Restaurant Technology

TableHop

Takeout, Reclaimed. Profits, Restored.

TableHop equips independent urban restaurant owners with a real-time order dashboard and instant curbside arrival alerts, slashing takeout errors and wait times. Families order ahead, skip lines, and avoid third-party fees, while restaurateurs reclaim profits and control the takeout experience—delivering fast, accurate handoffs that turn first-timers into loyal regulars.

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TableHop

Product Details

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

Vision & Mission

Vision
To empower every independent restaurant to reclaim takeout, delight customers, and thrive without third-party fees holding them back.
Long Term Goal
By 2028, enable 20,000 independent urban restaurants to reclaim $70 million annually in profits by cutting takeout errors 70% and wait times 40% through seamless, direct curbside pickup.
Impact
Reduces takeout order errors by 70% and customer wait times by 40% for independent urban restaurants, while eliminating up to 90% of third-party app fees—directly increasing owner profits and driving repeat business by delivering a smoother, more reliable curbside pickup experience for busy families.

Problem & Solution

Problem Statement
Independent restaurant owners in cities struggle to manage online takeout orders and curbside pickups efficiently, leading to frequent order errors and long wait times; existing third-party delivery apps increase costs and erode already slim profit margins.
Solution Overview
TableHop gives independent restaurants a real-time order dashboard and instant curbside arrival alerts, letting staff quickly match customers to orders and eliminate confusion. Busy families skip lines, while owners reclaim takeout profits lost to third-party apps by streamlining pickup from order to handoff.

Details & Audience

Description
TableHop streamlines online ordering and curbside pickup for independent restaurant owners. Busy urban families order ahead, skip lines, and enjoy hassle-free takeout without third-party markups. Restaurants cut order mix-ups, keep wait times low, and boost profits using TableHop’s real-time curbside arrival alerts—a tool designed to eliminate confusion and keep customers coming back.
Target Audience
Independent restaurant owners (30-55) managing urban eateries, eager to streamline takeout and maximize profits.
Inspiration
Parked outside a tiny family restaurant, I watched a server dash from car to car, juggling bags and a buzzing phone, trying to match names from three delivery apps. Orders grew cold, cars lined up, and tempers flared. In that curbside chaos, I saw how much local owners were losing—and knew there had to be a better way for small restaurants to take control of takeout.

User Personas

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

C

Creator Chloe

- Age 26, urban social media influencer - Audience: 20k Instagram and TikTok followers - Bachelor’s degree in Marketing - Rents downtown loft, $45k annual income - Posts daily food content

Background

Graduated with a Marketing degree and launched a food blog in college. Monthly collaborations with local restaurants sharpened her eye for shareable content.

Needs & Pain Points

Needs

1. On-time curbside pickups for scheduled content shoots 2. Clear restaurant branding for sponsored posts 3. Exclusive influencer promos to boost audience interest

Pain Points

1. Pickup delays disrupt timed content releases 2. Inconsistent packaging diminishes photo-quality appeal 3. Limited early-access spots for influencer partnerships

Psychographics

- Obsessed with fresh, shareable dining experiences - Seeks authentic, reciprocal brand collaborations - Craves novel menu discoveries and exclusivity - Measures success by audience engagement metrics

Channels

1. Instagram Stories (daily sharing) 2. TikTok (short-form video) 3. Email Newsletter (brand outreach) 4. Foodie Forums (community engagement) 5. Direct Messages (collaboration inquiries)

D

Discount Drew

- Age 35, suburban finance analyst - Married with two young kids - Household income $60k annually - Utilizes budget-tracking apps - Commutes 30 minutes daily

Background

Raised in a frugal household, Drew mastered couponing as a teenager. Balancing family expenses drives him to seek the sharpest restaurant discounts.

Needs & Pain Points

Needs

1. Clearly listed, valid discount codes without hidden fees 2. Easy bundle deals for family meals 3. Seamless redemption at curbside pickup

Pain Points

1. Unexpected fees eat into perceived savings 2. Expired or unclear promo codes frustrate attempts 3. Complicated redemption processes delay family dinners

Psychographics

- Obsessively tracks savings and budgets - Thrives on beating promotional deadlines - Prioritizes value without compromising taste - Shares deals within tight-knit communities

Channels

1. Coupon Apps (Honey - browser extension) 2. Email Newsletters (promo alerts) 3. Facebook Groups (local deals) 4. Reddit (r/frugal - deal sharing) 5. SMS Alerts (time-sensitive)

S

Swift Sam

- Age 29, urban management consultant - Earns $90k annually - Lives in downtown apartment - Works 50+ hours weekly - Single, no dependents

Background

After surviving back-to-back client presentations, Sam demands seamless lunch logistics. Early mishaps in pickup lines taught him to prioritize efficiency above all.

Needs & Pain Points

Needs

1. Guaranteed pickup slots within strict time windows 2. Real-time tracking to coordinate lunch breaks 3. Customizable orders to meet dietary preferences

Pain Points

1. Delayed orders derail tight meeting schedule 2. Incorrect items cause unwelcome downtime 3. Unpredictable wait times waste valuable minutes

Psychographics

- Values strict punctuality in daily routines - Views time as most precious asset - Prefers minimal interaction, maximum efficiency - Seeks reliable, predictable service every time

Channels

1. Calendar Integration (Outlook - syncing) 2. Slack Notifications (team coordination) 3. LinkedIn Mobile (professional browsing) 4. Yelp App (quick reviews) 5. In-app Chat (customer support)

H

Healthy Hannah

- Age 32, urban yoga instructor - Earns $75k annually - Lives in eco-friendly co-op - Follows a plant-based diet - Active on wellness apps

Background

Transitioned from a corporate desk job to full-time yoga instructor. Chronic digestive issues motivated her to scrutinize meal ingredients.

Needs & Pain Points

Needs

1. Detailed nutrition facts on every menu item 2. Customizable ingredient swaps for dietary restrictions 3. Eco-friendly packaging for sustainable living

Pain Points

1. Hidden oils and sugars upset health goals 2. Inaccurate nutrition labels undermine meal planning 3. Non-recyclable packaging conflicts with values

Psychographics

- Prioritizes health and nutritional transparency always - Values sustainably sourced, organic ingredients - Avoids artificial additives and preservatives - Shares healthy finds with wellness community

Channels

1. MyFitnessPal (meal tracking) 2. Instagram (wellness inspiration) 3. Health Blogs (recipe research) 4. Email (nutritional updates) 5. App Notifications (fresh options)

Product Features

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

AngleSnap View

Provides a 360° rotating view of dishes by capturing images from multiple angles. This feature lets customers examine every detail—from the plating to portion size—ensuring they know exactly what to expect when they pick up their order.

Requirements

Multi-Angle Capture Module
"As a restaurant manager, I want the system to automatically capture multiple images of each dish from different angles so that customers can examine plating and portion sizes in detail."
Description

Implement a camera control component that automatically captures a sequence of high-resolution images of each dish from predefined angles (e.g., top-down, side, 45°). It should integrate with existing POS workflows and kitchen display systems to trigger snapshots upon order readiness. Benefits include consistent image quality, reduced manual intervention, and uniform data for the 360° viewer.

Acceptance Criteria
Automated Capture on Order Ready
Given a kitchen order is marked as ready in the POS system When the order readiness event is received Then the capture module automatically triggers and sequentially captures images at top-down, side, and 45° angles without manual intervention
High-Resolution Multi-Angle Image Quality
Given the capture sequence is initiated When images are captured Then each image must be at least 3000×3000 pixels in PNG format with no visible compression artifacts
Seamless POS and KDS Integration
Given an order ID is generated in the POS When the capture module receives the order ID Then it must map and tag each captured image to the correct order record within 500ms
360° Viewer Update Latency
Given images have been captured and tagged When they are sent to the 360° viewer Then the complete set of images must be available for rotation within 5 seconds
Capture Failure Recovery Mechanism
Given a capture attempt fails at any angle When the failure is detected Then the system must retry up to two additional times and log the error If still unsuccessful Then an alert is sent to kitchen staff
Interactive 360° Viewer
"As a customer, I want to rotate and zoom in on a dish’s 360° view so that I can inspect every detail before placing my order."
Description

Develop a front-end component that stitches the captured images into a smooth, user-controllable 360° rotational view. Include intuitive controls (drag, swipe, rotate) and zoom functionality to allow customers to inspect dishes on web and mobile platforms. Ensure the viewer is responsive and accessible across devices.

Acceptance Criteria
Desktop Rotation Functionality
Given a fully loaded 360° viewer on a desktop browser When the user clicks and drags the dish image horizontally Then the image rotates smoothly following the drag direction without stutter or frame skips And completes a full 360° rotation without visual glitches
Mobile Swipe Gesture Control
Given a fully loaded 360° viewer on a mobile device When the user swipes left or right on the dish image Then the image rotates corresponding to the swipe direction and velocity And the rotation remains fluid and responsive throughout the gesture
Zoom Viewer Interaction
Given the viewer is displayed on desktop or touch device When the user pinches outward or uses the mouse wheel scroll up Then the image zooms in up to 200% without pixelation or distortion When the user pinches inward or scrolls down Then the image returns to original scale smoothly
Loading Performance under Low Bandwidth
Given network speed below 1 Mbps When the viewer initializes Then the first frame must render within 2 seconds And the remaining frames load progressively without user-perceived delay or freezing
Responsive Viewer Layout
Given a range of screen widths from 320px to 1920px When the viewer is rendered Then it scales to fit its container while maintaining a 16:9 aspect ratio And all controls (rotate, zoom) remain fully visible and operable
Keyboard and Screen Reader Accessibility
Given the viewer is focused via keyboard When the user presses the left or right arrow keys Then the image rotates counterclockwise or clockwise respectively And assistive technology announces the rotation angle When the user presses the plus or minus keys Then the zoom level increases or decreases with corresponding announcements
High-Resolution Image Stitching
"As a developer, I want a reliable image stitching service so that the 360° views load quickly and look seamless on all devices."
Description

Create a backend service to process and stitch multiple angle images into a seamless high-resolution panorama. Include algorithms for edge blending, color normalization, and quality optimization. Integrate with cloud storage and CDN delivery to ensure fast load times and minimal bandwidth usage.

Acceptance Criteria
Seamless Panorama Generation
Given a set of 6 input images captured at evenly spaced angles around a dish, when the stitching service processes them, then the resulting panorama must exhibit no visible seams or misalignments, with seam detection metrics below the defined threshold.
Color Normalization Verification
Given the stitched panorama, when color normalization algorithms are applied, then the mean DeltaE between overlapping regions must be ≤ 2.0 to ensure consistent color across the final image.
Stitching Performance Benchmark
Given 8 high-resolution (12 MP) input images, when the stitching pipeline runs under normal system load, then the end-to-end processing time must not exceed 3 seconds.
Cloud Storage & CDN Integration
Given a successfully stitched panorama, when the service uploads the file to cloud storage, then the image must be available via its CDN URL within 200 ms of upload completion.
Graceful Error Handling for Missing Inputs
Given one or more corrupted or missing input images, when the stitching service processes the remaining valid images, then it must generate a partial panorama without failing and log an error for each missing file.
Real-Time Preview Integration
"As a chef, I want to see the 360° preview of a dish right after capture so that I can retake images if the lighting or angle is incorrect."
Description

Enable kitchen staff to preview the assembled 360° view on a local dashboard immediately after image capture. Provide a feedback mechanism for retakes or adjustments (lighting, angle). Integrate notifications into the POS system to alert staff when the preview is ready for approval.

Acceptance Criteria
Image Capture Preview Availability
Given a dish image capture completes, when processing finishes, then the 360° preview appears on the local dashboard within 5 seconds.
Feedback Mechanism Trigger
Given the preview is displayed, when staff selects 'Request Retake', then the system logs the request and prompts the imaging station to recapture within 3 seconds.
Lighting and Angle Adjustment Workflow
Given staff identifies suboptimal lighting or angle in the preview, when they adjust the settings and confirm, then the updated preview reflects the new capture within 5 seconds.
POS Notification Delivery
Given the preview is ready for approval, when processing completes, then a notification is sent to the POS within 2 seconds and visible on the staff terminal.
Preview Approval Process
Given staff reviews the preview, when they click 'Approve', then the system marks the 360° view as approved and removes the item from the pending queue.
Performance and Optimization
"As an end user, I want the 360° view to load quickly and smoothly so that I can browse dishes without delays."
Description

Implement caching, lazy loading, and image compression techniques to ensure smooth interactions with the 360° viewer under varying network conditions. Monitor performance metrics and set up automated scaling for peak usage. Ensure compliance with web performance standards and maintain sub-2-second load times.

Acceptance Criteria
Initial Image Load on Slow Network
Given a user accesses the 360° viewer on a network with 3G speed, when the viewer initiates, then the initial view loads within 2 seconds and displays a low-resolution placeholder until high-resolution images are fully loaded.
Angle Transition Performance
Given a user rotates the view between angles, when they switch from one angle to another, then each new angle image loads within 500ms with no stutter or frame drops.
Caching Efficiency
Given a user revisits a previously viewed angle in the same session, when that angle is requested again, then the image is served from cache without additional network requests, resulting in load time under 200ms.
Lazy Loading Subsequent Angles
Given a user opens the 360° viewer, when the initial angle is loaded, then subsequent angles load on-demand as the user rotates, reducing average bandwidth usage by at least 50%.
Peak Traffic Load Handling
Given the system experiences 10,000 concurrent viewers, when users request 360° images, then the system auto-scales within 30 seconds to maintain load times under 2 seconds for all requests.
Image Compression Quality
Given the system compresses images before delivery, when images are displayed, then image quality maintains an SSIM score above 0.95 and file sizes are reduced by at least 60%.

Ingredient Insight

Overlays key ingredient lists and allergen alerts directly on the dish photo. Customers can tap on any component to see nutritional details, dietary tags, and possible allergens, empowering them to make informed choices and avoid surprises.

Requirements

Ingredient Overlay Display
"As a customer, I want to see a clear list of ingredients overlaid on each dish photo so that I can immediately understand what I’m ordering without navigating away."
Description

Integrate an overlay on dish photos that clearly lists all ingredients associated with the menu item. The overlay should appear when users view a dish, ensuring ingredients are legible and positioned to not obscure the image. It should seamlessly integrate with the existing menu interface, leveraging your current image rendering framework to load and display text overlays dynamically. This functionality helps users quickly understand what goes into each dish, reducing uncertainty and improving decision-making.

Acceptance Criteria
Dish Detail Ingredient Overlay
Given the user taps on a dish photo, when the detail view loads, then the overlay displays all ingredients legibly without covering more than 20% of the photo area.
Allergen Indicator Display
Given a dish contains common allergens, when the overlay appears, then allergen ingredients are highlighted with red icons and tooltip descriptions appear on tap.
Scrollable Ingredient List
Given the number of ingredients exceeds the visible overlay height, when the overlay is opened, then the ingredient list is vertically scrollable and all items can be accessed without cutoff.
Overlay Render Performance
Given the overlay feature is enabled, when a user opens any dish, then the overlay renders within 300ms and image load time increases by no more than 10%.
Responsive Overlay Layout
Given a device with varying screen resolutions, when the overlay is displayed, then ingredient text adjusts size and position to remain fully visible within the image boundaries.
Ingredient Tap Interaction
"As a customer, I want to tap an ingredient in the overlay to see its nutritional details and dietary tags so that I can make informed choices based on my dietary needs."
Description

Enable users to tap on any ingredient listed in the overlay to open a detailed pop-up. The pop-up should display nutritional data, dietary tags (e.g., vegan, gluten-free), and allergen warnings for the selected ingredient. Implement smooth transitions and ensure accessibility compliance. This interaction empowers users to drill down into specifics without leaving the menu screen, streamlining their selection process.

Acceptance Criteria
Ingredient Pop-up Initialization
Given the menu screen displays a dish overlay, When the user taps on any ingredient listed, Then a detailed pop-up launches within 200ms showing the selected ingredient's name, nutritional data, dietary tags, and allergen warnings.
Real-time Nutritional Data Display
Given an ingredient is selected and the pop-up is open, When displayed, Then the nutritional values (calories, fats, proteins, carbs) must match the backend data to within 1% and include correct measurement units.
Dietary Tag Interaction
Given the pop-up shows dietary tags, When the user taps on a tag (e.g., gluten-free, vegan), Then a tooltip appears within 150ms explaining the tag and related dietary considerations.
Allergen Warning Visibility
Given the ingredient contains allergens, Then the pop-up clearly highlights each allergen with a red icon and text, and screen readers announce ‘Warning: Contains [allergen]’ upon opening.
Screen Reader Accessibility
Given the user is using a screen reader, When the pop-up appears, Then it must have proper ARIA labels for all elements, be navigable via keyboard or swipe gestures, and announce each section in a logical order.
Allergen Alert Highlighting
"As a customer with allergies, I want allergenic ingredients to be prominently highlighted so that I can avoid dishes that might harm me."
Description

Automatically highlight ingredients flagged as common allergens (e.g., nuts, dairy, shellfish) within the overlay using a distinct visual indicator such as a red outline or icon. This requirement involves tagging allergenic ingredients in the database and front-end logic to render alerts. The feature enhances safety by drawing immediate attention to potential allergens.

Acceptance Criteria
Dish Photo with Nut Allergen
Given a dish photo tagged with nuts When the ingredient overlay is displayed Then nut ingredients must have a distinct red outline and allergen icon
Tooltip Display on Allergen Icon Tap
Given a highlighted allergen icon When the customer taps the icon Then a tooltip appears showing nutritional details, dietary tags, and allergen information
Non-Allergenic Ingredient Visibility
Given ingredients without allergen flags When the overlay renders Then non-allergenic ingredients display normally without red highlights or icons
Overlay Load Performance
Given the overlay is requested When network latency is simulated up to 3 seconds Then allergen highlights render within 2 seconds
Accessibility Compliance for Allergen Alerts
Given a user relies on a screen reader When the overlay loads Then each allergenic ingredient is announced with its name and allergen status
Nutritional Information Panel
"As a health-conscious user, I want to view the complete nutritional breakdown of my dish so that I can monitor my calorie and nutrient intake."
Description

Develop a standardized information panel that displays full nutritional breakdown for a selected dish, aggregating data from all ingredients. The panel should include calories, macronutrients, and micronutrients. It must integrate with back-end nutrition data services and maintain consistent design with other app panels. Providing comprehensive nutritional info supports health-conscious customers in tracking their intake.

Acceptance Criteria
User Views Nutritional Panel
Given a user has selected a dish, when they tap the nutrition icon, then a panel displays total calories, macronutrients, and micronutrients for that dish.
Ingredient Detail Nutrition Access
Given the nutrition panel is open, when the user taps on an individual ingredient, then the app displays that ingredient’s calories, macronutrients, micronutrients, dietary tags, and allergen alerts.
Correct Aggregation of Nutritional Data
When the panel aggregates data from backend services, then the sum of individual ingredient nutrient values matches the displayed totals within a 1% variance.
Design Consistency with App Panels
When the nutritional panel is rendered, then its layout, typography, colors, and iconography match the app’s design specifications.
Nutritional Panel Load Performance
When a user opens the nutritional panel, then it loads and fully renders on screen within 2 seconds on supported devices.
Dietary Tag Filtering
"As a vegetarian, I want to filter the menu by my dietary preference so that I only see dishes I can eat without manually checking each ingredient."
Description

Implement a filter that allows users to search and view menu items based on dietary tags (e.g., vegetarian, vegan, keto). The filter should dynamically update the displayed dishes and overlay labels accordingly. This feature ties into the ingredient metadata and requires updates to the search and menu rendering components. It improves discoverability for users with specific dietary preferences.

