instant alerts when my inventory dips below critical thresholds."
Description

Implement a background service that continuously tracks inventory levels in real time, comparing live counts against configured low-stock thresholds. The service will fetch updates from the inventory database every minute, calculate current stock availability, and flag any items that fall below their thresholds. It will be designed for high efficiency and minimal performance impact, supporting large menus and rapid order volumes without degrading dashboard responsiveness.

Acceptance Criteria
Threshold Breach Detection
Given the real-time inventory service is running and monitoring stock levels When any menu item’s available stock count drops below its configured low-stock threshold Then the dashboard must highlight that item with a “Low Stock” status within 30 seconds of the drop
Continuous Polling Interval
Given the background service is deployed in production When the service runs continuously over 10 consecutive minutes Then it should perform inventory data fetches from the database every 60 ± 2 seconds without missing or overlapping intervals
High Volume Performance
Given a sustained order rate of 500 orders per minute When the service executes its inventory check Then the entire fetch-and-compare cycle must complete in under 5 seconds and consume no more than 5% additional CPU on the dashboard server
Database Failure Resilience
Given an intermittent database connectivity error When an inventory fetch fails Then the service retries up to three times at 20-second intervals and, if still unsuccessful, logs a descriptive error without crashing or delaying the next scheduled fetch
Accuracy of Stock Calculation
Given multiple concurrent order submissions affecting the same ingredient When the service aggregates stock changes Then the calculated inventory level on the dashboard must match the actual database records with a discrepancy of no more than one unit
Alert Notification Delivery
"As a busy food truck owner, I want to receive low-stock notifications via my preferred channel so that I can take immediate action without constantly monitoring the dashboard."
Description

Design and implement a notification engine that sends instant low-stock alerts through multiple channels, including in-app pop-ups, email, and SMS. The engine will respect user preferences for delivery methods and frequency, queue notifications to prevent duplicates, and allow for snoozing alerts if restocking is in progress. It will include retry logic for failed deliveries and logging for audit trails, ensuring that critical inventory alerts reliably reach users.

Acceptance Criteria
Threshold Breach In-App Notification
Given a menu item’s stock falls below its configured low-stock threshold When the system detects the threshold breach Then an in-app pop-up must display within 5 seconds showing the item name and remaining stock count And the pop-up must not repeat for the same item within 10 minutes
Email Alert Delivery with Retry Logic
Given the user has enabled email notifications for low-stock alerts When a threshold breach occurs Then an email must be sent within 1 minute containing the item name, threshold, and current stock level And if the email delivery fails, the system must retry sending up to 3 times at 2-minute intervals
SMS Alert Delivery Preference Enforcement
Given the user has selected SMS as a delivery method When multiple low-stock events occur simultaneously Then the system must batch SMS notifications into a single message listing all items below threshold, sent within 2 minutes of the first event
Notification Snooze Functionality
Given the user has snoozed alerts for a specific item When the item’s stock remains below threshold during the snooze period Then no new alerts are sent for that item until the snooze period ends or the stock is replenished above threshold
Audit Logging of Alert Deliveries
Given any alert is generated for a threshold breach When the alert is sent or attempted Then the system must record a log entry including timestamp, item ID, delivery method, delivery status, and retry attempts
Threshold Adjustment Recommendations
"As a food truck owner, I want the system to recommend low-stock threshold values based on my historical usage so that I can set more accurate triggers without manual analysis."
Description

Integrate a recommendation engine that analyzes historical sales and usage data to suggest optimal low-stock thresholds for each menu item. The engine will consider seasonality, past stockouts, and average daily usage to generate threshold recommendations. Recommendations will be displayed alongside current settings, with a one-click option to apply suggested values. This feature will help owners fine-tune thresholds and reduce manual guesswork.

Acceptance Criteria
Display of Recommended Thresholds
Given the user opens the threshold settings page, when the recommendation engine runs, then each menu item’s suggested low-stock threshold is displayed next to its current threshold value.
One-Click Apply of Suggested Thresholds
Given a user clicks the “Apply Recommendation” button for a menu item, when the action is confirmed, then the item’s low-stock threshold updates to the recommended value and persists across page reloads.
Recommendation Accuracy Validation
Given a test dataset of historical sales and usage, when the engine generates recommendations, then at least 90% of suggested thresholds fall within ±10% of the expected optimal values.
Seasonality and Usage Analysis
Given seasonal sales patterns in the historical data, when recommendations are generated for a peak season, then the suggested thresholds reflect a statistically significant increase compared to off-peak recommendations.
Real-Time Update of Threshold Settings
Given updated sales and usage data, when the dataset is refreshed, then new recommendations are calculated and displayed within 2 seconds in 95% of test runs.
Historical Threshold Analytics
"As a food truck owner, I want to review analytics on past low-stock alerts so that I can identify trends and optimize my inventory management processes."
Description

Provide an analytics dashboard that visualizes low-stock events over time, highlighting patterns in threshold breaches and restocking behaviors. The dashboard will offer charts showing frequency of alerts by item, correlation with busy service periods, and the impact on sales. Users can filter by date range, item category, and notification channel. This data will empower owners to fine-tune inventory practices and make data-driven decisions.

Acceptance Criteria
Low-Stock Frequency Chart Display
Given the user navigates to the Historical Threshold Analytics dashboard When the system retrieves low-stock event data Then a chart displays the frequency of threshold breaches per item over the selected period
Service Period Correlation Analysis
Given the user selects a time range and service period filter When the system applies the filter Then the dashboard shows a correlation chart between alert frequency and defined service periods
Sales Impact Visualization
Given the user views analytics for a chosen date range When the system overlays sales data with low-stock events Then a visual representation shows the impact of threshold breaches on total sales
Date Range Filter Functionality
Given the user adjusts the date range selector When a new range is applied Then all charts and data tables refresh to display information only within that range
Category and Channel Filtering
Given the user chooses an item category or notification channel filter When the filter is confirmed Then the dashboard updates to show analytics only for the selected category and channel

Predictive Resupply

Analyzes historical sales and current inventory trends to forecast future needs for each truck. Generates recommended restock quantities and schedules, helping you order precisely the right amount and avoid both overstocking and stockouts.

Requirements

Historical Sales Data Ingestion
"As a Food Truck Owner, I want to import my past sales and inventory records automatically so that the predictive resupply feature can generate accurate forecasts based on reliable data."
Description

Develop a module to import historical sales and inventory data from POS systems, spreadsheets, and manual entries, normalize it, and store it in a secure database for analysis. It must support scheduled and on-demand synchronization, perform data validation and error handling, and ensure high data quality to fuel accurate forecasting models.

Acceptance Criteria
Scheduled POS System Data Synchronization
Given a scheduled sync time is reached, when the module connects to the POS system, then all new sales and inventory records since the last sync are imported, validated with zero critical errors, and stored in the database within 10 minutes.
On-Demand Spreadsheet Import
Given a user uploads a historical sales spreadsheet, when the import process is initiated, then the system normalizes data formats, validates fields against schema rules, and completes the import within 5 minutes with a summary report of successful and failed records.
Manual Sales Data Entry Validation
Given a user enters sales data manually via the UI, when the user submits the entry, then required fields are checked, format rules are enforced, and any invalid entries trigger inline error messages preventing submission until corrected.
Error Handling for Malformed POS Data
Given malformed or incomplete data in a POS feed, when the ingestion process runs, then invalid records are quarantined, detailed error logs are generated, and a notification is sent to the administrator without interrupting the import of valid records.
Secure Data Storage and Transmission
Given any data ingestion operation (scheduled or on-demand), when data is transmitted and saved, then all data in transit is encrypted using TLS, and data at rest is encrypted with AES-256, with successful encryption verified in audit logs.
Forecast Algorithm Engine
"As a Food Truck Owner, I want the system to predict future inventory requirements so that I can plan restocks proactively and avoid stockouts or overstock situations."
Description

Implement the core predictive algorithms using time-series analysis and machine learning to forecast demand for each menu item based on historical sales, current inventory levels, seasonality, and recent sales trends. The engine should retrain automatically with new data, expose forecast endpoints, and provide adjustable confidence intervals.

Acceptance Criteria
API Endpoint Response Time
Given the Forecast Algorithm Engine API endpoint is deployed and accessible When an authenticated request for a 7-day demand forecast is made Then the endpoint returns valid forecast data including item IDs, predicted quantities, and confidence intervals within 200 milliseconds 95% of the time
Scheduled Model Retraining
Given new sales and inventory data are ingested daily When the automated retraining job runs at the scheduled interval Then the model retrains using the latest 30 days of data without manual intervention and logs success metrics to the monitoring dashboard
Confidence Interval Customization
Given a user specifies a desired confidence level (e.g., 90%, 95%, 99%) in the forecast request When the forecast endpoint processes the request Then it returns prediction intervals that correspond to the requested confidence level and the interval width adjusts accordingly
Seasonal Trend Accuracy
Given historical sales that include seasonal peaks (holidays, weekends) When generating forecasts for a comparable period Then the forecast error (MAPE) for seasonal items is below 15% compared to actual historical demand
Inventory Level Impact
Given current inventory levels for each menu item are below 20% of typical daily sales volume When forecasting demand for those items Then the predicted demand accounts for the low inventory level and reduces forecasted quantities by at least 10% to avoid recommending impossible restock amounts
Restock Recommendation Dashboard
"As a Food Truck Owner, I want to review and adjust recommended restock quantities in a clear dashboard so that I can make informed ordering decisions quickly."
Description

Create a user interface within the mobile dashboard that displays recommended restock quantities for each item, combining forecasted demand, current stock, and suggested reorder dates. Include filters, sorting, and visual urgency indicators, and allow owners to review and adjust recommendations before submitting orders.

Acceptance Criteria
Initial Restock Recommendations Overview
Given the user opens the Restock Recommendation Dashboard; When the system has fetched current inventory and demand forecasts; Then the dashboard displays each item with its current stock, recommended restock quantity, and suggested reorder date.
Filtering Recommendations by Urgency
Given the user selects the 'Urgency' filter set to 'High'; When the filter is applied; Then only items with a visual urgency indicator of 'High' are visible.
Sorting Recommendations by Reorder Date
Given the user clicks the 'Sort by Reorder Date' header; When the sort is applied; Then items are ordered chronologically by suggested reorder date, from soonest to latest.
Adjusting and Submitting Restock Orders
Given the user reviews the recommended quantities; When the user modifies the restock quantity for any item and clicks 'Submit Order'; Then the system validates the adjusted quantities against maximum order limits, confirms the adjustments, and submits the restock order with the updated quantities.
Handling Zero Forecast Items
Given an item has a forecasted demand of zero for the selected period; When the dashboard calculates restock recommendations; Then the recommended restock quantity for that item is zero and the item is marked as 'Not Recommended' for restock.
Notification & Alerts Module
"As a Food Truck Owner, I want to receive alerts when my inventory is forecasted to run low or when new restock recommendations are ready so that I can act promptly to restock."
Description

Build a notification system that alerts users when inventory levels are forecasted to fall below thresholds, when new restock recommendations are available, or when anomalies emerge in forecast confidence. Notifications should be configurable by channel (push, email, SMS) and urgency level to ensure timely response.

Acceptance Criteria
Threshold Breach Alert Triggered
Given a truck's projected inventory falls below the predefined threshold, when the forecast runs, then the system sends an alert via the user's configured channels within one minute, including item name, current stock level, and threshold value.
Restock Recommendation Available
Given sales and inventory data are updated, when a restock recommendation is generated, then the user receives a notification listing recommended items and quantities via their chosen channel within two minutes.
Forecast Anomaly Detected
Given the forecast confidence falls below 80%, when an anomaly is detected, then the system triggers an alert specifying the affected item and confidence level to the user immediately.
Notification Channel Configuration
Given the user accesses notification settings, when they select or deselect channels and urgency levels, then changes are saved and applied to all future alerts without requiring a system restart.
Urgent Alert Escalation
Given an urgent alert is not acknowledged within 15 minutes, when the timer expires, then the system escalates the alert via alternate channels and displays a high-priority notification on the dashboard.
Supplier Integration API
"As a Food Truck Owner, I want orders to be sent directly to my supplier through the system so that I can save time and reduce manual errors in the ordering process."
Description

Develop integration points to connect with common supplier ordering systems (e.g., Sysco, US Foods) via API or EDI to automate sending restock orders. Support SKU mapping, order confirmation, and status tracking to reduce manual effort and streamline the ordering workflow.

Acceptance Criteria
Automated Order Placement with Sysco
Given a validated Shopify SKU mapping to a Sysco SKU, when inventory falls below the reorder threshold, then the system automatically sends a restock order to Sysco’s API with correct item codes, quantities, and delivery details.
SKU Mapping Configuration for US Foods
Given a new menu item added in MenuZap, when the user configures its supplier SKU mapping, then the mapping is saved and can be edited or deleted in the supplier integration settings.
Order Confirmation Receipt Handling
Given a restock order is sent to a supplier’s API, when the supplier returns an order confirmation, then the system records the confirmation ID, updates order status to “Confirmed,” and notifies the user via dashboard and email.
Order Status Tracking and Update
Given an in-flight restock order, when the supplier updates order status (e.g., “Processing,” “Shipped,” “Delivered”) via API or EDI, then MenuZap reflects the new status in real time on the dashboard and sends a status change notification to the user.
Supplier API Error Handling and Retry Mechanism
Given an API call to a supplier fails due to a network or server error, when the system detects the failure, then it retries the request up to three times with exponential backoff and logs all attempts; if still unsuccessful, it alerts the user.

Transfer Hub

Provides an intuitive interface to request, approve, and track inter-truck inventory transfers. Streamlines the movement of ingredients with built-in pick lists and transfer confirmations, cutting down on paperwork and manual tracking.

Requirements

Inter-Truck Transfer Request
"As a food truck operator, I want to request inventory from another truck so that I can quickly replenish low-stock items without manual forms."
Description

Enable operators to create and submit transfer requests by selecting source and destination trucks, choosing ingredients and quantities, and providing an optional note. The system validates availability, reserves stock, and logs the request in the dashboard for visibility. This feature reduces manual paperwork, accelerates restocking, and integrates seamlessly with existing order and inventory modules.

Acceptance Criteria
Successful Transfer Request Creation
Given the operator selects a valid source truck, destination truck, and a list of ingredients with available quantities, when they submit the transfer request, then the system reserves the specified quantities, logs the request with timestamp and operator ID, and displays a confirmation message.
Prevent Transfer When Insufficient Stock
Given the operator selects a quantity that exceeds the available stock in the source truck, when they attempt to submit the transfer request, then the system displays an error message indicating insufficient stock and does not create or log the request.
Optional Note Inclusion
Given the operator enters an optional note along with the transfer request details, when they submit the request, then the system saves the note and displays it in the request details view.
Transfer Request Visibility in Dashboard
Given a transfer request has been successfully submitted, when the operator views the Transfer Hub dashboard, then the new request appears in the request list with correct source, destination, ingredient details, quantities, status as "Pending", and timestamp.
Stock Reservation Rollback on Request Deletion
Given the operator deletes a pending transfer request, when the deletion is confirmed, then the system removes the request from the dashboard and restores the reserved quantities back to the source truck inventory.
Dynamic Pick List Generation
"As a line cook, I want to receive a clear pick list of items to transfer so that I can gather the correct ingredients quickly and accurately."
Description

Automatically generate a detailed pick list for source trucks based on approved transfer requests. The pick list groups items by storage location, displays quantities, and highlights special handling instructions. It integrates with mobile dashboards to guide staff, streamlining the gathering process and reducing errors.

Acceptance Criteria
Pick List Generation for Approved Transfer
Given an approved transfer request exists, When the system generates the pick list, Then items are grouped by storage location, quantities match the request, and special handling instructions are included.
Mobile Dashboard Display of Pick List
Given a generated pick list, When staff access it on a mobile device, Then the pick list displays location headers, item names, quantities, and handling instructions in real time.
Real-time Inventory Update After Pick
Given a pick list is marked as completed on mobile, When staff confirm all items picked, Then the source truck’s inventory decrements accordingly and the pick list status updates to “Completed.”
Insufficient Stock Error Handling
Given a transfer request exceeds available stock, When generating the pick list, Then the system flags insufficient items, highlights them on the list, and notifies the user of the shortfall.
Pick List Re-generation After Transfer Modification
Given a transfer request is modified after initial pick list creation, When the pick list is re-generated, Then the new list reflects updated quantities and locations and replaces the previous list.
Transfer Approval Workflow
"As a fleet manager, I want to review and approve inter-truck transfer requests so that I can control inventory movement and ensure stock availability across trucks."
Description

Provide a structured approval workflow where managers can review incoming transfer requests, see current stock levels, approve or reject requests, and leave feedback. The workflow triggers notifications to both source and destination teams and updates request statuses in real time.

Acceptance Criteria
Manager views pending transfer requests
Given a manager is on the Transfer Approval dashboard When pending transfer requests exist Then the manager sees a list of requests with item details, quantities, and current stock levels for both source and destination trucks
Manager approves a transfer request
Given a manager selects a pending transfer request When the manager clicks ‘Approve’ Then the request status updates to ‘Approved’, and an approval confirmation message is displayed
Manager rejects a transfer request with feedback
Given a manager selects a pending transfer request When the manager clicks ‘Reject’ and enters feedback Then the request status updates to ‘Rejected’, feedback is recorded, and an error notification is shown
Source team receives transfer approval notification
Given a transfer request is approved When the system processes the approval Then a real-time notification is sent to the source team’s dashboard indicating the request has been approved
Destination team receives transfer rejection notification
Given a transfer request is rejected When the system processes the rejection Then a real-time notification with feedback is sent to the destination team’s dashboard
Real-Time Transfer Tracking
"As a food truck operator, I want to track the status of my inventory transfer so that I know when to expect the items and can plan my menu accordingly."
Description

Track each transfer request through stages—pending, approved, picked, in transit, and completed. Display live status updates, timestamps, and responsible user information. Integrate push notifications to alert operators of status changes, ensuring transparency and timely handoffs.

Acceptance Criteria
Viewing transfer request status in real-time
Given a transfer request exists When a user opens the Transfer Hub dashboard Then the request’s status should update automatically in under 2 seconds without a page refresh
Receiving push notifications on status change
Given a transfer request status changes When the status moves from one stage to another Then all subscribed operators receive a push notification within 5 seconds
Updating transfer request stage manually
Given an approved transfer When the responsible operator marks items as picked Then the system should update the status to “picked” and record the operator’s user ID
Displaying responsible user details for each stage
Given a transfer request has progressed through multiple stages When viewing the request’s history Then each stage should display the timestamp and the responsible user’s name and ID
Timestamp verification for transfer events
Given all transfer status changes When any status transition occurs Then the system must record an accurate UTC timestamp and the event must be retrievable in the audit log
Inventory Sync Post-Transfer
"As a food truck operator, I want inventory levels to automatically update after a transfer so that both truck inventories remain accurate and minimize stock discrepancies."
Description

Automatically update inventory levels for both source and destination trucks upon transfer confirmation. Adjust quantities in real time, generate audit logs, and reconcile discrepancies. This ensures accuracy across the fleet and keeps sales and menu availability in sync.

Acceptance Criteria
Inventory Deduction on Transfer Confirmation
Given a user confirms a transfer of 10 units of Ingredient A from Truck X to Truck Y, When the transfer is confirmed, Then Truck X's inventory for Ingredient A is reduced by 10 in real time.
Inventory Addition on Transfer Receipt
Given a transfer of 15 units of Ingredient B is confirmed for Truck Y, When the transfer confirmation is processed, Then Truck Y's inventory for Ingredient B is increased by 15 in real time.
Audit Log Generation
Given any transfer confirmation, When the transfer is finalized, Then an immutable audit log record is generated capturing source truck, destination truck, item, quantity, timestamp, and user ID.
Discrepancy Reconciliation
Given an inventory mismatch detected after a transfer, When the system runs reconciliation, Then a discrepancy report is generated highlighting expected vs actual quantities and sent to the inventory manager.
Real-Time Dashboard Update
Given a transfer is confirmed, When the inventory levels are updated, Then the live mobile dashboard for both source and destination trucks reflects the new inventory levels within 2 seconds.

Fleet Heatmap

Visualizes real‐time inventory levels across all your trucks on a color-coded map or dashboard. Instantly identify which locations are well-stocked or low on key items, enabling quick decision-making and efficient fleet management.

Requirements

Real-Time Inventory Sync
"As an operations manager, I want up-to-the-second inventory updates across all trucks so that I can quickly identify low-stock locations and redistribute supplies proactively."
Description

The system continuously collects and aggregates inventory data from each food truck in real time, updating the fleet heatmap dashboard with the latest stock levels. This ensures decision makers have immediate visibility into which locations are low on key items and supports accurate, up-to-the-second fleet management decisions. The data integration layer handles incoming telemetry, normalizes item categories across trucks, and propagates updates within a maximum latency of 30 seconds.

Acceptance Criteria
Low Stock Threshold Visualization
Given a food truck reports an item’s inventory level below the configured threshold, when the data integration layer receives the update, then the fleet heatmap must reflect the truck location in a warning color within 30 seconds.
High-Frequency Data Burst Handling
Given simultaneous inventory updates from multiple trucks at peak operating times, when the system processes incoming telemetry, then all updates are normalized and displayed on the heatmap without data loss or UI errors, maintaining under 30 seconds end-to-end latency.
Consistent Category Normalization
Given trucks reporting the same item under different category names, when the normalization process runs, then all variants of the item are aggregated under a single category label on the heatmap with correct stock levels.
Initial Dashboard Load
Given a user opens the fleet heatmap dashboard, when no prior data is loaded in the session, then the system must fetch and render the latest inventory levels for all trucks within 30 seconds.
Telemetry Data Latency Monitoring
Given the data integration layer is operational for over 1 hour, when monitoring system metrics, then average end-to-end latency from truck telemetry receipt to dashboard update must remain below 30 seconds and alert if any update exceeds 45 seconds.
Interactive Heatmap Display
"As a fleet coordinator, I want an interactive map showing stock levels in color-coded segments so that I can visually assess inventory distribution across trucks at a glance."
Description

The dashboard presents a color-coded map overlay indicating inventory status at each truck location. Green, yellow, and red gradients represent well-stocked, moderate, and low-stock statuses respectively. Users can hover or tap on a location to view detailed item counts, last update timestamp, and stock change history. The interface is intuitive and leverages performance optimization to ensure smooth map interactions even with hundreds of active trucks.

Acceptance Criteria
Heatmap Rendering Performance
When the dashboard loads with up to 200 truck locations, the heatmap fully renders within 2 seconds on a standard mobile device.
Accurate Color-Coding of Inventory Levels
Given defined thresholds for well-stocked (≥50%), moderate (20–49%), and low (<20%) inventory, each truck marker displays green, yellow, or red correctly based on its current inventory percentage.
Location Detail Display on Interaction
When a user hovers over or taps a truck location, a detail panel appears within 300ms showing current item counts, the timestamp of the last update, and the past 24-hour stock change history.
Real-Time Inventory Update Synchronization
Given an inventory status change for any truck, the heatmap updates the corresponding marker’s color and detail data within 5 seconds across all connected devices.
Scalability with High Number of Active Trucks
When displaying 500 active trucks, map interactions (pan, zoom, hover) maintain a minimum of 30 FPS and no interaction lag exceeds 200ms.
Stock Level Alerts
"As a food truck owner, I want to receive alerts when stock levels fall below my defined thresholds so that I can restock in time and avoid running out of popular items."
Description

Users can set customizable alert thresholds for individual items or overall stock status. The system triggers notifications via email, SMS, or in-app messages when any truck's stock moves into warning or critical levels. Alerts include actionable details such as location, item name, current quantity, and suggested replenishment quantities. This capability minimizes the risk of sell-outs during peak service periods.

Acceptance Criteria
Low Stock Warning Email Trigger
Given a truck’s item stock falls below the user-defined warning threshold, When the system checks inventory levels, Then an email notification is sent within 60 seconds containing truck location, item name, current quantity, and suggested replenishment quantity.
Critical Stock SMS Notification
Given a truck’s item stock falls below the critical threshold, When the threshold breach is detected, Then an SMS notification is sent instantly to the user’s phone number with location, item name, current quantity, and urgent restock recommendation.
In-App Alert for Warning Level
Given a user opens the mobile dashboard and any truck has items at or below warning threshold, When the dashboard loads, Then an in-app alert banner displays the truck location, affected item names, and current quantities.
Suggested Replenishment Calculation
Given a user receives any type of stock alert, When viewing the alert details, Then the system provides a suggested replenishment quantity calculated based on average sales rate and time until next service window.
Aggregate Stock Status Summary
Given a user has multiple trucks selected, When the user requests a summary report, Then the system generates a consolidated alert list showing each truck’s stock status (normal, warning, critical) with item-level details and timestamps.
Filter and Drill-Down Controls
"As a supply chain analyst, I want to filter the heatmap by item type and region so that I can focus on subsections of the fleet and generate targeted restocking plans."
Description

The heatmap supports dynamic filters allowing users to focus on specific menu items, regions, or time ranges. Drill-down controls let users narrow the view from fleet-wide to individual trucks or item categories. Filter states are preserved across sessions and can be saved as custom views. This feature helps users concentrate on high-priority analysis tasks without extraneous data clutter.

Acceptance Criteria
Filter by Menu Item Across Fleet
Given a fleet heatmap view; When the user selects a specific menu item filter; Then only trucks offering that item display on the map with accurate color coding reflecting current inventory levels.
Region-Specific Heatmap Filtering
Given the fleet heatmap; When the user applies a region filter (e.g., East Coast); Then the map updates to show only trucks in the selected region with real-time inventory status.
Time Range Filter Application
Given historical and real-time data; When the user sets a time range filter (e.g., last 2 hours); Then the heatmap reflects inventory changes and statuses only within that period.
Drill-Down to Individual Truck
Given a filtered heatmap view; When the user clicks a truck icon; Then detailed inventory levels and menu item categories for that truck appear in a side panel.
Save and Load Custom Views
Given a user-defined filter combination; When the user saves the view with a custom name; Then the view is available in a ‘Saved Views’ list and can be reloaded with the same filter and drill-down settings across sessions.
Mobile-Optimized View
"As a field supervisor, I want to view the fleet heatmap on my smartphone so that I can monitor inventory levels while attending onsite operations."
Description

The heatmap dashboard is fully responsive, offering optimized layouts for mobile and tablet devices. On smaller screens, the interface collapses secondary details into slide-out panels, and map interactions use touch-friendly gestures. Performance is tuned to guarantee sub-second load times and fluid panning/zooming on mobile. This ensures field managers can access critical fleet insights on the go.