Acceptance Criteria
Vegetarian Filter Application on Menu
Given a user views the restaurant menu and selects the "Vegetarian" tag filter, When the filter is applied, Then only dishes tagged as vegetarian are displayed, And each displayed dish shows a "Vegetarian" overlay label.
Vegan Dietary Tag Search in Search Bar
Given a user enters "vegan" in the search bar and applies the dietary filter, When the search executes, Then the results list only dishes tagged as vegan, And no non-vegan dishes appear in the results.
Keto-friendly Label Overlay on Dish Photo
Given a user browses dish photos on the menu, When the dish has the "Keto" dietary tag, Then a "Keto-friendly" badge is overlaid on the photo, And tapping the badge shows nutritional details confirming compliance.
Combined Dietary Tag Selection
Given a user selects multiple dietary tags (e.g., "Vegetarian" and "Keto"), When the filters are applied simultaneously, Then only dishes that meet all selected dietary criteria are displayed.
Real-time Dynamic Filter Update
Given a user toggles dietary tag filters on the filter panel, When each tag is selected or deselected, Then the displayed menu updates instantly without page reload.

Chef’s Spotlight

Displays a short ‘behind-the-scenes’ note from the chef along with a high-res image. Customers gain insight into cooking techniques, special ingredients, and the story behind the dish, creating a more engaging and personalized experience.

Requirements

Chef Note Content Management
"As a restaurant owner, I want to manage and update a chef’s note for each dish so that I can share stories, techniques, and special ingredients with customers directly."
Description

Implement a content management interface within the restaurant dashboard allowing chefs to create, edit, preview, and schedule short behind-the-scenes notes. This module must support rich text formatting, ingredient highlighting, markdown support, auto-save drafts, and version history. It integrates seamlessly with existing menu management and ensures notes are published in real time across all customer touchpoints.

Acceptance Criteria
Chef Creates New Note with Rich Text Formatting
Given the chef opens the note editor, When they apply bold, italic, bullet lists, and ingredient highlighting, Then the editor renders the formatted text correctly and saves the markup without errors.
Chef Previews Note Before Publishing
Given the chef has drafted a note, When they click the preview button, Then the system displays an accurate, full-screen preview showing how the note will appear to customers across all devices.
Chef Edits Note with Version History
Given the chef navigates to an existing note, When they make changes and save, Then the system records a new version, retains previous versions in history, and allows rollback to any prior version.
Chef Schedules Note Publication
Given the chef sets a future publication date and time for a note, When the scheduled time arrives, Then the note automatically publishes and appears on all customer-facing channels at the specified time.
Real-Time Note Display Across Customer Touchpoints
Given a note is published or updated, When the change is saved, Then the note appears instantly on the customer app, web menu, and email notifications without manual refresh.
High-Resolution Image Upload
"As a restaurant owner, I want to upload and optimize high-resolution images of my dishes so that customers can visually appreciate the presentation and ingredients."
Description

Enable chefs to upload, crop, and optimize high-resolution images for each dish’s spotlight note. The feature should include drag-and-drop upload, auto-scaling to multiple resolutions for different devices, EXIF data retention, and automated compression to balance quality and load performance. It integrates with the content management system to ensure images appear crisp and engaging.

Acceptance Criteria
Uploading and Cropping a High-Resolution Image
Given the chef drags and drops a valid JPEG or PNG high-resolution image into the upload area, when the upload completes, then a cropping interface appears, allowing the chef to select and preview the crop region with 16:9 and 4:3 aspect ratio presets.
Automatic Multi-Resolution Scaling
Given the chef finalizes the crop, when the image is saved, then the system generates optimized versions at 1920x1080, 1280x720, and 640x480 pixels, preserving the selected aspect ratio.
EXIF Data Retention Post-Upload
Given the chef uploads an image containing EXIF metadata, when the image is processed, then the system retains all original EXIF fields (including camera model, capture date, and geolocation) in each generated version.
Automated Compression Balancing Quality and Load Performance
Given the system has generated multiple scaled images, when applying compression, then each image is optimized to under 300KB for mobile resolutions and under 1MB for desktop resolutions, with perceptual quality maintained (SSIM ≥ 0.95).
Drag-and-Drop Interface Validation
Given a chef drops an unsupported file type (e.g., PDF or GIF) into the upload area, when the system detects the file, then it rejects the upload and displays an error message indicating supported formats (JPEG, PNG).
Spotlight Display Module
"As a customer, I want to view a chef’s note and image alongside the menu item so that I feel more connected to the dish and informed about its preparation."
Description

Develop a front-end component that renders the chef’s note and accompanying image on the customer-facing menu and order screens. The module must support asynchronous data fetching, animated transitions, lightbox view for images, and accessibility compliance (ARIA labels, keyboard navigation). It should integrate with the existing UI framework and maintain consistent styling.

Acceptance Criteria
Chef's Note and Image Load on Menu Screen
Given a customer opens the menu screen, when the component mounts, then the chef's note and image are fetched asynchronously and displayed within 2 seconds without disrupting other menu items.
Animated Transition of Chef's Spotlight Module
Given the chef's note and image data is available, when the module enters the viewport, then a fade-in animation of 300ms is applied to both text and image.
Image Lightbox Activation and Navigation
Given a customer clicks the chef's image thumbnail, when the click event is received, then the image opens in a full-screen lightbox with zoom controls, close button, and clicking outside or pressing ESC closes the lightbox.
Accessibility Compliance for Spotlight Module
The module exposes appropriate ARIA labels for the chef's note and image, all interactive elements are reachable via keyboard navigation in a logical tab order, and pressing Enter or Space on focusable elements triggers the expected actions.
Error Handling on Data Fetch Failure
Given the asynchronous fetch of chef's note or image fails, when an error occurs, then a generic placeholder note and image are displayed, and a retry button appears that, when clicked, re-attempts the fetch.
Responsive Layout for Spotlight
"As a mobile customer, I want the chef’s note and image to display correctly on my phone so that I can easily read and interact with the content on any device."
Description

Ensure the Chef’s Spotlight component is fully responsive across device sizes—from smartphones to large monitors. This requirement includes adaptive grid layouts, responsive typography, touch-friendly image interactions, and performance optimizations for mobile networks. It must integrate with the application’s responsive design system and pass mobile usability testing.

Acceptance Criteria
Mobile View Layout Adaptation
Given a user opens the Chef’s Spotlight on a mobile device (viewport width ≤ 480px), when the component loads, then the layout must switch to a single-column grid, the image must span 100% of the viewport width, text font size must adjust to between 14px and 16px, and all interactive elements must have touch targets ≥ 48px.
Tablet View Layout Adaptation
Given a user views the Chef’s Spotlight on a tablet device (viewport width between 481px and 768px), when the component renders, then the layout must use a two-column grid with image and text side by side, typography scales to 16px–18px, and spacing between elements adheres to the design system margin tokens.
Desktop View Layout Adaptation
Given a user accesses the Chef’s Spotlight on a desktop device (viewport width ≥ 1024px), when the page loads, then the component must display in a multi-column grid (image, text, and optional decorative content), image resolution must be at least 1920×1080, typography must scale to 18px–20px, and layout must align with the responsive design system guidelines.
Touch Interaction on Mobile
Given a user taps the Chef’s Spotlight image on a touchscreen device, when the tap occurs, then the image must animate to a full-screen preview without layout shift, and the close action must be triggered by a 48px × 48px close icon in the top corner.
Performance Under Low Network Conditions
Given a user with a 3G or slower network loads the Chef’s Spotlight, when the component fetches images and text, then image file sizes must not exceed 300KB using optimized formats, critical CSS and JS for the component must load within 1 second, and lazy-loading must defer non-critical assets.
Spotlight View Analytics Tracking
"As a restaurant owner, I want to see analytics on how often customers view and interact with the chef’s spotlight so that I can measure engagement and refine my content."
Description

Implement analytics tracking for Chef’s Spotlight interactions, capturing metrics such as note views, image expansions, time spent per spotlight, and click-through to order. Integrate with existing analytics platforms (e.g., Google Analytics, Mixpanel) and set up event schemas, dashboards, and automated reports to help restaurateurs gauge customer engagement and iterate on content.

Acceptance Criteria
Tracking Chef’s Spotlight Note Views
Given the Chef’s Spotlight note is loaded on the dish detail page, When a user scrolls it into view, Then an event 'spotlight_note_viewed' is sent to Google Analytics and Mixpanel with properties: dish_id, user_id, timestamp; And no duplicate event is recorded for multiple scrolls in the same session.
Tracking Image Expansion Events
Given a user clicks the Chef’s Spotlight image to expand, When the image modal opens, Then an event 'spotlight_image_expanded' is sent to Google Analytics and Mixpanel with properties: dish_id, user_id, timestamp, expansion_count.
Tracking Time Spent on Chef’s Spotlight
Given the Chef’s Spotlight panel is visible on screen, When the panel loses focus or the user navigates away, Then an event 'spotlight_time_spent' is sent with properties: dish_id, user_id, session_id, duration_seconds.
Tracking Click-through to Order from Spotlight
Given a user clicks the 'Order Now' button in the Chef’s Spotlight, When the click occurs, Then an event 'spotlight_order_click' is logged with properties: dish_id, user_id, timestamp, destination_url.
Integration with Analytics Platforms
Given the analytics SDKs are initialized, When any Chef’s Spotlight event occurs, Then events 'spotlight_note_viewed', 'spotlight_image_expanded', 'spotlight_time_spent', and 'spotlight_order_click' are forwarded to both Google Analytics and Mixpanel adhering to the defined event schema version 1.0.
Dashboard & Automated Reports Generation
Given Chef’s Spotlight events are collected in the analytics platforms, When the daily ETL job runs at 03:00 UTC, Then dashboards in Google Analytics and Mixpanel display metrics: total note views, image expansions, average time spent per spotlight, and click-through rate; And an automated report is emailed to restaurateur stakeholders at 08:00 UTC containing the same metrics.

Share-a-Snack

Enables one-tap sharing of real-time dish photos to social media or via messaging apps. Customers can show off their upcoming meal, gather feedback from friends, and generate buzz—turning every order into a social moment.

Requirements

In-App Photo Capture
"As a takeout customer, I want to take a high-quality photo of my dish within the app so that I can share it instantly with friends."
Description

Provide a built-in camera interface within the order confirmation screen, enabling users to capture high-quality photos of their prepared dishes. The interface should support autofocus, flash controls, basic cropping, and simple editing tools. It must integrate seamlessly into the existing order flow so customers can snap and review dish images immediately after preparation, enhancing user engagement and ensuring timely sharing.

Acceptance Criteria
Initiating In-App Photo Capture
Given the user is on the order confirmation screen When the user taps the camera icon Then the built-in camera interface opens with autofocus enabled and flash controls visible
Capturing a High-Quality Dish Photo
Given the camera interface is active When the user frames the dish and taps the capture button Then the app captures a clear photo using autofocus and the selected flash setting and displays a preview
Editing and Cropping the Captured Photo
Given the photo preview is displayed When the user selects crop or basic editing tools and applies adjustments Then the preview updates to reflect the changes and the user can confirm the final image
Saving and Sharing the Edited Photo
Given the user has finalized the edited photo When the user taps the share button Then the app attaches the photo to the order and opens the device’s share sheet for social media or messaging apps
Seamless Return to Order Flow
Given the user completes the share or save action When the user returns to the order confirmation screen Then the app navigates back seamlessly without errors and displays the captured photo alongside the order details
Real-Time Photo Upload
"As a takeout customer, I want my dish photo to upload in real time so that it's ready for sharing without delay."
Description

Automatically upload captured dish photos to the TableHop server immediately upon capture. The upload process must minimize latency, gracefully handle network fluctuations with retry logic, and compress images to balance quality and bandwidth. Uploaded photos should be stored securely and made instantly available for sharing across integrated platforms.

Acceptance Criteria
Immediate Photo Upload
Given a user captures a dish photo in the app When the photo is saved Then the upload to the TableHop server must start within 2 seconds And complete without further user intervention
Network Fluctuation Handling
Given the network connection drops during upload When connectivity is restored Then the app retries the upload automatically up to 5 times with exponential backoff intervals And resumes from the last byte transmitted
Image Compression Quality
Given a high-resolution dish photo When preparing for upload Then the image is compressed to no more than 300KB file size While preserving a minimum resolution of 1024x768 pixels
Secure Storage Verification
Given a photo is uploaded to the server When stored Then the image data is encrypted at rest using AES-256 And access requires authenticated user credentials over HTTPS
Instant Availability for Sharing
Given a photo upload completes successfully When queried via the sharing interface Then the photo URL is returned within 1 second And is immediately usable in social media and messaging integrations
Social Media Integration
"As a social user, I want to share my dish photo directly to my social media accounts so that I can engage my friends and followers."
Description

Integrate with major social media platforms (Facebook, Twitter, Instagram) via their public APIs to enable one-tap sharing of dish photos. Implement OAuth-based authentication, request and manage necessary permissions, and comply with each platform’s content policies. Provide a user-friendly interface to select accounts, preview posts, and confirm before publishing.

Acceptance Criteria
OAuth Authentication for Social Platforms
Given a user selects a social platform for sharing, when the user initiates the share action for the first time, then the app redirects to the platform’s OAuth consent screen and securely stores the returned access token upon successful authentication.
Permission Management for API Sharing
Given the user has authenticated with a social platform, when the app requests permissions to publish content, then it requests only the minimum required scopes and displays an error message if any permission is denied.
User Account Selection for Sharing
Given the user has linked one or more social accounts, when the user taps the share button, then the app displays a list of connected accounts with platform icons and allows the user to select one or multiple accounts.
Preview and Confirmation of Social Post
Given the user has selected a dish photo and accounts, when the share dialog opens, then the app shows a formatted preview with editable caption, platform-specific metadata, and ‘Confirm’ and ‘Cancel’ buttons.
Publishing Dish Photos to Social Media
Given the user confirms the share action, when the app submits the post, then it calls the correct API endpoint, handles success and error responses, and displays a corresponding success or failure message, ensuring compliance with the platform’s content policy.
Messaging App Sharing
"As a user, I want to share my dish photo via messaging apps so that I can get immediate feedback from friends."
Description

Generate shareable rich content for messaging apps such as WhatsApp, Messenger, and SMS. Create a share card containing the dish photo, restaurant name, and order details. Leverage the system share sheet for user selection, and ensure that received links deep-link back to the TableHop app or a mobile-friendly web page displaying the shared photo and ordering options.

Acceptance Criteria
Selecting Messaging App via System Share Sheet
Given a dish ready to share When the user taps the share button and the system share sheet appears Then the list must include installed messaging apps including WhatsApp, Messenger, and SMS options
Shared Content Displays Correct Dish Details
Given the user shares a dish When the share card is generated Then it displays the correct dish photo, restaurant name, order summary including dish name and quantity
Deep Link Opens TableHop App When Installed
Given a recipient taps the shared link on a mobile device With TableHop installed Then the link must open the app directly to the shared dish detail page
Deep Link Falls Back to Mobile Web Page
Given a recipient taps the shared link on a device without TableHop installed Then the link must open a mobile-friendly web page showing the shared photo, restaurant details, and ordering options
Shareable SMS Content Within Character Limits
Given the user selects SMS When the share card is sent Then the message content including link must not exceed 160 characters and still provide clear dish and restaurant information
Share Preview Customization
"As a creative user, I want to customize my dish photo with captions and filters so that my shared post is unique and engaging."
Description

Offer in-app editing tools to customize dish photos before sharing. Include options for adding captions, emoji stickers, and basic filter adjustments (brightness, contrast, saturation). Ensure that edits are non-destructive, preserving the original image for future sharing, downloads, or reference.

Acceptance Criteria
In-App Caption Addition
Given a dish photo in editing mode When the user selects the caption tool and enters text Then the caption appears on the photo preview and is saved as a separate layer preserving the original photo
Emoji Sticker Placement
Given a dish photo in editing mode When the user taps the emoji sticker icon and chooses a sticker Then the user can position and resize the sticker on the photo and the edited version retains the sticker layer separately from the original
Adjusting Brightness, Contrast, and Saturation
Given a dish photo in editing mode When the user adjusts the brightness, contrast, or saturation sliders Then the preview updates in real time and the original image file remains unchanged
Preview Saving and Original Preservation
Given completed edits to a dish photo When the user saves the edited preview Then the app stores the edited version in a separate file and the original image remains intact and accessible
Seamless Sharing Post-Edit
Given an edited dish photo When the user taps the share button and selects a social media or messaging app Then the edited photo with all applied customizations is shared while the original photo remains unaltered in the app library

Freshness Ticker

Shows a live countdown timer indicating how long ago the dish was plated and its optimal window for quality. This feature reassures customers of freshness and helps them time their arrival for the perfect pick-up experience.

Requirements

Real-time Plating Timestamp
"As a restaurant manager, I want the system to automatically record when a dish is plated so that the freshness timer starts immediately and accurately."
Description

Capture and store the exact moment each dish is plated, ensuring the system has an accurate baseline for calculating freshness. This requires integrating with back-of-house kitchen display systems or POS terminals to automatically log plating events without manual input, minimizing errors and delays.

Acceptance Criteria
Automated Plating Capture from Kitchen Display
Given a dish is marked 'plated' on the kitchen display system, When the system receives the plating event, Then it records the timestamp in the backend database in ISO 8601 format within 2 seconds of the event.
POS Terminal Plating Event Logging
Given a plating confirmation on the POS terminal, When the staff taps 'Ready for Pickup', Then the system automatically logs the plating timestamp with no manual input.
Timestamp Sync Accuracy
Given the backend server time is the source of truth, When a plating event timestamp is saved, Then the recorded time matches the server clock within a 1-second margin.
High Throughput Event Handling
Given 50 plating events per second during peak hours, When events are captured simultaneously, Then all timestamps are recorded without loss or duplication and with less than a 5% increase in average capture latency.
Data Integrity on Network Failure
Given a temporary network outage, When plating events occur, Then events are queued locally and synchronized to the server within 5 seconds of network restoration, preserving the original plating timestamp.
Live Countdown Display
"As a takeout customer, I want to see a live countdown of how long ago my dish was plated so that I can time my arrival for peak quality."
Description

Present a dynamic countdown timer on the customer-facing dashboard that updates in real time to show how many minutes remain within the optimal freshness window. The UI should be visually clear, mobile-responsive, and refresh seamlessly without full page reloads.

Acceptance Criteria
Mobile Customer Access to Freshness Countdown
Given a customer opens the dashboard on a mobile device, When the page loads, Then the countdown timer is visible within 2 seconds and clearly legible.
Real-Time Timer Update Without Page Reload
Given the dashboard is open, When one second elapses, Then the countdown timer updates automatically without a full page refresh and reflects the new remaining time.
Accurate Remaining Freshness Calculation
Given a dish was plated 3 minutes ago and the optimal freshness window is 15 minutes, When viewing the timer, Then it displays “12 minutes remaining” correctly.
Responsive UI Across Device Screen Sizes
Given a customer resizes their browser or changes device orientation, When viewing the countdown timer, Then the timer layout adjusts responsively and remains fully visible without overlap.
Expiration State Display After Freshness Window
Given the countdown timer reaches zero, When the freshness window expires, Then the timer switches to an “Expired” indicator displayed in red.
Configurable Freshness Window Settings
"As a restaurant owner, I want to set custom freshness windows for each dish so that the freshness ticker reflects the true quality span of every menu item."
Description

Enable restaurant administrators to define and adjust the optimal freshness duration (e.g., 0–10 minutes) for each menu item via an intuitive settings panel. Changes should propagate instantly to the countdown logic and customer dashboard.

Acceptance Criteria
Admin Sets Freshness Window for a Menu Item
Given the admin is on the menu item settings page, When they set the freshness window to a valid number of minutes and save, Then the system stores the value in the database and displays a confirmation message.
Immediate Propagation to Customer Dashboard
Given the freshness window is updated by the admin, When a customer views or reloads the dashboard, Then the countdown timer reflects the new freshness window without requiring a full application restart.
Validation of Input Values
Given the admin enters a value below 0 or above 60 minutes, When they attempt to save, Then the system displays a validation error message and prevents saving until a valid value is entered.
Default Freshness Window Applied to New Items
Given a new menu item is created without a specified freshness window, When the item is saved, Then the system automatically applies the default freshness window of 10 minutes.
Individual Freshness Settings for Multiple Items
Given the admin updates freshness windows for multiple menu items, When each item is viewed by customers, Then each countdown timer displays the correct, item-specific freshness window.
Threshold-Based Arrival Alerts
"As a busy customer, I want to receive an alert when my food’s freshness window is about to close so that I don’t miss the ideal pickup time."
Description

Implement optional push or SMS notifications that alert customers when their dish is approaching the end of its freshness window (e.g., 2 minutes remaining), encouraging timely pickup. Notifications should respect user communication preferences and support retry logic on failure.

Acceptance Criteria
Alert Trigger at Threshold
Given a plated dish with exactly 2 minutes remaining in its freshness window, when the countdown reaches the 2-minute threshold, then the system sends a notification to the customer’s device.
Notification Delivery by User Preference
Given a customer’s communication preference is set to SMS, when an alert is triggered, then the system sends an SMS message; if set to push notification, then the system sends a push notification.
Accurate Notification Content
Given a notification is sent, then the message includes the dish name, remaining freshness time, and a link to view order details.
Retry Logic on Failure
Given the first notification attempt fails due to network or service errors, when retries are triggered, then the system retries delivery up to 3 times at 1-minute intervals.
Suppression After Pickup
Given a customer confirms order pickup, when the pickup is marked complete, then no further freshness alerts are sent.
Time Synchronization and Resilience
"As a technical operations lead, I want all devices to stay time-synced and resilient so that reported freshness times remain reliable regardless of network issues."
Description

Ensure all system components (kitchen tablets, servers, and customer apps) use a synchronized time source (e.g., NTP) to prevent discrepancies in freshness calculations. Include fallback mechanisms to handle network outages or service failures, maintaining accurate timing even under degraded conditions.

Acceptance Criteria
Initial NTP Synchronization for All Components
Given all system components power on; When each component connects to the NTP server; Then the system clock is adjusted to within ±500 milliseconds of the NTP reference; And a successful sync is logged.
Continuous Time Drift Correction
Given the system is running continuously; When 15 minutes have elapsed since the last sync; Then each component performs a synchronization check with the NTP server; And any drift exceeding 200 milliseconds is corrected.
Fallback to Local Clock During NTP Outage
Given the NTP server is unreachable; When a sync attempt fails; Then each component switches to its local high-precision oscillator; And logs the fallback event with a timestamp.
Automatic Re-synchronization After Network Restoration
Given components are in fallback mode; When network connectivity to the NTP server is restored; Then each component automatically re-attempts NTP sync; And confirms time drift is corrected to within ±500 milliseconds.
Customer App Timer Accuracy in Offline Mode
Given a customer’s mobile device loses network connectivity; When the freshness countdown continues locally; Then the timer remains accurate within ±1 second per minute; And displays an 'Offline Mode' indicator.

Urgent Ping

Automatically flags allergy alerts and critical special requests with high-priority notifications that flash on the kitchen dashboard and the customer’s device, ensuring urgent needs are addressed immediately and misorders are prevented.

Requirements

Allergy Alert Recognition
"As a restaurant staff member, I want orders containing allergy alerts to be automatically flagged so that I can prioritize and handle them with extra care, reducing the risk of serving unsafe food."
Description

Implement a mechanism to detect and flag orders containing allergy-related items by analyzing special request input fields and menu metadata. When a customer selects or enters an allergy, the system automatically marks the order with a distinct priority indicator to ensure immediate visibility on the kitchen dashboard and prevents potential health risks. This feature integrates with the product’s order processing pipeline and leverages existing menu item attributes to maintain accuracy and consistency.

Acceptance Criteria
Customer Adds Allergy in Special Requests
Given a customer types "peanuts" in the special requests field When the customer submits the order Then the system flags the order with a red allergy icon and priority indicator on the kitchen dashboard and in the order details
Customer Selects Allergy from Dropdown
Given a customer selects "shellfish" from the allergy dropdown on the menu page When the order is confirmed Then the order summary displays a shellfish allergy badge next to relevant items and triggers a high-priority notification to the kitchen dashboard
Menu Item Metadata Allergy Detection
Given a menu item tagged with "gluten" allergen in its metadata When a customer orders that item without specifying an allergy Then the system automatically flags the order with a gluten allergy indicator and alerts the kitchen staff
Multiple Allergy Handling
Given a customer enters "nuts, dairy" in the special requests field When the order is processed Then each allergen is listed separately in the allergy badge and the system triggers distinct high-priority notifications for both
Kitchen Dashboard Notification Behavior
Given an order flagged for an allergy When the kitchen dashboard receives new orders Then the flagged order flashes at the top of the queue, remains highlighted until acknowledged, and logs the acknowledgment time
Customer Device Urgent Alert
Given an order has been flagged for an allergy When the kitchen acknowledges the flag Then the customer’s device receives an urgent ping confirming the allergy alert has been noted by the restaurant
Critical Request Highlighting
"As a kitchen manager, I want critical special requests to be highlighted prominently so that my team can address them immediately and fulfill customer expectations."
Description

Create functionality to identify and distinguish other critical special requests—such as dietary restrictions, temperature preferences, or rush orders—by assigning a high-priority tag. The system should differentiate between standard and critical requests, ensuring that all flagged items receive enhanced visibility through color-coding and placement at the top of the kitchen queue.

Acceptance Criteria
Placing a Rush Order
Given a customer marks an order as "Rush", when the order is submitted, then the system tags it with "High Priority", displays it at the top of the kitchen queue, and highlights it in red.
Submitting an Allergy Restriction Request
Given a customer selects a critical allergy restriction, when the order reaches the dashboard, then the restriction is flagged with a red icon, the order is moved to the top of the list, and an alert flashes on both the kitchen and customer devices.
Setting Specific Temperature Preference
Given a customer specifies a temperature preference labeled "Critical", when the order is processed, then the preference is color-coded orange, the order is repositioned to the top of the queue, and the kitchen staff receives a visual notification.
Multiple Critical Requests in One Order
Given an order contains more than one critical request type, when it arrives in the system, then all requests are aggregated under a single high-priority tag, the order is sorted above standard orders, and each critical request is individually color-coded.
Viewing Only Critical Requests
Given the kitchen staff activates the critical-only filter, when applied, then only orders tagged as high priority appear in the queue, color-coded correctly, and standard orders are hidden until the filter is reset.
Flashing Notification Mechanism
"As a chef working during peak hours, I want a flashing alert that won’t go away until someone acknowledges it so that I’m certain urgent orders get the attention they need."
Description

Develop a flashing alert mechanism on the kitchen dashboard and customer app that activates when an urgent ping is triggered. This mechanism should include intermittent visual flashes, distinct sound alerts, and a brief vibration cue on mobile devices. The alerts must persist until acknowledged, ensuring that urgent needs are not overlooked during busy service periods.

Acceptance Criteria
Kitchen Dashboard Flash Activation
Given an urgent ping is received on the kitchen dashboard When the flashing alert mechanism activates Then the dashboard background flashes red every 500ms And a distinct audible tone plays for at least 3 seconds
Customer App Alert Activation
Given a user’s order triggers an urgent ping When the customer app receives the ping Then the screen flashes yellow at 500ms intervals And a unique notification sound plays for at least 3 seconds And the device vibrates in a pattern of three short pulses
Persistent Alert Until Acknowledgement
Given an urgent ping is active When no acknowledgement occurs Then the visual flash, sound alert, and vibration repeat continuously without auto-dismissing for up to 5 minutes or until manual acknowledgement
Acknowledge Stops Alerts
Given an active urgent ping alert When the user taps the acknowledge button on the dashboard or app Then all flashing, sounds, and vibrations stop within 1 second And a confirmation message indicating the ping has been acknowledged is displayed
Concurrent Notifications Priority Handling
Given simultaneous standard and urgent notifications When both arrive at the same time Then the urgent ping alert supersedes and appears on top of other notifications And plays its distinct alert sequence without interference from standard alerts
Dual-channel Notification Delivery
"As a customer with a severe peanut allergy, I want to receive instant confirmation that the restaurant saw my allergy alert so that I know they’re preparing my order safely."
Description

Enable the urgent ping notifications to be delivered simultaneously to both the kitchen dashboard and the customer’s device. This requires integrating push notification services for mobile and web applications, plus real-time updates on in-house display screens. The feature ensures that both parties remain informed of critical alerts, facilitating immediate confirmation and reducing miscommunication.

Acceptance Criteria
Kitchen Dashboard Notification Trigger
Given an order with an allergy alert or critical special request When the order is submitted Then the kitchen dashboard displays a high-priority visual alert with flashing border and plays a distinct sound within 2 seconds
Customer Push Notification Receipt
Given the customer’s device is online and the app is running in foreground or background When an urgent ping is generated by the restaurant Then the customer receives a push notification with a red badge, distinct tone, and the alert content within 3 seconds
In-house Display Screen Alert
Given the restaurant’s in-house display screens are connected to the notification service When an urgent ping is triggered Then the display screens flash the alert message in red at the top of the queue view and remain visible until acknowledged by staff
Simultaneous Delivery Confirmation
Given both the kitchen dashboard and the customer have received the notification When the staff or customer taps “Acknowledge” Then the system logs the confirmation timestamp in both views and displays a confirmation icon beside the order within 1 second
Delivery Under Poor Connectivity
Given intermittent network connectivity on mobile and display screens When an urgent ping is sent Then the system retries delivery up to 3 times at 5-second intervals and displays a queued delivery indicator until both channels confirm receipt
Acknowledgement and Escalation Workflow
"As a restaurant supervisor, I want unacknowledged urgent alerts to automatically escalate so that critical customer needs are never missed, even if the primary staff member is distracted."
Description

Design an acknowledgement system where staff must confirm they’ve seen each urgent ping. If no acknowledgment occurs within a configurable timeout (e.g., 30 seconds), the system escalates the alert by reopening the flash cycle and sending an additional notification to a supervisor or secondary device until it’s confirmed.

Acceptance Criteria
Staff Acknowledges Ping Within Timeout
Given an urgent ping is sent, When a staff member taps 'Acknowledge' on the kitchen dashboard or device within 30 seconds, Then the flashing notification stops immediately, the alert is marked as acknowledged in the system, and the acknowledgment timestamp is recorded.
Escalation Trigger Post Timeout Without Acknowledgment
Given an urgent ping remains unacknowledged for the configured timeout (default 30 seconds), When the timeout expires, Then the system automatically reopens the flashing cycle on the original device and logs an escalation event.
Notification Received by Supervisor on Escalation
Given an urgent ping has escalated after the initial timeout, When escalation occurs, Then a high-priority notification is sent to the supervisor or secondary device, the alert flashes on that device, and a separate escalation log entry is created.
Configurable Timeout Adjustment Reflects Correctly
Given the administrator updates the acknowledgment timeout to a new value (e.g., 45 seconds), When the next urgent ping is generated, Then the system enforces the updated timeout duration before triggering escalation.
Dashboard Flash Cycle Reopens on Escalation
Given an urgent ping has not been acknowledged and reached its timeout, When escalation is triggered, Then the kitchen dashboard’s flash indicator resets its cycle (e.g., re-flashes 5 more times) and shows an escalation badge until acknowledgment.

Quick Presets

Offers one-tap message templates for common requests (e.g., extra napkins, no onions, gluten-free), allowing customers to communicate their needs instantly while reducing response time for kitchen staff.

Requirements

Quick Preset Selection
"As a customer, I want to tap a preset button for my common requests so that I can communicate my needs instantly and accurately."
Description

Implement a user interface component within the TableHop mobile and web apps that displays a list of commonly used order modification messages (e.g., extra napkins, no onions, gluten-free) as one-tap buttons. The component should be accessible on the checkout summary and order detail screens, allow seamless integration with existing order data, and visibly confirm selection. This feature will reduce customer input time, minimize keystrokes, and ensure consistent communication of special requests to kitchen staff for faster, error-free fulfillment.

Acceptance Criteria
Selecting a Quick Preset on Checkout Summary
Given the user is on the checkout summary screen, when they tap a quick preset button, then the corresponding message is added to the order’s special instructions.
Adding Multiple Quick Presets to an Order
Given the user taps multiple quick preset buttons in succession, then each selected message appears in the order’s instruction list without replacing previous selections.
Removing a Selected Quick Preset
Given the user taps a quick preset button that is already selected, then the corresponding message is removed from the order’s instruction list.
Visual Confirmation of Preset Selection
Given the user selects a quick preset, then the button visibly highlights and a confirmation toast appears stating “Preset added”.
Integration with Order Submission Payload
Given the user submits the order, then all selected quick presets are included in the API request payload under the special instructions field.
Preset Template Management
"As a restaurant owner, I want to manage the list of preset messages so that I can ensure customers see only relevant and up-to-date options."
Description

Build an administrative dashboard module that enables restaurant owners and managers to create, edit, reorder, and delete default preset messages available to customers. The interface should support categorization (e.g., condiments, dietary needs), previewing, and saving changes in real time. Integration with the central presets database will ensure changes propagate instantly to all customer apps, empowering restaurateurs to tailor messaging to their menu and service workflows.

Acceptance Criteria
Add New Preset Template
Given the manager is on the Preset Template Management dashboard When they click “Add New Preset” and fill in the Template Name, Category, and Message fields and click “Save” Then the new template is saved to the database, a success notification appears, and the template is immediately listed under the correct category
Modify Existing Preset Template
Given the manager selects an existing template and clicks “Edit” When they update the Template Name, Category, or Message and click “Save” Then the dashboard updates the template in the database, displays a confirmation message, and reflects the changes instantly without a full page reload
Reorder Preset Templates
Given the manager views templates within a category When they drag and drop templates to a new position Then the new order is saved automatically, persists after page refresh, and is reflected in the customer app listing
Remove Preset Template
Given the manager clicks the “Delete” icon next to a template When they confirm deletion in the modal dialog Then the template is removed from the database, a deletion confirmation appears, and the template no longer appears in the dashboard list
Live Category Assignment and Preview
Given the manager is creating or editing a template When they change the Category dropdown or update the Message field Then the preview pane updates in real time to show the selected category tag and final message as customers will see it
Custom Preset Creation
"As a frequent customer, I want to create and save my own preset messages so that I can reuse my favorite special requests quickly."
Description

Enable registered users to define and save their own custom message templates for special requests beyond the default library. The feature should include an input form with validation, a naming field, and options to edit or delete saved presets. Stored custom presets should sync across the user’s devices and appear alongside default presets during order checkout, enhancing personalization and repeat-order efficiency.

Acceptance Criteria
User creates a custom preset
Given a registered user on the custom preset creation form When the user enters a unique, non-empty name and valid message content Then the Save button is enabled and clicking it stores the preset, which appears immediately in the user’s preset list
User inputs invalid preset name
Given the user on the preset creation form When the user enters an empty or duplicate preset name Then a clear validation error message is displayed and the preset is not saved
User edits an existing custom preset
Given the user has at least one custom preset saved When the user selects Edit on a preset, modifies the name or message, and saves changes Then the updated preset replaces the old version in the list with the new name and message
User deletes a custom preset
Given the user has one or more custom presets When the user selects Delete on a preset and confirms the action Then the preset is removed from the list and no longer appears at checkout
Custom presets sync across devices
Given the user has created custom presets on one device When the user logs in on a second device within 60 seconds of creation Then all presets created or updated on the first device appear in the second device’s preset list
Real-time Kitchen Notification
"As kitchen staff, I want to see customer preset requests immediately on my order display so that I can prepare orders accurately without delays."
Description

Integrate the selected preset messages directly into the restaurant’s kitchen display system and order dashboard, ensuring that any tap on a preset instantly appends the request to the order ticket. The system should trigger a visual highlight or alert to kitchen staff for modifications, maintain audit logs of time stamps, and guarantee delivery even under intermittent connectivity to ensure no request is missed.

Acceptance Criteria
Single Preset Selection Under Stable Connection
Given the customer taps the “extra napkins” preset while online, When the message is sent, Then the request is appended to the order ticket within 1 second, a visual alert highlights the modification on the kitchen dashboard, and an audit log entry with a timestamp is created.
Multiple Preset Selections Queued
Given the customer selects “no onions” and then “gluten-free” presets before finalizing the order, When the order is confirmed, Then both requests are appended to the ticket in the sequence tapped, visual alerts display sequentially, and audit logs record each tap with its timestamp.
Offline Mode and Deferred Delivery
Given the device loses network connection after a preset tap, When connectivity is restored, Then the queued preset messages are delivered and appended to the kitchen dashboard, visual alerts trigger for each, and audit logs record both initial tap and delivery timestamps.
Audit Log Integrity Check
Given an order with preset modifications, When reviewing the order details in the admin interface, Then the audit log shows each preset, its tap timestamp, delivery timestamp, and delivery status.
Visual Alert Visibility During High Order Volume
Given the kitchen dashboard processes over 10 orders per minute, When a preset message is received, Then the visual highlight for the modified order remains visible for at least 5 seconds and adheres to the defined contrasting color in UI guidelines.
Preset Usage Analytics
"As a restaurant owner, I want to view analytics on which presets are most used and how they affect operations so that I can optimize our service offerings."
Description

Develop a reporting module that tracks the frequency, type, and performance impact of each preset message over time. Metrics should include total uses, usage per preset category, effect on order preparation time, and error reduction rates. Provide interactive charts and exportable data to help restaurant owners identify high-value presets, optimize menu options, and refine the presets library based on real customer behavior.

Acceptance Criteria
Daily Preset Usage Summary Viewed
Given the restaurant owner accesses the analytics dashboard When they select the daily view Then the system displays a table and chart showing total uses for each preset category for that day
Preset Performance Impact Analysis
Given the restaurant owner views preset impact metrics When comparing orders with and without presets Then the system shows average preparation times for each and calculates the percentage difference
Export Preset Analytics Data
Given the restaurant owner requests a data export When they click the export button Then the system generates and downloads a CSV file containing preset type, usage count, average prep time, and error reduction rates
Interactive Chart Filters Applied
Given the restaurant owner filters analytics by date range or preset category When they apply the filters Then the charts update within 2 seconds to reflect the selected criteria
High-Value Preset Identification Alert
Given the system processes weekly analytics When a preset exceeds 100 uses and yields over 10% reduction in prep time Then that preset is highlighted with an alert icon in the dashboard
Localization and Accessibility Support
"As a non-English-speaking or visually impaired customer, I want the presets feature to be in my language and accessible so that I can place orders without barriers."
Description

Ensure that the presets interface supports multiple languages and complies with accessibility standards (WCAG 2.1 AA). Implement dynamic translation of preset labels and descriptions, screen reader compatibility, keyboard navigation, and sufficient color contrast. This will make the quick presets feature usable by diverse customer demographics and inclusive of users with differing abilities.