Acceptance Criteria
Mobile Dashboard Load Time Under 1 Second
Given a mobile device on a 4G or better network, when the user opens the heatmap dashboard in mobile view, then the full interface must render and be interactive within 1 second.
Touch Gesture Zoom and Pan Responsiveness
Given a touchscreen mobile device, when the user performs pinch-to-zoom or swipe-to-pan on the heatmap, then the map must respond within 100ms of the gesture and maintain at least 30 FPS during the interaction.
Collapsible Slide-out Panels on Small Screens
Given a device with a viewport width under 600px, when the user taps the details icon, then the secondary details panel must slide out covering no more than 60% of the viewport and collapse back when dismissed.
Responsive Layout on Tablet Devices
Given a tablet device with a screen width between 600px and 1024px, when the user rotates between portrait and landscape, then all UI elements must reflow without overlap or cutoff and all map controls remain visible and accessible.
Fluid Panning and Zooming on High Inventory Data
Given the heatmap displaying 100+ real-time inventory points, when the user zooms or pans on a mobile device, then interactions must complete within 100ms and maintain a minimum of 30 FPS.

SurgeWave Alerts

Delivers real-time push notifications to your team when an upcoming customer surge is predicted, ensuring staff are briefed and stations prepped to handle rushes effortlessly.

Requirements

Surge Prediction Engine Integration
"As a food truck operator, I want the system to predict customer surges so that I can prepare my team and inventory accordingly."
Description

Integrate a predictive analytics engine that processes historical sales, real-time order data, weather, and location information to forecast upcoming customer surges with time estimates and confidence levels. This module should seamlessly feed predictions into SurgeWave Alerts in real time, enabling proactive staff scheduling and inventory prep.

Acceptance Criteria
Real-time Prediction Generation
Given historical sales, real-time order, weather, and location data are available, when the data pipeline runs every 5 minutes, then the engine must generate a surge forecast with a timestamp and confidence level within 2 minutes of ingestion.
SurgeWave Alert Dispatch
Given a forecast is generated, when the confidence level ≥ 80%, then the system must push a SurgeWave alert to all registered devices within 10 seconds.
Historical Trend Validation
Given stored historical data for the past 7 days, when comparing predicted surges to actual sales peaks, then the engine must achieve at least 85% prediction accuracy for time windows within ±15 minutes.
Data Source Failure Handling
Given one or more data sources (weather or real-time orders) fail to respond within 30 seconds, when running the prediction, then the system must log the failure, continue using available data, and notify the admin dashboard of degraded prediction.
Dashboard Integration Verification
Given Surge Prediction Engine output, when viewing the SurgeWave dashboard, then the forecasted surge time, expected order volume, and confidence level must display correctly and update in real time as new predictions arrive.
Customizable Alert Thresholds
"As a manager, I want to configure the surge thresholds so that alerts are relevant to my business patterns."
Description

Enable users to define and adjust surge trigger parameters—such as a minimum percentage increase in order volume within a rolling time window, confidence score threshold, and notification lead time. These settings should be accessible via the dashboard and stored per location, ensuring alerts align with each truck's unique operational profile.

Acceptance Criteria
Setting Minimum Order Surge Percentage
Given the user is on the Customizable Alert Thresholds page When they enter a minimum percentage increase between 10% and 500% and save Then the system persists the value and displays a confirmation message; And the input field retains the entered value after page reload
Adjusting Confidence Score Threshold
Given the user sets a confidence score threshold between 0.0 and 1.0 and saves When the system validates the input Then it stores the value per location and shows it in the dashboard
Configuring Notification Lead Time
Given the user selects a lead time of 5 to 60 minutes before predicted surge and saves When the configuration is accepted Then the dashboard displays the updated lead time and triggers alerts accordingly
Saving Threshold Settings by Location
Given the user manages multiple truck locations When they save different threshold values for each location Then each location’s settings are isolated, stored, and retrievable on page refresh
Verifying Alert Triggering Behavior
Given the system receives real-time order volume data When the volume increase exceeds the configured percentage and meets the confidence score threshold within the rolling window Then a push notification is sent to the team the configured lead time before the surge
Multi-Channel Notification Delivery
"As a team member, I want to receive surge alerts on my preferred channel so that I never miss important notifications."
Description

Deliver predicted surge alerts across multiple channels—including in-app push notifications, SMS, and email—to designated staff roles. Implement channel fallback logic to guarantee delivery if the primary channel fails, ensuring the entire team receives timely alerts regardless of connectivity or device preferences.

Acceptance Criteria
In-App Push Notification Delivery
Given a predicted surge alert is generated and the designated staff member has the mobile app installed and push enabled; When the system triggers the alert; Then the staff member receives the notification via the in-app push channel within 5 seconds and can view the alert details in the dashboard.
SMS Primary Channel with Email Fallback
Given a predicted surge alert is triggered for a designated staff role with SMS as the primary channel and email as fallback; When the SMS delivery attempt fails (e.g., network error or invalid number); Then the system automatically sends the alert via email within 2 seconds and logs the SMS failure reason.
Email Primary Channel with SMS Fallback
Given a predicted surge alert is configured to deliver email as the primary channel and SMS as fallback; When the email is sent but bounces or is delayed beyond 10 seconds; Then the system detects the bounce/delay and sends the alert via SMS within 5 seconds.
Low Connectivity Channel Fallback Sequence
Given a staff member’s device has low connectivity preventing in-app and SMS delivery; When a surge alert is triggered; Then the system tries in-app push for 5 seconds, then SMS for 5 seconds, and finally sends an email, ensuring at least one channel is successful within 15 seconds.
Role-Based Notification Receipt Acknowledgment
Given a surge alert is delivered to multiple staff roles across channels; When each staff member receives the alert; Then the system logs an acknowledgment timestamp per staff member and updates the dashboard with "Delivered" status for each role within 30 seconds.
Acknowledgement and Escalation Workflow
"As a shift supervisor, I want to ensure surge alerts are acknowledged so that we can take timely action."
Description

Introduce an acknowledgement feature allowing staff to confirm receipt of surge alerts. If an alert remains unacknowledged within a configurable timeframe, automatically escalate notifications to the next on-duty staff member or supervisor. Track acknowledgements and escalations in the system log to ensure accountability and timely response.

Acceptance Criteria
Acknowledgement Confirmation by Staff
Given a surge alert is received by a staff member and they tap the 'Acknowledge' button within the configured timeframe, when they confirm acknowledgement, then the system records the acknowledgement timestamp, updates the alert status to 'Acknowledged', and prevents further escalations for this alert.
Alert Escalation after Timeout
Given a surge alert is unacknowledged by the initial staff member and the configured acknowledgement timeframe elapses, when the timeframe expires, then the system automatically sends the alert notification to the next on-duty staff member or supervisor, updates the escalation count, and logs the escalation event.
Supervisor Acknowledgement of Escalated Alert
Given an alert has been escalated to a supervisor, when the supervisor taps the 'Acknowledge' button in their notification, then the system records the supervisor's acknowledgement and marks the alert status as 'AcknowledgedEscalated', preventing further escalations.
System Logging of Acknowledgements and Escalations
Given any alert acknowledgement or escalation event occurs, when the event is processed, then the system logs the event details (user ID, timestamp, alert ID, action type) in the system log, and an audit report can retrieve these entries.
Configurable Acknowledgement Timeframe Enforcement
Given the acknowledgement timeframe setting is updated by an administrator, when a new surge alert is generated, then the system uses the updated timeframe to determine expiry and escalation timing for that alert.
Surge History and Analytics Dashboard
"As a food truck owner, I want to review past surge performance so that I can refine my staffing and inventory strategies."
Description

Develop a comprehensive analytics dashboard that logs all predicted surges alongside actual order volumes, comparing forecast accuracy and tracking staff response times. Provide visualizations and exportable reports to help owners analyze surge patterns, refine prediction models, and adjust staffing and inventory strategies for future shifts.

Acceptance Criteria
Recording Surge Predictions and Actual Order Volumes
Given a predicted surge is generated When actual order volumes are logged Then the system records both in the surge history with accurate timestamps and no data loss
Comparing Forecast Accuracy
Given historical surge data exists When the user views the surge accuracy report Then the dashboard displays comparison metrics including mean absolute percentage error and trend analysis
Visualizing Surge Pattern Trends
Given multiple surge events over a selected time range When the user accesses the trends view Then the dashboard renders interactive line charts comparing predicted vs actual volumes with zoom and filter controls
Exporting Surge Analytics Reports
Given a user-selected date range When the user requests an export Then the system generates and downloads a CSV and PDF report containing prediction accuracy, total surge counts, and response time statistics
Tracking Staff Response Time
Given a surge alert and logged staff response events When the dashboard processes response timestamps Then it calculates and displays average, median, and maximum staff response times per surge event
Performance Under High Data Load
Given a surge history dataset exceeding 1000 events When the user navigates to any analytics view Then dashboard rendering and data queries complete within 3 seconds with no errors

EventPulse Sync

Integrates local event calendars and geo-targeted data to automatically factor nearby concerts, festivals, and sports games into your rush forecasts, keeping your predictions accurate and timely.

Requirements

Calendar API Integration
"As a food truck owner, I want to connect MenuZap to local event calendars so that the system can automatically pull in upcoming event details and improve my rush predictions."
Description

Implement secure connections to local event calendar APIs (e.g., city council, Ticketmaster, Eventbrite) using OAuth or API keys. Map and normalize event data fields (date, time, location, event type, expected attendance) into MenuZap’s data model. Ensure data is ingested in a scalable, fault-tolerant pipeline with logging and error-handling. This integration enables MenuZap to automatically retrieve up-to-date event information, forming the foundation for accurate rush forecasts tied to real-world happenings.

Acceptance Criteria
OAuth Authentication with Local Event Calendar
Given valid OAuth credentials, when the system attempts to connect to a city council calendar API, then the connection succeeds with a 200 response and a valid access token is stored.
API Key Authentication with Ticketmaster
Given a valid API key, when requesting events from the Ticketmaster API, then a secure HTTPS request is made and the system receives a 200 response with event data.
Event Data Mapping and Normalization
Given raw event data from external APIs, when ingested, then the system correctly maps date, time, location, event type, and expected attendance into MenuZap’s data model with valid formats.
Scalable, Fault-Tolerant Pipeline Under Network Failure
Given a temporary network failure during data ingestion, when the system retries, then the pipeline automatically retries up to 3 times and queues the request without data loss.
Comprehensive Logging and Error Handling
Given any API error or data inconsistency, when an error occurs, then the system logs the error details with timestamps and error codes, and alerts the monitoring service.
Geo-Targeted Event Extraction
"As a food truck owner, I want MenuZap to consider only events within my service radius so that my forecasts reflect local demand drivers and ignore irrelevant events."
Description

Build functionality to filter incoming event data by geolocation, comparing event coordinates against the user-defined operating radius. Support configuration of custom radii per truck or route. Exclude events beyond the boundary and tag nearby events with distance metrics. This ensures only relevant events influence the demand forecast and eliminates noise from distant activities.

Acceptance Criteria
Filtering events within operating radius
Given a set of incoming event data with geocoordinates both inside and outside the defined radius, when the system processes the events, then only those events whose distance from the truck location is less than or equal to the operating radius are included in the output.
Custom radius configuration per truck
Given a truck owner updates their custom operating radius to X kilometers in the settings, when filtering new events, then the system applies the updated radius X for including or excluding events.
Tagging nearby events with distance metrics
Given an event passes the radius filter, when the system generates its output record, then it includes a “distance_km” field calculated using the Haversine formula accurate to two decimal places.
Excluding distant events from forecast
Given event data beyond the operating radius, when generating the demand forecast input, then no events outside the radius appear in the forecast dataset and summary reports.
Real-time update of event data
Given new or updated event data from the external calendar API, when data is ingested every five minutes, then the system re-evaluates all events against the current radius and updates the filtered event list accordingly without manual intervention.
Dynamic Demand Forecast Algorithm
"As a food truck owner, I want MenuZap to adjust my sales forecasts dynamically based on nearby events so that I can stock ingredients and staff appropriately for expected traffic spikes."
Description

Extend the existing demand forecasting engine to incorporate event attributes—attendance estimates, event type, time window—using weighted factors derived from historical performance. Combine baseline sales trends with event-induced surges to produce an adjusted forecast. Provide configurable sensitivity settings to fine-tune event impact. This algorithmic enhancement delivers more accurate, real-time predictions during high-impact local events.

Acceptance Criteria
Event Surge Forecast Adjustment
Given a scheduled event with attendance data When the algorithm runs Then the forecasted demand increases by a weighted factor within ±5% of historical surge values
Configurable Sensitivity Testing
Given sensitivity settings adjusted by ±20% When the forecast recalculates Then the event impact on demand shifts proportionally within the same percentage range
Real-time Calendar Sync Impact
Given a new local event added to the calendar When the data sync completes in under 60 seconds Then the updated forecast reflects the event impact immediately
Historical Weighting Validation
Given historical event performance data When weighted factors are applied Then the combined forecast aligns within ±10% of actual past demand during similar events
Peak Event Window Prediction
Given an event time window defined in hours When forecasting demand Then the peak demand time in the forecast matches the window start ±15 minutes
Event Sync Scheduler
"As an administrator, I want MenuZap to automatically refresh event data on a set schedule so that my forecasts always reflect the latest available event information."
Description

Create a scheduling service to periodically poll integrated event APIs at configurable intervals (e.g., hourly, daily). Implement retry logic with exponential backoff for transient failures and alerting for persistent errors. Ensure sync jobs run efficiently without degrading dashboard performance. This scheduler keeps event data fresh and maintains forecast accuracy without manual intervention.

Acceptance Criteria
Hourly Event Data Polling
Given the Event Sync Scheduler is set to an hourly interval, when the scheduler executes, then all configured event APIs are polled and any new or updated events are persisted to the local event store without errors.
Configurable Polling Interval Adjustment
When the administrator updates the polling interval setting (e.g., from hourly to daily), then the scheduler adjusts its next execution time to the new interval and executes accordingly.
Retry Logic with Exponential Backoff
Given a transient API error occurs during polling, when the scheduler's retry mechanism is invoked, then it should retry the request up to three times with exponential backoff delays and succeed without manual intervention.
Persistent Error Alerting Mechanism
When a polling job fails after reaching the maximum retry attempts, then an error is logged in the system and an alert notification is sent to the configured alert channel within five minutes.
Performance Impact Assessment
When multiple sync jobs run concurrently, then dashboard response times must remain under 200ms on average and CPU utilization must not exceed 70%.
Event Dashboard Visualization
"As a food truck owner, I want to see upcoming local events and their projected impact on my sales dashboard so that I can make informed operational decisions."
Description

Design and implement a dashboard component displaying upcoming events on an interactive map and list view. Show key details—event name, time, distance, expected attendance—and highlight their forecast impact on sales. Allow users to drill into individual events for deeper insights. This visualization empowers owners to understand and trust how events alter demand predictions.

Acceptance Criteria
Viewing Upcoming Events on Map
Given upcoming events are available, the map displays a marker for each event at its correct geolocation; when a marker is clicked, it shows the event name, time, and distance in a tooltip.
Switching Between Map and List View
Given the Event Dashboard is open, the user can toggle between map view and list view without page reload; when switched, the selected view renders all upcoming events with consistent data.
Filtering Events by Distance and Time
Given the user applies a distance or time filter, the dashboard updates in real time to show only events within the specified radius and timeframe.
Drilling into Event Details
Given the user selects an event from the list or map, a detail panel opens displaying event name, time, distance, expected attendance, and forecast impact calculation.
Highlighting Forecast Impact
Given events are displayed, each event entry visually indicates its forecast impact (e.g., color-coded or icon) and the magnitude of impact is accurate based on attendance data.

PrepPerfect Scheduler

Automatically adjusts and suggests shift schedules based on predicted peak times, ensuring you have the right number of staff on deck when customer demand spikes.

Requirements

Peak Demand Analysis
"As a food truck owner, I want the system to analyze past sales and external factors so that I can anticipate busy periods and prepare staffing accordingly."
Description

Develop a robust data collection and analysis engine that continuously ingests historical sales data, real‐time order volumes, and external factors such as weather and local events to accurately predict upcoming peak demand periods for each food truck location. This engine should normalize diverse data sources, apply statistical and machine learning models to forecast hourly demand spikes, and expose an API to make predictions accessible to the scheduling module. The solution must ensure data accuracy, handle missing or noisy inputs, and update predictions at configurable intervals without impacting dashboard performance.

Acceptance Criteria
Initial Data Ingestion Validation
Given the data engine is connected to historical sales, real-time orders, weather, and events feeds, When data is ingested at the configured interval, Then all records from each source must be successfully stored, normalized, and timestamped without errors.
Forecast Accuracy Verification
Given 30 days of historical data and recent external factor inputs, When the demand forecast runs for the upcoming day, Then the prediction error (MAPE) must be less than or equal to 10%.
Real-time Prediction Refresh
Given new order volume or weather updates mid-shift, When the scheduled refresh interval is reached, Then the demand forecast must update within 2 minutes without impacting dashboard response times.
API Response Performance Under Load
Given concurrent requests from the PrepPerfect Scheduler module, When 100 requests per second are sent to the prediction API, Then the 95th percentile response time must remain under 200ms and error rate under 1%.
Data Quality Handling
Given occasional missing or noisy data points in any external feed, When such anomalies are detected during ingestion, Then the engine must flag them, apply the predefined cleaning rules, and log a warning without failing the entire ingestion process.
Dynamic Schedule Generator
"As a manager, I want the system to auto-generate shift schedules based on predicted demand so that I can ensure adequate coverage without manual spreadsheet work."
Description

Implement a dynamic scheduling module that uses demand forecasts to automatically suggest optimal shift assignments. This component should factor in staff roles, skill levels, availability, labor regulations, and desired coverage ratios to generate shift proposals. It must support editing and manual overrides, recalculate suggestions on data changes, and integrate seamlessly into the existing MenuZap dashboard. The module should deliver intuitive UI elements for reviewing and approving schedules, as well as exporting finalized rosters in common formats.

Acceptance Criteria
Peak-Time Staffing Optimization
Given the demand forecast indicates a peak between 12:00–14:00, When the dynamic schedule generator runs, Then the suggested schedule includes at least 3 servers and 2 cooks to meet the coverage ratio of 1 staff per 10 expected orders.
Manual Override and Recalculation
Given a manager manually adjusts a staff assignment, When availability or forecast data changes, Then the module recalculates and updates only unapproved shifts without overwriting approved overrides.
Compliance with Labor Regulations
Given an employee’s weekly hours are approaching the legal limit, When the schedule is generated, Then no shift is assigned that would exceed 40 hours per week or violate minimum rest period of 12 hours between shifts.
Skill-Based Role Assignment
Given a predicted lunch rush requiring a bilingual cashier, When the schedule generator assigns roles, Then at least one bilingual cashier slot is filled by a staff member with the bilingual skill tag.
Schedule Export Functionality
Given the finalized roster is approved, When the manager selects export, Then the system generates and downloads the schedule in both CSV and PDF formats with correct formatting and staff details.
Staff Availability Integration
"As a team member, I want to share my availability with the scheduler so that I only receive shift assignments that fit my personal schedule."
Description

Create an integration layer that allows staff members to input and update their availability preferences directly through the MenuZap mobile dashboard or a connected portal. The system should validate availability against requested shifts, notify managers of conflicts, and ensure that auto-generated schedules respect these constraints. Data should sync in real time, support recurring availability patterns, and maintain an audit log of changes for compliance and planning reviews.

Acceptance Criteria
Staff Updates Availability in Mobile Dashboard
Given a staff member accesses the availability input form when not currently on shift, When they submit valid start and end times without overlap, Then the system updates their availability preferences within 2 seconds and displays a confirmation message.
Manager Resolves Availability Conflict
Given the system detects a scheduling conflict based on staff availability and assigned shifts, When a manager opens the notifications panel, Then they see clear conflict details and can reassign or override availability within 1 minute.
Recurring Availability Patterns Setup
Given a staff member defines a recurring weekly availability pattern, When they save the pattern, Then the system generates and displays availability entries for the next four weeks matching the rule.
Real-time Data Synchronization
Given a staff member updates availability on any connected portal, When the change is saved, Then the updated availability reflects across all managers’ dashboards and the scheduling engine within 5 seconds.
Audit Logging of Availability Changes
Given any creation, update, or deletion of availability by a staff member or manager, When the action is performed, Then an audit log entry is recorded capturing user ID, timestamp, old values, new values, and action type.
Schedule Adjustment Notifications
"As a staff member, I want to receive alerts when my shift changes so that I can plan my day accordingly."
Description

Develop a notification engine that alerts staff and managers when schedules are created, updated, or require adjustments due to forecast changes. Notifications should be dispatched via email, SMS, and in-app push messages, containing clear summary details and links to view or confirm shifts. The system must track delivery status, allow users to acknowledge or reject proposed shifts, and trigger re-scheduling workflows if key personnel declines assignments.

Acceptance Criteria
Notification Dispatch to Staff
Given a new or updated shift schedule requiring staff notification When the notification engine is triggered Then email must be sent within 2 minutes, SMS within 1 minute, and in-app push delivered immediately, each containing a clear shift summary and a link to view or confirm the shift
Notification Delivery Status Tracking
Given notifications have been dispatched When querying the notification dashboard or API Then each notification shows a status of sent, delivered, failed, or acknowledged, updated in the system within 5 minutes of dispatch
User Acknowledgement Workflow
Given a staff member receives a schedule notification When the user clicks the confirm or reject link Then the system records the user’s response, updates their shift status accordingly, and displays a confirmation message within the notification channel
Shift Change Rejection Handling
Given a key staff member rejects a proposed shift When the rejection is recorded Then the system automatically triggers the re-scheduling workflow, notifies the manager within 1 minute, and suggests available replacements based on staff availability
In-app Push Notification Display
Given a user is actively using the MenuZap app When a schedule change notification is sent Then an in-app push notification appears with the shift summary, timestamp, and a deep link to the schedule details screen
Peak Time Forecast Visualization
"As a manager, I want to see visual demand forecasts so that I can quickly understand when I need more staff."
Description

Design and embed a forecast visualization dashboard that displays predicted demand curves, historical performance overlays, and recommended staffing levels over time. Visual elements should include interactive graphs, heatmaps, and threshold indicators to highlight upcoming peaks. The visualization must update dynamically with new data, allow time-range selection, and integrate into the main MenuZap interface without adding clutter, providing managers with at-a-glance insights for scheduling decisions.

Acceptance Criteria
Predicted Demand 24-Hour Overview
Given the manager opens the forecast dashboard, When the system loads, Then an interactive graph displays predicted demand for the next 24 hours with demand curves and historical overlays.
Time-Range Selection Filter
Given the forecast dashboard is displayed, When the manager selects a custom time range, Then the visualization updates to reflect predicted and historical data only within the chosen time window.
Real-Time Data Refresh
Given new sales and inventory data arrive, When the refresh interval completes or manager triggers a manual update, Then the forecast visualization dynamically updates without full page reload.
Peak Threshold Indicator Alert
Given the predicted demand curve exceeds predefined peak thresholds, When the forecast displays the threshold breach, Then a visual indicator highlights the upcoming peak periods on the graph.
Interactive Heatmap Highlighting
Given the manager hovers over any point on the heatmap, When the hover occurs, Then a tooltip displays the exact predicted demand, historical comparison, and recommended staffing level for that time slot.

StockSurge Recommender

Provides actionable ingredient preparation and inventory recommendations ahead of busy periods, helping you pre-portion ingredients and optimize stock levels to prevent shortages.

Requirements

Real-Time Demand Forecasting
"As a food truck owner, I want to see real-time forecasts of ingredient demand so that I can pre-portion supplies and avoid running out during busy periods."
Description

Utilize historical sales data combined with real-time order and inventory information to predict ingredient demand ahead of peak service periods. The forecasting engine continuously analyzes trends and external factors (e.g., day of week, weather) to provide accurate demand projections, helping operators prepare the right quantities of ingredients, minimize waste, and prevent stockouts.

Acceptance Criteria
Early Morning Prep Suggestion
Given the current date is the start of the business day and historical sales data for the same weekday over the past 4 weeks is available, When the system processes real-time orders up to 6 AM, Then it generates ingredient preparation quantities with ±10% variance thresholds and displays a suggestion for pre-portioning ingredients.
Pre-Lunch Peak Demand Forecast
Given it's 11:00 AM and historical lunch period sales data for similar days exists, When real-time order velocity and local weather data are analyzed, Then the forecast engine predicts ingredient demand for the next 90 minutes within a 95% confidence interval and alerts the operator if projected demand exceeds current stock.
Weekend Outdoor Event Planning
Given an outdoor event scheduled for Saturday and expected foot traffic is high based on historical event attendance, When the system analyzes past weather, day-of-week, and event-specific sales data, Then it produces a recommended ingredient order list that covers at least 120% of average sales for similar events.
Adverse Weather Impact Assessment
Given an incoming weather alert predicts heavy rain during peak hours and historical data shows a 30% drop in sales under similar conditions, When the system integrates weather forecast data, Then it adjusts demand forecasts downward by at least 25% and notifies the operator.
Low Stock Warning for High-Margin Items
Given real-time inventory levels drop below the forecasted threshold for high-margin ingredients and daily sales velocity is above average, When forecasting indicates a potential stockout within 2 hours, Then the system triggers a low stock warning alert and suggests reorder quantities.
Personalized Prep Recommendations
"As a food truck owner, I want personalized ingredient prep recommendations so that I can efficiently prepare just the right amount of stock before rushes."
Description

Generate actionable, itemized ingredient preparation instructions based on forecasted demand, past consumption patterns, and current inventory levels. The system proposes optimal portion sizes and quantities for each ingredient, allowing operators to quickly prepare stock trays, adhere to freshness standards, and reduce over-preparation.