Acceptance Criteria
Dynamic Translation of Preset Labels
Given a user selects their preferred language from the settings menu, when the Quick Presets interface loads, then all preset labels and descriptions are displayed in the chosen language within 1 second.
Screen Reader Compatibility
Given a user is navigating with a screen reader, when they tab to each preset button, then the screen reader announces an accessible name and description that matches the visual label and conveys its purpose.
Keyboard Navigation Through Presets
Given a user uses keyboard navigation, when they press Tab and Shift+Tab, then focus moves sequentially through each preset button and activation via Enter or Space triggers the correct preset action.
Color Contrast Compliance
Given the Quick Presets interface is displayed, then all text and interactive elements meet the WCAG 2.1 AA contrast ratio of at least 4.5:1 for normal text and 3:1 for large text in all presets states.
Fallback Language Handling
Given a preset has no translation available in the user’s selected language, when the interface loads, then the default (English) label and description are displayed and a missing-translation event is logged.

Instant Translate

Delivers real-time translation for messages in over 20 languages, enabling seamless communication between customers and kitchen staff regardless of language barriers, ensuring clarity and satisfaction.

Requirements

Real-time Language Detection
"As a restaurant manager, I want the system to automatically detect the language of incoming messages so that I can receive accurate translations without manually selecting languages."
Description

Automatically detect the source language of every incoming message from customers or kitchen staff and route it through the translation engine instantaneously, eliminating manual language selection and potential errors. This functionality ensures messages are correctly translated in real time, enabling seamless multilingual communication and improving order accuracy and response times.

Acceptance Criteria
Incoming Customer Message in Spanish
Given a customer sends a message in Spanish, when the message is received by TableHop, then the system auto-detects the language as Spanish within 500ms and forwards it to the translation engine without manual input, and the translated message in the recipient’s default language is delivered with 100% text fidelity.
Kitchen Staff Response in Mandarin
Given kitchen staff send a response in Mandarin, when the message is detected, then the system correctly identifies the source language, translates it into the customer’s preferred language within 500ms, and displays the translation without requiring manual language selection.
Rapid Consecutive Multilingual Messages
Given multiple messages in different supported languages are received consecutively within 1-second intervals, when each message arrives, then the system auto-detects each language and processes translations in sequence with no message loss and each translation completed within 1 second of receipt.
Unrecognized Language Handling
Given a customer sends a message in a language not supported by the system, when auto-detection is performed, then the system flags the language as unsupported, notifies the sender within 200ms, and prompts the sender to choose a supported language manually.
High Volume Message Translation
Given 100 messages in various supported languages are received within a 60-second window, when processed concurrently, then the system auto-detects and translates each message with an average processing time per message under 500ms and achieves a 0% translation failure rate.
Seamless Integration with Chat Interface
"As a kitchen staff member, I want translated messages to appear inline in the chat interface so that I can understand and respond to customer requests without leaving the conversation flow."
Description

Embed the instant translation feature directly within the existing messaging interface, providing inline translated text alongside the original message. This integration maintains chat continuity, reduces cognitive load, and ensures staff can respond promptly without switching contexts or applications.

Acceptance Criteria
Inline Translation Toggle
Given a chat message in a foreign language When a staff member clicks the translation icon Then the message is instantly replaced with the translated text inline
Automatic Language Detection
Given an incoming message When the system receives the message Then the language is detected automatically and translation is triggered without manual input
Real-Time Translation Update
Given an ongoing chat conversation When a new foreign-language message arrives Then the translated text appears within two seconds inline with the original message
Original and Translated Text Side by Side
Given a translated chat message When the staff views the message Then the original and translated texts are displayed side by side with clear visual separation
Handling Unsupported Languages
Given a message in an unsupported language When the system cannot translate Then a clear notification is displayed offering to use a default language fallback
Contextual Phrase Suggestions
"As a customer service representative, I want context-relevant phrase suggestions when communicating in another language so that I can quickly send accurate, culturally appropriate responses."
Description

Provide users with smart, context-aware translation suggestions for common phrases used in order modifications, dietary requests, and greetings to ensure translations are accurate and culturally appropriate. This feature enhances clarity and speeds up communication by offering pre-translated options suited to restaurant scenarios.

Acceptance Criteria
Order Modification Suggestion
Given a user types an order modification phrase (e.g., 'no onions please'), when the suggestions panel appears, then the system displays a context-aware translation suggestion (e.g., 'sin cebolla, por favor') that can be selected to replace the typed text.
Dietary Request Suggestion
Given a user selects or types a dietary request (e.g., 'gluten-free'), when the input is detected, then the system provides a culturally appropriate translation (e.g., 'sin gluten') with industry-specific terminology within 2 seconds.
Greeting Suggestion
Given a user begins a conversation with a greeting (e.g., 'Good evening'), when the message starts, then the system offers at least two appropriate greeting translations (e.g., 'Buenas tardes', 'Buenas noches') and enables insertion with one click.
Fallback Suggestions for Unknown Phrases
Given the user inputs a phrase not found in the phrase library, when no exact match is available, then the system returns the top three contextually relevant translation suggestions ranked by relevance score above the threshold.
Dialect and Locale-Specific Suggestions
Given the restaurant’s locale setting (e.g., Mexico City), when suggesting translations for ambiguous terms (e.g., 'tortilla'), then the system prioritizes dialect-specific translations (e.g., 'tortilla de maíz') and displays them at the top of the suggestions list.
Offline Translation Caching
"As a server, I want recent translations to be available offline so that I can continue communicating with non-English-speaking customers during network outages."
Description

Implement a local cache of recent translations and phrase libraries to allow the translation feature to function even when connectivity is intermittent. This ensures that critical communications between staff and customers remain uninterrupted, improving reliability and user trust.

Acceptance Criteria
Basic Offline Translation Retrieval
Given the user has recently translated a message and the device is offline, when the user requests translation of the same message, then the cached translation is displayed within 1 second without errors.
Offline Phrase Library Access
Given the device is in offline mode, when a staff member attempts to translate a phrase from the built-in library, then the system retrieves and displays the correct translation from the local cache 95% of the time.
Cache Synchronization Upon Reconnection
Given the device regains network connectivity, when the user initiates a sync, then all offline-translated messages and new phrase library entries are successfully uploaded to the server within 30 seconds.
Cache Eviction Under Storage Constraints
Given the local cache exceeds the 50MB storage limit, when a new translation is added, then the system evicts the least-recently-used translation entries until the total cache size is below the limit.
Fallback on Cache Miss in Offline Mode
Given the device is offline and the requested translation is not in the cache, when the user requests the translation, then the system displays a clear error message and offers to retry when back online.
Accuracy Feedback Loop
"As a kitchen staff member, I want to provide feedback on translation accuracy so that the system can learn and refine translations to better match our restaurant’s terminology."
Description

Allow staff to submit feedback on translation accuracy and suggest corrections, feeding this data back into the model to continuously improve translation quality over time. This mechanism helps tailor translations to restaurant-specific terminology and enhances future communication.

Acceptance Criteria
Real-time Correction Submission
Given a staff member views a translated customer message When they select 'Suggest Correction' and submit corrected text Then the system stores both the original and corrected translations in the feedback database and displays a confirmation message to the staff
Feedback Processing Queue Integration
Given feedback submissions have been stored When the feedback processing service runs Then each entry is queued for model retraining with correct metadata (timestamp, language pair, restaurant ID) and no data loss occurs
Terminology Glossary Enhancement
Given a submitted correction contains a new restaurant-specific term When the feedback is processed Then the term is added to the restaurant’s translation glossary with the approved corrected translation and marked for linguistic review
Staff Feedback History Access
Given a staff member opens the feedback dashboard When they filter or sort feedback history Then the system displays all past corrections with statuses (Pending, Processed) sorted by submission date
Translation Quality Improvement Verification
Given processed feedback has been integrated into the translation model When new translations are generated Using restaurant-specific terminology Then translation accuracy for corrected phrases improves by at least 15% as measured by post-update user satisfaction ratings or automated quality metrics

DishSnap Confirm

Enables customers to attach a photo of their selected dish or ingredient list directly within the chat, giving kitchen staff visual confirmation of the order and minimizing mistakes in customizations.

Requirements

Photo Attachment Interface
"As a customer, I want to attach a photo of my selected dish or ingredients within the chat so that kitchen staff can see exactly what I want and reduce customization errors."
Description

Integrate a photo attachment feature within the customer chat module, allowing users to upload images from their device camera or gallery. The interface should support common image formats (JPEG, PNG) and provide a seamless attachment button within the chat input area. Uploaded photos must display as thumbnails before sending and attach to the corresponding order.

Acceptance Criteria
Camera Photo Upload
Given a user is in the chat input area, when they tap the attachment button and choose the device camera, then they can capture a photo and see it listed as an attachment ready to send.
Gallery Photo Upload
Given a user is in the chat input area, when they tap the attachment button and select a photo from their device gallery, then the chosen image is attached to the chat and displayed as a thumbnail.
Unsupported File Format Handling
Given a user attempts to attach a file in an unsupported format (e.g., GIF, BMP), when they select the file, then the system displays an error message stating only JPEG and PNG formats are allowed and prevents the attachment.
Thumbnail Preview Display
Given a user has selected a valid JPEG or PNG image for attachment, when the file is processed, then the chat input area shows a thumbnail preview of the image within 2 seconds of selection.
Order Association Verification
Given a user attaches one or more photos and submits their order, when the restaurant staff views the order details, then all attached images are visible and correctly linked to that specific order.
Image Preview and Annotation
"As a customer, I want to preview and crop my dish photo before sending so that the image clearly shows my customization details."
Description

Enable customers to preview, crop, rotate, and annotate their uploaded dish photos before sending. The feature should provide simple editing tools to highlight specific customization details or ingredients, ensuring clarity in the visual confirmation sent to the kitchen.

Acceptance Criteria
Photo Upload Preview
Given a user uploads a valid image file, when the upload completes, then the original image is displayed in the preview panel with accurate dimensions and no distortion.
Image Cropping Functionality
Given the image preview is displayed, when the user selects a crop region and applies the crop, then the preview updates to show only the cropped area, and the cropped image meets minimum dimension requirements (e.g., at least 200x200 pixels).
Image Rotation Functionality
Given the image preview is displayed, when the user clicks rotate buttons (left or right), then the image rotates by 90 degrees per click and the rotation persists in the final image.
Annotation Tool Usage
Given the image preview is displayed, when the user selects annotation tools (pen, highlighter, text), then they can draw or type on the image, change color and stroke width, and annotations render correctly and can be undone/redone.
Edited Image Submission
Given the user finalizes edits and sends the image, when the user clicks 'Send', then the edited image (with crops, rotations, annotations) is transmitted to the kitchen chat and displays correctly for staff, matching the user's preview.
Backend Image Storage and Linking
"As a system administrator, I want all uploaded dish images stored and linked to orders in the database so that we maintain an audit trail and ensure accurate retrieval of visual confirmations."
Description

Implement secure backend storage for all uploaded dish photos, linking each image record to its order in the database. Ensure images are stored with metadata including upload timestamp, order ID, and customer ID. Define a retention policy and access controls to protect customer privacy.

Acceptance Criteria
Image Upload and Metadata Recording
Given a valid image file and order details, when the image is uploaded, then the system stores the image in secure backend storage, creates a database record containing the upload timestamp accurate to within 1 second, the correct order ID, and customer ID, and returns a 201 Created response.
Order-Image Link Verification
Given an existing order with an associated image, when order details are requested via API or dashboard, then the response includes the image URL, metadata (upload timestamp, order ID, customer ID), and the link correctly references the stored image.
Access Control and Privacy Compliance
Given a request to view or download a stored image, when the requester is authenticated and authorized for the associated order, then the system returns the image securely; if unauthorized, the system returns a 403 Forbidden error.
Image Retention and Purge Policy Enforcement
Given images and metadata older than the defined retention period (e.g., 90 days), when the scheduled purge job runs, then the system permanently deletes the image files and metadata from storage and database, and verifies no residual references remain in order records.
Error Handling During Image Upload
Given an invalid or corrupted image file or missing required metadata, when the upload is attempted, then the system rejects the upload with a 400 Bad Request response and descriptive error message without creating any storage or database records.
Kitchen Notification Workflow
"As a kitchen staff member, I want to receive instant notifications with attached dish images in my order dashboard so that I can visually confirm custom requests before preparation."
Description

Extend the kitchen dashboard to display image thumbnails alongside new incoming orders. When an order with an attached photo arrives, kitchen staff should receive an instant visual notification and be able to click the thumbnail for a full-size view, ensuring they confirm custom requests before preparation.

Acceptance Criteria
Order with Attached Dish Image
Given an order includes a customer-uploaded photo, when the order appears on the kitchen dashboard, then a thumbnail of the photo is displayed next to the order within 2 seconds.
Thumbnail Click Opens Full-Size Image
Given a thumbnail is displayed for an order, when a kitchen staff member clicks the thumbnail, then the system opens a modal showing the full-size image at original resolution with zoom controls.
No-Attachment Order Display
Given an order without an attached photo arrives, when it appears on the dashboard, then no thumbnail space is reserved and orders are listed without image elements.
Visual and Audible Alert for Photo Orders
Given an order with an attached photo arrives, when it is delivered to the dashboard, then the system triggers a visual highlight animation and an audible alert within 1 second.
Thumbnail Load Performance
Given multiple orders with attached photos appear simultaneously, when the dashboard loads, then all thumbnails render correctly within 3 seconds without impacting dashboard responsiveness.
Image Quality Validation
"As a customer, I want the system to validate the quality of my uploaded photo and prompt me if it’s too low resolution so that kitchen staff can correctly identify my order."
Description

Incorporate client-side validation to check the resolution, file size, and clarity of uploaded photos. If an image does not meet the minimum quality thresholds, prompt the user to reupload or choose a different photo, ensuring the kitchen receives usable visual confirmations.

Acceptance Criteria
Low-resolution Image Upload
Given a user selects an image with resolution below 800x600 pixels, when the upload is attempted, then the system displays an error message 'Image resolution too low. Please upload at least 800x600 pixels.' and prevents submission.
Oversized Image Upload
Given a user selects an image larger than 5 MB in file size, when the upload is attempted, then the system displays an error message 'File size exceeds 5 MB. Please choose a smaller image.' and blocks the upload.
Blurry Image Upload
Given a user selects an image with a clarity score below the acceptable threshold (e.g., variance of Laplacian < 100), when the upload is attempted, then the system displays an error 'Image appears blurry. Please upload a clearer photo.' and requires a new selection.
Valid High-Quality Image Upload
Given a user selects an image meeting resolution, file size, and clarity thresholds, when the upload is completed, then the system accepts the image, displays a preview thumbnail, and enables the user to proceed with order confirmation.
Image Reupload After Validation Failure
Given a previous upload failed validation, when the user selects a new image, then the system revalidates against all quality criteria without retaining the previous error state, and allows submission if the new image passes.

Request Insights

Provides kitchen managers with analytics on chat interactions, highlighting frequent requests, peak special-order times, and error reduction metrics to help optimize menu offerings and staff training.

Requirements

Real-Time Chat Logging
"As a kitchen manager, I want all chat interactions logged in real time so that I can analyze communication patterns and identify areas for staff training immediately."
Description

Automatically capture and log all customer–staff chat interactions in real time, with the ability to filter and search by date, customer, or agent. Integrate this log into the Request Insights dashboard to provide immediate visibility into communication patterns, enabling managers to identify training needs and process bottlenecks as they occur.

Acceptance Criteria
Instant Log Capture During Active Conversation
Given a customer and staff member are exchanging messages in the chat interface, When either party sends a message, Then the system logs the message within 1 second of sending, And the log includes timestamp, sender ID, recipient ID, and message content.
Filter Logs by Date, Customer, and Agent
Given the chat logs dashboard is open, When the manager selects a date range and/or enters a customer name or agent ID, Then the system filters and displays only the logs matching the selected criteria, And the filter response time is under 2 seconds.
Search Chat Logs with Keyword Query
Given the manager enters a keyword into the search bar, When they submit the search, Then the system returns all chat logs containing the keyword in the selected date range, And highlights the keyword occurrences in the log view within 3 seconds.
Real-Time Log Integration into Dashboard
Given the Request Insights dashboard is open, When new chat messages are logged, Then the dashboard updates its visualizations and latest logs pane automatically, And the new entries appear within 5 seconds without manual refresh.
Export Filtered Chat Logs to CSV
Given the manager has applied filters or search criteria, When they click the 'Export Logs' button, Then the system generates a CSV file containing only the displayed logs, And initiates a file download within 10 seconds.
Frequent Request Heatmap
"As a kitchen manager, I want a heatmap of the most frequent requests so that I can adjust menu offerings and inventory accordingly."
Description

Generate a dynamic heatmap of the most frequently requested special orders and menu modifications over selectable time periods. Integrate with both chat logs and order data to highlight top custom requests, enabling data-driven menu optimization and inventory planning based on actual customer preferences.

Acceptance Criteria
Weekend Peak Special Requests Visualization
- The heatmap displays the top 10 most frequent special orders during weekend periods (Fri 6pm to Sun midnight). - Users can select the weekend date range via the time period selector and the heatmap updates within 3 seconds. - Data includes combined counts from order entries and chat log requests for accuracy. - The heatmap highlights each item with a color scale representing frequency, with a legend indicating frequency ranges.
Weekday Lunch Customization Trend Analysis
- The heatmap shows the top 5 customizations requested daily between 11am–2pm for any selected weekday. - Selecting a specific weekday filters the heatmap to only that day’s lunch period within 2 seconds. - Only customization requests (add-ons, modifications) are included; base menu items without modifications are excluded. - The frequency data reflects actual served orders, matching order database records.
Monthly Special Order Comparison
- Users can select two distinct months to compare special order frequencies side by side. - The system renders two heatmaps simultaneously, one per month, each showing the top 10 requests. - Selecting new months re-renders both heatmaps within 3 seconds. - Frequency differences between months are highlighted by a color differential indicator.
Inventory Planning Heatmap Export
- Users can export the current heatmap data as a CSV file containing item names, frequencies, and time periods. - The exported CSV matches the on-screen heatmap data, with no discrepancies in counts or labels. - Export functionality is accessible via a button labeled "Export Heatmap Data" and initiates download within 5 seconds.
Chat Log and Order Data Integration Validation
- The heatmap’s frequency counts match combined chat log request counts and order data entries for the selected time period. - A sample data set with known values yields identical heatmap frequencies when processed. - Any mismatches between chat and order data trigger an alert in the UI indicating integration errors.
Peak Special-Order Timeline Analytics
"As a kitchen manager, I want to see peak times for special orders so that I can optimize staffing and prep schedules."
Description

Provide time-series analytics showing peak times for special and custom orders, with filters for daily, weekly, and monthly views. Overlay order volume and staff workload to help managers optimize staffing levels and prep schedules during busy periods, reducing wait times and improving order accuracy.

Acceptance Criteria
Daily Peak Identification Scenario
Given the kitchen manager selects the daily filter on the special-order timeline When the timeline is generated for the selected date Then the system highlights the hour with the highest special-order volume and displays the total order count for that hour
Weekly Filter Application Scenario
Given the kitchen manager switches to the weekly view When the timeline is rendered Then the system aggregates special-order data by day, identifies the peak day, and shows its order volume
Monthly View Overlay Scenario
Given the kitchen manager applies the monthly filter When the system generates the timeline Then the timeline overlays daily special-order volumes with daily average staff workload and marks the top three busiest days
Staff Workload Correlation Scenario
Given the kitchen manager enables the workload overlay When the timeline is updated Then the system displays correlated graphs of special-order volume and staff utilization side by side for the selected period
Comparative Period Analysis Scenario
Given the kitchen manager selects two custom date ranges for comparison When the system processes the request Then it displays side-by-side timelines of special-order volumes for both periods and highlights the percentage change in peak volumes
Error Reduction Metrics
"As a kitchen manager, I want to view error reduction metrics to measure the impact of training and process changes on order accuracy."
Description

Track and display error rates for special orders before and after training or process changes, calculating reduction percentages and trend lines. Integrate with order fulfillment logs to visualize improvements over time and demonstrate the effectiveness of staff training initiatives.

Acceptance Criteria
Baseline Error Rate Calculation
Given historical order data for the past 30 days, when the manager opens the Error Reduction Metrics dashboard, then the system calculates and displays the baseline special order error rate as a percentage with two decimal places.
Percentage Reduction Calculation
Given baseline and post-training error rates, when a training date filter is applied, then the system computes and displays the percentage reduction between the two error rates accurately.
Trend Visualization Rendering
Given daily error rate data over the last 90 days, when the dashboard loads, then a trend line chart is rendered showing daily special order error rates with correctly labeled axes and data point tooltips.
Data Integration with Fulfillment Logs
Given new order fulfillment logs are received, when the logs are ingested, then the system updates error counts and recalculates all related metrics within five minutes.
Report Export Functionality
Given a filtered view of the Error Reduction Metrics dashboard, when the manager clicks the export button, then a CSV report is downloaded containing date, total orders, special order errors, baseline rate, post-training rate, and reduction percentage.
Automated Report Export & Alerts
"As a kitchen manager, I want to receive automated reports and threshold alerts so that I can stay informed and react promptly to analytics insights."
Description

Enable exporting analytics reports in CSV and PDF formats and configure custom threshold alerts (e.g., when request volumes exceed predefined limits). Integrate with email and SMS notification systems to deliver timely insights and prompt managers to take action when key metrics warrant immediate attention.

Acceptance Criteria
Export Reports in CSV Format
Given analytics data is available When the manager chooses “Export as CSV” Then a CSV file downloads containing all selected fields with correct headers and data values
Export Reports in PDF Format
Given analytics data is available When the manager selects “Export as PDF” Then a PDF document downloads displaying the report in a readable layout with charts and tables matching on-screen data
Configure Custom Threshold Alerts
Given the manager accesses the alerts settings When the manager sets a threshold for request volume or error rate Then the system saves the threshold, displays a confirmation, and lists it among active alerts
Send Alerts via Email
Given an active threshold is exceeded When the system detects that threshold breach Then an email alert is sent to the manager’s configured address within 5 minutes with relevant metrics and timestamp
Send Alerts via SMS
Given an active threshold is exceeded When the system detects that threshold breach Then an SMS is sent to the manager’s registered phone number within 5 minutes containing the alert summary

BioPay Unlock

Leverages device-native biometric authentication (Face ID, Touch ID) to instantly authorize payment with a simple scan—eliminating PINs and passwords for a frictionless, secure checkout under three seconds.

Requirements

Biometric Enrollment Module
"As a customer, I want to enroll my fingerprint or facial recognition on TableHop so that I can quickly and securely pay without entering a PIN."
Description

Enable users to enroll their device-native biometric credentials (e.g., Face ID, Touch ID) within the TableHop app. Utilize secure OS-level biometric APIs to capture and store a cryptographic token representing the user’s biometric profile, without storing actual biometric data. Provide an interface for users to view, add, or remove enrolled biometric methods, ensuring seamless integration with user account settings and maintaining compliance with platform security guidelines.

Acceptance Criteria
User Initiates Biometric Enrollment
Given a logged-in user without enrolled biometrics When they navigate to Settings > Biometric Enrollment and tap “Enable Face ID” Then the OS-level biometric prompt appears within 2 seconds and on successful authentication a cryptographic token is generated and stored securely
Secure Token Storage
Given the OS returns a successful biometric authentication token When enrollment completes Then the app stores only the cryptographic token in encrypted storage and does not log or persist any raw biometric data
Manage Biometric Methods
Given a user has an enrolled biometric method When they view the Biometric Enrollment screen Then they see the enrolled method listed and can remove it via a “Remove” action which deletes the token and disables biometric checkout
Handle OS Enrollment Failure
Given the OS biometric enrollment fails or is not available When the user attempts to enroll Then the app displays an error message explaining the issue and disables the enroll button until OS-level biometric configuration is resolved
Restrict Enrollment to Authenticated Devices
Given an unauthenticated session on a user’s device When the app is launched Then the Biometric Enrollment option is hidden or disabled until the user successfully logs in
Instant Biometric Authorization
"As a user, I want to authenticate my payment with a simple biometric scan so that I can complete my order quickly and securely without typing a password."
Description

Implement checkout flow integration that invokes the device’s native biometric prompt (Face ID, Touch ID) to authorize payments in under three seconds. Ensure the process calls the payment gateway only after successful biometric validation, handles API responses gracefully, and provides a secure transaction token. Optimize for speed and reliability to deliver a frictionless user experience.

Acceptance Criteria
Face ID Authentication Success
Given a user with Face ID enrolled, when they confirm payment on the checkout screen, then the Face ID prompt must appear within 1 second, and upon a successful scan completed in under 3 seconds, the system invokes the payment gateway with a valid secure transaction token.
Touch ID Authentication Success
Given a user with Touch ID enrolled, when they confirm payment on the checkout screen, then the Touch ID prompt appears within 1 second, and upon a successful fingerprint scan under 3 seconds, the system invokes the payment gateway with a valid secure transaction token.
Biometric Timeout Fallback
Given the biometric prompt fails to complete within 5 seconds, when the timeout threshold is reached, then the system displays a fallback PIN entry screen and does not call the payment gateway until the correct PIN is entered.
Payment Gateway Invocation After Successful Biometric
Given a successful biometric authorization, when the biometric validation completes, then the client calls the payment gateway endpoint within 500ms with the transaction details and secure token, and waits for a response status code of 200 before confirming the payment.
Error Handling on Payment Gateway Failure
Given the payment gateway returns an error response, when the client receives a non-200 status, then the app displays a clear error message to the user within 2 seconds and logs the error for retry or support intervention without exposing sensitive information.
Fallback Authentication Mechanism
"As a user, I want an alternative login method if my biometric scan fails so that I can still complete my payment."
Description

Design and integrate a secondary authentication option allowing users to enter a PIN or password when biometric authentication is unavailable or fails. Ensure secure input fields, validation logic, and clear messaging to switch between biometric and fallback methods. Maintain consistent security standards across both authentication paths.

Acceptance Criteria
Fallback PIN Entry After Biometric Unavailability
Given the device’s biometric sensor is unavailable, when the user taps “Use PIN instead”, then a secure PIN input field is displayed within 2 seconds and accepts exactly a 6-digit numeric PIN.
Switch to Password Authentication on Repeated Biometric Failures
Given the user has two consecutive biometric authentication failures, when the user selects “Use password”, then the password field enforces a minimum of 8 characters including at least one uppercase letter, one digit, and one special character.
Secure Masked Input for PIN
Given the PIN input screen is displayed, when the user enters their PIN, then each digit is masked immediately and clipboard copy/paste is disabled.
Validation Error Message Display
Given the user submits an invalid PIN or password, when validation fails, then an inline error message appears stating “Invalid credentials. Please try again.” and the input field is highlighted in red.
Seamless Return to Biometric Option
Given the user is on the fallback authentication screen, when the biometric sensor becomes available again, then a “Use Face ID/Touch ID” button is displayed and enabled without refreshing the page.
Authentication UI and Error Handling
"As a user, I want clear prompts and feedback during biometric authentication so that I understand whether my scan was successful or why it failed."
Description

Develop intuitive UI components for biometric authentication prompts, including success indicators, failure messages, and retry options. Provide real-time feedback (e.g., progress spinners, error tooltips) and handle edge cases such as sensor unavailability or user cancellation. Ensure accessibility compliance and consistency with the app’s design system.

Acceptance Criteria
Successful Biometric Authentication
Given the user has enrolled biometrics and initiates BioPay, When the user completes a Face ID/Touch ID scan, Then payment is authorized in under 3 seconds and a green success indicator appears.
Authentication Failure with Retry
Given the biometric scan fails, When the user is shown an error tooltip, Then the error message describes the cause and a ‘Retry’ button is available and functional.
Sensor Unavailability Fallback
Given the device’s biometric sensor is unavailable or disabled, When the user attempts BioPay, Then the UI offers a PIN entry fallback within 2 seconds and clearly explains the alternate method.
User Cancellation Handling
Given the biometric prompt is active, When the user taps ‘Cancel’, Then the prompt closes immediately, and the user is returned to the payment screen without processing a transaction.
Accessibility Compliance
Given a user with accessibility needs, When the biometric prompt appears, Then it must be fully navigable via screen reader and voice control, with all labels and buttons correctly announced.
Security Logging and Compliance
"As a security officer, I want to review logs of each authentication attempt so that we can audit transactions and ensure compliance with security standards."
Description

Implement detailed logging for each authentication event, capturing metadata such as timestamp, user ID, authentication method, and result status. Ensure logs do not store sensitive biometric data. Integrate with existing security monitoring tools and maintain compliance with PCI DSS and GDPR requirements. Provide an audit interface for administrators to review authentication records.

Acceptance Criteria
Authentication Event Logging
Given a user attempts authentication using Face ID or Touch ID; When the authentication process completes (success or failure); Then the system logs a record containing timestamp, user ID, authentication method, and result status in the secure logging store.
Sensitive Data Exclusion
Given any log record is generated; Then it must exclude raw biometric data (e.g., face maps, fingerprints) and only include metadata fields: timestamp, user ID, authentication method, and result status.
Security Monitoring Integration
Given new authentication log entries are created; When entries are available; Then they are forwarded to the existing security monitoring tool within 5 seconds; And any transmission failures generate an alert for the security operations team.
PCI DSS and GDPR Compliance Enforcement
Given log entries reach retention thresholds; Then the system automatically applies PCI DSS and GDPR retention/deletion rules (e.g., purge logs older than specified period); And ensures data subject requests for log deletion are honored within regulatory timeframes.
Administrator Audit Interface Functionality
Given an authenticated administrator accesses the audit interface; When they apply filters by date range, user ID, or authentication method; Then the interface displays the matching log entries; And provides an option to export results as a CSV file.

AutoTender

Intelligently selects the optimal saved payment method based on factors like order size, loyalty rewards, and past preferences—ensuring you always pay with the card or wallet that gives you the best value and fastest processing.

Requirements

Payment Method Scoring Algorithm
"As a busy customer, I want the system to pick the best card automatically so that I maximize rewards and minimize transaction time."
Description

Develop an intelligent scoring engine that evaluates each saved payment method against dynamic criteria—order total, merchant-specific offers, card issuer promotions, loyalty tier benefits, and historical processing speed. The system should calculate a composite score in real time to identify the optimal method for each transaction. This algorithm will run client-side or server-side with minimal latency, seamlessly integrating into the checkout flow to automatically select the best card or wallet without additional user input.

Acceptance Criteria
Optimal Loyalty Points Selection
Given the user has multiple saved payment methods with varying loyalty benefits, when the order total is finalized, then the algorithm calculates the total loyalty points each method would earn and selects the method with the highest points.
Best Promotional Offer Utilization
Given available merchant-specific and issuer promotions, when an order qualifies for promotions, then the algorithm computes the discount for each method and selects the one with the maximum monetary benefit.
Fastest Transaction Processing Tie-breaker
Given two methods yield equal composite scores, when processing time metrics are available, then the algorithm selects the method with the historically faster authorization and settlement time.
Real-time Low-latency Scoring
Given the scoring engine operates under network constraints, when a scoring request is made, then the algorithm returns the selected method within 150 milliseconds in 95% of transactions.
Default Method Fallback
Given no method provides additional benefits, when the scoring is applied, then the algorithm defaults to the user's primary saved payment method.
Rewards and Discounts Integration
"As a value-conscious diner, I want to earn the highest possible rewards on every order so that I save money over time."
Description

Implement integration with loyalty programs, credit card issuer offers, and in-app promotional discounts. The feature must fetch and apply eligible reward rates, cash-back percentages, and coupon codes associated with each payment method. It should reconcile these incentives with the scoring algorithm to ensure the chosen payment method yields the highest net value for the customer.

Acceptance Criteria
Fetching and Applying Multiple Rewards
Given the user has multiple saved payment methods with associated loyalty program reward rates, when the user initiates a payment, then the system fetches and displays the reward rates and cash-back percentages for each method; and the system accurately computes and displays the net value for each option.
Applying In-App Promotional Coupons
Given the user has a valid in-app coupon code saved, when the user applies the coupon in checkout, then the system validates the coupon, applies the discount to the calculation, and recalculates the net value of the selected payment method.
Selecting Highest Net Value Payment Method
Given the system has computed net values for all eligible payment methods including rewards and discounts, when recommending a payment method, then the system selects the method with the highest net value and highlights it as the default choice.
Handling Expired or Invalid Offers
Given some saved payment methods have expired or invalid reward offers, when the system retrieves reward data, then invalid or expired offers are excluded from calculations and only valid incentives are considered.
Fallback on Rewards API Failure
Given the rewards integration API is unavailable or returns an error, when the user proceeds to payment, then the system bypasses reward retrieval, notifies the user of limited incentive data, and defaults to the user's primary payment method without blocking the transaction.
User Payment Preferences Override
"As a cautious user, I want to lock in my preferred card so that I know exactly which account will be charged."
Description

Allow customers to set explicit preferences or exclusions for their saved payment methods. Provide an interface for users to pin a preferred card, exclude certain cards from AutoTender selection, or define payment method priority tiers. The system should respect these overrides before applying algorithmic selection, ensuring user control remains paramount.

Acceptance Criteria
Pin Preferred Card
Given a user with multiple saved payment methods When the user pins a card as preferred Then the preferred card is automatically selected by AutoTender on checkout And the pinned card appears at the top of the payment method list
Exclude Specific Card
Given a user marks a saved card as excluded When AutoTender runs to select a payment method Then the excluded card is not considered for selection And the user cannot choose the excluded card via AutoTender
Define Priority Tiers
Given a user assigns priority tiers to their saved cards When processing an order Then AutoTender selects the highest-priority available card According to the user-defined tier order
Override AutoTender at Checkout
Given a user has a pinned or algorithm-selected card When the user manually chooses a different payment method at checkout Then the manual selection overrides the pinned preference and AutoTender algorithm And the order is processed using the manually selected method
Persist Payment Preferences
Given a user sets or updates pinned, excluded, or tiered preferences When the user logs out and logs back in Then all preferences remain unchanged And AutoTender applies these settings on subsequent orders
Fallback Payment Handler
"As a user experiencing a decline, I want the app to retry with another card so that my order isn’t interrupted."
Description

Design a robust fallback mechanism that sequentially attempts alternate saved payment methods if the primary selection fails (e.g., declined, network error). The handler should notify the user of each retry attempt and request confirmation on switch if multiple failures occur. This ensures orders can still be completed without manual payment re-entry.

Acceptance Criteria
Primary Payment Declined, Secondary Method Used
Given the primary payment method is declined; When the payment gateway returns a 'decline' response; Then the system must attempt payment with the secondary saved method within 2 seconds; And the order must complete successfully using the secondary method; And the user must receive a notification indicating the fallback payment method used.
Network Error Triggers Fallback to Next Method
Given a network timeout or connectivity error occurs during processing of the primary payment; When the system detects the network error; Then it must automatically retry payment with the next available saved method within 3 seconds; And the order must complete successfully if the retry succeeds; And the user must receive a notification indicating the network error and fallback activation.
User Confirmation After Two Consecutive Failures
Given two consecutive payment failures (declined or network error) on the primary and secondary methods; When the second failure is detected; Then the system must pause further automatic retries and prompt the user to confirm proceeding with another saved method; And no additional payment attempts must occur without explicit user confirmation; And the prompt must display available saved methods for selection.
Handling Exhaustion of All Saved Payment Methods
Given all saved payment methods (primary, secondary, tertiary, etc.) fail to process the payment; When the final available method fails; Then the system must halt further payment attempts; And display an error message advising the user to add or update a payment method; And the order must remain pending until a valid payment is provided.
Fallback Retry Counter Reset for New Transactions
Given a user initiates a new order after previous payment failures; When the new order process begins; Then the system must reset all fallback retry counters and status flags; And start payment attempts beginning with the primary method as if no prior failures occurred; And ensure no residual retry state affects the new transaction.
Admin Configuration Dashboard
"As a restaurant owner, I want to configure payment optimization settings so that I can align AutoTender with my business priorities."
Description

Create an administrative interface within the merchant portal where restaurant staff can enable or disable AutoTender, adjust scoring weights (e.g., prioritize speed over rewards), and view analytics on payment method selections. This dashboard will provide insights into transaction success rates and customer savings, empowering restaurateurs to fine-tune the experience.

Acceptance Criteria
Enable/Disable AutoTender Feature Toggle
Given an admin is on the Admin Configuration Dashboard When the admin toggles the AutoTender switch to "On" Then new customer orders must use the AutoTender algorithm; and when toggled to "Off" Then new orders must bypass AutoTender and follow the standard payment flow; and the toggle state must persist after page reload and across sessions.
Adjust Scoring Weight Parameters
Given an admin enters numerical values for speed, rewards, and preference weights When the admin clicks "Save Weights" Then the system must validate that each value is between 0 and 100 and that all weights sum to 100% before applying them to the AutoTender selection algorithm; and display an error message if validation fails.
View Payment Method Selection Analytics
Given an admin selects a date range on the analytics panel When the admin clicks "Generate Report" Then the dashboard must display a table and chart showing the count and percentage of each payment method chosen by AutoTender within 30 seconds, accurately reflecting transaction data for the selected period.
Access Transaction Success Rate Dashboard
Given an admin navigates to the "Transaction Success Rate" tab When the page loads Then the system must show the total number of transactions processed via AutoTender, the number of successful vs failed transactions, and allow the admin to filter results by date and export raw data as a CSV within one click.
Monitor Customer Savings Reports
Given an admin selects a reporting timeframe When the admin clicks "View Savings" Then the dashboard must calculate and display the total and per-order customer savings achieved through reward-optimized payments, include a bar chart of savings by day, and provide a download button for a CSV export of the detailed report.

TipFlow Slider

Integrates a dynamic tipping slider directly into the one-tap checkout flow—letting you effortlessly adjust gratuity before payment without adding extra steps or delays, boosting satisfaction for customers and staff alike.

Requirements

Backend Tip Data Integration
"As a restaurant owner, I want tipped amounts recorded accurately in the order system so that I can reconcile payments and maintain transparent financial reporting."
Description

Ensure the selected tip amount is captured in the order payload, stored in the database, transmitted to payment processors, and reflected in receipts and reporting dashboards to maintain accurate financial records and reconciliation.