Acceptance Criteria
High-Demand Lunch Rush Forecast Scenario
1. System generates itemized ingredient prep recommendations at least 2 hours before the scheduled lunch rush;2. Recommendations list each ingredient’s portion size and total quantity based on forecasted demand, past consumption patterns, and current inventory;3. System excludes any ingredient with insufficient stock and adjusts quantities to prevent negative inventory;4. Recommendations update automatically if forecast parameters change within the 2-hour window.
Low Inventory Alert Scenario
1. When any ingredient’s inventory falls below the predefined threshold, system flags the ingredient in the recommendation list;2. Recommended prep quantities for flagged ingredients are reduced or omitted, and an alert is sent to the operator;3. System logs the inventory alert and provides a suggestion for reorder quantity based on forecasted requirements.
Weekend Event Overestimate Prevention Scenario
1. System incorporates special weekend event modifiers into demand forecast to adjust prep volumes;2. Recommendations ensure total prep volume does not exceed 110% of expected demand to prevent over-preparation;3. Each item’s recommended portion size aligns with freshness standards, and system highlights any deviations.
Unexpected Demand Surge Mid-Shift Scenario
1. If actual sales velocity exceeds forecast by more than 20% within a 30-minute window, system recalculates prep recommendations in real time;2. Updated recommendations are delivered within 5 minutes of detecting the surge;3. System ensures adjusted recommendations respect remaining inventory levels and prevent stockouts of critical ingredients.
Daily Prep Summary Verification Scenario
1. At the end of the prep planning cycle, system generates a consolidated summary of all ingredient recommendations;2. Summary includes item names, total quantities, portion sizes, and timestamp of generation;3. Operator can download the summary as a PDF or CSV;4. System records user confirmation with date/time stamp to close the prep planning task.
Customizable Surge Thresholds
"As a food truck owner, I want to set custom thresholds for surge alerts so that I receive recommendations only when inventory levels truly warrant action."
Description

Allow users to configure threshold settings for when surge recommendations activate, such as minimum order volume or projected shortage risk percentage. These adjustable thresholds ensure that alerts and recommendations align with individual operational preferences and risk tolerances.

Acceptance Criteria
Surge Threshold Access by Admin
Given an admin user is on the StockSurge Settings page, the Surge Thresholds section displays fields for Minimum Order Volume and Shortage Risk Percentage
Setting Minimum Order Volume Threshold
When the user enters a valid integer between 1 and 500 in the Minimum Order Volume field and clicks Save, the system displays a success message and updates the threshold value accordingly
Configuring Risk Percentage Threshold
When the user enters a percentage between 0 and 100 in the Shortage Risk Percentage field and clicks Save, the system confirms the update and applies the new risk threshold
Saving Custom Threshold Profiles
Given the user has configured both thresholds and provides a unique profile name, when they click Save Profile, the system stores the profile and lists it under Saved Threshold Profiles
Validating Threshold Alerts Activation
When projected order volume or shortage risk for the upcoming period exceeds the configured thresholds, the system triggers an in-app alert and notification email to the user
Automated Notification Alerts
"As a food truck owner, I want automated alerts when predicted demand outstrips my current inventory so that I can restock or prepare additional ingredients before I run dry."
Description

Implement push notifications and in-app alerts to inform users when forecasted demand exceeds defined thresholds or when inventory levels drop below safe levels. Alerts should include summary insights and direct links to the prep recommendation details, ensuring timely action without navigating through multiple screens.

Acceptance Criteria
Demand Forecast Exceeds Threshold Notification
Given a user-defined demand threshold for an item, when forecasted demand for that item exceeds the threshold for the next shift, then a push notification and in-app alert must be delivered within 5 seconds containing the item name, forecasted demand, threshold value, and a link to the prep recommendations.
Inventory Level Falls Below Safe Threshold Alert
Given safe inventory thresholds set per ingredient, when actual inventory count falls below the threshold, then a push notification and in-app alert must be delivered within 5 seconds specifying the ingredient name, current inventory level, safe threshold, and a link to replenishment suggestions.
Combined Demand and Inventory Alert Notification
When both forecasted demand exceeds the defined threshold and inventory falls below the safe level for the same item, then a single consolidated alert must be delivered within 5 seconds summarizing both conditions with respective values and a link to the combined prep recommendations.
Alert Contains Summary Insights and Link to Recommendation Details
For any triggered notification, the alert must include a summary of key metrics (e.g., forecasted demand and current inventory vs. thresholds) and a ‘View Prep Recommendations’ link that navigates directly to the StockSurge prep recommendation details page for the affected item.
Notifications Retry on Delivery Failure
If a notification fails to deliver due to a network or server error, the system must retry delivery up to 3 times at 30-second intervals; if still unsuccessful, it must log the failure in notification history and display a red badge on the in-app alerts menu indicating undelivered alerts.
Historical Trends Dashboard
"As a food truck owner, I want to view historical sales trends and past surge events so that I can learn from previous data and trust the accuracy of future recommendations."
Description

Create a visual dashboard that displays historical sales trends, peak service periods, and past surge events. The dashboard helps users understand patterns over time and validate forecasting accuracy, enabling more informed decision-making and refining future surge recommendations.

Acceptance Criteria
Viewing Overall Sales Trend
Given the user opens the Historical Trends Dashboard, when the past 30 days view is selected, then a line chart displays daily total sales with correctly labeled axes and tooltips showing exact sales values matching the database.
Identifying Peak Service Period
Given the user accesses the service period analysis section, when they hover over each time slot, then the dashboard highlights the hour with the highest average order volume and displays the corresponding date, time, and order count.
Analyzing Surge Event Accuracy
Given the user reviews past surge events, when they select a specific event, then a comparison table shows forecasted vs. actual sales with an accuracy percentage calculated within ±5% of the backend’s computed value.
Filtering Trends by Time Range
Given the user selects a custom date range filter, when they apply the filter, then all displayed charts and tables update to include only data within the selected dates and exclude any outside records.
Exporting Trend Data
Given the user clicks the export button, when they choose CSV or PDF format, then the system generates and downloads a file containing all currently visible trend data in the chosen format within 5 seconds.

WaitWatch Dashboard

Visualizes expected wait times and queue lengths in a live dashboard, allowing managers and frontline staff to monitor service speed and make real-time adjustments to staffing and workflows.

Requirements

Real-time Wait Time Calculation
"As a food truck manager, I want to see live wait time estimates for each menu item so that I can adjust workflows to reduce customer wait and optimize service speed."
Description

Continuously compute and update estimated wait times for each menu item based on real-time order data and preparation times. This feature leverages live order queue metrics and historical preparation durations to provide accurate, up-to-the-second wait time estimates displayed on the WaitWatch Dashboard. It ensures staff and managers have current insights into service speed, enabling informed decisions to improve throughput and customer satisfaction.

Acceptance Criteria
Dashboard Initialization Wait Time Calculation
Given the dashboard loads initial data for existing orders, when displayed, then wait times for each menu item appear within ±15 seconds of the actual estimated preparation duration.
Real-time Update on New Order Placement
Given a new order is placed, when the order enters the queue, then wait time estimates for all affected menu items update within 5 seconds reflecting the new queue length.
Wait Time Adjustment on Order Completion
Given an order is completed, when preparation time is recorded, then the system recalculates and updates wait times for remaining orders within 5 seconds.
Cancellation Impact on Wait Time
Given an order is cancelled, when cancellation is confirmed, then wait time estimates for all pending orders adjust within 5 seconds to reflect the reduced queue.
Historical Data Influence on Estimates
Given historical preparation times are available, when computing wait times, then the system uses the moving average of the last 20 preparation durations per menu item to calculate estimates.
Queue Length Visualization
"As a frontline staff member, I want to view current queue lengths in real-time so that I can prioritize tasks and manage customer expectations effectively."
Description

Display the number of pending orders and active queues for each service channel (walk-up, mobile, pickup) in a clear, color-coded format on the WaitWatch Dashboard. This visualization updates in real-time, highlighting queue buildups and helping staff quickly identify pressure points. Integrating directly with order management systems, it improves situational awareness and aids in workload balancing across service channels.

Acceptance Criteria
Walking Up: Peak Hour Queue Monitoring
Given the dashboard is open, When 5 or more walk-up orders remain pending for over 2 minutes, Then the walk-up queue indicator turns red within 5 seconds.
Mobile Order Queue Real-Time Update
Given a new mobile order is placed, When the order enters the pending state, Then the mobile queue count on the dashboard increases by 1 in under 2 seconds and displays correctly.
Pickup Channel Load Balancing Alert
Given the pickup queue exceeds 10 orders, When this threshold is reached, Then the pickup queue indicator flashes yellow and displays the count in bold.
Cross-Channel Pressure Point Identification
Given multiple service channels are displayed, When the difference between the highest and lowest queue lengths exceeds 50%, Then the busiest channel’s bar is highlighted in orange.
Dashboard Refresh Consistency Under High Load
Given 100 simultaneous order updates across channels, When the dashboard refreshes, Then all queue length indicators update without dropped or duplicated counts within 3 seconds.
Historical Trend Analysis
"As a food truck owner, I want to analyze past wait time trends so that I can schedule staff appropriately and anticipate busy shifts."
Description

Provide charts and heatmaps showing historical wait time and queue length trends over selectable time ranges (e.g., hourly, daily, weekly). Users can identify peak periods and recurring bottlenecks, informing staffing and menu planning decisions. By integrating past performance data, this feature helps managers forecast demand patterns and proactively prepare for high-traffic intervals.

Acceptance Criteria
Selecting Time Range for Trend Analysis
Given a manager is viewing the Historical Trend Analysis panel, When they select a time range filter (hourly, daily, weekly), Then the charts and heatmaps update to reflect data within the selected time range without page reload.
Displaying Historical Wait Times Chart
Given past wait time data exists for the selected time range, When the user opens the historical wait times chart, Then the chart plots wait times per interval with correct axes labels and tooltips showing exact values.
Rendering Queue Length Heatmap
Given queue length records are stored, When the user switches to heatmap view, Then the heatmap displays days on one axis and time intervals on the other, coloring each cell by average queue length with a legend.
Peak Period Detection Highlight
Given historical data covers multiple days, When the analysis runs, Then the UI highlights the top three peak periods by wait time and queue length distinctly in both chart and heatmap views.
Data Refresh and Performance
Given the user is interacting with the dashboard, When any filter or view is changed, Then the data refresh completes within two seconds and displays a loading indicator if processing takes longer than 500ms.
Alert Notifications
"As a shift supervisor, I want to receive alerts when wait times exceed acceptable limits so that I can deploy additional resources and prevent service delays."
Description

Implement configurable alert rules that notify staff when wait times or queue lengths exceed predefined thresholds. Alerts can be delivered via on-screen pop-ups, push notifications, or SMS, enabling rapid response to service slowdowns. This feature integrates with user-defined rules to ensure timely interventions, reducing customer frustration and maintaining consistent service levels.

Acceptance Criteria
Exceeding Wait Time Threshold
Given an alert rule is configured for wait times over 5 minutes, when the live wait time surpasses 5 minutes, then an on-screen pop-up alert appears within 3 seconds and the alert event is recorded in the system log.
Exceeding Queue Length Threshold
Given an alert rule is set for queue lengths exceeding 10 orders, when the dashboard queue length exceeds 10 orders, then a push notification is triggered and delivered to the manager’s device within 5 seconds.
Delivery of Push Notifications
Given push notifications are enabled for a staff member, when any alert rule is triggered, then a push notification containing the alert type, threshold value, current metric, and timestamp is sent to the registered device and the delivery receipt is logged.
Delivery of SMS Alerts
Given SMS notifications are enabled and a valid phone number is configured for a staff member, when an alert rule is triggered, then an SMS message with the alert details is sent within 60 seconds and delivery confirmation is recorded.
Custom Alert Rule Configuration
Given the user is on the alert configuration screen, when a new alert rule is created with valid metric, threshold, notification channel, and recipient, then the rule is saved, appears in the list with correct settings, and persists after a page refresh.
Customizable Threshold Settings
"As a food truck manager, I want to set custom thresholds for queue alerts so that the dashboard aligns with my truck’s service capabilities."
Description

Allow managers to define and adjust threshold values for wait times and queue lengths directly within the WaitWatch Dashboard settings. Thresholds are saved per location and service type, enabling tailored alerting and visualization. This customization ensures the dashboard reflects each food truck’s unique capacity and service standards, supporting continuous improvement.

Acceptance Criteria
Setting wait time threshold for location
Given a manager opens the Threshold Settings for 'Central Food Truck' location When the manager sets the wait time threshold to 8 minutes and clicks Save Then the dashboard displays the new threshold value and returns a success confirmation
Adjusting queue length threshold per service type
Given a manager selects the 'Curbside Pickup' service type in Threshold Settings When the manager enters a queue length threshold of 12 and saves the change Then only the Curbside Pickup queue is updated to 12 and a success message appears
Verifying persistence of saved thresholds
Given a manager has configured custom thresholds for all service types and locations When the manager logs out and logs back into the system Then the previously set thresholds are loaded exactly as configured in the Threshold Settings
Triggering alert when threshold exceeded
Given the wait time threshold is set to 5 minutes When the live dashboard measures an average wait time of 6 minutes Then a visual alert (red highlight and icon) appears next to the wait time indicator
Resetting thresholds to default values
Given a manager views custom thresholds in the settings page When the manager clicks the 'Reset to Default' button and confirms Then all thresholds revert to the system default values and a confirmation message is displayed

OffPeak Optimizer

Identifies upcoming lulls after peak rushes and suggests targeted promotions or menu adjustments to drive traffic during slower periods, maximizing sales throughout the day.

Requirements

Real-time Lull Detection
"As a food truck owner, I want the system to automatically detect upcoming slow periods at least 15 minutes in advance so that I can deploy promotional tactics before sales decline."
Description

Continuously analyze incoming order volume and historical sales patterns to detect upcoming off-peak periods in real time. The system should process transactional data streams, apply time-series analysis, and trigger lull predictions at least 15 minutes before the expected slowdown. This ensures truck owners have actionable lead time to implement targeted strategies and maintain consistent foot traffic throughout the day.

Acceptance Criteria
Real-Time Transaction Stream Monitoring
Given live order data streams, when an order is placed, then the system ingests and stores the transaction within 1 second for analysis.
Detecting Post-Lunch Slowdown
Given a 15-minute rolling average of orders between 12:00 and 14:00, when the order rate decreases by 25% or more for three consecutive minutes and matches historical lull patterns, then the system predicts an off-peak period at least 15 minutes before its onset.
15-Minute Lead Time Prediction
Given detected trends signaling a slowdown, when the system generates a lull prediction, then it must issue an alert to the dashboard with a timestamp at least 15 minutes prior to the predicted lull start time.
Historical Sales Pattern Analysis
Given historical sales data segmented by day and time, when analyzing current order volume, then the system compares against the same time periods over the past 30 days and calculates a confidence score of at least 80% for lull predictions.
Anomalous Spike Filtering
Given sudden order spikes due to promotions or events, when current volume deviates more than 50% from the 15-minute average but does not align with historical spikes, then the system classifies the data as anomalous and excludes it from lull detection calculations.
Promotion Recommendation Engine
"As a food truck owner, I want the system to recommend the most effective promotions when a lull is predicted so that I can attract more customers and boost sales during slow periods."
Description

Generate targeted promotional suggestions based on predicted lulls, current inventory levels, historical item popularity, and margin goals. The engine should produce a ranked list of up to three promotions, including discount percentages or bundle ideas, and justify each suggestion with expected uplift metrics. Integrate seamlessly into the dashboard for one-click deployment.

Acceptance Criteria
Off-Peak Period Promotion Generation
Given an upcoming off-peak period is forecasted within the next 2 hours, When the Promotion Recommendation Engine runs, Then it generates a list of up to three promotional suggestions aligned with the lull timing.
Inventory and Margin Compliance Check
Each suggested promotion is validated against current inventory to ensure all items are in stock and meets or exceeds the configured minimum profit margin; any suggestion containing out-of-stock items or margin below goal is excluded.
Promotion Uplift Justification Accuracy
Each suggestion includes an expected uplift metric based on historical sales and traffic data, and the uplift calculation is accurate within a ±5% error margin.
Promotion Ranking and Prioritization
Suggestions are ordered by projected uplift in descending order; if two suggestions have equal uplift, the suggestion with the higher profit margin appears first.
Dashboard One-Click Deployment Integration
From the dashboard, the user can deploy any suggested promotion with a single click, which updates the live menu and applies the discount or bundle in real time without errors or page reload.
Inventory-Aware Promotion Filter
"As a food truck owner, I want promotion suggestions to automatically exclude items with low inventory so that I can avoid disappointing customers and minimize manual checks."
Description

Ensure all suggested promotions only include menu items with sufficient stock to fulfill anticipated demand. The filter should cross-reference real-time inventory counts, forecasted sales uplift, and minimum stock thresholds, removing any items at risk of running out during a promotion. This prevents stockouts and preserves customer satisfaction.

Acceptance Criteria
Selecting Promotions Based on Real-Time Inventory
Given the optimizer has access to real-time inventory data and forecasted uplift figures, when suggesting promotions for the next off-peak period, then only items with inventory counts >= (forecasted uplift + minimum stock threshold) are included.
Excluding Items Near Stock Depletion
Given an item’s current inventory level is at or below its defined minimum stock threshold, when building the promotion list, then that item must not appear in any suggested promotions.
Validating Forecasted Demand Against Inventory
Given forecasted uplift values for each menu item, when comparing these forecasts with current stock levels, then any item where forecasted uplift > available stock is removed from the promotion suggestions.
Enforcing Minimum Stock Thresholds
Given minimum stock threshold settings are configured per item, when generating off-peak promotions, then the system verifies that each suggested item’s stock >= configured threshold before inclusion.
Dynamic Re-filtering Upon Inventory Changes
Given a live stock adjustment event (sale or manual update) that reduces an item’s available quantity below the promotion requirement, when this event occurs, then the system immediately removes the affected item from any pending promotion suggestions.
Dynamic Menu Highlighting
"As a food truck owner, I want promotional items to be clearly highlighted on my live menu during slow periods so that customers immediately see and are encouraged to choose these offers."
Description

Automatically update the dashboard’s live menu interface to spotlight active promotions during predicted off-peak windows. Promotional items should display visual badges (e.g., “OffPeak Special”) and dynamic pricing indicators. Ensure UI consistency across web and mobile views for maximum customer visibility.

Acceptance Criteria
Automatic Promotion Highlighting Activation
Given the system predicts an off-peak period, when the off-peak window starts, then the dashboard automatically displays the “OffPeak Special” badge and updated price on relevant menu items.
Web View Promotion Badge Display
When viewing the live menu on the web interface during off-peak windows, promotional items must display the “OffPeak Special” badge and dynamic pricing indicator in accordance with the promotion settings.
Mobile View Promotion Badge Display
When viewing the live menu on a mobile device during off-peak windows, promotional items must display the “OffPeak Special” badge and dynamic pricing indicator without layout issues or truncation.
Promotion Window Timing Accuracy
The promotional badges and dynamic pricing should appear exactly at the predicted off-peak start time and revert to standard menu display immediately after the off-peak end time with no more than a 10-second delay.
Cross-Platform UI Consistency
The style (badge color, font, size) and placement of promotional badges and dynamic pricing indicators must be consistent across both web and mobile interfaces, matching the design specifications in the style guide.
Scheduled Campaign Manager
"As a food truck owner, I want to schedule promotional campaigns ahead of time so that I don’t need to manually activate them during busy service hours."
Description

Allow owners to schedule off-peak promotional campaigns in advance based on predicted lull times. The scheduler should let users define start and end times, select promotion templates, and set automatic activation and deactivation. Include notification reminders and conflict checks against other campaigns.

Acceptance Criteria
Create and Schedule a New Promotional Campaign
Given the user is on the campaign scheduler page and has entered a valid future start time and end time and selected a promotion template, when the user clicks Save, then the new campaign appears in the upcoming campaigns list with the correct times and template details and a confirmation message is displayed.
Prevent Overlapping Campaign Times
Given an existing campaign is scheduled from 12:00 to 14:00, when the user attempts to schedule a new campaign that overlaps any portion of that time, then the system displays an error message indicating the conflict and prevents saving the new campaign.
Receive Notifications Before Campaign Activation
Given a campaign is scheduled to start at 15:00 and the user has notifications enabled, when the current time is 30 minutes before the campaign start time, then the system sends a reminder notification to the user including campaign name and start time.
Automatic Campaign Activation and Deactivation
Given the current time matches a campaign’s scheduled start time, when the system clock reaches that time, then the campaign status changes to Active and a notification is sent; and when the system clock reaches the scheduled end time, then the campaign status changes to Inactive and promotions are removed from the live menu.
Select and Apply Promotion Templates
Given the user opens the promotion template selector, when the user views the list of available templates, then each template displays a preview and a description; and when the user selects a template, then the campaign form populates with the template’s discount values and settings.
Promotion Performance Analytics
"As a food truck owner, I want to view detailed analytics on how off-peak promotions performed so that I can understand their impact and refine future strategies."
Description

Provide post-campaign analytics detailing key performance indicators such as additional units sold, revenue uplift, conversion rate changes, and ROI for each off-peak promotion. Include visual dashboards with trend lines, comparative charts to baseline periods, and exportable reports for strategic review.

Acceptance Criteria
Campaign Summary Dashboard View
Given a completed off-peak promotion, when the user navigates to the Campaign Summary dashboard, then the dashboard displays total units sold, revenue uplift, conversion rate changes, and ROI correctly for the selected promotion period.
Trend Analysis Visualization
Given daily sales data before, during, and after the promotion, when the user views the trend line chart, then the chart accurately reflects changes in units sold and revenue against the baseline with correct axis labels and time intervals.
Baseline Comparison Report Export
Given baseline and promotional period data, when the user exports the comparative report, then a PDF and CSV file is generated containing side-by-side tables and comparative charts of key metrics, and the file is downloadable without errors.
ROI Calculation Accuracy
Given the total promotion cost and revenue figures, when the system calculates ROI, then ROI is computed as (Revenue Uplift – Promotion Cost) / Promotion Cost × 100% and matches manual calculations within a 0.1% tolerance.
Data Export Functionality
Given the full set of campaign analytics data, when the user selects export options, then the system provides buttons for PDF and CSV exports and clicking each initiates a download within 5 seconds with correct data formatting.

ProfileGuard

Creates personalized allergen profiles for customers, storing their specific sensitivities once and automatically filtering menus in real time to show only safe options. Empowers diners with confidence and speeds up the ordering process by eliminating manual checks.

Requirements

Personal Allergen Profile Setup
"As a customer, I want to set up my allergen profile so that only safe menu items are shown to me, preventing accidental exposure."
Description

Enable customers to create and customize personal allergen profiles by selecting or specifying their individual sensitivities. The system should allow users to add, remove, and update allergens in their profile, store profiles securely, and ensure data privacy. Integration with user accounts should be seamless, enabling first-time setup and later edits. The feature should validate inputs, provide guidance on common allergens, and confirm successful profile creation.

Acceptance Criteria
First-Time Allergen Profile Creation
Given a logged-in user on the profile setup page, when the user selects one or more allergens from the provided list and clicks “Save,” then the system stores the selected allergens in the user’s profile and displays a success notification.
Editing Existing Allergen Profile
Given a user with an existing allergen profile, when the user modifies selections by adding or removing allergens and clicks “Save,” then the system updates the stored profile accordingly and shows a confirmation message.
Removing an Allergen from Profile
Given a user viewing their allergen profile, when the user deselects an allergen and submits the changes, then the deselected allergen is removed from the profile and no longer appears in future menu filters.
Validating Allergen Input Format
Given a user enters a custom allergen in the text field, when the input contains invalid characters or exceeds 50 characters, then the system displays an inline validation error and prevents saving until corrected.
Secure Storage of Allergen Profiles
When a profile is created or updated, then all allergen data is encrypted at rest, stored within the user’s secure account scope, and inaccessible to other users or services without proper authorization.
Allergen Data Integration
"As an administrator, I want to update allergen definitions so that menu filtering remains accurate and current."
Description

Integrate a comprehensive, updatable allergen database that maps all menu ingredients to known allergens. The system must support importing standardized allergen definitions, allow administrative updates, and maintain version history. Integration should include data validation to prevent inconsistencies and ensure reliable filtering. This backend requirement underpins all ProfileGuard functionality.

Acceptance Criteria
Standardized Allergen Import
Given an administrator uploads a valid standardized allergen definitions file When the system processes the file Then all allergens are added or updated in the database without duplicates and a confirmation message is returned within two minutes
Administrative Allergen Update
Given an administrator edits existing allergen definitions When the edit is submitted Then the system saves the changes, logs the editor’s user ID and timestamp, and displays the updated definition in the admin interface
Ingredient-Allergen Mapping Validation
Given a menu item’s ingredient list When the system maps ingredients to allergens Then every ingredient must be associated with zero or more known allergens and any unmapped ingredient triggers a validation warning
Version History Tracking
Given any change to an allergen definition or mapping When the change is saved Then the system creates a new version record with details of the changes, user ID, and timestamp and allows rollback to any previous version
Data Consistency and Validation
Given the current allergen database When periodic validation runs occur Then the system detects and reports any missing fields, inconsistent entries, or schema violations and flags them in an admin dashboard
Real-Time Menu Filtering
"As a customer, I want the menu to automatically show only safe items when I'm logged in so that I don't risk ordering allergens."
Description

Implement dynamic menu filtering that instantly updates displayed items based on the active allergen profile. When a customer is logged in or selects a profile, the menu should refresh to hide or flag unsafe items without page reloads. Performance must remain optimal even on low-bandwidth connections. The UI should indicate filtered items clearly and allow users to view hidden items with warnings if they choose.

Acceptance Criteria
Customer Logs In With Saved Allergen Profile
Given a customer with a saved peanut allergen profile When the customer logs in Then all menu items containing peanuts are hidden or flagged in the menu view without a full page reload
Customer Changes Allergen Profile Mid-Session
Given a logged-in customer viewing the menu When the customer updates their allergen profile from tree nuts to gluten Then the menu dynamically hides or flags all gluten-containing items within two seconds without reloading the page
Customer Views Hidden Items With Warnings
Given certain items have been hidden due to allergen filtering When the customer clicks “Show All Items” Then previously hidden items reappear with a clear allergen warning icon and tooltip
Menu Filtering on Low-Bandwidth Connection
Given the application is used on a connection slower than 2G When an allergen profile is applied or changed Then the menu updates to hide or flag unsafe items within three seconds while preserving UI responsiveness
New Allergen Profile Creation Applies Filter Immediately
Given a customer creates a new allergen profile for shellfish When the profile is saved Then the menu instantly hides or flags all shellfish-containing items without requiring a manual refresh
Cross-Device Profile Sync
"As a customer, I want my allergen profile saved across devices so that I see consistent filtering whether I use my phone or laptop."
Description

Ensure allergen profiles and menu filtering states are synchronized across all customer devices—mobile, tablet, and desktop. Profile updates must propagate in real time, and the system should use secure session management to maintain consistency. Offline changes made on one device should queue and sync when connectivity is restored, preserving data integrity.

Acceptance Criteria
Real-Time Profile Sync Across Devices
Given a user updates their allergen profile on Device A, when Device B is online and the user is logged in, then Device B automatically reflects the updated allergen profile within 5 seconds.
Offline Changes Queued and Synced
Given a user updates their allergen profile while Device C is offline, when connectivity is restored, then the queued updates are correctly applied to the central server without data loss and propagate to all other devices.
Secure Session Management for Profile Access
Given a user is authenticated, when the session token expires, then the system prompts re-authentication before allowing access to allergen profiles on any device.
Menu Filtering Consistency Across Devices
Given an allergen profile exists, when the user views the menu on any device, then only items not containing allergens are displayed consistently across mobile, tablet, and desktop.
Conflict Resolution for Simultaneous Updates
Given simultaneous updates to the allergen profile occur on Device A and Device B, when the last write timestamp is compared, then the system retains the most recent change and notifies the user of the applied update.
Allergen Alert Notifications
"As restaurant staff, I want to be notified of customer allergens when a new item may conflict so that I can prevent dangerous orders."
Description

Provide proactive notifications to both diners and food truck staff when menu items are added or modified that conflict with existing allergen profiles. Alerts should appear in the dashboard for staff and as in-app messages or email notifications for customers. Notification templates must be customizable and clearly indicate the allergen risk and affected menu items.

Acceptance Criteria
Staff Dashboard Allergen Conflict Alert
Given a staff member is viewing the live dashboard When a menu item is added or modified that conflicts with an existing customer allergen profile Then an alert appears immediately in the dashboard’s notification panel indicating the allergen risk and the affected menu item
Customer In-App Allergen Notification
Given a customer has an allergen profile saved When a new or modified menu item conflicts with their allergen Then the customer receives an in-app message clearly stating the allergen risk and listing the affected item
Email Allergen Notification to Customer
Given a customer has opted in for email notifications and has an allergen profile When a menu item is added or updated that conflicts with their allergen Then an email is sent within two minutes, using the customizable template, highlighting the allergen risk and the item name
Notification Template Customization
Given an administrator accesses notification settings When they update the allergen notification template fields (e.g., header, body text, risk labels) Then the changes are saved and subsequent alerts (dashboard, in-app, email) reflect the updated template
Real-Time Menu Update Propagation
Given any change is made to the menu items related to allergens When the change is saved Then the system triggers allergen checks and sends conflict alerts to staff dashboards and customer channels in under five seconds

ContamiScan

Monitors ingredient prep workflows and flags potential cross-contamination risks by analyzing order sequences and station usage. Alerts staff to cleanse or change utensils before handling allergen-sensitive items, ensuring food safety and reducing incident risk.

Requirements

Real-time Sequence Analyzer
"As a food truck chef, I want the system to monitor order sequences in real time so that I can be alerted to potential allergen cross-contact before it happens."
Description

Continuously analyzes incoming orders and prep station usage to identify sequences that may lead to allergen cross-contamination. The system leverages order metadata and station assignment logs to detect when an allergen-sensitive item is prepared immediately after a different allergen without an intervening sanitization step. It integrates seamlessly with the mobile dashboard, updating analysis results in real time and supporting instant visibility into potential risks.

Acceptance Criteria
Immediate Allergen Sequence Without Sanitization
Given an order for a peanut-containing item followed immediately by a tree nut-containing item is assigned to the same prep station with no sanitization logged, when the Real-time Sequence Analyzer processes the sequence, then a cross-contamination alert must be generated and displayed on the mobile dashboard within 2 seconds.
Sequential Preparation of Different Allergens at Single Station
Given multiple orders containing different allergens are queued for a single prep station, when the system detects consecutive preparation without an intervening sanitization record, then it must mark the station as ‘Requires Sanitization’ and notify staff via push notification.
Confirmation of Sanitization Step in Order Workflow
Given a sanitization step (e.g., utensil change or station cleaning) is logged between allergen-sensitive orders, when the sequence analyzer reviews the station logs, then it should clear any pending cross-contamination alerts for that station.
Real-Time Alert Visibility on Mobile Dashboard
Given a cross-contamination risk is detected, when an alert is triggered, then the mobile dashboard must display a red warning icon next to the station name and provide details of the conflicting items within the interface in under 2 seconds.
High-Volume Order Processing Under Peak Load
Given 100+ orders per minute during peak hours, when the real-time sequence analyzer receives station usage and order metadata, then it must process sequences and generate any necessary alerts with no more than 5% delay above the standard 2-second threshold.
Station Usage Tracker
"As a kitchen manager, I want to view a station’s recent usage history so that I can verify whether it’s safe to use for allergen-sensitive preparations."
Description

Logs and visualizes the usage history of each prep station, including timestamps, order IDs, and ingredients handled. The tracker maintains a rolling window of recent activities per station, enabling the contamination engine to reference precise usage data. It stores this data efficiently and allows for quick lookups, ensuring accurate correlation between station usage and flagged contamination risks.

Acceptance Criteria
Retrieving Recent Station Activities
Given a valid station ID and time range, when a user requests recent station usage, then the system returns all activity records with timestamps, order IDs, and ingredients handled within that time range.
Rolling Window Maintenance
Given the retention window of 24 hours, when an activity record exceeds this window, then the system automatically purges it and it is no longer retrievable.
Efficient Data Retrieval Under Load
When handling at least 100 concurrent lookup requests, then the system returns station usage data within 200ms for each request with error rate below 1%.
Integration with Contamination Engine
Given a contamination engine request for the last ten activities of a station, when the request is sent, then the system responds within 100ms with the correct ten most recent activity records.
Data Storage Efficiency
When storing daily activity logs for up to 50 stations, then total storage used does not exceed 500MB and average write latency remains under 50ms.
Cross-Contamination Alert System
"As a server, I want to receive clear alerts about contamination risks so that I can take corrective action before serving the customer."
Description

Generates and delivers immediate alerts when the analyzer detects a high risk of cross-contamination. Notifications appear prominently on the mobile dashboard and can be configured to trigger audible or vibration cues on staff handheld devices. Each alert includes details on the risk type, affected order items, and recommended next steps, such as utensil change or station cleaning.

Acceptance Criteria
Immediate Alert on Allergen Sequence Violation
Given the analyzer identifies that a nut-containing item was prepared immediately before a nut-free order When no utensil or station reset has been logged Then the system must display a red visual alert on the mobile dashboard within 2 seconds
Audible and Vibration Notification Triggered
Given the staff handheld device has audible and vibration notifications enabled When a high cross-contamination risk is detected Then the device must trigger an audible alarm at a minimum of 80 dB or a vibration alert within 2 seconds
Detailed Alert Information Display
Given an alert is generated When the alert appears on the dashboard Then it must display the risk type, list of affected order items, and a recommended next steps section
Configurable Alert Preferences
Given a user accesses the notification settings in the dashboard When they configure channels and threshold parameters Then the system must persist changes and apply the new settings to all subsequent alerts
Real-Time Station Cleaning Confirmation
Given a station is cleaned and the staff logs the cleaning action in the dashboard When the cleaning is marked complete Then the system must suppress further alerts for that station until a new potential cross-contamination sequence is detected
Utensil Sanitation Prompt
"As a food prep staff member, I want precise sanitation instructions after a contamination alert so that I can quickly remedy the risk and continue cooking safely."
Description

Provides contextual prompts to replace or sanitize utensils based on detected risk events. After an alert, the system displays specific instructions (e.g., rinse knife, swap cutting board) and offers one-tap confirmation once the task is completed. Prompts are intelligently tailored to the type of allergen and the utensils involved in the flagged sequence.

Acceptance Criteria
Utensil Replacement Prompt for Nut Allergen
Given a pending order containing nut-based ingredients When the order is selected for preparation Then the system displays a prompt instructing the user to replace or sanitize the designated utensil before proceeding And the user can confirm completion with one tap
Cross-Station Utensil Sanitation Alert
Given a utensil was last used at a seafood station and is needed for a shellfish-free menu item When the system detects potential cross-contamination risk Then a sanitation prompt appears detailing the required cleaning action And the prompt must remain until the user confirms completion
Confirmation Logging and Time Stamp Verification
Given the user taps the one-tap confirmation After completing the sanitation task When the confirmation is registered Then the system logs the user ID, time stamp, utensil type, and allergen context in the audit trail
Prompt Blocks Next Order Processing
Given an active contamination risk has been flagged When the sanitation prompt is displayed Then the system prevents the next order from entering the preparation queue Until the user confirms the sanitation task is complete
Contextual Instruction for Cutting Board Swap
Given a change from a dairy-based item to a gluten-free product When a cutting board swap is required Then the system displays tailored instructions including board color or material And provides visuals to guide the user in selecting the correct board
Contamination History Report
"As the food truck owner, I want a summary of contamination events so that I can review safety performance and implement improvements."
Description

Aggregates all flagged contamination events into a daily and weekly report, highlighting risk patterns, frequent station issues, and staff responsiveness metrics. Reports are accessible via the dashboard and can be exported as CSV or PDF for compliance audits. This feature helps identify training needs and optimize workflows to reduce future risk incidents.

Acceptance Criteria
Daily Report Generation
Given at least one contamination event logged in the past 24 hours When the user requests the daily contamination history report Then the system generates a report listing all events from the last day with timestamps and event details
Weekly Trend Analysis
Given contamination events logged over the past seven days When the user requests the weekly contamination history report Then the system aggregates events by day and station, highlights trends, and calculates total incidents per station
CSV Export Capability
When the user selects the CSV export option for any report Then the system downloads a CSV file containing all report fields formatted correctly with headers, comma separators, and no data truncation
PDF Export Formatting
When the user selects the PDF export option for any report Then the system generates a PDF file that matches the dashboard layout, includes charts and tables, and prompts the user to download
Dashboard Accessibility
Given a valid MenuZap user When the user navigates to the Contamination History Report section Then the report options and data are visible and accessible on desktop, tablet, and mobile browsers without layout issues

IngredientLens

Breaks down every menu item into its full ingredient list, highlighting hidden allergens and preparation notes. Allows users to drill into composite dishes and understand exactly which components pose a risk, promoting transparency and trust.

Requirements

Ingredient Data Sync
"As a food truck owner, I want a single source of truth for all ingredient details so that I can confidently display accurate information to customers and maintain compliance with allergen regulations."
Description

Establish a centralized ingredient database that aggregates detailed information on ingredients, including names, allergens, preparation notes, and nutritional data. Implement automated synchronization with external data sources and supplier feeds to ensure information remains up-to-date and accurate across the system.

Acceptance Criteria
Daily Automated Sync Verification
Given the system’s scheduled synchronization runs daily at 2 AM; When the sync job completes; Then the central ingredient database reflects all updates from external data sources within 5 minutes of job completion and no synchronization errors are logged.
New Supplier Data Ingestion
Given a newly onboarded supplier feed file is received; When the ingestion process runs; Then all new ingredients and their metadata are added to the central database with correct field mappings and any duplicates are flagged for review.
Allergen Data Update Propagation
Given an external source updates allergen information for existing ingredients; When the next synchronization occurs; Then the allergen fields in the central database match the updated source data and a change log entry is generated.
Data Conflict Detection and Resolution
Given conflicting data entries from multiple external sources; When the synchronization process detects a conflict; Then the system applies predefined data source priority rules to resolve the conflict automatically and logs unresolved entries for manual review.
Manual Re-Sync on Data Correction
Given a user submits a corrected ingredient entry through the admin interface; When the user triggers a manual resynchronization; Then the central database is updated immediately with the corrected data and the changes are visible in the IngredientLens feature.
UI Ingredient Breakdown
"As a customer viewing the menu, I want to see each dish’s detailed ingredient list so that I can make informed choices based on my dietary restrictions."
Description

Design and implement a user interface component that dynamically displays a full breakdown of every menu item into its constituent ingredients. Ensure the breakdown is clearly formatted, accessible on both mobile and desktop dashboards, and updates in real time with menu changes.

Acceptance Criteria
View ingredient details on mobile device
Given a user is on the mobile dashboard When they tap the “Ingredient Breakdown” icon for a menu item Then a pane displays all base and composite ingredients with allergen highlights and preparation notes
View ingredient details on desktop dashboard
Given a user is on the desktop dashboard When they hover or click the “Ingredient Breakdown” section of a menu item Then a detail panel lists every ingredient clearly formatted and scrollable
Real-time synchronization after menu change
Given a menu item’s composition is updated in the CMS When the change is saved Then the ingredient breakdown UI reflects the new data within 2 seconds without a page reload
Highlight allergens and preparation notes
Given an ingredient has an allergen or special preparation note When the breakdown is displayed Then these attributes are visually distinguished by color and tooltip descriptions
Expandable composite dishes breakdown
Given a composite dish in the ingredient list When the user expands a parent ingredient Then the UI reveals its sub-ingredients indented with proper formatting
Allergen Highlighting
"As a customer with allergies, I want allergens clearly highlighted in ingredient lists so that I can quickly identify and avoid dishes that contain ingredients harmful to me."
Description

Add functionality to detect and visually emphasize known allergens within the ingredient lists. Use standardized labels (e.g., icons, color coding) to flag potential risks and include customization options for users to set personal allergen profiles and receive tailored alerts.

Acceptance Criteria
Custom Allergen Profile Setup
Given the user opens the Allergen Settings page When they add or remove allergens to their personal profile and save Then the selected allergens are persisted and displayed in their profile list
Default Allergen Icon and Color Legend Display
Given the user views an ingredient list for any menu item When the list loads Then each known allergen is preceded by the correct standardized icon and color code and a legend explains each symbol
IngredientLens Allergen Highlight Rendering
Given a composite dish with hidden allergens When the user drills into its ingredient breakdown Then all allergenic components are visually highlighted according to the user’s profile and default legend
Real-time Allergen Availability Update
Given an ingredient is marked sold out in inventory When the user views the menu item’s ingredient list Then any allergens tied to that ingredient are flagged as unavailable and visually greyed out
Tailored Allergen Alert Notifications
Given the user has added allergens to their profile When they select a menu item that contains any of these allergens Then they receive a visible in-app alert specifying which allergens are present before confirming an order
Composite Dish Navigation
"As a health-conscious customer, I want to explore the sub-components of complex dishes so that I can fully understand what I’m eating and identify any hidden ingredients."
Description

Enable interactive drill-down for composite menu items that contain sub-recipes or bundled components. Provide expandable sections or nested views so users can explore every layer of a dish’s composition and understand each element’s origin and preparation note.

Acceptance Criteria
Expanding Composite Dish Layers
Given a menu item with nested sub-recipes, when the user clicks the expand icon next to the main dish, then all first-level sub-recipe names and ingredient counts are displayed; and when the user clicks expand on a sub-recipe, then its underlying ingredients are displayed in a nested view.
Viewing Ingredient Details
Given an expanded list of ingredients, when the user taps on an ingredient name, then a detail panel appears showing the ingredient’s origin, allergen information, and preparation notes without losing the current drill-down context.
Collapsing Expanded Sections
Given one or more expanded composite sections, when the user clicks the collapse icon on any section, then that section and all its nested sub-items collapse and are removed from view without affecting other expanded sections.
Displaying Sold-Out Sub-Components
Given a composite dish where one or more sub-components are sold out, when the user drills down to view ingredients, then sold-out components are flagged with a red ‘Sold Out’ badge and disabled in the list.
Mobile Navigation Usability
Given a mobile device viewport, when the user drills down into composite dishes, then the nested lists and expansion controls remain fully accessible, and horizontal scrolling is not required to view any part of the hierarchy.
Ingredient Management Admin Panel
"As a system administrator, I want to manage ingredient information directly so that I can ensure the database remains accurate and comprehensive."
Description

Create an administrative interface for managing ingredient records, allowing users to add new ingredients, update allergen information, attach preparation notes, and organize ingredients into categories. Implement validation rules and audit logs to maintain data integrity.

Acceptance Criteria
Adding a New Ingredient
Given the admin is on the Ingredient Management Admin Panel When the admin fills all required fields with valid data and clicks 'Save' Then a new ingredient record is created, displayed in the ingredient list with correct name, category, allergen flags, and preparation notes
Updating Allergen Information
Given an existing ingredient with outdated allergen flags When the admin selects the ingredient, updates the allergen information, and clicks 'Update' Then the ingredient’s allergen flags reflect the new values and the update timestamp is recorded
Attaching Preparation Notes to Ingredient
Given an ingredient without notes When the admin clicks 'Add Notes', enters preparation instructions, and confirms Then the notes are saved, visible on the ingredient detail view, and editable
Organizing Ingredients into Categories
Given multiple ingredients across categories When the admin selects ingredients, chooses a category from the dropdown, and applies the change Then each ingredient is assigned to the selected category and displayed under that category filter
Logging Ingredient Data Changes
Given any creation, update, or deletion of an ingredient When the action is performed Then an audit log entry is created containing the timestamp, user ID, action type, and before-and-after data

SafeSwap

Suggests real-time substitutions or alternative menu items based on current inventory and the customer’s allergen profile. Helps staff quickly recommend safe options, minimize waste, and maintain service speed even during busy shifts.

Requirements

Real-Time Inventory Sync
"As a food truck operator, I want the inventory to update instantly on all devices so that I never sell items that are out of stock and can manage my service efficiently during busy times."
Description

Enable continuous synchronization of inventory data across all devices and systems, updating in real time whenever an item is sold, returned, or restocked. This requirement ensures that the menu availability reflects current stock levels within seconds, preventing order errors and reducing customer disappointment. Integration with point-of-sale transactions and the central inventory database is essential, with automated triggers recalculating availability and notifying connected dashboards immediately. The expected outcome is near-zero latency in inventory updates, resulting in accurate menu displays and smoother operations during peak service periods.

Acceptance Criteria
Inventory Update on Sale
Given a completed sale transaction, when the transaction is recorded, then the inventory count for the sold item is decremented by the exact quantity sold and propagated to all connected dashboards within 2 seconds.
Inventory Update on Return
Given a return transaction is processed, when the item return is confirmed in the system, then the inventory count increases by the returned quantity and the updated count appears on all devices within 2 seconds.
Concurrent Multi-Device Sync
Given multiple orders are placed simultaneously on different devices, when each order is completed, then inventory updates occur in the correct sequence without conflicts and all devices reflect the same stock levels within 2 seconds.
Automated Low Stock Alerts
Given an item’s stock falls below its predefined threshold, when the inventory is recalculated, then the system generates a dashboard alert and sends an email notification to the manager within 5 seconds.
Restock Push Notification
Given new stock is added to the central database, when the restock event is recorded, then all connected dashboards update to show the increased inventory and clear any sold-out flags within 2 seconds.
Customer Allergen Profile Management
"As a staff member, I want to access a customer’s allergen profile when taking an order so that I can automatically exclude unsafe items and protect customers with allergies."
Description

Implement a secure module for capturing and storing individual customer allergen profiles, allowing staff to link orders with specific dietary restrictions. The system should allow customers or staff to select allergens from a predefined list and store these preferences under customer identifiers or session tokens. This requirement enhances customer safety by ensuring that allergen data is consistently applied when suggesting substitutes. Integration with the substitution engine will filter out unsafe options based on stored profiles, reducing manual checks and liability risks.

Acceptance Criteria
Customer Creates Allergen Profile
Given a customer is on the allergen profile setup screen When they select one or more allergens from the predefined list and save Then the system securely stores the selected allergens under the customer’s identifier and displays a confirmation message
Staff Links Allergen Profile to Order
Given a staff member is processing a new order and a customer identifier is provided When they retrieve and attach the customer’s allergen profile Then the order should display the linked allergen information and prevent confirmation until a profile is attached
System Filters Substitutions Based on Allergens
Given an order contains items that are sold out When the substitution engine suggests alternatives Then only menu items free of the customer’s stored allergens should be presented
Customer Updates Allergen Profile
Given a customer has an existing allergen profile When they modify the selected allergens and save changes Then the system should update the stored profile and use the updated data for all new orders
Session Token Persists Allergen Preferences
Given a guest customer is browsing without an account When they select allergens and begin an order Then the system should store preferences with a session token and apply them to substitutions until the session expires
Substitution Suggestion Engine
"As a staff member, I want the system to automatically suggest safe alternative menu items when something is unavailable so that I can offer customers timely options without manual checking."
Description

Design and develop the core logic that analyzes current inventory and customer allergen profiles to generate real-time alternative menu recommendations. The engine should rank substitutes by similarity, availability, and preparation time, ensuring high service speed. It must handle complex substitution rules, including ingredient hierarchies and cross-allergen exclusions. The expected outcome is a rapid list of safe, in-stock alternatives that staff can present to customers instantly, minimizing waste and maintaining order flow.

Acceptance Criteria
Highly Allergenic Item Substitution
Given a customer with a peanut allergy and selecting a dish containing peanut sauce, when the substitution engine is triggered, then the engine suggests at least three peanut-free alternatives ordered by ingredient similarity and availability, and none of the suggestions contain peanut or cross-reactive allergens.
Out-of-Stock Menu Item Replacement
Given an order for a sold-out fish taco, when staff requests a substitute, then the engine recommends at least two in-stock items with similar flavor profiles and cooking methods, ensuring suggestions are available within standard prep time.
Cross-Allergen Hierarchy Handling
Given a customer allergic to shellfish but not to fish, when ordering a shrimp salad, then the engine excludes all shellfish substitutes, includes fish-based options, and logs the allergen exclusion in the recommendation metadata.
Preparation Time Ranking
Given multiple valid substitutes for a requested item, when the engine generates recommendations, then suggestions are sorted ascending by estimated preparation time and include prep time data in the recommendation payload.
Real-Time Inventory Sync
Given live inventory changes marking an item sold out during service, when staff queries substitutions for that item, then the engine uses updated stock data within 500ms to exclude unavailable items from recommendations.
Staff Suggestion Notification Interface
"As a food truck staff member, I want to receive clear, actionable suggestions on my dashboard so that I can offer alternatives to customers quickly and keep lines moving."
Description

Create a user interface component within the mobile dashboard that displays substitution suggestions prominently when an item is marked sold out or flagged for allergens. The interface should support touch interactions for quick acceptance or manual override, display details like ingredient differences and preparation notes, and provide visual cues for allergen safety. Integration with the main order entry screen is required to streamline the workflow. The expected result is a reduction in service delays and a more intuitive staff experience under high-pressure conditions.

Acceptance Criteria
Sold Out Item Replacement Prompt
Given a staff member adds a sold-out item to an order, when the substitution interface appears, then at least three alternative menu items with allergen-safe indicators and ingredient differences are displayed within 2 seconds.
Allergen Flag Replacement Notification
Given a customer’s allergen profile is detected and the selected item contains allergens, when the item is chosen, then only substitutions that meet the allergen profile are shown with preparation notes, and unsafe items are excluded.
Quick Accept Touch Interaction
Given substitution suggestions are displayed, when the staff member taps on a suggested replacement, then the original item is replaced in the order, the subtotal updates, and a confirmation toast appears within 1 second.
Manual Override Option
Given substitution suggestions are displayed, when the staff member selects manual override, then a warning prompt appears detailing allergen risks, and the staff must confirm to proceed, after which the order updates accordingly.
Integrated Order Entry Workflow
Given the main order entry screen, when a substitution is accepted or overridden, then the order entry reflects the change without navigating away and requires no more than two taps to complete the action.
Substitution Feedback Loop and Analytics
"As a manager, I want to see reports on how substitution suggestions perform so that I can refine our menu and reduce waste over time."
Description

Establish a feedback mechanism where staff can record whether suggested substitutions were accepted or rejected, and capture customer satisfaction ratings. Aggregate this data into analytics dashboards to track substitution success rates, common rejection reasons, and waste reduction metrics. The requirement integrates with the reporting module, enabling data-driven adjustments to substitution rules and inventory planning. The expected outcome is continuous improvement of suggestion accuracy, reduced food waste, and enhanced decision-making for inventory orders.

Acceptance Criteria
Recording Substitution Acceptance
Given a staff member reviews a suggested substitution, when they mark it as accepted, then the system logs the acceptance event including original item, substituted item, timestamp, and staff ID.
Capturing Rejection Reasons
Given a staff member marks a suggested substitution as rejected, when they select or enter a reason, then the system records the rejection reason along with associated substitution suggestion and timestamp.
Submitting Customer Satisfaction Ratings
Given a customer provides feedback on a substitution via the customer-facing interface, when they submit a satisfaction rating, then the system stores the rating linked to the substitution event.
Aggregating Substitution Success Metrics
Given multiple substitution events over a configurable period, when analytics are generated, then the dashboard calculates and displays acceptance rate, rejection rate, and average satisfaction score.
Visualizing Common Rejection Reasons
Given recorded rejection events, when generating analytics, then the dashboard lists the top three rejection reasons sorted by frequency and percentage of total rejections.

AllergyInsights

Generates actionable reports and analytics on allergen-related orders, incidents, and customer profiles. Provides trend visualizations, peak times for allergen orders, and high-risk items, enabling data-driven decisions to improve safety protocols and menu planning.

Requirements

Allergen Data Collection
"As a food truck operator, I want automatic collection of allergen-related data from orders and customer profiles so that I can ensure the accuracy and completeness of allergen records for reporting."
Description

The system shall collect and aggregate allergen-related data from order entries and customer profiles in real time, ensuring all allergen attributes are accurately captured and stored for reporting and analysis.

Acceptance Criteria
Real-time Order Entry Allergen Capture
Given a new order is placed with items containing allergens, when the order is submitted, then the system shall capture and persist all selected allergen attributes in the order record within 1 second, with no data loss.
Customer Profile Allergen Update
Given a user updates their customer profile with allergy information, when the profile changes are saved, then the system shall store the specified allergen attributes in the customer’s profile and apply them to all subsequent orders.
Real-time Aggregation of Allergen Data
Given multiple orders and profile updates over a rolling 1-minute window, when data is ingested, then the system shall aggregate and update the live allergen analytics dashboard within 2 seconds of the latest entry.
Error Handling for Missing Allergen Attributes
Given an order submission without any allergen attributes specified, when the system validates the entry, then it shall flag the missing allergen fields and require the operator to confirm ‘No known allergies’ or input specific allergens before allowing completion.
Validation of Allergen Data Accuracy
Given stored allergen data from orders and customer profiles, when performing a data integrity check, then 100% of allergen attributes shall match exactly between input and stored records, with no duplicates or mismatches.
Incident Reporting Integration
"As a safety manager, I want allergen incidents logged alongside order history so that I can trace back issues and implement corrective measures efficiently."
Description

Integrate allergen incident reporting into the existing incident management module, linking each reported incident with the relevant order, customer profile, and staff notes to provide a comprehensive audit trail.