Acceptance Criteria
Tip amount added to order payload
Given a user selects a tip amount in the TipFlow Slider When the order is submitted Then the order payload includes a "tip_amount" field with the selected value
Tip information stored in database
Given the backend receives an order payload containing "tip_amount" When the order is persisted to the database Then the order record contains a "tip_amount" column matching the payload value
Tip forwarded to payment processor
Given an order stored with a "tip_amount" When the backend sends the payment request to the payment processor Then the tip amount is included in the transaction details and processed as gratuity
Tip displayed on customer receipt
Given a completed payment that includes a tip amount When generating the customer receipt (digital or printed) Then the receipt shows both the tip amount and the updated total amount
Tip reflected in reporting dashboard
Given multiple orders with various tip amounts in the system When querying the financial reporting dashboard for tip totals Then the dashboard aggregates and displays the correct sum of all tip_amount values
Dynamic Tip Slider UI Component
"As a customer, I want to adjust my tip using a slider in checkout so that I can quickly set gratuity before payment without extra steps."
Description

Integrate a responsive tipping slider into the one-tap checkout interface, allowing users to select a gratuity percentage between 0% and 30% with smooth drag-and-drop interaction, clear visual markers, and real-time feedback.

Acceptance Criteria
Dragging Tip Slider Updates Tip Percentage
Given the user is on the one-tap checkout screen, When the user drags the tip slider to a new position, Then the displayed tip percentage updates in real time and the total payment amount recalculates accordingly.
Selecting Predefined Tip Values
Given the slider shows predefined markers at 0%, 10%, 15%, 20%, 25%, and 30%, When the user taps on any marker, Then the slider thumb moves to the selected marker and the tip percentage and total amount update instantly.
Responsive Slider on Multiple Devices
Given the one-tap checkout interface is viewed on devices with screen widths from 320px to 1920px, When the tip slider is displayed, Then the slider is fully visible and functional without overflow or clipping at each tested breakpoint.
Real-Time Tip and Total Amount Feedback
Given the user adjusts the tip percentage via dragging or tapping, When the tip percentage changes, Then the tip amount and updated order total are displayed and accurate within a $0.01 rounding tolerance.
Accessibility Support for Tip Slider
Given a user navigates via keyboard or screen reader, When the tip slider receives focus, Then users can adjust the tip in 1% increments using arrow keys, and screen readers announce the current tip percentage and total amount.
Real-Time Tip Calculation
"As a customer, I want to see the updated total cost when adjusting the tip so that I know exactly how much I'll pay before confirming my order."
Description

Display the updated total order amount instantly as the user moves the tipping slider, recalculating item subtotals, tax, and tip to give accurate, up-to-the-moment payment information.

Acceptance Criteria
Adjusting tip slider updates order total instantly
Given the checkout screen displays items with subtotal and tax, When the user moves the tip slider to 15%, Then the total order amount is recalculated and displayed as subtotal + tax + 15% tip within 100ms of the slider stop.
Rapid adjustments reflect in real-time calculation
Given the user drags the tip slider rapidly between 10%, 20%, and 30%, When the slider position stabilizes at each percentage, Then the total amount updates correctly to reflect the selected tip percentage without errors or display glitches.
Initial default tip percentage displays correct total
Given the checkout screen loads with the tip slider at its default position (0%), When the screen is fully rendered, Then the total amount shown equals subtotal + tax + 0% tip.
Handling slow network during tip recalculation
Given network latency up to 2 seconds, When the user adjusts the tip slider, Then a loading indicator appears on the total amount field and the final total displays correctly once recalculated, preventing payment submission until update completes.
Adjusting to maximum tip percentage computes correctly
Given the tip slider’s maximum value is 50%, When the user moves the slider to its maximum position, Then the total amount displays as subtotal + tax + 50% tip and the slider cannot be moved beyond this maximum.
Accessibility Compliance
"As a visually impaired user, I want to adjust the tip using accessible controls so that I can use the tipping feature independently."
Description

Ensure the tipping slider is fully accessible, with keyboard navigation, ARIA labels, screen-reader announcements of tip values, and sufficient color contrast to meet WCAG 2.1 AA standards.

Acceptance Criteria
TipFlow Slider Keyboard Navigation
Given the TipFlow slider is focused, when the user presses the Right Arrow key, the tip value increases by the defined step size; when the Left Arrow key is pressed, the value decreases by the same step size; Tab moves focus to and from the slider; Enter or Spacebar activates the slider for adjustment.
TipFlow Slider ARIA Label Support
The slider element must include appropriate ARIA attributes: aria-valuemin, aria-valuemax, aria-valuenow reflecting current tip value, and an aria-label or aria-labelledby describing the control as 'Tip percentage'.
Real-Time Screen Reader Announcements
When the tip value changes via keyboard or touch input, an ARIA live region must announce the new tip percentage or amount change immediately without requiring additional focus or interaction.
Color Contrast Compliance for Slider Elements
All slider components (track, thumb, filled portion) must achieve a minimum contrast ratio of 4.5:1 against their background in both light and dark modes as per WCAG 2.1 AA guidelines.
Visible Focus Indicator on Slider Thumb
When the slider thumb receives keyboard focus, it must display a visible focus indicator (outline or shadow) of at least 2px thickness with a contrast ratio of at least 3:1 relative to adjacent colors.
Tip Preset Options
"As a busy user, I want default tip presets so that I can quickly choose a common gratuity without having to adjust the slider manually."
Description

Provide quick-select preset buttons for common tip percentages (e.g., 10%, 15%, 20%) adjacent to the slider, enabling users to apply standard gratuity amounts with a single tap.

Acceptance Criteria
Selecting a Preset Tip Percentage
Given the user is on the one-tap checkout screen When the user taps the 15% preset button Then the tip slider moves to 15% and displays “15%” And the order total updates to include the 15% tip
Changing Tip After Preset Selection
Given the user selected the 10% preset button When the user drags the tip slider to 12% Then the 10% preset button is deselected And the slider displays “12%” And the order total updates to reflect the new tip percentage
Highlighting Active Preset Button
Given the user adjusts the tip slider to exactly 20% Then the 20% preset button is highlighted as active And all other preset buttons are displayed as inactive
Default Preset Tip on Load
Given the user opens the checkout screen without selecting a tip When the screen loads Then the 15% preset button is highlighted by default And the order total includes a 15% tip
Device Compatibility of Preset Buttons
Given the user accesses the checkout on mobile, tablet, and desktop devices When the user taps any preset button Then the system registers the tap accurately on each device And the correct tip percentage is applied

Instant Receipt

Delivers a digital receipt the moment payment is complete, with a single tap to view, download, or share—providing real-time confirmation and reducing post-pickup queries or disputes.

Requirements

Real-time Receipt Generation
"As a customer, I want to receive a digital receipt the moment my payment is processed so that I have immediate confirmation of my order and can avoid any uncertainty or disputes afterward."
Description

Automatically generate and display a digital receipt immediately after payment confirmation, ensuring customers receive instant proof of purchase. This functionality integrates with the payment gateway to retrieve transaction details, formats the receipt with order information, itemization, taxes, and total, and delivers it in-app without delay. By providing instant confirmation, it reduces customer queries, improves transparency, and enhances trust in the TableHop ordering experience.

Acceptance Criteria
Successful Payment Completion
Given the customer completes payment successfully, When the payment gateway confirms the transaction, Then the system automatically generates and displays the digital receipt in-app within 2 seconds, including order ID, itemized list, taxes, total amount, payment method, and timestamp.
Receipt Generation Under Network Latency
Given intermittent or high-latency network conditions, When the payment confirmation is received, Then the system retries receipt generation up to 2 times and still displays the receipt in-app within 5 seconds, or shows a 'Retry Receipt' option if generation fails.
Receipt Download and Viewing
Given the receipt is displayed in-app, When the user taps 'Download Receipt', Then the receipt is saved as a PDF with the correct formatting and filename containing the order ID, is accessible in the device's Downloads folder, and the app shows a 'Download Successful' notification.
Receipt Sharing Functionality
Given the receipt is displayed in-app, When the user taps 'Share Receipt', Then the system invokes the device's share sheet with the PDF attached, ensuring the receipt content matches the in-app view without truncation.
Error Handling on Payment Failure
Given the payment fails or is declined, When the payment gateway returns an error, Then the system does not generate a receipt, displays an error message explaining the failure, and offers options to retry payment or cancel the order.
Receipt Formatting and Accuracy
Given a completed transaction, When the receipt is generated, Then all monetary values are formatted according to the user's locale, item names are correctly displayed, and the total matches the sum of items plus taxes within a $0.01 tolerance.
Receipt Download & Sharing
"As a customer, I want to download or share my receipt so that I can easily keep a personal record or send proof of purchase to others for reimbursement or dispute resolution."
Description

Enable customers to download their digital receipt as a PDF or image file and share it through various channels (email, SMS, social apps) with a single tap. This feature accesses the generated receipt, converts it into the chosen format, and invokes native sharing capabilities, allowing customers to archive receipts externally or send proof to third parties. It enhances flexibility and reduces support requests related to providing proof of purchase.

Acceptance Criteria
Download Digital Receipt as PDF
Given a completed payment and the digital receipt displayed When the user taps the "Download as PDF" button Then the device file picker prompts for a save location And a PDF file containing the correct order details and formatting is saved And the user sees a confirmation message indicating the file location
Download Digital Receipt as Image
Given a completed payment and the digital receipt displayed When the user taps the "Download as Image" button Then the device file picker prompts for a save location And an image file (PNG or JPEG) with the accurate receipt layout is saved And the user receives a confirmation message indicating the file location
Share Receipt via Email
Given a completed payment and the digital receipt displayed When the user taps the "Share" button and selects the email option Then the native email client opens with a new draft And the receipt file is attached in the chosen format And the email subject is pre-filled with "Your TableHop Receipt"
Share Receipt via SMS
Given a completed payment and the digital receipt displayed When the user taps the "Share" button and selects the SMS option Then the native messaging app opens with a new message And the receipt file link or attachment is included in the message body And the user’s text input cursor is active for entering recipient details
Handle Failed Share Attempt with Retry Option
Given the user attempts to share the receipt but the sharing action fails due to network or system error When the sharing attempt does not complete successfully Then the user sees an error message describing the failure And a "Retry" option is presented When the user taps "Retry" Then the share action is re-attempted
Persistent Receipt Storage
"As a customer, I want to view my past receipts in the app so that I can track my spending and retrieve old receipts if needed."
Description

Maintain a history of all digital receipts within the user’s TableHop account, accessible through an order history section. Receipts are stored securely on the server for a configurable retention period (e.g., 90 days) and can be searched by date, order ID, or restaurant name. This persistent storage empowers customers to retrieve past receipts, track spending over time, and manage returns or warranty claims without relying on email or local downloads.

Acceptance Criteria
Order History Access
Given a logged-in user on the TableHop app, when they navigate to the Order History section, then the system displays all stored receipts for completed orders within the retention period, sorted by descending order date and including order ID, restaurant name, date, and total amount.
Date-based Receipt Search
Given a user in the Order History section, when they filter receipts by a specific date range, then the system returns only receipts from orders placed within that date range.
Order ID-based Receipt Search
Given a user in the Order History section, when they input a valid order ID into the search field and submit, then the system returns the single receipt matching that order ID.
Restaurant Name-based Receipt Search
Given a user in the Order History section, when they enter a restaurant name into the search field and submit, then the system returns all receipts associated with that restaurant.
Receipt Retention Management
Given the system’s configurable retention period is set to 90 days, when receipts exceed 90 days since the payment date, then those receipts are automatically purged and no longer appear in the user’s Order History.
Secure Receipt Retrieval
Given a user attempts to view a stored receipt, when they select a receipt from the Order History, then the system verifies the user’s authentication token and displays the receipt details only if the token is valid.
Email & SMS Receipt Delivery
"As a customer, I want to receive my receipt via email or SMS so that I can access it even when I'm not using the app."
Description

Offer optional delivery of digital receipts via email and SMS immediately after purchase. This requirement integrates with email and SMS providers (e.g., SendGrid, Twilio) to send the receipt link or attachment directly to the user’s registered contact details. Users can configure their preferred channels in settings. Providing multi-channel delivery ensures customers without app access still receive prompt confirmation and increases overall satisfaction.

Acceptance Criteria
Email Receipt Delivery to Registered Email
Given a completed purchase and a valid registered email, When payment is confirmed, Then an email containing the receipt link or PDF attachment is delivered within 5 seconds.
SMS Receipt Delivery to Registered Phone Number
Given a completed purchase and a valid registered phone number, When payment is confirmed, Then an SMS with the receipt link is sent within 5 seconds.
User Channel Preference Configuration
Given a user updates their settings to select email, SMS, or both as preferred receipt channels, When the settings are saved, Then future receipts follow the user’s preference without further confirmation prompts.
Fallback Delivery When Primary Channel Fails
Given an attempt to send via the primary channel fails, When the system detects a delivery error or timeout, Then the receipt is sent via the secondary channel within 10 seconds and a retry log is recorded.
Receipt Access Without App
Given a customer has no app installed, When a receipt link is delivered via email or SMS, Then the link opens in a mobile browser and allows the user to view, download, or share the digital receipt.
Customizable Receipt Branding
"As a restaurant owner, I want to brand my digital receipts with my logo and promotional content so that I can reinforce my brand identity and drive repeat orders."
Description

Allow restaurant owners to customize the appearance of digital receipts by uploading logos, choosing color themes, and adding promotional messages or loyalty program details. The customization interface previews changes in real time, and the system applies these settings to all receipts generated by that restaurant. Branded receipts reinforce the restaurant’s identity, promote special offers, and encourage repeat business by integrating marketing content into transactional communications.

Acceptance Criteria
Logo Upload and Preview
Given the owner is on the receipt branding page When they upload a valid logo file in SVG, PNG, or JPG format under 2MB Then the logo appears in the preview area within 2 seconds at correct scale And the system rejects files exceeding 2MB or invalid formats with an error message
Color Theme Selection
Given the owner accesses the color theme selector When they choose a primary and secondary color via color picker or hex code Then the preview updates instantly to reflect the new color scheme And colors meet WCAG AA contrast ratio standards
Promotional Message Integration
Given the owner enters a promotional message up to 140 characters When they click 'Add Message' Then the message appears in the preview positioned below the logo And the message supports basic markdown formatting (bold, italics)
Saving and Persisting Customization Settings
Given the owner has configured logo, colors, and message When they click 'Save Settings' Then the system stores the settings and displays a success notification And the saved settings persist across page reloads and user sessions
Receipt Generation with Branding Applied
Given a customer completes a payment When the system generates a digital receipt Then the receipt includes the uploaded logo, selected color theme, and promotional message And the receipt layout matches the preview exactly

QuickReorder Pass

Stores your most recent order details and payment credentials securely, enabling true one-tap reorders with biometric authentication—perfect for regulars who want their favorite meals in under three seconds.

Requirements

Secure Payment Vault
"As a returning customer, I want my payment credentials securely stored so that I can complete reorders without re-entering my payment details each time."
Description

Implement a secure, encrypted storage system for users’ payment credentials and most recent order details, integrating with the existing backend infrastructure to ensure PCI compliance and data privacy. This storage must support tokenization, automatic expiration management, and seamless retrieval during reorder operations.

Acceptance Criteria
Storing New Payment Credentials Securely
- Given a user opts to save new payment credentials, when the credentials are received by the backend, then the system tokenizes the card data and stores only the token in the vault. - The token storage process completes within 2 seconds with AES-256 encryption at rest.
Retrieving Stored Credentials for One-Tap Reorder
- Given a returning user with a saved payment token, when they tap 'QuickReorder', then the system retrieves the token, decrypts it in memory, populates the payment field securely, and initiates authorization within 1 second.
Automatic Token Expiration Management
- Given a token is older than 12 months or marked expired, when the user attempts a reorder, then the system prompts for re-authentication and refuses to use the expired token.
Data Encryption and Tokenization Verification
- All stored tokens and order details at rest are encrypted using AES-256; no sensitive data appears in plaintext logs or database dumps. - Tokenization ensures that the original PAN cannot be derived from the stored token.
PCI Compliance Audit Logging
- The system logs all create, retrieve, and delete operations on payment tokens with timestamp, user ID, and operation success/failure, without logging raw PAN or CVV.
Biometric Authentication Integration
"As a user, I want to authenticate with my fingerprint or face so that I can reorder quickly and securely without typing a password."
Description

Integrate device-native biometric authentication (fingerprint and facial recognition) into the reorder workflow, enabling users to authenticate in under one second. Ensure fallbacks to PIN or password for devices without biometric support.

Acceptance Criteria
User reorders using fingerprint authentication
Given a user on a device with a registered fingerprint When the user taps the one-tap reorder button Then the fingerprint prompt appears within 0.5 seconds And the order is authenticated and completed within 3 seconds
User reorders using facial recognition
Given a user on a device with facial recognition enrolled When the user taps the one-tap reorder button Then the face scan prompt appears within 0.5 seconds And the order is authenticated and completed within 3 seconds
Fallback to PIN authentication after biometric failure
Given a user whose biometric scan fails three times in a row When the third biometric attempt is unsuccessful Then the system automatically displays a PIN entry screen
Reorder on device without biometric support
Given a user on a device without biometric hardware When the user taps the one-tap reorder button Then the system bypasses biometric prompts and directly displays the PIN or password entry screen
Biometric prompt latency within reorder workflow
Given any supported device When the user initiates a reorder Then the biometric authentication prompt must display in under 1 second of the tap action
One-Tap Reorder UI
"As a regular customer, I want a visible one-tap reorder button so that I can place my usual order in under three seconds."
Description

Design and implement a prominent one-tap reorder button on the main dashboard and order history views. The button should display the user’s most recent order summary and initiate the reorder flow with a single tap, updating in real time if the order context changes.

Acceptance Criteria
Dashboard One-Tap Reorder Activation
Given the user has at least one previous order stored When the user opens the main dashboard Then a prominent one-tap reorder button displaying the last order summary appears And tapping the button initiates the reorder flow immediately
Order History Quick Reorder
Given the user navigates to order history When the user views the most recent order item Then a one-tap reorder button appears next to that order And tapping it triggers the reorder sequence without additional input
Real-Time Order Context Update
Given the user's most recent order details change (e.g., items added or removed) When the dashboard is refreshed or reopened Then the one-tap reorder button summary updates to reflect these changes within 2 seconds
Biometric Authentication Flow
Given the user has biometric authentication enabled When the user taps the one-tap reorder button Then the app prompts for biometric verification And upon successful verification, the reorder is completed in under three seconds
Error Handling for Failed Reorder
Given the order placement fails due to network or payment issues When the user taps the one-tap reorder button Then the app displays an error message explaining the failure And provides options to retry or cancel the reorder action
Instant Order Confirmation Feedback
"As a customer, I want to receive instant confirmation when my reorder is placed so that I know my food is on the way without checking multiple screens."
Description

Provide immediate visual and haptic feedback upon successful quick reorder, including an on-screen confirmation banner and optional push notification. Ensure feedback is delivered in under one second to reinforce user confidence.

Acceptance Criteria
Successful Quick Reorder Confirmation
Given a registered user with saved payment credentials and biometric authentication enabled, when the user performs a QuickReorder Pass and authenticates biometrically, then an on-screen confirmation banner displaying the order number and confirmation message must appear within 1 second.
Push Notification Delivery
Given the user has enabled push notifications for TableHop, when a QuickReorder Pass is successfully completed, then a push notification containing the order details and confirmation message must be delivered to the device within 1 second.
Confirmation Banner Display Duration
Given a successful quick reorder, when the on-screen confirmation banner appears, then it must remain visible for at least 3 seconds and include a dismiss icon that closes the banner when tapped.
Haptic Feedback in Silent Mode
Given the device is set to silent or Do Not Disturb mode, when the quick reorder is successfully confirmed, then the device must emit a single haptic vibration and display the on-screen confirmation banner within 1 second.
Background Feedback via Push Notification
Given the TableHop app is running in the background, when the QuickReorder Pass completes successfully, then a push notification with the confirmation message and order summary must be delivered within 1 second.
Error Handling and Fallback Mechanisms
"As a user, I want clear guidance and alternative options if my quick reorder fails so that I can still place my order without confusion."
Description

Develop robust error detection and fallback procedures for quick reorder failures (e.g., network issues, expired payment tokens). Automatically prompt users to retry, update payment details, or fall back to the full checkout flow with minimal friction.