Acceptance Criteria
Incident Report Submission
Given a user submits an allergen incident report within the incident management module When the report form is completed and submitted Then the system shall create a new incident record with a unique ID, timestamp, and 'Allergen Incident' tag
Order Association
Given an incident record exists When a user selects the 'Link Order' option and enters a valid order ID Then the system shall save the order ID in the incident record and provide a clickable link to the order details
Customer Profile Linking
Given an incident record exists When the system identifies a matching customer profile based on the incident’s customer information Then the system shall automatically associate the customer profile ID to the incident record and display the customer’s name and contact details
Staff Notes Recording
Given a staff member adds notes to an existing incident When the notes are saved Then the system shall store the notes with the staff member’s user ID, a timestamp, and display them chronologically in the incident record
Audit Trail Visibility
Given an incident record is viewed When a user accesses the 'Audit Trail' section Then the system shall display a chronological log of all incident events, including creation, updates, linked order additions, profile associations, and staff note entries, each with user ID and timestamp
Trend Visualization Dashboard
"As a restaurant owner, I want to view charts showing trends in allergen orders and incidents so that I can spot patterns and adjust menus or procedures accordingly."
Description

Provide interactive trend visualizations—including line charts, bar graphs, and customizable date ranges—to display allergen order volumes, incident counts, and customer allergy profiles over time.

Acceptance Criteria
Date Range Selection and Data Rendering
Given the user selects a custom date range, when the dashboard loads, then the line chart and bar graph update to reflect allergen order volumes and incident counts only within the selected range.
Peak Incident Period Detection
Given the dashboard displays incident counts over time, when large spikes occur, then the system highlights peak periods in the chart and displays the top three peak dates.
Customer Allergy Profile Trend Analysis
Given the dashboard shows customer allergy profiles, when data is aggregated monthly, then the bar graph displays counts of customers per allergy type for each month and allows toggling to weekly view.
High-Risk Item Trend Visualization
Given the dashboard is open, when the user filters by 'High-Risk Items', then the line chart shows trend lines for each high-risk item, with distinct colors, including tooltips on hover.
Real-Time Data Refresh
Given live data updates, when new allergen orders or incidents are received, then the dashboard auto-refreshes the visualizations within 30 seconds without a full page reload.
Peak Allergen Time Analytics
"As an operations manager, I want to see peak allergen order times so that I can allocate resources and staff appropriately during busy allergen-sensitive periods."
Description

Identify and highlight peak times and dates for allergen-related orders using heatmaps and time-series analytics, enabling targeted staffing and resource planning.

Acceptance Criteria
Viewing Peak Allergen Heatmap
Given the user is on the Peak Allergen Analytics page When they select a valid date and time range Then the heatmap displays allergen-related order counts per hour with color intensity matching predefined thresholds
Filtering by Allergen Type
Given the heatmap is displayed When the user selects a specific allergen type filter Then the heatmap updates to show only orders containing that allergen across the selected time range
Time-Series Graph Visualization
Given the user switches to the time-series view When a date range is applied Then the line graph plots hourly allergen order volumes with data points showing exact counts on hover
Identifying Peak Days in Calendar View
Given the user opens the calendar summary When they hover over a date cell Then the tooltip displays the total allergen orders for that date and dates exceeding the high-risk threshold are highlighted
Exporting Peak Time Report
Given the user clicks the Export Report button When they choose CSV format Then the system generates and downloads a file containing timestamp, allergen order count, and intensity rating for the selected date range
High-Risk Item Identification
"As a menu planner, I want to know which items have the most allergen incidents so that I can revise recipes or provide additional warnings to customers."
Description

Analyze menu items to detect those with the highest frequency of allergen incidents and flag them for review, providing recommendations for recipe adjustments or enhanced customer warnings.

Acceptance Criteria
Monthly High-Risk Item Flagging
Given incident log data for the past 30 days, when analysis runs, then the system identifies and flags the top 5 menu items by incident count and lists them in the High-Risk Items report.
Recipe Adjustment Recommendations
Given a flagged high-risk item, when the item is reviewed, then the system generates at least two actionable recipe adjustment or warning enhancement suggestions per item.
Admin Notification of High-Risk Items
Given new items are flagged in a weekly analysis, when the weekly report is finalized, then the system sends a notification to the admin dashboard and via email summarizing the flagged items.
Trend Visualization of High-Risk Incidents
Given historical incident data for flagged items over the last 6 months, when viewing the High-Risk Items dashboard, then the system displays an accurate trend chart showing incident counts per month for each flagged item.
Incident Data Threshold Filtering
Given incident counts for all menu items, when filtering for high-risk candidates, then the system excludes items with fewer than 5 incidents in the analysis period.

Dynamic Bundle Builder

Automatically assembles optimal meal bundles by analyzing real-time inventory levels and live sales trends, ensuring each combo maximizes profit potential while minimizing waste.

Requirements

Real-time Inventory Synchronization
"As a food truck operator, I want the bundle builder to only suggest combos that include items I actually have in stock so that I avoid disappointing customers and minimize food waste."
Description

Continuously syncs inventory levels from all active food trucks to the Dynamic Bundle Builder in real time, ensuring bundle suggestions only include items currently available. This prevents overselling, reduces waste, and maintains accurate stock visibility across the system.

Acceptance Criteria
Initial Inventory Load on Bundle Builder Startup
Given the Bundle Builder initializes, When all active food trucks are detected, Then the system retrieves and displays each truck’s current inventory levels within 5 seconds.
Inventory Update After Sale Transaction
Given a sale is completed at any food truck, When the transaction is finalized in the POS, Then the inventory on the Bundle Builder updates to reflect the sale within 2 seconds with zero discrepancy.
Inventory Adjustment Upon Manual Stock Change
Given a manager adjusts stock levels manually in the mobile dashboard, When the adjustment is saved, Then the Bundle Builder reflects the new inventory count immediately and confirms the update to the user.
Offline Reconnection Inventory Reconciliation
Given a food truck experiences a network outage, When the connection is restored, Then the system reconciles and applies all missed inventory changes within 10 seconds and matches the final counts recorded during the outage.
High-Frequency Sales Spike Handling
Given a surge of sales (e.g., 100 transactions per minute), When live synchronization is active, Then the Bundle Builder processes all updates without errors, maintains under 5-second latency per update, and excludes any sold-out items from suggested bundles.
Sales Trends Analysis Engine
"As a food truck owner, I want the system to analyze my real-time sales and past trends so that I can offer bundles that maximize profit and clear slow-moving inventory."
Description

Implements a predictive analytics engine that analyzes live sales data and historical trends to identify high-demand items and optimal bundle combinations. This engine adjusts bundle suggestions dynamically based on peak times, slow-moving items, and seasonal preferences.

Acceptance Criteria
Peak Hour Bundle Adjustment
Given live sales data during peak hours, when an item's sales volume exceeds the high-demand threshold, then the engine updates bundle suggestions within 30 seconds to prioritize items with the highest demand and a profit margin above 25%.
Slow-Moving Item Promotion
Given an item with zero sales in the past 6 hours, when generating bundles, then the engine includes the slow-moving item in at least one discounted bundle with a minimum combined profit margin of 20% and flags the expected clearance time.
Seasonal Preference Adaptation
Given historical seasonal sales data indicating a 20% uptick in a category during a season, when the current date falls within that season, then the engine adjusts bundle suggestions to feature seasonal items and predicts sales uplift within ±5% accuracy.
Inventory Shortage Response
Given an item’s inventory level drops below the predefined threshold during active service hours, when updating bundle suggestions, then the engine excludes that item from all bundles and provides alternative high-margin suggestions within 2 seconds.
Real-Time Trend Forecast Accuracy
Given the engine processes 24 hours of live sales data and historical trends, when forecasting bundle demand for the next 2 hours, then prediction accuracy meets or exceeds 85% compared to actual sales.
Optimal Bundle Computation Algorithm
"As a food truck manager, I want the system to compute the best possible bundle combinations based on cost and availability so that I can increase average order value without manual calculation."
Description

Develops the core algorithm that combines cost, profit margin, and inventory constraints to generate the highest-value meal bundles. The algorithm runs automatically at configurable intervals and updates suggestions immediately when input data changes.

Acceptance Criteria
Real-Time Bundle Generation at Peak Hours
Given the system is under peak sales load and inventory levels are current, When the optimal bundle algorithm runs, Then it must generate and display at least three meal bundles ranked by profit potential within 2 seconds.
Dynamic Recalculation on Inventory Update
Given an inventory adjustment is made for any menu item, When the inventory data is updated in the system, Then the algorithm must recalculate and update affected bundle suggestions in the dashboard within 1 second.
Profit Optimization with Cost Fluctuations
Given a change in ingredient cost or selling price for any item, When the cost input data is modified, Then the algorithm must adjust the profit margin calculation and regenerate bundle suggestions that reflect the new optimal profit mix.
Threshold Alert for Low Inventory Impact
Given a menu item’s inventory level falls below a predefined threshold, When the algorithm completes its run, Then any bundle containing that item must be flagged, and alternate high-profit bundles excluding the low-inventory item must be suggested.
Scheduled Interval Bundle Refresh
Given the bundle refresh interval is configured to every 5 minutes, When the scheduled time arrives, Then the algorithm must automatically execute and refresh the bundle suggestions without manual intervention.
Bundle Configuration Interface
"As a food truck operator, I want a dashboard interface to review and tweak the suggested bundles so that I maintain full control over promotions and pricing."
Description

Creates a user-friendly interface within the dashboard where operators can review, customize, and approve automatically generated bundles. The interface allows manual overrides, adjustment of bundle pricing, and toggling of suggested combos on or off.

Acceptance Criteria
Auto-Generated Bundle Review
Given the dashboard displays a list of auto-generated bundles, when the operator clicks on a bundle entry, then the bundle details (items, quantities, suggested price, profit margin) are shown for review; and the operator can click Approve to confirm the bundle, at which point the bundle status changes to Approved in the UI.
Manual Pricing Adjustment
Given an approved or pending bundle is selected, when the operator edits the price field and enters a new value, then the system validates the price falls within the configured markup range and reflects the updated price in the bundle summary; saving the change persists the new price and recalculates projected profit.
Combo Activation Toggle
Given the list of suggested combos is displayed, when the operator toggles the On/Off switch for a combo, then the combo is immediately enabled or disabled for customer ordering; and the combo’s status icon and availability label update accordingly.
Inventory Constraint Override
Given an auto-generated bundle contains an item with low stock, when the operator clicks Replace Item, then the system displays alternative items that meet the same category and price range; selecting a replacement updates the bundle composition and recalculates total cost.
Bulk Bundle Approval
Given multiple auto-generated bundles are listed with checkboxes, when the operator selects multiple bundles and clicks Approve All, then each selected bundle’s status changes to Approved, and a confirmation banner appears indicating the number of bundles approved.
Bundle Performance Reporting
"As a food truck owner, I want reports on how each dynamic bundle performs so that I can identify the most profitable combos and adjust strategies accordingly."
Description

Introduces reporting features that track bundle sales performance, waste reduction metrics, and profit contributions. Provides visual charts and exportable data so operators can evaluate the effectiveness of each bundle and refine settings.

Acceptance Criteria
Viewing Bundle Sales Performance Dashboard
Given an operator is on the Bundle Performance Reporting page and selects a valid date range When the dashboard loads Then it displays a chart listing each bundle with total sales count and revenue generated And highlights the top five bundles by profit margin within 2 seconds of selection
Exporting Bundle Performance Data
Given an operator clicks the “Export CSV” button When the system generates the export Then a CSV file downloads within 5 seconds containing columns: Bundle ID, Bundle Name, Total Sales, Waste Reduced (units), Profit Contribution And the column order matches the specification
Real-Time Waste Reduction Metrics Display
Given the system processes new bundle sales and inventory updates When sales reduce available stock Then the waste reduction metrics widget updates to show actual vs. forecast savings within 10 seconds And reflects the change in the displayed chart
Historical Profit Contribution Analysis
Given an operator requests a profit report for a previous period When the report is generated Then it shows a table listing each bundle’s total profit and percentage contribution of overall profit And percentage values are calculated as (bundle profit / total profit) * 100 within a 0.01% tolerance
Filtering Report by Date Range
Given an operator defines a custom date range filter on the reporting page When the filter is applied Then all charts and tables update to reflect only data from the selected range And the filter selection persists until the operator clears it

TrendSync Spotlight

Highlights trending menu items and suggests high-demand pairings on the fly, helping you capitalize on popular flavors and boost combo appeal effortlessly.

Requirements

Real-Time Analytics Engine
"As a food truck owner, I want the system to process sales data instantly so that I can see which items are trending at any moment and adjust offerings accordingly."
Description

Develop a backend engine that ingests live sales and inventory data, processes item popularity metrics in real time, and produces up-to-the-second trend scores. This service must integrate with existing order and inventory APIs, handle high-frequency data updates during peak service periods, and expose a lightweight endpoint for front-end consumption. Expected outcomes include accurate identification of trending items within seconds of order activity, minimal latency, and scalable performance to support multiple simultaneous food trucks.

Acceptance Criteria
High-Frequency Data Ingestion
Given the system receives 500 order and inventory updates per second during peak hours, when the analytics engine ingests data, then 100% of events are processed without loss and reflected in trend scores within 1 second.
Low-Latency Trend Score API Response
Given a valid request for trending items during live service, when the frontend calls the /trend-scores endpoint, then the API returns the top 10 trending items in JSON format with HTTP 200 and response time under 200ms.
Cross-API Integration Verification
Given an order is placed or inventory is updated via the existing order/inventory APIs, when the analytics engine polls or receives the event, then the corresponding change is accurately reflected in trend score calculations within 2 seconds.
Sold-Out Item Exclusion from Trends
Given an item’s inventory count reaches zero, when trend scores are computed, then the sold-out item is excluded from the trending list and no longer appears in API responses.
Scalability Across Multiple Food Trucks
Given 10 simultaneous food truck data streams sending live updates, when the engine processes all streams, then trend score update latency per truck remains under 3 seconds and overall CPU utilization stays below 70%.
Trending Items Dashboard
"As a food truck owner, I want a clear display of my highest-demand items so that I can promote them and reduce waste on slower-selling options."
Description

Create a front-end dashboard widget that visually highlights top trending menu items using clear indicators such as heat maps, ranking badges, or sparkline charts. The widget should fetch data from the analytics engine at configurable intervals, allow quick toggling between time ranges (e.g., last 5 minutes, 30 minutes, 2 hours), and integrate seamlessly within the existing MenuZap interface. Benefits include rapid visibility into customer preferences and the ability to promote popular items instantly.

Acceptance Criteria
Real-Time Data Refresh Interval
Given the TrendSync Spotlight widget is loaded, Then it performs its first data fetch within 5 seconds; When a user configures the refresh interval to 1, 5, 15, or 30 minutes, Then the widget fetches new trending data exactly at the configured interval (±5 seconds) and updates the display within 3 seconds of each fetch; When the refresh interval is changed, Then subsequent fetches adhere to the new setting without requiring a page reload.
Time Range Toggle Functionality
Given the widget displays trending items, When the user selects a time range option (5 minutes, 30 minutes, or 2 hours), Then the widget refreshes the data to reflect the chosen range within 2 seconds; And the active time range toggle is visually highlighted to indicate the current selection.
Visual Highlight Accuracy
Given the trending data is available, Then the top three items are labeled with ranking badges (#1, #2, #3); And heatmap colors correctly represent relative popularity on a green-to-red scale; And sparklines render accurate trend lines over the selected time range without missing or overlapping elements.
Seamless Interface Integration
Given the widget is embedded in the MenuZap dashboard, Then it conforms to the existing UI style guidelines for fonts, colors, and spacing; And it does not cause layout shifts, content overflow, or scrolling issues on desktop and mobile viewports.
Performance Under High Load
Given a simulated backend load of 1,000 concurrent users fetching trending data, Then each widget update completes within 3 seconds; And the presence of the widget does not increase initial page load time by more than 500 milliseconds.
High-Demand Pairing Suggestions
"As a food truck owner, I want automatic pairing recommendations for my best sellers so that I can create attractive combo deals and increase average ticket value."
Description

Implement an algorithmic component that analyzes historical order combinations and current trending data to generate suggested item pairings. Suggestions should update dynamically based on live trends and consider factors such as complementary flavors, order frequency, and inventory availability. The feature should present the top two pairings alongside each trending item, enabling one-click addition of combos to the menu or promotional displays.

Acceptance Criteria
Real-Time Trending Pairing Generation
Given a menu item’s live trending score is above threshold When TrendSync Spotlight processes trending data Then the top two algorithmically generated pairings are displayed next to the item within two seconds
Inventory-Aware Pairing Suggestions
Given current inventory levels are provided When pairings are calculated Then suggested combinations exclude any items with inventory below reorder threshold
Flavor Complement Validation
Given historical order flavor profiles exist When the algorithm analyzes complementary flavors Then generated pairings must have at least a 75% historical pairing success rate
One-Click Combo Addition
Given suggested pairings are displayed When the user clicks the “Add Combo” button Then the paired items are added to the menu as a single combo with correct pricing and description
Dynamic Update Under High Load
Given high concurrent user activity When live trend data updates occur Then pairing suggestions refresh without UI lag or errors within five seconds
Instant Trend Notifications
"As a food truck owner, I want to receive alerts when an item becomes especially popular so that I can restock or promote it before running out."
Description

Build a notification system that alerts users when a menu item’s trend score crosses defined thresholds. Notifications can be delivered via in-app banners or mobile push messages, allowing owners to react immediately by adjusting promotions or inventory. Configuration options should let users set custom threshold levels and notification frequency to avoid alert fatigue while ensuring timely awareness of sudden demand spikes.

Acceptance Criteria
High Trend Score Trigger
Given a menu item’s trend score crosses the user-defined high threshold, when the system evaluates trend scores in real time, then an in-app banner and a mobile push notification are delivered within 5 seconds of crossing the threshold.
Custom Threshold Configuration
Given the user sets a new trend score threshold and saves settings, when the threshold configuration is applied, then future notifications respect the updated threshold without requiring a page reload or app restart.
Notification Frequency Control
Given the user configures a minimum interval of X minutes between notifications for the same item, when the item’s trend score fluctuates above the threshold within that interval, then no additional notification is sent until X minutes have elapsed.
Multi-Channel Delivery
Given the user has both in-app banners and mobile push enabled, when a trend threshold is breached, then the system sends both an in-app banner and a mobile push message to the user’s registered devices.
Re-Notification on Resurgence
Given a trend notification has already been sent for an item and the trend score falls below the threshold before rising again, when the score rises above the threshold a second time, then a new notification is issued following all frequency controls.
Customizable Trend Filters
"As a food truck owner, I want to filter trends by criteria like category or time range so that I can focus on the insights most relevant to my current service context."
Description

Add filtering capabilities that enable users to segment trending data by category, time window, location, or custom tags (e.g., vegetarian, spicy). This feature should provide dropdown selectors or tag-based filters within the dashboard, allowing quick refinement of trend insights to match specific business strategies or event contexts. Expected integration with existing menu metadata ensures coherence across the platform.

Acceptance Criteria
Category Trend Filtering
Given the user is viewing the TrendSync Spotlight dashboard, When the user selects a specific category from the category dropdown, Then only items within the selected category appear in the trending list.
Time Window Trend Filtering
Given the user is on the TrendSync Spotlight dashboard, When the user selects a time window (e.g., last 24 hours, last week) and applies the filter, Then the trending items list updates to reflect trends only within that time window.
Location-Based Trend Filtering
Given the user is on the TrendSync Spotlight dashboard, When the user selects a location from the location filter, Then trending items are displayed only for that location's sales data.
Custom Tags Trend Filtering
Given the user is on the TrendSync Spotlight dashboard, When the user selects one or more custom tags (e.g., 'vegetarian', 'spicy') from the tag filter, Then the trending items list updates to show items matching the selected tags.
Combined Filters Application
Given the user has selected multiple filters (category, time window, location, custom tags), When the user applies all selected filters, Then the trending items list reflects the intersection of all selected filters.

MarginMaximizer

Calculates and recommends the ideal price points for each meal bundle by balancing customer value and profit margins, driving higher revenue without compromising customer satisfaction.

Requirements

Dynamic Pricing Algorithm
"As a food truck owner, I want the system to automatically compute ideal bundle prices based on sales trends and inventory so that I can maximize profits without manually adjusting prices."
Description

Develop a robust pricing algorithm that analyzes historical sales data, current inventory levels, and customer purchasing patterns to calculate optimal price points for each meal bundle in real time. The algorithm should balance customer perceived value against desired profit margins, adjust prices dynamically based on demand fluctuations and stock availability, and integrate seamlessly with MenuZap’s existing order management system to ensure recommended prices are updated instantly across all user interfaces.

Acceptance Criteria
Peak Hour Demand-Based Pricing Update
Given the system detects order volume for a specific bundle has increased by 20% compared to the same time last week When the algorithm recalculates pricing During peak hours Then the bundle price is increased by up to 10% of the base price and the updated price is reflected in the dashboard within 5 seconds
Inventory Level-Based Price Adjustment
Given the inventory level for a meal bundle falls below the predefined low-stock threshold When the pricing algorithm executes Then the price of the bundle is automatically increased by at least 5% and the sold-out indicator is triggered at 0 units
Sales Trend-Driven Discount Optimization
Given a meal bundle’s sales have decreased by more than 15% over the past two hours When the algorithm evaluates demand trends Then the bundle price is decreased by no more than 5% to boost demand and the change is logged with timestamp
Loyal Customer Personalized Pricing
Given a customer has placed more than five orders for the same bundle in the last week When the algorithm identifies customer purchasing patterns Then a loyalty discount of 3% is applied to their recommended price without dropping below the minimum margin threshold
Real-Time Integration with Order Management
Given the algorithm generates new price recommendations When the system pushes updates to the order management API Then all front-end interfaces reflect the new prices within 2 seconds and API responses return HTTP 200
Profit Margin Threshold Settings
"As a food truck owner, I want to set minimum and target profit margins for my bundles so that the system won’t recommend prices below my acceptable profitability levels."
Description

Implement configurable settings that allow users to define minimum and target profit margin thresholds for each meal bundle. Users should be able to set global defaults as well as override thresholds at the individual bundle level. The system must validate these thresholds, provide warnings when recommended prices would breach the defined limits, and ensure that any automated pricing recommendations respect the user’s specified margin constraints.

Acceptance Criteria
Setting Global Default Margin Thresholds
Given the user navigates to the MarginMaximizer settings, When they enter valid numeric values for minimum and target profit margin thresholds and save, Then the system persists these as the global defaults and displays a confirmation message.
Overriding Bundle-Specific Margin Thresholds
Given the user views an individual meal bundle in the dashboard, When they override the default profit margin thresholds for that bundle and save, Then the system applies and displays the new thresholds for that bundle without altering the global defaults.
Validating Threshold Input Ranges
Given the user inputs a profit margin threshold outside the allowable range (0-100%), When they attempt to save, Then the system rejects the input and displays a descriptive validation error.
Price Recommendation Breach Warning
Given the system generates a price recommendation that would violate either the minimum or target threshold for a bundle, When the recommendation is displayed, Then the system shows a clear warning message indicating which threshold would be breached.
Automated Pricing Respect Constraints
Given the user triggers an automated pricing update for all bundles, When the system calculates new prices, Then no recommended price exceeds the user-defined target margin or falls below the minimum margin.
Bundle Profitability Dashboard
"As a food truck owner, I want a dashboard that shows profit metrics for each bundle so that I can easily monitor performance and adjust my offerings."
Description

Create an interactive dashboard module within MenuZap that visualizes the profitability of all meal bundles. The dashboard should display key metrics such as current price, cost of ingredients, calculated margin, and projected daily revenue. Include filtering and sorting capabilities by margin percentage, sales volume, and inventory status to help users quickly identify high- and low-performing bundles and make data-driven pricing decisions.

Acceptance Criteria
Viewing Profitability Metrics on the Dashboard
Given the user navigates to the Bundle Profitability Dashboard, When the page loads, Then the dashboard must display a table with columns: Bundle Name, Current Price, Ingredient Cost, Calculated Margin (in % and $), and Projected Daily Revenue, and load within 2 seconds.
Filtering Bundles by Margin Percentage
Given the user applies a margin percentage filter set to '>= 20%', When the filter is applied, Then only meal bundles with a calculated margin of 20% or higher are displayed.
Sorting Bundles by Sales Volume
Given the user clicks the 'Sales Volume' column header, When sorting is triggered, Then meal bundles are ordered correctly in ascending or descending order based on sales volume.
Identifying Out-of-Stock Bundles
Given the dashboard displays inventory status, When a bundle contains any ingredient below the replenishment threshold, Then the bundle row is highlighted in red and appears at the top when sorting by inventory status.
Projecting Daily Revenue Based on Current Sales
Given the dashboard updates in real time, When the user views the 'Projected Daily Revenue' column, Then the projected revenue is calculated accurately using current sales rate extrapolated over the defined business day length.
Real-time Market Data Integration
"As a food truck owner, I want pricing recommendations to account for competitor prices and local demand so that my bundles stay competitively priced and maximize sales opportunities."
Description

Integrate external market data sources such as competitor pricing feeds and local demand indicators (e.g., event schedules, weather forecasts) to refine price recommendations. The feature should fetch and normalize data from third-party APIs, analyze it alongside in-house metrics, and factor these insights into the dynamic pricing algorithm to ensure recommendations reflect real-world market conditions.

Acceptance Criteria
Competitor Price Feed Retrieval
Given the system is connected to the competitor pricing API, When a fetch is initiated, Then the system retrieves pricing data for all listed items within 60 seconds and stores it in the database in the predefined format with no schema validation errors.
Market Data Normalization
Given raw market data is received from third-party sources, When the normalization process runs, Then data fields (price, timestamp, location) are converted to standard units, duplicates removed, and anomalies flagged within 2 minutes.
Local Event Data Integration
Given the local event schedule API is accessible, When event data is fetched for the next 7 days, Then events are tagged to relevant menu items based on location and timeframe and displayed in the dashboard.
Dynamic Price Adjustment with Market Insights
Given live market data inputs and in-house sales metrics, When the dynamic pricing algorithm executes, Then price recommendations are updated within 30 seconds to reflect competitor pricing and demand indicators, achieving at least a 5% margin increase in test scenarios.
Market Data API Error Handling
Given the market data API returns an error or times out, When a fetch attempt fails, Then the system logs the error, retries up to 3 times with exponential backoff, sends an alert to the admin if still unsuccessful, and continues serving the last known recommendations.
Price Recommendation Notifications
"As a food truck owner, I want to receive alerts when the system suggests new prices so that I can quickly approve or review changes without checking the dashboard constantly."
Description

Enable push and in-app notifications to alert users when significant pricing updates are recommended by MarginMaximizer. Notifications should include the bundle name, current price, suggested price, and rationale (e.g., low inventory, high demand). Users should be able to configure notification preferences for frequency and channels (SMS, email, mobile app) to stay informed without constant manual monitoring.