Acceptance Criteria
Network Failure During Quick Reorder
Given the user taps the QuickReorder Pass button and the network connection drops, When the order request fails to reach the server within 5 seconds, Then display a 'Network error' message with options to retry or proceed to full checkout.
Expired Payment Token Detected
Given the stored payment token is expired at reorder time, When the token validation endpoint returns an 'expired token' response, Then prompt the user to update payment details before proceeding or switch to full checkout flow.
Automatic Retry After Transient Error
Given a transient server error (HTTP 500) occurs on the first reorder attempt, When the system automatically retries up to two more times with exponential backoff, Then either succeed on a subsequent attempt or surface the failure fallback options.
User Chooses Full Checkout Fallback
Given the QuickReorder Pass fails and the fallback prompt appears, When the user selects 'Full Checkout', Then redirect to the standard checkout flow with previous order details pre-populated.
Successful Biometric Authentication After Failure
Given a prior reorder failure and fallback prompt, When the user authenticates via biometrics and selects 'Retry Quick Reorder', Then the system attempts the quick reorder again and confirms the order success within 3 seconds.
Audit Logging and Usage Analytics
"As an administrator, I want detailed logs and analytics on quick reorder usage so that I can monitor performance, detect anomalies, and improve the feature."
Description

Implement comprehensive logging of quick reorder events, authentication attempts, and errors. Capture metrics on reorder frequency, success rates, and user engagement to inform future optimizations and ensure compliance with security policies.

Acceptance Criteria
Successful Reorder Event Logging
Given a user completes a QuickReorder Pass order successfully, When the order confirmation is sent, Then an audit log record is created containing userID, orderID, timestamp, item details, total amount, and status "success" within 500ms
Authentication Attempt Audit
Given a user initiates biometric authentication for QuickReorder Pass, When the authentication is processed, Then an audit entry is recorded with userID, authentication method, timestamp, result (success or failure), and any error codes
Error Logging for Reorder Failures
Given a QuickReorder Pass attempt fails due to payment or network issues, When the failure occurs, Then the system logs an error entry including userID, orderID (if generated), timestamp, error type, and error code
Usage Analytics Data Capture
Given multiple QuickReorder Pass orders are placed over a time period, When each order is completed, Then the system updates analytics metrics for reorder frequency per user, per item, average reorder time, and success rate in the analytics datastore
Data Retention Compliance Verification
Given audit log entries reach the defined retention period, When the retention threshold is exceeded, Then the system archives or purges old log entries according to policy and logs the purge event with timestamp and record count

Streak Saver

Tracks your consecutive curbside pickups and rewards you with escalating bonuses for each day you maintain a streak—keeping you motivated to stick with your favorite restaurants and unlock exclusive perks at every milestone.

Requirements

Daily Streak Tracker
"As a frequent customer, I want the app to automatically track each day I pick up my order so that I can maintain my streak without manual effort."
Description

Automatically records each day a user completes a curbside pickup and maintains a count of consecutive days, ensuring real-time accuracy and seamless integration with the order dashboard.

Acceptance Criteria
Initial Streak Registration
Given a user completes their first curbside pickup of the day, When the system processes the order completion event, Then the user’s daily streak count increments from 0 to 1 and displays “1-Day Streak” on their dashboard.
Consecutive Day Pickup
Given a user has an active streak count of N days and completes a curbside pickup before 11:59 PM local time, When the system records the new pickup event, Then the streak count increments to N+1 and the new count is displayed immediately.
Missed Pickup Reset
Given a user fails to complete a curbside pickup by end of day, When the system’s daily job runs at 00:00 local time, Then the user’s streak count resets to 0 and a notification about streak reset is sent.
Dashboard Streak Display Update
Given any change in the user’s streak count, When the user opens or refreshes the order dashboard, Then the updated streak count and next reward milestone message are displayed without needing a manual page reload.
Offline Order Synchronization
Given a user completes a curbside pickup while offline, When the app reconnects to the network within 24 hours, Then the system backfills the pickup event, updates the streak count correctly, and notifies the user of any changes.
Streak Milestone Rewards
"As a customer, I want to earn rewards at each streak milestone so that I stay motivated to continue ordering from my favorite restaurants."
Description

Defines and delivers escalating rewards at predefined streak milestones (e.g., free item at 5 days, discount at 10 days, VIP perk at 30 days), enhancing user motivation and driving repeat visits.

Acceptance Criteria
5-Day Streak Reward Grant
Given a user has completed 4 consecutive curbside pickups When the user completes a 5th consecutive pickup Then the system automatically grants a free item reward and adds it to the user's account balance
10-Day Streak Discount Application
Given a user has completed 9 consecutive curbside pickups When the user completes a 10th consecutive pickup Then the system applies a predetermined discount code to the user's next order
30-Day VIP Perk Activation
Given a user has completed 29 consecutive curbside pickups When the user completes a 30th consecutive pickup Then the system upgrades the user's account with VIP status and enables exclusive perk access
Streak Reset After Missed Pickup
Given a user has an active streak of N days When the user fails to complete a pickup on a consecutive day Then the system resets the streak count to zero and notifies the user of the reset
Milestone Notification Delivery
Given a user is one day away from a streak milestone (day 4, 9, or 29) When the user's pickup is completed for the current day Then the system sends an in-app and push notification informing the user of the upcoming reward milestone
Push Notifications
"As a customer, I want to receive notifications about my streak status so that I don’t forget to pick up my order and risk losing my streak."
Description

Sends timely notifications to users reminding them of upcoming streak resets, congratulating them on new milestones, and prompting them to complete daily pickups, increasing engagement and retention.

Acceptance Criteria
Daily Pickup Reminder
Given a user with an active streak has not completed today's pickup by 12:00 PM local time, When the system time reaches 12:00 PM local, Then a push notification titled 'Don't forget your pickup today!' is sent to the user's device, including the user's name, restaurant name, and a link to mark pickup as completed, delivered within 1 minute of trigger.
Streak Reset Warning
Given a user with an active streak has 1 hour remaining before the daily streak reset, When the remaining time equals 1 hour, Then a push notification titled 'One hour left to keep your streak alive!' is sent, displaying the remaining time countdown and a link to the order status page, delivered within 1 minute of trigger.
Streak Milestone Achievement
Given a user's pickup completes and reaches a streak milestone (3, 7, 14, or 30 days), When the pickup confirmation is received, Then a push notification titled 'Congratulations! You've reached a [N]-day streak!' is sent immediately, specifying the milestone and teasing the next reward.
Reward Unlocked Notification
Given a user's streak milestone unlocks a reward, When the reward is available, Then a push notification titled 'Reward unlocked! Redeem your [reward description] now' is sent with a button linking directly to the rewards redemption page, delivered within 1 minute of unlock.
Streak Lapse Notification
Given a user's streak has lapsed at the daily reset time due to no completed pickup, When the streak reset occurs, Then a push notification titled 'Oh no! Your streak has ended.' is sent within 1 minute, encouraging the user to start a new streak with a link to place a new order.
Streak History Dashboard
"As a customer, I want to view my streak history and statistics so that I can track my progress over time and set personal goals."
Description

Provides a visual timeline and statistics of a user’s streak activity—including current streak length, longest streak, and past resets—offering transparency and insights into progress.

Acceptance Criteria
Current Streak Display
Given a user with an active streak of N days, when the user opens the Streak History Dashboard, then the displayed current streak length equals N and is shown prominently at the top of the dashboard.
Longest Streak Display
Given the user’s complete streak history, when the user views the dashboard, then the longest streak metric reflects the maximum consecutive days achieved and matches historical data.
Streak Reset History
Given multiple past streak resets, when the user scrolls through the timeline, then each reset event is clearly marked on the timeline and the total count of resets matches the number of days the streak was broken.
Timeline Visualization Interaction
Given the visual timeline, when the user hovers over any day marker, then a tooltip displays the exact date, streak count for that day, and whether the streak was active or reset.
Statistics Summary Accuracy
When the user examines the summary statistics section, then the total number of streak days, total resets, and average streak length are accurately calculated based on the underlying streak data.
Streak Reset Safeguard
"As a customer, I want a grace period in case of unexpected delays so that I don’t lose my streak unfairly."
Description

Implements a configurable grace period and extension options (e.g., traffic delays) to prevent users from unfairly losing a streak, improving user satisfaction and reducing frustration.

Acceptance Criteria
Grace Period Activation on First Missed Pickup
Given a user’s scheduled curbside pickup time has passed When the user arrives within the configured grace period Then the system must preserve the user’s streak and not decrement the streak count
Extension Request for Traffic Delays
Given a user selects a traffic delay extension before pickup time expires When the extension request is submitted within the allowed window Then the system must grant the additional time without resetting the streak
Admin Update of Grace Period Settings
Given an administrator configures a new grace period duration or extension policy When the settings are saved in the system Then all subsequent streak evaluations must use the updated configuration
User Notification of Upcoming Grace Period Expiry
Given a user’s grace period is about to end When there are 5 minutes remaining in the configured grace period Then the system must send a push notification alerting the user of the imminent streak reset risk
Automatic Streak Reset after Grace Period Expiry
Given a user fails to arrive before the end of the configured grace period and has no pending extension When the grace period expires Then the system must automatically reset the user’s streak and notify the user of the reset
Reward Configuration Panel
"As a restaurant owner, I want to customize my Streak Saver rewards so that I can align promotions with my business goals and customer preferences."
Description

Offers restaurants an admin interface to define custom reward types, values, milestone thresholds, and eligibility rules, enabling tailored loyalty programs aligned with business objectives.

Acceptance Criteria
Creating a New Reward Type
Given the restaurant admin is on the Reward Configuration Panel When they enter a unique reward name, select a reward type, define its value, and click Save Then the new reward type appears in the rewards list with the correct name, type, and value
Editing Reward Milestone Thresholds
Given an existing reward with milestones configured When the admin updates the milestone thresholds and clicks Update Then the system persists the new thresholds and reflects them accurately in the rewards list
Configuring Eligibility Rules for Rewards
Given the admin is defining eligibility rules for a specific reward When they specify criteria such as minimum order count, spend amount, or specific dates and save Then the eligibility rules are stored, and the reward is only applicable when those rules are met
Deleting an Existing Reward
Given the admin selects a reward from the list and chooses Delete When they confirm the deletion Then the reward is removed from the list and cannot be redeemed by customers
Previewing Reward Impact Before Saving
Given the admin has configured a reward and its parameters When they click Preview Then a summary modal displays the reward type, value, milestones, and eligibility rules for review

Credit Cascade

Automatically applies your available loyalty credits in the most valuable way—covering item costs first, then rolling any leftover balance into your next order—so you always get maximum savings without manual juggling.

Requirements

Automated Credit Application Engine
"As a loyal customer, I want my available credits to be applied automatically to each item and then to the remaining order total so that I maximize my savings without having to manage credits manually."
Description

Develop a backend engine that automatically applies available loyalty credits to a user’s order, prioritizing the allocation to individual item costs before applying any remaining balance to the overall order total. This engine must integrate with the existing checkout pipeline, calculate credit usage in real time, handle edge cases (such as partial credit coverage and minimum spend thresholds), and ensure accurate transaction records for both customers and restaurateurs. The solution should be scalable, performant, and maintainable, enabling seamless automatic savings without manual intervention.

Acceptance Criteria
Apply Full Credits to Items
Given a user has loyalty credits sufficient to fully cover the cost of individual items When the user proceeds to checkout Then the engine applies credits to each item cost first, reducing each item's price to $0 until credits are exhausted
Apply Remaining Credits to Order Total
Given a user has leftover credits after covering item costs When checkout calculates the order total Then the engine applies remaining credits to the overall order total, reducing the customer's payable amount accordingly
Handle Partial Credit Coverage
Given a user has credits that are insufficient to cover an item When credit is applied Then the engine applies available credits to the item cost proportionally and adjusts the remaining payable amount
Enforce Minimum Spend Threshold
Given the restaurant's minimum spend threshold is $X and user credits would reduce payable below $X When user applies credits Then the engine ensures the final payable amount meets or exceeds the minimum spend threshold and notifies the user of any additional required payment
Accurate Transaction Record Logging
Given credits are applied to an order When the order is completed Then the system logs credit usage per item and order total in transaction records for both customer and restaurateur, matching applied amounts
Real-Time Credit Calculation During Checkout
Given user updates cart contents When items are added, removed, or quantities change Then the engine recalculates credit application in real-time, updating the displayed payable amount within 200ms latency
Residual Credit Roll-over Mechanism
"As a frequent diner, I want any unused credits from my current order to roll over and be applied automatically to my next order so that I never lose out on savings."
Description

Implement a mechanism that captures any leftover loyalty credit after order application and securely stores it to be automatically applied on the customer’s next order. This system should update the user’s credit balance immediately upon checkout completion, ensure consistency across sessions and devices, and handle concurrent transactions to prevent credit duplication or loss. The feature will enhance user trust by preserving every earned credit point for future use.

Acceptance Criteria
Leftover Credit Rollover Activated
Given a customer completes an order with unused loyalty credits, when the checkout is finalized, then the system automatically stores any leftover credits and applies them to the customer’s next order without manual intervention.
Immediate Credit Balance Update Post-Checkout
Given an order has been completed, when the confirmation page is displayed, then the user’s credit balance reflects the new leftover amount and is updated in the user profile immediately.
Credit Balance Consistency Across Devices
Given a user with rolled-over credits logs into any other device or session, when viewing their account balance, then the displayed credit balance matches the most recent leftover credit from the previous session.
Concurrent Orders Do Not Duplicate Credits
Given a user places two orders concurrently from different devices, when both transactions complete, then the system deducts credits correctly once and preserves any leftover credits without duplication or loss.
Customer Notification of Rollover
Given leftover credits are rolled over, when the checkout process is complete, then the user receives an in-app notification specifying the exact amount of credits carried over to the next order.
Credit Balance Display Update
"As a customer, I want to see my credit balance update immediately when credits are applied so that I understand how much I’m saving and what remains for future orders."
Description

Create a real-time display in the checkout interface that shows the user’s current loyalty credit balance before and after credit application. The display should update dynamically as credits are applied to items and the order total, providing clear visual feedback on savings achieved and remaining balance. It must seamlessly integrate with both web and mobile app views, maintain accessibility standards, and support localization for multi-region deployments.

Acceptance Criteria
User Views Current Credit Balance on Checkout Page
Given the user navigates to the checkout page, When the page loads, Then the system displays the user's current loyalty credit balance and the projected remaining balance after credit application.
Applying Credits to Individual Order Items
Given the user toggles credit usage on an order item, When the selection changes, Then the order total and remaining credit balance update in real time within 500 milliseconds.
Credit Balance Display Across Web and Mobile Interfaces
Given the user accesses the checkout interface on web or mobile, Then the credit balance display component appears consistently styled, positioned, and functional across both platforms.
Accessibility Compliance for Credit Balance Display
Given the credit balance display is rendered, Then it includes descriptive ARIA labels, meets WCAG AA color contrast ratios, and supports full keyboard navigation.
Localization of Credit Balance Display
Given the user's locale is set, When the credit balance display renders, Then numeric formatting, currency symbols, and labels reflect the locale’s language and conventions, and the layout adapts to text length changes.
Credit Usage Notification
"As a customer, I want to receive notifications showing how my credits were used and what remains so that I stay informed about my loyalty benefits."
Description

Implement in-app and email notifications that inform users when loyalty credits are automatically applied and when leftover credits are rolled over. Notifications must include details such as the amount of credits used, savings earned, and remaining balance, enhancing transparency and user engagement. This feature should integrate with the notification system, allow users to opt in or out, and adhere to communication frequency guidelines to avoid notification fatigue.

Acceptance Criteria
Automatic Loyalty Credit Application Confirmation
Given a user places an order with available loyalty credits When the order is confirmed Then an in-app notification and an email are sent within 5 minutes detailing credits applied, savings earned, and remaining balance
Leftover Credit Rollover Notification
Given a user's loyalty credit exceeds the order total When the system rolls over leftover credits Then an in-app notification and an email are sent specifying rolled-over amount and updated balance
Opt-In and Opt-Out Preference Management
Given a user accesses notification settings When the user opts in or out of credit notifications Then the system updates their preference and confirms the change in-app immediately
Notification Frequency Compliance
Given system sending credit notifications When a user has multiple orders in a 24-hour period Then notifications are throttled to no more than one email and one in-app alert per 24 hours
Notification Delivery Channel Verification
Given a user has valid email and device token When a credit notification is triggered Then the notification is delivered successfully via both email and in-app channels as evidenced by delivery confirmations
Manual Credit Adjustment Option
"As a savvy saver, I want the ability to choose exactly how many credits to apply so that I can balance immediate savings with future credit retention."
Description

Provide an interface allowing users to manually adjust how many loyalty credits they wish to apply to their current order, overriding the default automated allocation. This option should include controls to select partial credit usage, preview the effect on order total, and revert to automatic allocation if desired. Integrate validation to prevent overuse and ensure credit balances remain accurate post-transaction.

Acceptance Criteria
Initiate Manual Credit Adjustment
Given a user with available loyalty credits on the checkout page, When the user clicks on 'Manual Credit Adjustment', Then the system displays an input control allowing credit selection between 0 and the lesser of available credits and order subtotal.
Apply Partial Credits and Update Total
Given the manual credit adjustment control is visible, When the user enters a credit amount less than their available balance, Then the order's subtotal, tax, and total are recalculated and displayed correctly reflecting the applied credits.
Prevent Overuse of Credits
Given the user attempts to apply more credits than available or exceeding the order total, When the user submits the credit amount, Then the system shows an error message indicating the maximum allowable credits and prevents submission.
Revert to Automatic Allocation
Given the user has modified credit usage manually, When the user clicks 'Revert to Automatic', Then the system resets the credit allocation to the automated default and updates the order total accordingly.
Post-Transaction Credit Balance Accuracy
Given an order is completed with manually adjusted credits, When the transaction succeeds, Then the user's account balance reflects the remaining loyalty credits accurately, and the transaction record shows the exact credits used.
Credit Savings Insights Dashboard
"As a regular customer, I want to view insights on how I use my credits and the total savings achieved so that I can make informed decisions about future orders."
Description

Develop a dashboard within the user account section that provides insights into credit usage patterns, total savings over time, and forecasted benefits based on current accrual rates. The dashboard should include visualizations (charts, graphs), filter options (date range, order type), and actionable recommendations (e.g., optimal times to use credits). This analytics feature will drive user engagement by highlighting the value of loyalty participation.

Acceptance Criteria
Displaying Credit Usage Patterns
Given the user is on the Credit Savings Insights Dashboard When the dashboard loads Then the credit usage patterns chart displays the number of credits applied per order over the last 30 days and updates dynamically based on any date range selection
Filtering Credit Usage by Date Range
Given the user selects a custom date range filter When the filter is applied Then the dashboard refreshes to show credit usage patterns, total savings, and forecast data strictly within the selected period
Forecasting Future Credit Savings
Given the user's current credit balance and accrual rate When the user views the forecast section Then the system calculates and displays projected credit savings for the next three months based on average monthly credit earning
Visualizing Total Savings Over Time
Given the user chooses between weekly or monthly views When the view is selected Then the cumulative savings chart accurately plots total credits saved over the chosen interval with clear axis labels and data points
Providing Actionable Usage Recommendations
Given the user's credit balance and historical usage patterns When the recommendation panel is opened Then the dashboard displays at least three personalized tips on optimal credit application timing to maximize savings

Milestone Mania

Celebrate significant loyalty milestones with surprise rewards triggered at key pickup counts (e.g., 5th, 10th, 25th). Earn free add-ons, percentage discounts, or access to limited-time menu items as you hit each tier.