Acceptance Criteria
Recommended Price Notification Content
Given a price recommendation is generated by MarginMaximizer When a notification is created Then it must include the bundle name, current price, suggested price, and rationale for the recommendation.
User Configures Notification Preferences
Given the user navigates to notification settings When the user selects frequency (immediate, hourly, daily) and channels (SMS, email, in-app) Then the system saves and applies these preferences for all future notifications.
Timely Delivery of Price Recommendations
Given a pricing update triggers a notification When the user’s frequency preference is immediate Then the notification is delivered to the selected channels within 5 seconds of generation.
Multi-Channel Notification Delivery
Given the user has enabled multiple notification channels When a price recommendation is available Then the system sends identical notification content via all enabled channels without duplication errors.
Notification Opt-out Functionality
Given the user disables a specific notification channel in settings When a subsequent price recommendation is generated Then no notification is sent via that disabled channel until the user re-enables it.
User Override and Feedback Loop
"As a food truck owner, I want to override suggested prices and provide feedback so that the system learns from my preferences and improves future recommendations."
Description

Provide users with the ability to accept, modify, or reject each recommended price directly within the dashboard. Capture user decisions and feedback to refine the pricing algorithm over time. The system should log override reasons and adjust future recommendations based on patterns in user adjustments to improve accuracy and build trust in the automated pricing model.

Acceptance Criteria
User Accepts Recommended Price
Given a recommended bundle price is displayed, when the user clicks ‘Accept’, then the system applies that price to the bundle, updates the live menu, and shows a success confirmation within two seconds.
User Modifies Recommended Price
Given a recommended bundle price is displayed, when the user edits the price field and clicks ‘Save’, then the system validates the new price, applies it to the menu, records the adjustment, and displays the updated price with confirmation.
User Rejects Recommended Price
Given a recommended bundle price is displayed, when the user clicks ‘Reject’, then the system removes the recommendation, prompts for an override reason, logs the rejection, and retains the previous price.
Override Reason Logging
Given a user overrides or rejects a recommendation, when the user submits an override reason, then the system logs the reason with timestamp, user ID, original recommendation, and final price in the audit trail.
Feedback Influences Future Recommendations
Given a history of stored override reasons and adjustments, when the pricing algorithm runs its next batch calculation, then it analyzes patterns from the last 30 days of user feedback and adjusts its price recommendations accordingly.

Smart WasteTracker

Monitors ingredient shelf life and stock movement to prioritize bundles that use at-risk items first, reducing spoilage and cutting food costs.

Requirements

Real-Time Shelf-Life Tracking
"As a food truck owner, I want to track ingredient shelf life in real time so that I can use items before they spoil and reduce waste."
Description

Implement a system that continuously monitors the shelf life of all ingredients by recording their receipt dates and expiration thresholds. The feature will integrate with existing inventory data in MenuZap, calculate real-time freshness scores, and display visual indicators on the dashboard for each ingredient. By knowing the exact remaining shelf life, operators can make informed decisions, reduce spoilage, and maintain accurate inventory records, ensuring only fresh ingredients are used in orders.

Acceptance Criteria
Receiving New Ingredient Shipment
Given a new ingredient batch is added with receipt date and expiration threshold, when the data is saved, then the system records the timestamps and calculates the correct expiration date for each item.
Ingredient Shelf-Life Indicator Display
Given ingredients with recorded shelf-life data, when the operator views the inventory dashboard, then each ingredient shows a colored freshness indicator reflecting the real-time shelf-life percentage.
Near-Expiration Alert Trigger
Given an ingredient’s freshness score drops below 10%, when the system recalculates shelf-life, then an alert is generated and displayed prominently on the dashboard.
Inventory Consumption Update
Given ingredients are used in an order, when the order is completed, then the system updates remaining quantities and recalculates freshness scores for impacted items.
Data Integration and Sync
Given inventory data is updated externally, when MenuZap syncs data, then real-time shelf-life calculations and indicators reflect the latest changes within 30 seconds.
At-Risk Ingredient Identification
"As a food truck operator, I want to see which ingredients are at risk of expiring soon so that I can prioritize them in menu bundles and reduce spoilage."
Description

Develop an algorithm that flags ingredients approaching their expiration date within a configurable time window. This requirement involves setting customizable thresholds, highlighting at-risk items in the dashboard list, and prioritizing them in notifications. By identifying these items early, the system helps food truck owners focus on using perishable goods first, minimizing waste and improving cost management.

Acceptance Criteria
Threshold Configuration Validation
Given a user sets an expiration threshold of X days, when the system evaluates inventory, then all ingredients with time-to-expiration ≤ X days are flagged as at-risk.
Dashboard Highlight Display
Given ingredients are flagged as at-risk, when the user views the dashboard list, then at-risk items are visually highlighted with a distinct color and an expiration countdown.
Notification Prioritization
Given multiple at-risk ingredients exist, when the system generates notifications, then ingredients closest to expiration are listed first and grouped separately from other alerts.
Threshold Adjustment Persistence
Given a user updates the at-risk threshold value, when the new value is saved, then subsequent evaluations use the updated threshold without reverting to default upon page reload.
Bulk Import Expiration Check
Given inventory is imported via CSV upload, when the import completes, then all imported ingredients nearing expiration within the threshold are automatically flagged in the dashboard.
Smart Bundle Suggestion
"As a food truck manager, I want the system to suggest menu bundles using soon-to-expire ingredients so that I can promote them and minimize waste."
Description

Create a recommendation engine that analyzes current inventory levels, ingredient shelf life, and sales trends to suggest menu item bundles incorporating soon-to-expire ingredients. Suggestions will appear directly in the mobile dashboard, allowing operators to quickly promote these bundles to customers. This feature drives targeted sales of at-risk items, reduces waste, and optimizes daily menu offerings.

Acceptance Criteria
Dashboard Suggestion Display
Given the operator has ingredients with shelf life ≤ 2 days and sales trends available, when the operator opens the mobile dashboard, then at least one smart bundle suggestion appears in the dedicated suggestions section.
Expiry-Based Bundle Prioritization
Given multiple ingredients with varying expiration dates, when the engine analyzes inventory, then bundles are ordered by earliest average ingredient expiration date, with the top three displayed first.
Operator Bundle Promotion
Given a suggested bundle is listed, when the operator taps the 'Promote' button on a suggestion, then the bundle is added to the day's active menu and a confirmation message is displayed.
Suggestion Refresh Post Inventory Update
Given an inventory stock change (e.g., item marked sold out or new stock added), when the change occurs, then the smart bundle suggestions refresh within 30 seconds to reflect the updated inventory.
Inventory Threshold Compliance
Given any ingredient in a suggested bundle falls below the minimum stock threshold (<5 units), when suggestions are generated, then bundles do not include that ingredient to prevent recommending out-of-stock items.
Inventory Usage Alerts
"As a food truck owner, I want to receive alerts when ingredients are low on stock or near expiration so that I can take timely action to restock or use them."
Description

Implement a notification system that delivers real-time alerts when ingredient stock falls below predefined thresholds or when items near expiration. Alerts can be configured as push notifications, SMS, or in-dashboard messages. This proactive approach ensures owners are immediately informed of critical inventory statuses, enabling timely restocking or menu adjustments to prevent stockouts and spoilage.

Acceptance Criteria
Low Stock Threshold Push Notification Alert
Given an ingredient's stock falls below the user-defined threshold, When the inventory system detects the drop, Then a push notification is sent within 60 seconds to the user's device containing ingredient name, current quantity, and threshold value.
Expiration Date SMS Warning
Given an ingredient is within 3 days of expiration, When the system checks expiration dates at daily intervals, Then an SMS is sent to the owner listing all near-expiry items sorted by soonest expiration.
In-Dashboard Critical Stock Alert
Given an ingredient reaches zero units, When the dashboard loads for any user, Then a visible red banner appears in the inventory section highlighting the out-of-stock item and prompting restocking.
Custom Alert Configuration Confirmation
Given a user updates alert thresholds or channels in settings, When the user saves the changes, Then a confirmation message appears and the new settings are applied immediately and persist across sessions.
Alert Channel Fallback Mechanism
Given the primary alert channel fails to deliver, When a delivery failure is detected within 2 minutes, Then the system automatically sends the alert via the secondary configured channel without duplication.
Waste Reduction Analytics
"As a food truck owner, I want to view waste reduction analytics and cost-saving reports so that I can understand spoilage patterns and improve inventory decisions."
Description

Introduce an analytics module that aggregates data on ingredient usage, spoilage incidents, and cost savings achieved through bundle promotions. The dashboard will display interactive charts and reports on waste trends over time, highlighting high-waste categories and estimating financial impact. By providing actionable insights, this feature empowers operators to refine inventory strategies and achieve measurable reductions in food waste.

Acceptance Criteria
Time-Frame Waste Trends Analysis
Given the operator is on the Waste Reduction Analytics dashboard When the operator selects a custom date range Then the system displays an interactive line chart of total waste volume and cost for each day And the chart granularity adjusts based on the selected date range (daily for <30 days, weekly for 30–90 days, monthly for >90 days)
High-Waste Category Highlighting
Given the operator views the waste summary section When the data is loaded Then the system lists the top 5 ingredient categories by waste volume in descending order And displays each category’s waste volume and percentage of total waste And highlights categories exceeding 20% of total waste in red
Financial Impact Calculation Display
Given the operator accesses the cost savings tab When the date range is selected Then the system calculates and displays the estimated cost savings achieved through bundle promotions within that period And the calculation matches the formula: (standard ingredient cost × spoilage count) – promotional cost And shows a comparison against the previous period’s savings
Interactive Chart Drill-Down
Given the operator clicks on a data point in the waste trend chart When the click event is triggered Then the system opens a detail modal listing individual ingredients contributing to that data point And displays each ingredient’s name, expired quantity, spoilage incidents, and associated cost
Report Export Functionality
Given the operator clicks the export button When the export type (CSV or PDF) is selected Then the system generates a downloadable file containing the date range, waste trend data, high-waste categories summary, and cost savings estimates And the exported file contents exactly match the on-screen data

Template Pro

Provides customizable bundle templates that automatically adapt to inventory changes and sales targets, allowing you to define upsell rules and deploy new combos in seconds.

Requirements

Template Creation Interface
"As a food truck owner, I want an easy-to-use interface to build new bundle templates so that I can create and update promos quickly without technical help."
Description

Provide an intuitive, wizard-based interface within MenuZap that guides users step-by-step through creating new bundle templates. This feature should allow selection of items, grouping into sets, setting default quantities, and naming templates. It should integrate seamlessly with the existing dashboard, offering drag-and-drop arrangement and real-time previews. The interface must validate inputs, flag incompatible combinations, and enable saving drafts for later editing, ensuring that users can quickly craft and iterate on promotional bundles without coding knowledge.

Acceptance Criteria
Wizard Initialization
Given the user clicks “Create New Template” from the dashboard, When the wizard launches, Then the interface displays step 1 with fields for template name, description, and navigation controls.
Item Selection and Grouping
Given the wizard is on item selection, When the user selects or deselects menu items, Then the selected items appear in the bundle list with default quantities and grouping options.
Drag-and-Drop Arrangement
Given a list of selected items, When the user drags an item within the bundle layout, Then the interface reorders items accordingly and updates the preview position in real time.
Real-time Template Preview
Given any change to items, quantities, or grouping, When the user views the preview pane, Then the preview updates instantly to reflect the current bundle appearance and pricing.
Input Validation for Incompatible Combinations
Given specified upsell rules and item constraints, When the user adds incompatible items or exceeds quantity limits, Then the system highlights conflicts, displays a clear error message, and disables the “Next” button until resolved.
Save Draft and Resume Editing
Given a partially completed template, When the user selects “Save Draft,” Then the system stores all current selections and settings, And when reopened, The wizard restores the last saved state exactly.
Inventory Sync Engine
"As a food truck manager, I want my bundle templates to automatically reflect stock changes so that I never oversell or disappoint customers."
Description

Develop an automated syncing engine that continuously monitors real-time inventory levels and adjusts bundle template availability accordingly. This requirement ensures that when an ingredient or menu item is low or sold out, affected templates are disabled or updated to prevent order errors. The engine should hook into the core inventory module, perform incremental updates, and provide API endpoints for status queries. It must handle high transaction volumes without latency spikes.

Acceptance Criteria
Disable Template When Ingredient Sold Out
Given inventory level for any ingredient in a bundle reaches zero, When the sync engine processes the update, Then deactivate the associated bundle template so it no longer appears in the menu or accepts orders.
Update Template Availability on Low Stock Threshold
Given inventory level for any ingredient in a bundle falls below the predefined low-stock threshold, When the sync engine processes the update, Then mark the associated bundle template as 'Low Stock' in the dashboard and trigger a user notification.
Incremental Template Update for Changed Inventory
Given only specific items have updated inventory levels since the last sync, When the sync engine runs, Then recalculate availability only for bundle templates containing those items and leave all other templates untouched.
Sync Engine Performance Under High Load
Given a sustained rate of 1000 inventory updates per minute, When the sync engine processes these updates, Then complete all updates within an average latency of 200 ms per request and a maximum total processing time of 2 seconds without errors.
API Endpoint Returns Sync Status
Given a client requests GET /api/v1/sync/status, When the sync engine responds, Then return HTTP 200 with a JSON body containing 'lastSyncedAt', 'templatesUpdated', and 'pendingQueue' fields reflecting the current engine state.
Upsell Rule Builder
"As a food truck owner, I want to set automated upsell rules for bundles so that I can increase average order value without manual intervention."
Description

Implement a rule builder tool enabling users to define upsell conditions and cross-sell suggestions within each bundle template. Users should be able to set rules based on order size, customer history, time of day, or inventory thresholds. The builder must support conditional logic (if–then), offer percentage or fixed-price discounts, and preview upsell scenarios. Rules should be stored in a centralized repository and evaluated in real time during order placement.

Acceptance Criteria
Upsell Rule Creation by Order Size
Given a user is defining a new upsell rule When they select an order size condition (e.g., order quantity >= 3) And they specify an upsell item with a percentage discount Then the rule is saved and visible in the rule builder list
Upsell Rule Editing with Conditional Logic
Given an existing upsell rule with simple logic When the user modifies the rule to include an additional condition (e.g., time of day = happy hour) Then the rule’s conditional logic updates accordingly and passes validation
Real-time Rule Evaluation During Checkout
Given a customer’s order meets multiple upsell conditions When the customer proceeds to checkout Then the system evaluates all applicable rules in under 200ms And displays the highest priority upsell suggestion
Upsell Scenario Preview Rendering
Given a user has configured a new bundle with upsell rules When they click the "Preview Scenario" button Then the UI shows sample order data with applied upsell suggestions and discount calculations
Rule Repository Persistence
Given any new or edited upsell rule When the user saves changes Then the rule is persisted to the centralized repository And is retrievable via API GET requests
Combo Deployment Workflow
"As an operations coordinator, I want a controlled deployment process for bundle templates so that I can manage promotions reliably without downtime."
Description

Create a streamlined workflow for activating, pausing, or retiring bundle templates on the live menu. This includes approval steps, scheduling capabilities, and version control. Users must be able to preview changes in a staging environment before deploying to production, roll back to previous versions with one click, and schedule future activations. The workflow should log actions for audit purposes and integrate with notification services to alert stakeholders of status changes.

Acceptance Criteria
Bundle Template Activation with Approval
Given the user has created a bundle template requiring approval When the user submits the template for activation Then the system routes the template to the designated approver and displays the template status as 'Pending Approval' Given the approver reviews and approves the template When the approver clicks 'Approve' Then the template status updates to 'Active' on the live menu and an activation timestamp is recorded
Scheduling Future Activation of Bundle Templates
Given a user configures a bundle template activation time in the future When the user clicks 'Schedule' Then the system validates the date and time format and displays the template status as 'Scheduled' with the correct activation timestamp When the scheduled time arrives Then the system automatically activates the template on the live menu and notifies the user of successful activation
Preview Changes in Staging Environment
Given a user has made updates to a bundle template When the user selects 'Preview in Staging' Then the system displays the updated template in a staging menu view and highlights changes compared to the current live menu Then the user approves the preview And the system confirms the template is ready for deployment
One-Click Rollback to Previous Version
Given a previously active bundle template version exists When the user clicks 'Rollback' on the desired version Then the system deactivates the current version and reactivates the selected previous version on the live menu Then the system logs the rollback action with user ID and timestamp
Audit Logging of Workflow Actions
Given any activation, scheduling, approval, or rollback event occurs When the event completes Then the system logs the action type, user ID, timestamp, and template version in the audit log Then authorized users can retrieve and filter audit logs by date, user, or action type
Stakeholder Notification on Status Change
Given a bundle template changes status to 'Pending Approval', 'Active', 'Scheduled', or 'Retired' When the status change occurs Then the system sends email and in-app notifications to configured stakeholders and includes the template name, new status, user who performed the action, and timestamp Then the user is able to verify notification delivery status in the notification history view
Template Performance Analytics
"As a food truck owner, I want to analyze how each bundle template performs so that I can optimize offerings and maximize sales."
Description

Introduce a dashboard module that tracks and reports on the performance of bundle templates, including metrics like units sold, revenue generated, conversion rate, and inventory impact. The analytics should offer filters by date range, location, and template type, and visualize trends through charts and tables. Integrate with the existing reporting engine, allow export to CSV, and provide alerts for underperforming templates or inventory anomalies.

Acceptance Criteria
Filter Templates by Date Range and Location
Given the analytics dashboard is displayed When the user applies a specific date range and selects one or more locations Then the templates list, charts, and tables update to show only data for the chosen range and locations, and all metric values (units sold, revenue, conversion rate, inventory impact) match the filtered dataset
Underperforming Template Alert Trigger
Given a template’s conversion rate or units sold falls below the configurable threshold during a monitoring cycle When the analytics engine processes the latest data refresh Then an alert appears on the dashboard, identifying the underperforming template, its current metric values, and a prompt recommending review
Inventory Impact Visualization
Given a user selects a specific bundle template from the list When they view the inventory impact section Then the dashboard displays the change in ingredient stock levels attributable to that template, highlights any ingredients where stock decreased below reorder points, and recalculates in real time as new sales data arrives
Trend Chart Interactive View
Given the trend visualization panel is in focus When the user hovers over or clicks a data point on the time-series chart Then a tooltip displays detailed metrics for that date (units sold, revenue, conversion rate), and the chart dynamically redraws when the user adjusts filters or date ranges
CSV Export with Applied Filters
Given the user has applied filters for date range, location, and template type When they click the 'Export to CSV' button Then the system generates and initiates download of a CSV file named with the selected range and filters, containing columns for template ID, name, units sold, revenue, conversion rate, and inventory impact, with no missing or extra rows

Cross-Sell Catalyst

Integrates with active orders to propose timely add-on combos or side deals based on customer selections, seamlessly increasing average order value.

Requirements

Real-Time Suggestion Engine
"As a food truck owner, I want the system to automatically suggest complementary items in real time so that I can increase average order value without manual intervention."
Description

Develop a back-end service that analyzes active orders, customer selections, and menu data to generate real-time recommendations for complementary items, combo offers, and side deals. The engine should use configurable rules and sales data to optimize suggestions, ensuring relevance and maximizing average order value. It must integrate seamlessly with the existing order processing pipeline, maintaining sub-second response times under peak load.

Acceptance Criteria
Real-Time Recommendation Trigger
Given an active order with one or more selected items, When the order is updated, Then the engine generates at least three complementary item suggestions within 300 milliseconds.
Configurable Rule Application
Given updated combo and side-deal rules in the admin configuration, When the recommendation engine processes the next active order, Then all generated suggestions strictly adhere to the newly configured rules.
Peak Load Performance
Under a simulated peak load of 1000 concurrent order requests, When the recommendation service is called, Then 95% of responses return within 500 milliseconds and no requests fail.
Seamless Order Pipeline Integration
Given the front-end order processing flow, When a user accepts a suggestion, Then the engine logs the suggestion acceptance event and updates the order payload to include the suggested item before final checkout.
Recommendation Accuracy Validation
Given a dataset of historical orders and expert-curated suggestions, When the engine generates recommendations for test orders, Then at least 85% of suggestions match the expert benchmark.
Combo Deal Configuration
"As a food truck owner, I want to configure custom combo deals and discount rules so that I can tailor cross-sell offers to my menu and sales strategy."
Description

Create an intuitive configuration interface that allows owners to define, edit, and manage cross-sell combos and side deals. This includes setting pricing tiers, discount rules, eligibility conditions (e.g., minimum cart value or specific item combinations), and scheduling active periods. The configuration tool must validate inputs and provide real-time previews of how deals will appear to staff and customers.

Acceptance Criteria
Creating a New Combo Deal
Given the owner opens the combo deal configuration interface and clicks 'New Combo Deal', When the owner fills in a valid deal name, pricing tier, discount rule, and clicks 'Save', Then the new combo deal appears in the deals list with all entered parameters correctly stored.
Editing an Existing Combo Deal
Given an existing combo deal in the list, When the owner selects it and updates any field (e.g., price, discount rule) and clicks 'Save', Then the system updates the deal and displays the new values in the deals list.
Setting Eligibility Conditions
Given the owner defines eligibility conditions with a minimum cart value and specific item combinations, When the owner inputs valid condition parameters and clicks 'Save', Then the system accepts the conditions without errors and applies them to the deal.
Scheduling Active Period for a Deal
Given the owner selects start and end dates/times for a combo deal, When the owner clicks 'Save', Then the system prevents overlapping with existing schedules, accepts valid periods, and shows an 'Active Period' badge matching the selected timeframe.
Real-Time Preview of Combo Deals
Given the owner modifies any field of a combo deal, When the change is made, Then the preview panel updates within 2 seconds to reflect the exact appearance and details customers will see.
Contextual UI Display
"As a cashier, I want to see visual prompts for add-ons during order entry so that I can quickly present deals to customers."
Description

Design and implement front-end components within the mobile and desktop dashboards that surface cross-sell suggestions at key stages of the order flow. Visual prompts, callouts, or modals should appear during item selection and checkout review, with clear calls to action and pricing information. The UI must be responsive, accessible, and consistent with the MenuZap design language.

Acceptance Criteria
Suggestion Display During Item Selection
Given a user selects an item on the menu, when the cross-sell component loads, then at least three relevant add-on combos appear adjacent to the selected item, each showing name, price, and an “Add to Order” button within 300ms of selection.
Prompt Appearance at Checkout Review
Given a user proceeds to the checkout review screen, when cross-sell callouts are triggered, then a visually distinct modal or banner appears above the order summary displaying two side-deal suggestions with clear pricing and an “Add Deal” action that updates the order total immediately upon selection.
Responsive Layout on Mobile and Desktop
Given a user views the dashboard on any device, when screen width changes, then the cross-sell UI elements reflow correctly without horizontal scroll, maintain legible text sizes, and keep call-to-action buttons fully visible at all standard breakpoints (320px–1920px).
Accessibility Compliance for Cross-Sell Elements
Given a user navigates via keyboard or screen reader, when interacting with cross-sell suggestions, then each suggestion receives focus in logical order, uses ARIA labels for names and prices, and provides visible focus indicators that meet WCAG 2.1 AA contrast and size requirements.
Design Consistency with MenuZap Language
Given the cross-sell UI is rendered, when compared to the MenuZap style guide, then all colors, typography, iconography, spacing, and button styles exactly match the documented design tokens and CSS classes specified in the guide.
Inventory and Availability Sync
"As a customer, I want to only see available side items in suggestions so that I don’t select items that are sold out."
Description

Ensure that the suggestion engine only recommends items that are in stock by integrating with the real-time inventory service. Automatically exclude sold-out items from cross-sell offers and update suggestions immediately when inventory levels change. The system should handle race conditions and concurrent updates robustly to prevent inaccurate recommendations.

Acceptance Criteria
Filtering Suggestions Based on Real-Time Stock
Given the inventory service reports item A has quantity > 0, When the suggestion engine processes an active order containing item B, Then item A appears in the cross-sell recommendation list.
Immediate Update of Suggestions After Inventory Depletion
Given an item is sold out during peak operation, When the inventory level changes to zero, Then the suggestion engine removes the item from any pending or upcoming cross-sell suggestions within 1 second.
Concurrent Order Handling for Accurate Suggestions
Given two customers place orders for the last unit of an item nearly simultaneously, When both requests are processed, Then only the first processed order's suggestions include the item and the second request's suggestions exclude it, preventing overcommitment.
System Behavior when Inventory Service is Unavailable
Given the inventory service experiences downtime or API failure, When the suggestion engine attempts to retrieve stock levels, Then recommendations are disabled or a fallback default set excluding previously known sold-out items is used and an alert is logged.
Bulk Inventory Change Reflects in Suggestions Instantly
Given the operator marks multiple items as sold out through bulk update, When the bulk update API completes, Then the suggestion engine updates all active suggestion lists to exclude those items within 2 seconds.
Cross-Sell Performance Analytics
"As a food truck owner, I want to review cross-sell performance metrics so that I can optimize my deals and increase revenue."
Description

Build an analytics module that tracks and reports on cross-sell suggestion metrics, including impression count, acceptance rate, incremental revenue, and average order uplift. Provide dashboards and exportable reports for owners to analyze performance over time, filter by product, time period, and location, and identify high-performing deals.

Acceptance Criteria
Accessing Cross-Sell Analytics Dashboard
Given a truck owner is logged into MenuZap When they navigate to the Cross-Sell Performance Analytics section Then they should see a dashboard displaying impression count, acceptance rate, incremental revenue, and average order uplift metrics for the selected time frame
Filtering Reports by Time Period
Given the owner is on the Cross-Sell Analytics Dashboard When they select a custom date range Then the dashboard metrics and visualizations update to reflect data only within that period
Filtering Reports by Product
Given the owner is viewing analytics When they choose a specific menu item from the product filter Then the dashboard displays cross-sell metrics only for that item across all orders
Filtering Reports by Location
Given a chain of food trucks uses MenuZap When the owner selects a location filter Then the dashboard reflects cross-sell performance metrics exclusively for the chosen location
Exporting Cross-Sell Reports
Given the owner has applied desired filters on the analytics dashboard When they click the export button Then the system generates a CSV or PDF report containing filtered cross-sell metrics and downloads it to their device

TrendPulse Feed

Automatically detects top-selling or newly popular items and generates eye-catching social media posts highlighting these trends, ensuring your audience always sees what’s hot and driving customers to your truck at peak demand times.

Requirements

Real-Time Sales Trend Detection
"As a food truck owner, I want the system to detect my top-selling and newly popular items automatically so that I can highlight the hottest items on social media and drive customer interest."
Description

Analyze live sales and popularity data to automatically identify top-selling and emerging menu items in real time, ensuring the system surfaces the most relevant trends for social media promotion without manual intervention.

Acceptance Criteria
Top-Seller Identification
Given real-time sales data streams, when an item’s sales count ranks within the top 5 over the last 10 minutes, then the system flags it as a top-selling item.
Emerging Item Alert
Given a new or less-known menu item, when its sales increase by more than 50% within any 15-minute window, then the system identifies it as an emerging trend.
Data Processing Latency
Given continuous order inputs, when the system processes incoming data, then trends are updated and available within 5 seconds of receipt.
Trend Consistency Validation
Given trend results generated by the algorithm, when comparing against known sales data for the same period, then at least 95% of identified top-sellers match the actual sales ranking.
Trend Update Frequency
Given the dashboard refresh schedule, when new sales data is ingested, then the trend feed refreshes automatically at least once every minute.
Automated Social Media Post Generation
"As a marketing manager, I want the system to create ready-to-publish social media posts for trending items so that I can quickly engage my audience with minimal effort."
Description

Leverage the detected trends to generate eye-catching social media posts using pre-approved templates, dynamic captions, and high-quality item images, streamlining the content creation process and maintaining brand consistency.

Acceptance Criteria
Peak-Selling Item Social Post Generation
Given an item’s sales velocity exceeds the trending threshold and no related post was generated in the last 24 hours, When the system detects the trend, Then it generates a social media post draft containing the item name, a high-quality image, and a dynamic caption including key sales metrics.
Newly Popular Item Highlight Post
Given a newly introduced menu item reaches the trending threshold within 48 hours of launch, When TrendPulse identifies its rapid popularity, Then the system creates a social media post emphasizing “new favorite” messaging and uses the approved launch template.
Brand-Compliant Template Usage
Given the library of pre-approved brand templates and assets, When the system generates a social post, Then it selects a template that matches brand colors, fonts, and logo placement and does not require manual edits.
Scheduled Post During Peak Engagement Window
Given predefined peak engagement windows (e.g., 11:00–14:00 daily), When a post is generated outside this window, Then it is queued and automatically published at the start of the next peak window without user intervention.
High-Quality Image Rendering in Post
Given source item images at or above 1080×1080 resolution, When the system processes the image for social media, Then it compresses to platform-specific requirements without visible quality loss and uploads successfully.
Post Customization Workflow
"As a food truck owner, I want to review and customize the automatically generated posts so that the final content matches my brand voice and seasonal promotions."
Description

Provide an intuitive interface where users can preview, edit, and approve the automatically generated posts—allowing for adjustments to copy, images, hashtags, and scheduling details before publishing.

Acceptance Criteria
Preview Generated Post
Given the system has generated a social media post draft, When the user selects 'Preview', Then the interface displays the post's copy, image, hashtags, and scheduled time in a read-only view matching the generated content.
Edit Post Copy
Given a post draft is in preview mode, When the user edits the copy field and confirms changes, Then the system updates the draft preview to reflect the new copy text.
Update Post Image
Given a post draft is in preview mode, When the user uploads or selects a different image and saves it, Then the new image replaces the original in the post preview and is stored with the draft.
Customize Hashtags
Given a post draft contains default hashtags, When the user adds, removes, or modifies hashtags and saves changes, Then the updated hashtag list is displayed in the preview and persisted in the draft.
Schedule Post Publishing
Given a finalized post draft, When the user sets a custom publish date and time and clicks 'Schedule', Then the system validates the date/time is in the future and displays a confirmation of the scheduled post.
Automated Scheduling & Publishing
"As a busy vendor, I want trending posts to be scheduled and published automatically at peak times so that I can maintain a consistent social presence even during rush hours."
Description

Integrate with major social media platforms (Instagram, Facebook, Twitter) to schedule and automatically publish approved posts at optimal engagement times, reducing manual posting workload.

Acceptance Criteria
Schedule Post for Optimal Engagement
Given an approved social media post and the user selects a future date and time, when the user confirms the schedule, then the system stores the post with the correct timestamp, content, and target platforms in the scheduling queue.
Automatic Publishing on Connected Platforms
Given a scheduled post exists and the associated social media accounts are connected and authorized, when the scheduled time is reached, then the system automatically publishes the post to all selected platforms and records a confirmation of successful publication.
Authentication Token Refresh Handling
Given a connected social media account has an expired or invalid authentication token, when the system attempts to schedule or publish a post, then it automatically refreshes the token via the OAuth flow and proceeds with the operation without requiring additional user input.
Retry Logic for Failed Publications
Given a scheduled post fails to publish due to a transient error (e.g., network timeout or API rate limit), when the initial publish attempt fails, then the system retries publishing up to three times with exponential backoff intervals and logs each attempt; if all retries fail, it marks the post as failed and notifies the user.
Publishing Activity Logging and Reporting
Given any publishing event (successful or failed), when the event completes, then the system logs event details including timestamp, platform, post ID, status, and error message if applicable, and makes the log available for user review in the dashboard.
Trend Performance Analytics Dashboard
"As a vendor, I want to view performance analytics of my trend-based posts so that I can understand what resonates with customers and optimize future promotions."
Description

Track and visualize engagement metrics (likes, shares, comments, click-throughs, conversions) for each automated post, enabling users to assess the impact of trend-based marketing and refine strategies over time.

Acceptance Criteria
Viewing Engagement Metrics for a Specific Post
Given the user is on the Trend Performance Analytics Dashboard and selects a specific automated post, When the metrics load, Then the dashboard displays likes, shares, comments, click-through rate, and conversions for that post with data accuracy within 1%.
Comparing Trend Performance Over Time
Given the user selects a custom date range in the Trend Performance Analytics Dashboard, When the system renders the comparison chart, Then daily values for likes, shares, comments, click-throughs, and conversions are plotted correctly, and trend lines for each metric are visible.
Exporting Trend Analytics Report
Given the user clicks the Export button on the Trend Performance Analytics Dashboard, When the user chooses PDF or CSV format, Then the system generates and downloads a file containing all displayed metrics for the selected posts in the chosen format within 10 seconds.
Filtering Analytics by Social Media Platform
Given multiple social media platforms are connected, When the user applies a filter for a specific platform on the dashboard, Then the analytics refresh to show only metrics for posts published on that platform.
Receiving Alerts on Performance Thresholds
Given the user has configured performance thresholds for click-through rate or engagement, When a post’s metric crosses the defined threshold within a 24-hour period, Then the system sends an in-app notification to the user with details of the metric and the post.

InstaStory Snapshot

Creates polished, story-ready snapshots of current menu highlights or sold-out items complete with dynamic stickers and countdowns, allowing you to effortlessly share on Instagram and Facebook Stories to boost real-time engagement.

Requirements

Automated Snapshot Generation
"As a food truck owner, I want MenuZap to automatically generate a polished snapshot of my live menu so that I can quickly share up-to-date offerings on social media without spending time on design."
Description

Implement functionality that automatically composes a high-resolution image of the current menu state, including highlighted items, sold-out labels, dynamic stickers, and promotional overlays. This should integrate seamlessly with the MenuZap dashboard, generating consistent, branded visuals ready for social sharing without manual design work.

Acceptance Criteria
Routine Snapshot Generation
Given the MenuZap dashboard is active and synced When the scheduled snapshot time arrives Then a high-resolution image of the current menu state is automatically generated and available within 5 seconds
Sold-Out Item Highlight
Given items are marked as sold out in the dashboard When the snapshot is generated Then those items display a 'Sold Out' label with correct styling and position
Promotional Overlay Inclusion
Given there is an active promotional campaign configured When the snapshot is created Then the promotional overlay graphic appears at the designated area with correct branding colors and text
Dynamic Sticker & Countdown
Given dynamic stickers and countdown timers are enabled for a menu item When the snapshot is generated Then the snapshot image includes the sticker and an accurate countdown displaying time remaining
High-Resolution Export
Given a snapshot is generated When the user downloads or shares it Then the image resolution is at least 1080x1920 pixels and file size does not exceed 2 MB
Social Media Story Integration
"As a food truck owner, I want to share my menu snapshot directly from MenuZap to my Instagram and Facebook Stories so that I can engage followers without switching between apps."
Description

Develop integration with Instagram and Facebook APIs to allow users to send generated snapshots directly to their Stories feed. This requires OAuth-based authentication, handling token storage/refresh, and ensuring compliance with rate limits and platform guidelines.

Acceptance Criteria
User Authenticates with Instagram
Given a logged-in MenuZap user, when they initiate Instagram integration and submit valid OAuth credentials, then the system must securely store the access token and display a confirmation message.
Share Snapshot to Instagram Story
Given a valid stored Instagram token, when the user selects “Share to Instagram Story” for a generated snapshot, then the system must post the image to the user’s Instagram Story and return a success response within 5 seconds.
Automatic Token Refresh Flow
Given an expired Instagram access token, when the user attempts to share a snapshot, then the system must automatically use the refresh token to obtain a new access token and complete the share without additional user input.
Rate Limit Handling for Sharing
Given API rate limits are reached, when additional share requests are made, then the system must queue requests, retry after the rate limit reset period, and notify the user of any delays.
Platform Compliance Validation
Given a snapshot ready for sharing, when preparing the media payload, then the system must validate format, dimensions, and metadata against Instagram and Facebook requirements and reject non-compliant media with an error message.
Dynamic Sticker Library
"As a food truck owner, I want to add dynamic stickers to my snapshots so that I can draw attention to special items or sold-out status in a visually engaging way."
Description

Build a library of customizable, animated stickers and icons (e.g., 'Sold Out', 'Special Offer', emojis) that can be overlaid on snapshots. Stickers should support varying sizes, colors, and positioning, and be easily updated or expanded via a content management interface.

Acceptance Criteria
Sticker Selection for Sold-Out Item Snapshot
Given a menu item marked as sold out, when a user creates an InstaStory snapshot, then the 'Sold Out' sticker is listed in the library and can be applied to the snapshot without distortion.
Customizing Sticker Size and Color
Given a user selects a sticker, when they adjust size and color parameters, then the live preview updates in real time and the exported snapshot retains the exact size and color settings.
Positioning Stickers on Snapshot
Given a snapshot loaded in the editor, when a user drags and drops a sticker, then it moves smoothly, snaps to grid lines if enabled, and cannot be positioned outside the snapshot boundaries.
Adding New Stickers via CMS
Given an admin uploads a new animated sticker and metadata in the content management interface, when they save and publish, then the sticker appears in the user-facing library within five minutes without a system redeploy.
Previewing Animated Stickers
Given a user selects an animated sticker in the editor, when they click preview, then the animation plays at the correct frame rate and loops as configured until the user closes the preview.
Template and Layout Customization
"As a food truck owner, I want to choose from different snapshot templates so that my social media posts reflect my brand style and stand out to customers."
Description

Provide a set of pre-designed templates and layout options for snapshots (including background styles, font choices, and placement grids). Users should be able to preview and select their preferred template, with configurations saved per truck profile.

Acceptance Criteria
Selecting a Default Snapshot Template
Given a food truck owner navigates to the snapshot template settings, When they preview and select a template layout, Then the chosen template is applied to the profile and persists across sessions for that truck.
Previewing Template Variations
Given a user is on the layout customization screen, When they switch between different background styles, font choices, and placement grids, Then the preview pane updates in real time to reflect each change accurately.
Saving Custom Font and Color Settings
Given a user selects custom fonts and color schemes within a template, When they save their configuration, Then the custom font and color settings are stored in the truck profile and automatically loaded on subsequent visits.
Handling Sold-Out Item Tagging in Snapshot
Given an item is marked sold out in the inventory dashboard, When the user generates an InstaStory snapshot, Then the snapshot template automatically displays a sold-out sticker overlay on the corresponding item.
Exporting Customized Snapshot to Instagram Stories
Given a user has finalized their template and layout selections, When they choose the 'Share to Instagram Stories' option, Then the system exports a correctly sized image file and launches the Instagram Stories upload interface with the snapshot preloaded.
Live Countdown Overlay
"As a food truck owner, I want to include a live countdown in my snapshots so that I can build excitement for upcoming promotions or service end times."
Description

Enable users to add live countdown timers to snapshots for upcoming events or limited-time offers. The countdown should update in real time, display days/hours/minutes, and automatically expire or change styling when the timer ends.

Acceptance Criteria
Setting Up a Countdown for a Happy Hour Special
Given the user selects a future Happy Hour start and end time, When they enable the live countdown overlay on a snapshot, Then the overlay displays an accurate countdown in days, hours, and minutes and updates every second until the offer begins.
Expired Countdown Style Change
Given the countdown timer reaches zero, When the timer expires, Then the countdown overlay automatically changes styling to a predefined “expired” format (e.g., grayed out with “Offer Ended” text) and stops decrementing.
Multi-Unit Time Display Verification
Given a countdown with more than 24 hours remaining, When the overlay is displayed, Then it clearly shows days, hours, and minutes, and when less than 24 hours remain, Then it dynamically switches to showing only hours, minutes, and seconds.
Real-Time Countdown Accuracy During Snapshots
Given the user captures multiple snapshots over a 10-minute period, When each snapshot is generated, Then the countdown overlay reflects the exact remaining time at the moment of capture within a ±1 second accuracy.
Countdown Auto-Disable on Snapshot Expiry
Given the countdown has expired before the user takes a new snapshot, When the user attempts to capture a snapshot after expiration, Then the countdown overlay option is disabled and a prompt informs the user that the timer has ended.

GeoTag Booster

Automatically includes precise location tags and local event hashtags in each post, expanding your social reach to nearby potential customers and increasing foot traffic by making your truck easy to find on social platforms.

Requirements

Real-Time Geolocation Tagging
"As a food truck owner, I want my social media posts to include precise location tags so that customers can find my truck quickly and reliably."
Description

Automatically fetches the food truck’s current GPS coordinates with high accuracy (within 10 meters) at the moment each social post is created, and embeds them as standardized geotags to ensure customers can locate the truck easily via mapping services and social platforms.

Acceptance Criteria
Auto-Fetch GPS Coordinates on New Post
Given the user opens the social post composer When the page loads Then the system automatically fetches and populates the current GPS coordinates accurate within 10 meters
Validate Geotag Accuracy
When the system retrieves GPS data Then the coordinates must be within a 10-meter radius of a known reference point in at least 95% of validation tests
Embed Geotag into Post Metadata
Given valid GPS coordinates are fetched When the user submits the post Then the coordinates are embedded as standardized geotag fields in the post metadata
Handle Geolocation Service Failure
When GPS retrieval fails or exceeds a 5-second timeout Then the user is shown an error message with options to retry or manually input location
Update Geotag on Post Edit
Given a published post exists When the user edits the post within 10 minutes of publication Then the system fetches new GPS coordinates and updates the embedded geotag
Local Event Hashtag Integration
"As a food truck owner, I want my posts to include local event hashtags so that people attending nearby events see my offerings and head to my truck."
Description

Scans public event listings and local venue schedules within a configurable radius (e.g., 5 miles) to identify ongoing or upcoming events, then automatically suggests and appends relevant event-specific hashtags to each post to increase visibility among event attendees.

Acceptance Criteria
Identifying Local Events Within Configurable Radius
Given a user-defined radius setting, when the system scans public event listings, then only events located within the specified radius are retrieved.
Suggesting Relevant Event Hashtags in New Posts
Given retrieved local events, when a user initiates a new social media post, then the system suggests at least three event-specific hashtags relevant to those events.
Automatically Appending Suggested Hashtags to Social Media Posts
Given suggested hashtags are displayed, when the user publishes the post, then the selected hashtags are automatically appended to the post content without additional manual entry.
Handling Overlapping Events and Popularity Ranking
Given multiple events occur in the same area, when generating hashtag suggestions, then the system ranks and presents hashtags by event popularity and proximity to the food truck location.
Updating Hashtag Suggestions Upon Radius or Event List Change
Given changes to the user’s radius setting or updates in public event listings, when the system rescan is triggered, then hashtag suggestions are updated within five seconds to reflect the latest relevant events.
Relevant Hashtag Filtering
"As a food truck owner, I want only relevant and high-engagement hashtags in my posts so that my social media presence remains professional and effective."
Description

Applies contextual analysis and blacklist/whitelist controls to ensure only relevant and popular local hashtags are included, removing duplicates and filtering out irrelevant or low-engagement tags to maintain brand credibility and avoid spam detection.

Acceptance Criteria
Popular Local Event Hashtag Inclusion
Given a scheduled post with a specified location, when generating hashtags, then the top 5 local event hashtags (ranked by engagement in the last 24 hours) are included in the tags list.
Duplicate Hashtag Removal
Given a candidate list of hashtags containing duplicate entries, when filtering, then each hashtag appears only once in the final output.
Irrelevant Hashtag Exclusion
Given a candidate list of hashtags with varying engagement scores, when filtering, then hashtags with engagement below 1% of the location’s average are excluded from the final set.
Custom Whitelist Prioritization
Given a user-defined whitelist of preferred hashtags, when generating tags, then all whitelisted hashtags are included first in the final list in the order specified by the user.
Blacklist Enforcement
Given a user-defined blacklist of unwanted hashtags, when filtering, then none of the blacklisted hashtags are present in the final output.
Social Media API Connector
"As a food truck owner, I want MenuZap to automatically publish my social media posts with geotags and hashtags so I don’t have to switch between apps or manually post."
Description

Integrates with major social media platforms’ APIs (e.g., Instagram, Facebook, Twitter) to programmatically publish posts with embedded geotags and hashtags in compliance with each platform’s rate limits and content policies, ensuring seamless cross-platform posting.

Acceptance Criteria
Instagram Post with Geotag and Hashtag Compliance
Given valid post content and location data, When the user triggers a social media post to Instagram, Then the post is published within 2 seconds, contains the exact latitude and longitude in the metadata, includes specified hashtags in the caption, and returns a 200 OK response.
Facebook Post Rate Limit Handling
Given the API has reached its rate limit, When the user attempts to publish a new post, Then the system queues the request, waits the required cooldown period per Facebook's rate limit headers, retries automatically, and logs the retry with timestamps.
Twitter Post Character and Hashtag Integration
Given a post caption exceeding 280 characters including hashtags, When the user sends the post request to Twitter, Then the system truncates the text to 280 characters without splitting hashtags, and returns confirmation that the post was published with the adjusted content.
Error Handling for API Failures
Given an API failure such as a network timeout or 5xx error, When attempting to post, Then the system retries the request up to two times, and if still unsuccessful, logs the error, notifies the user with a descriptive message, and marks the post as failed in the dashboard.
Cross-Platform Post Consistency
Given a single post request, When the user publishes to all connected platforms, Then the system sends platform-specific API calls, verifies each returns a 200 OK response, and displays a consolidated success report indicating the status for Instagram, Facebook, and Twitter.
Manual Tag Override UI
"As a food truck owner, I want to review and modify suggested tags before posting so that I maintain full control over my social media content."
Description

Provides a user-friendly interface within the MenuZap dashboard that displays suggested geotags and hashtags for review, allowing users to approve, edit, remove, or add custom tags before finalizing and publishing each post.

Acceptance Criteria
Review Suggested Tags Before Publishing
Given the user is on the Manual Tag Override UI with suggested geotags and hashtags displayed, When the user selects one or more suggested tags and clicks 'Publish', Then only the selected tags are attached to the social media post.
Edit Auto-Generated Geotag
Given a suggested geotag is displayed, When the user clicks the 'Edit' icon next to the geotag, modifies the location text, and confirms the change, Then the updated geotag is displayed in the tag list and persists when saving.
Remove Unwanted Hashtag
Given the list of suggested hashtags includes unwanted entries, When the user clicks the 'Remove' (X) button next to a hashtag, Then that hashtag is immediately removed from the list and will not appear in the final published post.
Add Custom Hashtag Manually
Given the tag editor input is available, When the user enters a new custom hashtag, clicks 'Add', and the input matches hashtag format (alphanumeric, underscores), Then the custom hashtag appears in the list of tags and can be edited or removed.
Real-Time Preview of Adjusted Tags
Given the tag list is being edited, When the user adds, edits, or removes any tag, Then the preview panel updates in real time to reflect the current set of tags before publishing.
Location Sharing Permissions Management
"As a food truck owner, I want to control when my location is shared to maintain privacy compliance and customer trust."
Description

Implements permission settings and consent workflows that allow users to control when and how location data is accessed and shared, including options for session-based or always-on geotagging, ensuring compliance with privacy regulations and user preferences.

Acceptance Criteria
Session-Based Geotagging Consent
Given the user opts in to session-based geotagging, When the user confirms consent, Then the application collects location data only during the active session and ceases collection immediately upon logout or session end.
Always-On Geotagging Permission
Given the user opts for always-on geotagging, When the system displays the OS-level permission prompt and the user grants permission, Then the application continuously collects location in background and foreground until the user revokes permission.
Revoking Location Permissions
Given the user navigates to the Location Settings screen, When the user toggles off geotagging, Then the application stops all location data collection immediately and ensures no further location tags are added to posts.
Permission Denial Handling
Given the user denies the location permission request, When the denial is processed, Then the application disables geotagging features, displays an informative message explaining the impact, and provides a link to re-enable permissions.
Privacy Compliance Logging
Given any change to location consent (grant, deny, revoke), When the change occurs, Then the system logs the action with user ID, timestamp, and consent type in the audit log in compliance with privacy regulations.
GeoTag Booster Activation With Permission
Given the user has granted session-based or always-on location permission, When creating a social post, Then the GeoTag Booster automatically appends the precise location tag and relevant local event hashtags to the post.

HashtagHero

Suggests optimized, trending hashtags based on menu items, location, and time of day to maximize post visibility and engagement without manual research, helping you attract a broader, hungry audience.

Requirements

Hashtag Suggestion Engine
"As a food truck owner, I want the app to suggest a ranked list of high-performing hashtags for my menu items so that I can increase my social media reach and attract more customers without manual research."
Description

The system must generate optimized and trending hashtags based on menu items, current location, and time of day. It will leverage API integration with social media trend services to fetch real-time hashtag popularity metrics, analyze menu item keywords, and return a ranked list of relevant hashtags for the user. This requirement ensures that food truck owners can quickly select high-performing hashtags without manual research, boosting their post visibility and customer engagement directly from the MenuZap dashboard.

Acceptance Criteria
Generating Hashtags for a New Menu Item at Lunch Rush
Given the user requests hashtag suggestions for a newly added menu item at 12:00 PM local time When the system fetches real-time hashtag popularity metrics from the integrated social media API Then the system returns at least 5 relevant hashtags ranked by popularity within 2 seconds
Updating Hashtags Based on Changing Location Event
Given the user’s device GPS reports a location change When the system detects the updated coordinates Then within 5 seconds the system retrieves and displays at least 5 new hashtag suggestions relevant to the new location
Real-time Hashtag Update During Event Peak Hours
Given the current time is between 18:00 and 20:00 When the user views the hashtag suggestion list Then the system automatically prioritizes and displays up to 10 time-sensitive trending hashtags with their popularity scores
Handling No Trend Data Available
Given the external trend API returns an error or empty result When the user requests hashtag suggestions Then the system displays a predefined fallback list of popular food-related hashtags And logs the error details for diagnostic review
User Selects Hashtag Suggestions and Posts
Given the user selects one or more suggested hashtags When the user publishes their post through the MenuZap dashboard Then the system pre-populates the post caption with the selected hashtags And confirms the published post contains all chosen hashtags
Real-time Trend Analysis
"As a social media manager, I want the system to update hashtag popularity in real time so that I can ensure my posts always use the latest trending tags and drive more engagement."
Description

The feature must continuously monitor and update hashtag popularity metrics in real time, reflecting the most current trends and viral topics. It will poll social media APIs at configurable intervals, process incoming trend data, and feed updates into the Hashtag Suggestion Engine. By providing up-to-the-minute insights, this requirement helps users tap into trending conversations and optimize their posts at the moment, maximizing engagement potential.

Acceptance Criteria
Continuous Hashtag Popularity Refresh During Active Session
Given a user has enabled Real-time Trend Analysis and API keys are properly configured, When the system polls social media APIs at the default interval, Then the dashboard must reflect updated hashtag popularity metrics within 5 seconds of receiving new data.
Configurable Polling Interval Adjustment
Given a user sets a custom polling interval in the settings, When the change is saved, Then the system must adjust its polling schedule to the new interval and display the next scheduled poll time in the UI.
Location-based Trend Data Filtering
Given a user’s truck location is active, When trend data is fetched, Then only hashtags trending within a 10-mile radius of the truck’s GPS coordinates must be shown in the suggestion list.
Peak Hour Trend Surge Handling
Given the system detects incoming trend data exceeding predefined volume thresholds during peak hours, When data volume surpasses the limit, Then the system must queue and process all incoming data within the SLA without dropping any entries.
API Failure and Retry Mechanism
Given the social media API returns an error or times out, When the system encounters this failure, Then it must retry the request up to three times with exponential backoff, log each failure, and notify the user in the dashboard if all retries fail.
Location-based Optimization
"As a food truck operator, I want hashtags tailored to my current location so that my posts reach local customers more effectively and increase foot traffic to my truck."
Description

The capability must filter and prioritize hashtags based on the food truck’s current geographic location, incorporating local trends and region-specific popular tags. Using GPS or manually set locations, the module will fetch localized trend data to tailor hashtags that resonate with the local audience. This requirement enhances relevance and ensures that posts target nearby customers, driving foot traffic and immediate interest.

Acceptance Criteria
Real-Time GPS-Based Hashtag Generation
Given the food truck’s GPS is enabled and within the supported service area, When the user taps “Generate Hashtags”, Then the system retrieves and displays at least 10 unique, location-relevant hashtags sorted by descending popularity within 2 seconds.
Manual Location Override for Hashtag Suggestions
Given the user manually sets a different location via address or coordinates, When the user requests hashtags, Then the system fetches and displays at least 10 trending hashtags specific to the overridden location and persists this setting until changed.
Edge Case: Unsupported or Out-of-Coverage Area
Given the GPS or manually set location falls outside supported regions with no local trend data, When the user requests hashtags, Then the system displays a notification “Local trend data unavailable” and provides at least 5 default category hashtags.
High Traffic Event Location Integration
Given the food truck is detected at a high-traffic event location code, When generating hashtags, Then the system merges event-specific trending tags (minimum 5) with local tags and displays a combined list of at least 10 hashtags.
API Failure Fallback to Default Tags
Given the external trend data API call fails or returns an error, When the user requests hashtags, Then the system logs the error, shows a message “Unable to load local trends, displaying default hashtags,” and presents at least 10 generic default hashtags.
Time-based Relevance Filtering
"As a food truck owner, I want hashtag recommendations that consider time of day so that my posts align with peak engagement periods and reach more potential customers."
Description

The feature must adjust hashtag suggestions by time of day and day of week, taking into account peak social media usage periods and time-specific trends (e.g., #LunchSpecial at noon, #FridayFeeling on Fridays). This requires scheduling logic and trend correlation analysis to boost hashtag relevance during ideal posting windows. By recommending time-sensitive hashtags, the system helps users schedule posts when their audience is most active.

Acceptance Criteria
Peak Lunch Hour Hashtag Adjustment
Given the current time is between 11:00 and 14:00 on a weekday, When the user requests hashtag suggestions for a lunch menu item, Then at least two suggestions include #LunchSpecial or other high-engagement lunch hashtags trending locally.
Friday Feeling Promotion
Given the current time is between 17:00 and 20:00 on a Friday, When the user requests hashtag suggestions, Then the top three suggestions include #FridayFeeling or #TGIF and have engagement metrics above the configured threshold for the user’s location.
Weekend Brunch Boost
Given the current time is between 10:00 and 13:00 on a Saturday or Sunday, When the user seeks hashtags for brunch menu items, Then the system recommends at least one #Brunch or #WeekendBrunch hashtag that is in the top 10 trending locally.
Midweek Afternoon Engagement Surge
Given the current time is between 15:00 and 17:00 on a Wednesday, When the user fetches hashtag suggestions, Then the top three hashtags align with midweek snack engagement peaks and exclude hashtags outside peak engagement windows.
Early Morning Breakfast Rush
Given the current time is between 06:00 and 09:00 on any weekday, When the user requests hashtag suggestions for breakfast or coffee items, Then suggestions include #BreakfastTime or #CoffeeLovers trending locally, ordered by descending engagement rate.
In-App Post Composition Integration
"As a food truck owner, I want to insert recommended hashtags directly into my post drafts within the app so that I can streamline my social media workflow and avoid copying tags manually."
Description

The requirement must allow users to incorporate selected hashtags directly into posts within the MenuZap dashboard, offering an in-app editor that seamlessly inserts recommended hashtags into captions. The editor should support one-click insertion and allow manual adjustments. This integration streamlines the posting workflow, eliminating context switching between platforms and reducing posting errors.

Acceptance Criteria
Post Composition Editor Access
Given a logged-in user on the MenuZap dashboard When the user navigates to the social media post section Then the in-app post composition editor is displayed with an input field for the caption and a panel for suggested hashtags
Hashtag Suggestion Display
Given the user has typed or selected a menu item and location When the post composition editor loads suggestions Then the system displays at least ten trending, optimized hashtags relevant to the menu item, location, and time of day
One-Click Hashtag Insertion
Given suggested hashtags are visible in the editor panel When the user clicks the “Insert All” button Then all suggested hashtags are appended to the caption at the current cursor position in a single action
Manual Hashtag Adjustment
Given hashtags have been inserted into the caption When the user manually edits, removes, or adds hashtags in the caption field Then the editor saves and displays the updated hashtag list accurately without errors or duplication
Character Limit Enforcement
Given the combined length of the caption and hashtags exceeds the platform’s character limit When the user attempts to insert or add more hashtags Then the editor warns the user and prevents insertion beyond the limit, highlighting the overflow text

PromoScheduler

Allows you to plan and queue SocialSplash posts in advance for special offers, limited-time menus, or sold-out alerts, ensuring consistent social media presence even during the busiest service hours.

Requirements

Multi-Platform Integration
"As a food truck owner, I want to integrate my SocialSplash accounts for multiple platforms so that I can schedule and post promotions to all my social channels without manual intervention."
Description

Enable users to connect and authenticate their SocialSplash accounts on Facebook, Instagram, Twitter, and other social media platforms through OAuth, allowing PromoScheduler to automatically post scheduled promotions across multiple channels. This integration should handle token refresh, error handling, and display connection status within the dashboard.

Acceptance Criteria
Connecting SocialSplash Facebook Account
Given a logged-in user on the PromoScheduler dashboard, When they initiate the Facebook OAuth flow, Then they are redirected to Facebook for authentication, and upon successful login and consent, the dashboard displays “Connected” next to Facebook.
Token Refresh Handling
Given a connected account with an expired access token, When the scheduler attempts to post a promotion, Then the system automatically uses the refresh token to obtain a new access token and retries the post without user intervention.
Error Handling During Authentication
Given a user cancels or fails the OAuth process, When authentication fails for any social platform, Then the dashboard shows an error message “Connection failed: [error details]” and leaves the connection status unchanged.
Multi-Platform Scheduling Execution
Given the user has scheduled a promotion for multiple connected platforms, When the scheduled time arrives, Then PromoScheduler posts the promotion to each platform within one minute and logs a success entry for each.
Display Connection Status in Dashboard
Given the user views the Social Accounts section, When accounts are connected or disconnected or tokens are refreshed, Then each platform entry shows its current status (“Connected” or “Disconnected”) along with the last sync timestamp.
Calendar Scheduling Interface
"As a manager, I want a calendar view to schedule and modify my promotional posts so that I can easily plan content around my service hours."
Description

Provide a visual calendar interface that allows users to create, view, and adjust scheduled posts by selecting dates and times. Users should be able to drag and drop scheduled items to reschedule, view daily/weekly/monthly layouts, and access details of each post directly from the calendar.

Acceptance Criteria
Creating a New Scheduled Post
Given the user selects a date and time on the calendar and enters all required post details, when they click 'Save', then the post appears at the correct slot with the correct title and content.
Rescheduling via Drag-and-Drop
Given there is an existing scheduled post on the calendar, when the user drags it to a different date or time, then the post’s scheduled timestamp updates accordingly and the calendar reflects its new position.
Switching Calendar View Modes
Given the user is on the calendar interface, when they select the daily, weekly, or monthly view toggle, then the calendar updates to show the corresponding range and includes all scheduled posts within that period.
Accessing Scheduled Post Details
Given a post is displayed on the calendar, when the user clicks on it, then a detail pane opens displaying all editable fields including title, content, image preview, and scheduled time.
Conflict Detection for Overlapping Posts
Given two posts are scheduled for overlapping times, when the user attempts to save the second post, then the system displays a warning about the time conflict and prevents saving until the user resolves the overlap.
Template Library
"As a busy owner, I want to use saved templates for promotions so that I can quickly generate consistent social media posts during peak hours."
Description

Offer a library of customizable post templates with placeholders for item names, prices, images, and hashtags. Users should be able to create, save, edit, and clone templates for repeated promotions, ensuring brand consistency and reducing content creation time.

Acceptance Criteria
Creating a New Post Template
Given a user is on the PromoScheduler Template Library, When they click New Template, fill in name, placeholders for item names, prices, images, and hashtags, and click Save, Then the new template is stored and displayed in the library with correct details.
Editing an Existing Template
Given a user selects an existing template from the library, When they modify placeholders or content and click Save Changes, Then the template is updated and the changes are reflected immediately in the template list.
Cloning a Template for Reuse
Given a user views a template in the library, When they click Clone and provide a new template name, Then a duplicate template is created with identical placeholders and appears in the library under the new name.
Deleting a Template
Given a user selects the delete action on a template and confirms the deletion prompt, When they confirm, Then the template is removed from the library and no longer available for future promotions.
Template Placeholders Validation
Given a user attempts to save a template with missing mandatory placeholders, When they click Save, Then the system displays validation errors and prevents saving until all required placeholders are filled.
Automated Sold-Out Alerts
"As a vendor, I want sold-out alerts posted automatically so that my customers know what items are unavailable and avoid arriving only to find their favorite dish sold out."
Description

Automatically detect menu items marked as sold out in real time and queue a predefined alert post to notify customers on social media. The system should pull item details and availability, generate a templated message, and schedule it for the next possible posting slot.

Acceptance Criteria
Detection of Sold-Out Items in Real Time
Given a menu item is marked as sold out in the inventory dashboard, when the system syncs inventory status, then an alert event is triggered within 30 seconds.
Generation of Templated Alert Message
Given a sold-out event is detected, when the alert generator runs, then a social post is created using the predefined template including item name, sold-out status, and brand hashtag.
Scheduling of Alert Post in Next Available Slot
Given a templated alert message is generated, when queuing the post, then it is scheduled in the next available social media slot that respects minimum interval and peak engagement windows.
Integration with SocialSplash API for Posting
Given a scheduled alert post exists, when the posting time arrives, then the system successfully sends the post to SocialSplash API and receives a 200 OK response with a post ID.
Fallback Handling When No Posting Slot Available
Given no available posting slots in the next 24 hours, when attempting to schedule the alert, then the system flags the alert for manual review and notifies the operator via in-app notification.
Performance Analytics
"As a marketing lead, I want analytics on my promo posts so that I can understand which promotions drive the most engagement and optimize future campaigns."
Description

Provide analytics for scheduled posts, including metrics such as impressions, engagement rate, clicks, and conversions. Users should see visual charts and reports filtered by date range, platform, and post type to evaluate the effectiveness of their social promotions.

Acceptance Criteria
View Analytics Dashboard
Given a logged-in user has scheduled posts When the user navigates to the Performance Analytics page Then the dashboard displays charts for impressions, engagement rate, clicks, and conversions
Filter Analytics by Date Range
Given analytics data exists for multiple dates When the user selects a custom start and end date and applies the filter Then the charts and reports update to show metrics only within the selected date range
Filter Analytics by Platform
Given the user has scheduled posts across Facebook and Instagram When the user filters analytics by platform 'Facebook' Then only metrics for Facebook posts are displayed in the charts and reports
Export Analytics Report
Given filtered analytics data is displayed When the user clicks the 'Export Report' button and selects CSV format Then a CSV file downloads containing headers and rows for impressions, engagement rate, clicks, and conversions
Compare Performance Between Post Types
Given a user has scheduled both promotional and informational posts When the user groups analytics by post type Then the visual report displays side-by-side comparisons of metrics for each post type

Engagement Insights

Provides analytics on each SocialSplash post’s performance—likes, shares, clicks, and new followers—and offers actionable recommendations to refine future content and grow your audience over time.

Requirements

Real-time Engagement Dashboard
"As a food truck social media manager, I want to view real-time engagement metrics for each menu post so that I can quickly adjust my marketing strategies to boost customer interaction and sales."
Description

A live dashboard integrated into the MenuZap mobile and web interface that displays key engagement metrics—likes, shares, clicks, and new followers—for each post in real time. By consolidating performance data in a single view, users can quickly assess the success of social media promotions, adjust content strategies on the fly, and ensure marketing efforts align with customer interests, reducing wasted posts and driving higher engagement during peak business hours.

Acceptance Criteria
View Live Post Engagement Metrics on Mobile
Given a user opens the real-time engagement dashboard on a mobile device When a new interaction (like, share, click, or follow) occurs Then the corresponding metric count is displayed and updated every 5 seconds without requiring a manual refresh
Real-time Updating of Engagement Counts
Given the engagement dashboard is active When any metric for any post changes Then the updated value appears within 2 seconds and the metric cell briefly highlights to indicate the change
Filtering Posts by Engagement Metric
Given multiple posts are listed on the dashboard When the user selects a filter criterion (e.g., highest likes) Then the dashboard reorders posts correctly based on the selected metric within 3 seconds
Timestamp Accuracy for Engagement Data
Given that engagement metrics are displayed When metrics update Then each metric shows a timestamp reflecting the exact update time in the user’s local timezone
Handling Network Disruptions During Data Fetch
Given the user’s device loses internet connectivity While the dashboard attempts to fetch live metrics Then the dashboard displays a non-blocking offline indicator and automatically retries data fetch every 10 seconds until connectivity is restored
Multi-Platform Connectivity
"As a food truck owner, I want to connect all my social media accounts to MenuZap so that I can see unified engagement data without switching between platforms."
Description

Seamless integration with major social media platforms (Instagram, Facebook, Twitter, TikTok) via secure APIs, allowing MenuZap to automatically fetch and update engagement metrics for all posts published through the system. This connectivity ensures comprehensive data aggregation, eliminates manual data entry, and provides a unified view of performance across channels, saving time and reducing errors.

Acceptance Criteria
Real-time Data Fetch Initialization
Given a new social media post is published through MenuZap When the system initiates a sync Then engagement metrics for that post are fetched within 30 seconds and displayed in the dashboard without errors
Error Handling for API Failures
Given an API call to a social platform returns a failure or rate limit error When MenuZap retries the request Then it performs up to three retries with exponential backoff and logs errors with user-friendly messages if all retries fail
Data Aggregation Across Platforms
Given the user has published posts on Instagram, Facebook, Twitter, and TikTok When the engagement dashboard loads Then metrics from all connected platforms are aggregated and accurate totals for likes, shares, clicks, and new followers are displayed
Secure Authentication to Social Media APIs
Given the user connects a social media account When MenuZap completes the OAuth flow Then the system securely stores the access token using encryption and does not expose credentials in logs or UI
Data Refresh on Demand
Given the user clicks the “Refresh Metrics” button When the system regains network connectivity Then the latest engagement metrics are fetched for all posts and the dashboard displays the updated timestamp
Actionable Recommendation Engine
"As a marketing specialist, I want tailored suggestions for improving post performance so that I can optimize content strategy and increase audience reach."
Description

An intelligent recommendation engine within MenuZap that analyzes historical and real-time engagement data using machine learning models and preset business rules to suggest optimal posting times, content formats, hashtag strategies, and audience targeting. Recommendations are tailored to individual user profiles, helping food truck owners refine content strategy, increase reach, and boost customer interaction based on proven insights.

Acceptance Criteria
Optimal Posting Time Suggestion
Given a food truck owner with at least two weeks of historical post data, when the owner accesses the recommendation engine before scheduling a new post, then the system shall provide three optimal posting time slots that have generated the highest average engagement rate in the past two weeks.
Hashtag Strategy Recommendation
Given a selected menu item and past engagement performance, when the owner drafts a new SocialSplash post, then the engine shall recommend at least five contextually relevant hashtags ranked by predicted engagement uplift.
Content Format Optimization
Given analysis of previous post formats (image, video, text), when preparing a new post, then the system shall suggest the top two content formats that historically achieved the highest click-through rates for similar menu items.
Audience Targeting Accuracy
Given segmentation data and engagement history, when the owner selects target demographics, then the engine shall identify and recommend the demographic group with the highest projected engagement increase of at least 10%.
Recommendation Delivery Performance
Given user request for recommendations, when the recommendation engine processes data, then the engine shall deliver recommendations within two seconds and with 95% system uptime.
Customizable Reporting Interface
"As a food truck owner, I want to generate and share weekly engagement reports so that I can keep my team informed and make data-driven decisions."
Description

A flexible reporting module that enables users to create and schedule customized engagement reports by selecting specific metrics, date ranges, and social platforms. Reports can be exported in PDF or CSV formats and automatically delivered via email or available for download, facilitating performance sharing with stakeholders, sponsors, or team members and supporting data-driven decision-making.

Acceptance Criteria
Custom Report Template Creation
Given a user is on the reporting interface, When they select specific metrics, date ranges, and social platforms and click ‘Save Template’, Then the system saves the template with the provided name and displays it in the ‘My Templates’ list.
Report Schedule Configuration
Given a saved report template, When the user sets a schedule frequency, start date, and delivery method and clicks ‘Schedule’, Then the system activates the schedule, shows the next run date, and lists the scheduled report under ‘My Scheduled Reports’.
PDF Export Functionality
Given a user views a generated report, When they click ‘Export’ and choose ‘PDF’, Then the system generates a PDF matching the displayed data, prompts download, and ensures file integrity with correct formatting.
CSV Export Functionality
Given a user views a generated report, When they click ‘Export’ and choose ‘CSV’, Then the system generates a CSV file containing all selected metrics and data rows, prompts download, and ensures data accuracy without formatting errors.
Automated Email Delivery of Reports
Given a scheduled report is due to run, When the system executes the schedule, Then it generates the report in the selected format and sends it to the configured email recipients within 5 minutes of generation.
Historical Data Comparison Module
"As a marketing analyst, I want to compare current engagement metrics with past periods so that I can identify trends and measure the impact of our campaigns over time."
Description

A visual comparison tool integrated into MenuZap that allows users to analyze engagement trends over different periods (week-over-week, month-over-month) with side-by-side charts and percentage change annotations. By highlighting growth patterns, spikes, and anomalies, users can understand long-term performance, validate content strategies, and identify areas needing adjustment to maintain consistent audience growth.

Acceptance Criteria
User Applies Week-Over-Week Date Range
Given the user selects two consecutive weekly date ranges, when the module loads the data, then two side-by-side line charts are displayed with corresponding date labels and percentage change annotations for each metric.
User Applies Month-Over-Month Date Range
Given the user selects two consecutive monthly date ranges, when the module renders the comparison, then two side-by-side bar charts are displayed showing total likes, shares, clicks, and new followers with percentage change annotations.
Percentage Change Annotation Display
When the comparison charts are rendered, then each metric’s percentage change between the two periods is calculated correctly and displayed next to its corresponding data point with a positive or negative indicator.
Anomalies Highlighting in Comparison
Given engagement data contains spikes or drops exceeding a 20% threshold, when the charts are displayed, then those anomalies are highlighted in red or green and listed in an anomaly summary panel.
Trend Summary Panel Accessibility
When the user views the comparison module, then a summary panel displays overall growth patterns, average percentage changes across metrics, and a brief textual insight.

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Instantly flag and filter menu items by allergens per customer profile, eliminating cross-contamination risk and boosting diners’ confidence.

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Generate profit-maximizing meal bundles in real time based on live inventory and sales trends, driving upsells and reducing waste.

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Press Coverage

Imagined press coverage for this groundbreaking product concept.

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MenuZap Launches Real-Time Dashboard to Revolutionize Food Truck Operations

Imagined Press Article

City, State – 2025-08-05 – MenuZap today announced the official launch of its live mobile dashboard, designed to transform the way independent food truck owners manage orders, inventory, and menus in real time. The innovative platform enables owners to mark items as sold out instantly, eliminate order mistakes, and serve only what’s truly available—keeping lines moving, customers smiling, and daily sales on track, even during the busiest service hours. In an industry where speed and accuracy can make or break a sale, MenuZap brings restaurant-grade technology directly to the hands of solo chefs and small operators. By unifying order management, inventory tracking, and menu configuration into a single intuitive interface, the platform empowers vendors to respond to supply fluctuations and customer demand on the fly. Whether a chef is preparing gourmet tacos at lunch rush or serving late-night snacks at a music festival, MenuZap makes every transaction smoother. Key Features and Benefits: • Live Order Integration: Orders from multiple channels—point-of-sale terminals, online pre-orders, and mobile apps—feed directly into the dashboard, offering a consolidated view that reduces order miscommunications. • Real-Time Inventory Updates: Ingredient usage is tracked automatically as orders are processed. When stock levels drop to zero, relevant menu items are flagged sold out, preventing disappointing customer experiences. • Dynamic Menu Management: Owners can activate or deactivate menu items with one tap. Temporary promotions or daily specials become easy to introduce, test, and retire without downtime. • Custom Sales Reports: At any moment, vendors can generate up-to-the-minute sales performance reports, identifying top-selling items, revenue trends, and peak service times to refine their operations and boost profitability. “Independent food truck owners often juggle multiple roles at once, and they need a system that adapts as quickly as they do,” said Clara Mitchell, CEO of MenuZap. “Our mission is to replace stress and wasted time with confidence and control, so chefs can focus less on spreadsheets and more on crafting unforgettable dishes.” Real-World Impact: Solo Chef Maria Lopez, owner of SpiceWagon, piloted MenuZap during a six-week beta in Los Angeles. “Before MenuZap, I constantly worried about running out of key ingredients during peak hours. Now I see exactly what’s available the moment someone places an order. My kitchen runs smoother, my guests order more confidently, and I waste less food,” she said. Fleet operators also see immediate advantages. By monitoring multiple trucks through one dashboard, managers eliminate redundant trips to restock, align menus across locations, and address stock imbalances before they impact sales. Supporting Independent Operators: MenuZap is designed to fit into tight budgets and shifting schedules. There is no upfront hardware investment; the solution is device-agnostic and runs on any smartphone, tablet, or laptop. A tiered subscription model accommodates owners with a single truck and scales seamlessly for multi-unit fleets. About MenuZap: Founded in 2024 by a team of restaurateurs and software engineers, MenuZap bridges the gap between ambitious food entrepreneurs and enterprise-level operations tools. Headquartered in City, State, MenuZap is dedicated to delivering accessible, powerful solutions that help mobile vendors grow their businesses, delight customers, and operate sustainably. Press Contact: Jane Smith Public Relations Manager, MenuZap Email: jane.smith@menuzap.com Phone: (555) 123-4567 Website: www.menuzap.com

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MenuZap Unveils Intelligent Fleet Management with Predictive Resupply and Auto Rebalance

Imagined Press Article

City, State – 2025-08-05 – MenuZap, the leading real-time operations platform for food truck owners, today introduced two groundbreaking modules—Predictive Resupply and Auto Rebalance—to its mobile dashboard. These intelligent features leverage historical sales and current inventory data to forecast supply needs and automatically redistribute stock across multiple vehicles, ensuring fleets remain optimally stocked without manual effort. Managing inventory across a single food truck presents challenges; overseeing a fleet multiplies complexity. Fleet Manager Daniel Reed, who oversees eight gourmet food trucks in three states, said, “Before MenuZap’s new modules, I spent hours each week coordinating transfers and tracking orders. Now, the system recommends resupply quantities and triggers stock moves automatically. It’s like having a 24/7 supply chain coordinator in my pocket.” Feature Highlights: • Predictive Resupply: Analyzes each truck’s sales velocity and ingredient turnover to forecast future needs. Users receive recommended restock quantities and timing, reducing both overstocking and last-minute shortages. • Auto Rebalance: Continuously monitors inventory levels across your entire fleet. When a vehicle’s stock dips below optimal levels while another has surplus, the system initiates a transfer request through the integrated Transfer Hub. • Transfer Hub Integration: Streamlines inter-truck transfers by generating pick lists, tracking approvals, and confirming deliveries, cutting down paperwork and manual tracking. • Fleet Heatmap Visualization: Displays real-time stock levels on a color-coded map, enabling managers to pinpoint understocked or overstocked units at a glance. “Effective inventory management is a competitive advantage for any operator,” said Rajesh Chopra, CTO of MenuZap. “By empowering vendors with accurate forecasts and automated balancing, we help them reduce waste, maximize sales, and keep customers happy.” How It Works: Step 1: Data Collection – MenuZap captures sales data and ingredient consumption in real time, building a robust dataset for each truck. Step 2: Forecast Generation – The Predictive Resupply engine processes this data and schedules recommended restock orders based on upcoming demand patterns. Step 3: Automatic Redistribution – When Auto Rebalance detects imbalances, it triggers a transfer workflow, notifying both sending and receiving drivers. Transfer Hub captures confirmations, ensuring accountability. Step 4: Continuous Monitoring – The Fleet Heatmap updates dynamically, reflecting changes as transfers complete and new orders are processed. Early adopters report significant improvements. Catering company OnTheGo Eats saw a 30% reduction in waste and a 25% increase in on-time order fulfillment within four weeks of activating the modules. Supporting Growth: MenuZap’s fleet management enhancements are available as add-on modules to its core subscription. There is no additional hardware; features activate instantly on existing devices. Flexible pricing ensures operators pay only for the functionality they need, making advanced supply chain automation accessible to businesses of all sizes. About MenuZap: MenuZap was founded in 2024 by restaurateurs and technologists passionate about leveling the playing field for mobile food vendors. With headquarters in City, State, the company is committed to delivering user-friendly, enterprise-caliber tools that drive efficiency, profitability, and sustainability. Press Contact: Jane Smith Public Relations Manager, MenuZap Email: jane.smith@menuzap.com Phone: (555) 123-4567 Website: www.menuzap.com

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MenuZap Powers Event Vendors with EventPulse Sync and SurgeWave Alerts for Peak Performance

Imagined Press Article

City, State – 2025-08-05 – MenuZap today announced two specialized modules—EventPulse Sync and SurgeWave Alerts—designed specifically for event pop-up planners, festival vendors, and caterers. By integrating local event calendars and leveraging predictive analytics, MenuZap equips part-time and seasonal operators with the tools they need to anticipate customer surges and optimize staffing, inventory, and menu offerings for maximum impact. Event environments present unique challenges: irregular crowds, limited setup windows, and unpredictable demand spikes. Traditional inventory systems struggle to adapt to one-off events, leaving vendors underprepared or overstocked. MenuZap’s EventPulse Sync and SurgeWave Alerts change the game by blending geo-targeted data and machine learning to forecast rushes and recommend actionable steps. Core Capabilities: • EventPulse Sync: Connects to local event calendars—concerts, festivals, sporting events—to overlay scheduled attractions with historical attendance data. The dashboard highlights time windows when foot traffic is expected to swell. • SurgeWave Alerts: Generates real-time push notifications when a rush is imminent, advising planners to adjust ingredient prep, open additional service windows, or deploy extra staff. • PrepPerfect Scheduler Integration: Syncs surge forecasts with staff schedules, suggesting shift adjustments to ensure adequate coverage during predicted busiest times. • OffPeak Optimizer Coordination: Identifies post-rush lulls and recommends targeted promotions or limited-time menu items to maintain sales momentum. “Our pop-up catering clients have told us they need a system that feels like a seasoned festival manager in their pocket,” said Clara Mitchell, CEO of MenuZap. “EventPulse Sync and SurgeWave Alerts deliver that expertise by anticipating crowds before they form, eliminating wasted prep time and missed opportunities.” Real-World Success: Festival planner and Allergy Advocate Ava Harrison tested the modules at a three-day music festival. “With EventPulse Sync, I knew exactly when the morning coffee rush would hit and when the evening food binge would start. SurgeWave Alerts kept our stations prepped and lines moving. We reduced order errors by 40% and saw a 20% uptick in sales compared to last year’s setup.” How Operators Benefit: • Enhanced Efficiency: By knowing rush patterns in advance, vendors avoid last-minute scrambling and reduce labor costs associated with unanticipated overtime. • Inventory Optimization: Smart forecasts prevent spoilage by aligning prep volumes with actual attendance projections, rather than gut instincts. • Revenue Growth: Targeted off-peak promotions and timely menu adjustments keep guests engaged even during slower periods, driving incremental sales. Accessibility and Pricing: EventPulse Sync and SurgeWave Alerts are available immediately to all MenuZap subscribers as part of the platform’s event suite. There is no additional hardware or integration required—modules activate within minutes. A pay-per-use pricing model ensures that vendors only pay for the events they attend, delivering budget-friendly flexibility for small teams and large-scale planners alike. About MenuZap: Founded in 2024 by a collaborative group of restaurateurs, event specialists, and software developers, MenuZap is committed to empowering mobile food vendors with enterprise-grade tools. Headquartered in City, State, the company’s mission is to streamline operations, maximize profitability, and enhance the customer experience at every service point. Press Contact: Jane Smith Public Relations Manager, MenuZap Email: jane.smith@menuzap.com Phone: (555) 123-4567 Website: www.menuzap.com

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