Requirements

Milestone Tracking Engine
"As a returning customer, I want the system to recognize when I hit loyalty milestones so that I can receive surprise rewards automatically."
Description

Develop a backend service that accurately tracks each customer's pickup count in real time and detects when they reach defined loyalty milestones (e.g., 5th, 10th, 25th pickups). This service must integrate with the existing order database to increment counts automatically upon order completion, support configurable milestone thresholds, and expose APIs for other modules to query a customer's current milestone status.

Acceptance Criteria
Customer reaches 5th milestone
Given a customer has 4 completed pickups, when they complete their next order, then the system increments their pickup count to 5 and flags that they have reached the 5th milestone.
Admin configures milestone thresholds
Given an admin updates the milestone settings to new thresholds, when the changes are saved, then the engine applies the new thresholds for all subsequent pickup count evaluations.
Real-time count update on order completion
Given an order is marked as completed in the database, when the completion event is processed, then the customer's pickup count is updated within 2 seconds.
API provides milestone status
Given a valid customer ID, when a GET request is made to the /milestone-status API, then the response returns the current pickup count, achieved milestones, and the next milestone threshold.
System avoids false milestone triggers
Given a customer’s pickup count does not match any configured milestone threshold, when any order is completed, then no milestone reached notification or reward is generated.
Automated Reward Delivery
"As a loyalty program member, I want to receive my milestone rewards automatically so that I can redeem them without manual intervention."
Description

Implement a rewards module that, upon receiving milestone events from the tracking engine, generates appropriate rewards (free add-ons, percentage discounts, limited-time items) and automatically applies them to the customer's next eligible order. The module should support configurable reward types per milestone tier and ensure rewards have validity periods.

Acceptance Criteria
Reward Generation on Milestone Event
Given a milestone event for the 5th pickup is received from the tracking engine When the rewards module processes the event Then a free add-on reward configured for the 5th tier is generated for the customer's account
Admin Configures Reward Tiers
Given an admin user navigates to the rewards configuration interface When they assign a percentage discount to the 10th pickup tier and save the settings Then the rewards module stores the new configuration and reflects the updated reward type for the 10th tier
Reward Validity Period Enforcement
Given a generated reward with a 7-day validity period When the customer attempts to apply the reward within 7 days of generation Then the reward is applied successfully to the next eligible order And if the customer attempts to apply the reward after 7 days Then the reward is marked expired and cannot be applied
Automatic Reward Application to Next Order
Given a customer places a new eligible order after receiving a valid reward When the order confirmation is generated Then the system automatically applies the reward to the order total without manual intervention
Notification of Generated Reward
Given a reward has been generated for a customer When the rewards module confirms reward creation Then an in-app notification and email with reward details and expiry date is sent to the customer
Customer Notification System
"As a customer, I want to be notified immediately when I've reached a milestone and received a reward so that I can plan my next order accordingly."
Description

Create a notification subsystem that sends real-time alerts to customers when they achieve a milestone and when their rewards are available or nearing expiration. Notifications should be delivered through multiple channels (in-app push, SMS, email) based on customer preferences, with templated and localized message support.

Acceptance Criteria
Milestone Achievement Push Notification
Given a customer has opted in for in-app push notifications and reaches their 5th pickup milestone, When the system records the milestone, Then a push notification is delivered within 5 seconds containing the customer’s name, milestone count, reward details, and a “View Reward” button.
Email Notification for Milestone Reward
Given a customer prefers email communication and hits the 10th pickup milestone, When the milestone is logged, Then an email is sent within 2 minutes with a localized reward voucher attached, subject line personalized with the customer’s first name, and a clear expiration date displayed.
SMS Reminder for Reward Expiration
Given a customer has an unredeemed reward expiring in 24 hours and has enabled SMS alerts, When the reward’s expiration threshold is reached, Then an SMS is sent containing the reward name, expiration time, and a redemption link, and the system logs delivery status and response codes.
Localized Notification in Spanish
Given a Spanish-speaking customer with language preference set to Spanish and reaching their 25th pickup, When the system triggers the milestone notification, Then the notification (across all channels) is sent in Spanish using the correct localized template, and the content is verified against the translation file.
Notification Channel Fallback Mechanism
Given a customer prefers push as primary and SMS as secondary channel but does not receive the push notification within 10 seconds, When the push fails or times out, Then the system automatically sends the notification via SMS with identical content and records the fallback event in logs.
Admin Dashboard Enhancement
"As a restaurateur, I want to view detailed insights into my customers' milestone progress so that I can evaluate and optimize the loyalty program."
Description

Extend the existing restaurant admin dashboard to include a loyalty milestones overview, displaying customer pickup counts, upcoming milestones, reward issuance history, and redemption rates. Provide filtering and export capabilities for milestone data to help restaurateurs analyze program performance.

Acceptance Criteria
View Loyalty Milestones Overview
Given the restaurant admin is authenticated and on the dashboard When the admin selects the "Loyalty Milestones Overview" tab Then a table displays customer names, total pickup counts, next milestone tier, reward issuance history, and redemption rates And all displayed data matches the current records in the loyalty program database
Filter Milestone Data by Date Range
Given the admin is viewing the loyalty milestones table When the admin sets a start date and end date in the date-range filter and clicks "Apply" Then the table updates to show only records where pickups or reward events occurred within the selected range
Export Milestone Data to CSV
Given the filtered or unfiltered milestones table is visible When the admin clicks the "Export CSV" button Then a CSV file is generated containing all visible columns and rows in the table And the file downloads successfully to the admin’s device
Review Reward Issuance History Details
Given the admin sees the reward issuance history column When the admin clicks the "Details" icon for a specific customer row Then a modal opens showing a chronological list of all rewards issued to that customer, including dates, reward types, and redemption statuses
Assess Redemption Rates for Milestones
Given the milestones overview is displayed When the admin reviews the redemption rate column Then the redemption rate is calculated as (number of redeemed rewards ÷ number of issued rewards) × 100% And the value is rounded to one decimal place and matches backend calculations
Reward Redemption Validation
"As a customer, I want to be sure my milestone rewards are valid and applied correctly so that I have a seamless redemption experience."
Description

Develop a validation layer in the ordering workflow that ensures only valid, unexpired milestone rewards are applied, preventing double-usage or misuse. The layer should verify reward eligibility against the customer's milestone status and update the reward state upon redemption.

Acceptance Criteria
Valid Reward Redemption at Milestone
Given a customer has reached a milestone reward level and has an unexpired, unused reward When the customer applies the reward at checkout Then the system applies the correct discount or free add-on to the order total And the reward status is updated to redeemed in the customer’s account
Prevent Double Redemption of Reward
Given a customer attempts to redeem a reward that is already marked as redeemed When the customer applies the same reward again Then the system rejects the redemption attempt And displays an error message indicating the reward has already been used
Reject Expired Reward Usage
Given a customer has an expired milestone reward in their account When the customer tries to apply the expired reward at checkout Then the system prevents the reward from being applied And shows a notification that the reward has expired
Verify Reward Eligibility by Milestone Count
Given a customer has not yet reached the required pickup count for a milestone reward When the customer attempts to redeem the reward prematurely Then the system blocks the redemption And prompts the customer with the remaining pickups needed to unlock the reward
Update Reward State Post-Redemption
Given a customer successfully applies a valid milestone reward When the order is confirmed and completed Then the system updates the reward record to redeemed in the database And ensures the reward cannot be listed as available in subsequent orders

Loop Lab

Harnesses intelligent analytics to generate personalized deals and recommendations based on your ordering habits and taste preferences—ensuring every offer feels custom-tailored to you and boosts your satisfaction.

Requirements

Data Collection Module
"As a frequent user, I want the app to remember my past orders and preferences so that future recommendations feel tailored to my tastes."
Description

Implement a system that continuously gathers and stores detailed user order history, taste preferences, and interaction data from the TableHop app. The module should capture parameters such as cuisine type, frequency of orders, average spend, and time of day patterns, then normalize and structure this data for further analysis. The collected data will serve as the foundation for generating accurate, personalized deals and recommendations.

Acceptance Criteria
Order Placement Data Logging
Given a user completes an order in the TableHop app When the order is confirmed Then the system records cuisine type, order items, total spend, and timestamp in the data collection module within 2 seconds
User Preference Data Recording
Given a user updates taste preferences in their profile When the update is saved Then the system captures and stores the new preference data fields (e.g., preferred cuisines, flavor profiles) in the user’s data record
App Interaction Data Collection
Given a user navigates menus and views items When the user performs interactions (e.g., menu taps, item views, search queries) Then the system logs each interaction event with associated metadata (user ID, timestamp, context) for later analysis
Data Normalization and Structuring
Given raw data entries for order history and preferences When the data ingestion process runs Then data is normalized (consistent field formats, no duplicates) and structured into predefined schemas within the data warehouse
Real-Time Data Availability
Given new order and interaction events occur When data is logged and normalized Then the processed records become available in the analytics datastore within 5 minutes for query and personalization engines
Analytics Algorithm Engine
"As a data-driven product owner, I want an algorithm that learns from user behavior so that we can offer highly relevant deals that boost engagement."
Description

Develop an intelligent analytics engine that applies machine learning and pattern recognition to user data. The engine will identify trends, segment users by taste profiles, predict likely orders, and generate a ranked list of personalized deal offers. It must operate in near real-time and support continuous model updates as more data becomes available.

Acceptance Criteria
Real-Time Trend Identification
Given the engine receives order data within 60 seconds of placement When processing the data Then it outputs the top 3 trending menu items ranked by order frequency with at least 95% consistency over 10 runs
Taste Profile Segmentation on Onboarding
Given a new user completes taste preference questions During onboarding When the engine analyzes responses Then it assigns the user to one of the predefined taste segments with 100% assignment and stores the segment label in the user profile
Next Order Prediction Before Checkout
Given historical user order data over the past month When the engine predicts next likely order Then it generates a ranked list of the top 5 predicted items with a precision of at least 80% measured against actual orders in a test dataset
Ranked Personalized Deal Generation
Given a user visits the deals page When the engine compiles personalized offers Then it produces a list of at least 3 deals sorted by predicted interest score in descending order and achieves a minimum 10% uplift in engagement during A/B testing
Continuous Model Retraining and Update
Given new daily user interactions and order data When the engine retrains its model Then it completes the update within 2 hours and maintains predictive accuracy within 2% of the previous model version
Deal Recommendation Interface
"As a customer, I want to see custom offers and suggestions when I browse so that I can easily discover deals that interest me."
Description

Create a user-facing interface within the app where personalized deals and recommendations are displayed prominently. The interface should dynamically update with new offers, allow users to filter or save deals, and integrate seamlessly with the ordering flow. Visual elements should highlight deal value and recommended items.

Acceptance Criteria
New Personalized Deals Load
Given the user navigates to the Deals tab When the app fetches personalized offers Then at least five deals are displayed within 2 seconds sorted by relevance
Filter Deals by Category
Given the user selects a category filter When the filter is applied Then only deals matching the selected category are shown
Save Deal for Later
Given the user taps the “Save” icon on a deal When the action completes Then the deal appears in the Saved Deals section and remains after app restart
Seamless Integration with Ordering Flow
Given the user chooses a deal and taps “Order Now” When redirected to the order screen Then the deal’s items and discounted prices are pre-applied in the cart
Visual Highlight of Deal Value
Given the deals list is displayed Then deals with a discount of 20% or more show a “Best Value” badge and a highlighted background
Notification & Alert System
"As a busy parent, I want timely alerts about relevant deals so that I don’t miss out on offers that match my needs."
Description

Implement a notification framework that delivers personalized deal alerts via push notifications, email, and in-app messages at optimal times based on user behavior patterns. The system should schedule and throttle notifications to prevent overload and support user preferences for notification channels and frequency.

Acceptance Criteria
Push Notification Delivery
Given a user has opt-in for push notifications and a personalized deal is generated at the user’s optimal engagement time, When the deal is ready, Then the user receives a push notification containing the deal details and a deep link to view or redeem it.
Email Alert Scheduling
Given a user has email notifications enabled and a personalized deal is generated outside the user’s preferred engagement window, When the system processes the deal, Then the email is scheduled to send during the next optimal time slot without sending immediately.
In-App Message Display
Given a user opens the TableHop app and there are personalized deals available, When the user navigates to the home screen, Then an in-app banner or modal displays the top personalized deal, respecting the user’s maximum in-app notification frequency.
Notification Throttling
Given multiple personalized deals are generated within a short period, When the system prepares notifications, Then no more than three notifications are sent per user per channel in any 24-hour period, with additional deals queued and aggregated into a single summary notification.
User Preference Management
Given a user updates their notification channel or frequency preferences in the app settings, When the user saves their changes, Then the system applies the new preferences within 15 minutes and sends future notifications only via the selected channels and at the specified frequency.
A/B Testing Framework
"As a growth marketer, I want to test different recommendation tactics so that I can optimize which deals drive the highest engagement and revenue."
Description

Set up an A/B testing infrastructure that allows experimentation on different deal strategies, recommendation algorithms, and presentation formats. The framework should randomize user groups, track key metrics (click-through rates, conversion, average order value), and provide reporting tools to measure the impact of each variation.

Acceptance Criteria
Randomized User Cohort Assignment
Given a live A/B test with two deal strategies, When the test starts, Then the system randomly assigns incoming users into groups A and B with a variance of no more than ±2% from the configured 50/50 split and persists each user’s assignment across sessions.
Key Metrics Tracking
Given active variations running, When users view deals and complete transactions, Then the system captures and logs click-through rates, conversion events, and average order values for each variation without data loss or duplication.
A/B Test Results Reporting
Given a concluded A/B test, When the user accesses the reporting dashboard, Then the system displays a summary of each variation’s metrics, including statistical significance (p-value ≤ 0.05), and visualizes the results in comparative charts.
Variation Presentation in UI
Given a signed-in user assigned to a variation, When they open the deal recommendation page, Then the UI renders the correct variation content consistently on desktop and mobile devices.
Experiment Data Export API
Given a valid experiment ID, When a client calls the export endpoint, Then the API returns a downloadable JSON or CSV file containing timestamped records of group assignments and associated key metrics for all variations.
User Feedback Capture
"As a user, I want to rate the deals you suggest so that future offers better match my preferences."
Description

Integrate mechanisms for collecting explicit user feedback on deals—such as thumbs up/down, ratings, or comments—directly within the recommendation interface. This feedback should feed back into the analytics engine to refine personalization over time.

Acceptance Criteria
Thumbs Up Feedback Submission
Given a user is viewing a recommended deal, when the user taps the thumbs-up icon, then the system records positive feedback in the database, displays a confirmation message within 2 seconds, and increments the deal’s positive feedback count.
Thumbs Down Feedback Submission
Given a user is viewing a recommended deal, when the user taps the thumbs-down icon, then the system records negative feedback in the database, displays an acknowledgment message within 2 seconds, and increments the deal’s negative feedback count.
Rating-Based Feedback Submission
Given a user selects a star rating (1–5) for a deal, when the user confirms the rating, then the system saves the numeric rating, shows a thank-you notification, and recalculates the deal’s average rating in real time.
Comment-Based Feedback Submission
Given a user enters a text comment about a deal, when the user submits the comment, then the system stores the comment linked to the user and deal ID, displays the comment in the feedback list immediately, and sends the comment to the analytics engine for sentiment analysis.
Feedback Data Integration into Analytics
Given any type of feedback (thumbs up/down, star rating, or comment) is captured, when the feedback entry is processed, then the analytics engine receives the data within 5 minutes, updates the user’s preference profile, and adjusts future deal recommendations accordingly.

Surprise Spin

Turn every pickup into a mini game: spin a digital wheel after completing your order to win random instant perks like bonus points, complimentary sides, or exclusive discounts—adding an element of fun and surprise to loyalty rewards.

Requirements

Spin Wheel UI Component
"As a customer, I want to spin an engaging digital wheel after placing my order so that I can win surprise perks and feel rewarded."
Description

Design and implement an interactive digital spin wheel that appears immediately after order completion. The wheel must be responsive across devices, visually match TableHop’s branding, display distinct segments for each perk, and allow smooth touch or click interaction. The component should fetch available perks from the backend in real time and handle user input to initiate and animate the spin.

Acceptance Criteria
Responsive Spin Wheel Display on Mobile Devices
Given the user is on the order confirmation page on a mobile device When the spin wheel component loads Then the wheel scales to fit within the viewport, all segments are fully visible, and touch targets are at least 44x44 pixels
Spin Wheel Branding Consistency
Given the spin wheel is rendered on desktop or mobile When the component initializes Then the wheel colors, fonts, and logo match the TableHop brand guidelines
Real-Time Perks Fetch and Display
Given the user opens the spin wheel after completing an order When the backend API returns available perks with HTTP 200 Then the wheel displays all returned perk segments sorted by priority within 200ms
Smooth Spin Animation on User Interaction
Given the user taps or clicks the spin button When input is detected Then the wheel spins with a 2-second easing animation and stops on a single segment
Error Handling for Perk Retrieval Failure
Given the API request for perks fails with an error When the spin wheel component loads Then an error message 'Unable to load perks. Please try again later.' is displayed and the spin button is disabled
Random Reward Generation Engine
"As a customer, I want the perk I win to be selected fairly and transparently so that the surprise feels genuine and trustworthy."
Description

Develop a backend service responsible for selecting random rewards based on configurable probabilities. The engine must support weighted distribution, ensure fairness, prevent awarding out-of-stock perks, and scale to handle concurrent spin requests. It should log each spin outcome for auditing and analytics.

Acceptance Criteria
User Spins the Digital Wheel After Order Completion
Given a user has completed a takeout order, When the user clicks the ‘Spin’ button, Then the system must select one reward from the active rewards pool according to configured weights and display it immediately.
Reward Weighting Honors Configured Probabilities
Given rewards with assigned probability weights, When 1000 consecutive spins are simulated, Then each reward’s selection count must be within ±5% of its configured probability distribution.
Prevention of Out-of-Stock Perk Distribution
Given a reward marked as out-of-stock in the inventory service, When a spin occurs, Then the engine must exclude that reward from the selection pool so it cannot be awarded.
High-Concurrency Spin Requests Handling
Given 500 concurrent spin requests from different users, When processed by the reward engine, Then all requests complete within 200ms without errors and each returns a valid reward.
Spin Outcome Logging for Auditing
Given the reward engine determines a spin outcome, When the outcome is finalized, Then the system logs spinId, userId, rewardId, timestamp, and probability weight to the audit log for each spin.
Reward Redemption Workflow
"As a customer, I want my spin winnings to be automatically applied to my order or account so that I don’t have to manually claim or enter any codes."
Description

Create an automated workflow that processes the outcome of each spin and applies the corresponding perk to the user’s account or current order. This includes updating loyalty point balances, adding complimentary items to orders, adjusting order totals for discounts, and issuing unique promo codes when necessary. The workflow must handle edge cases and rollback on failure.

Acceptance Criteria
Loyalty Points Update Validation
Given a user wins bonus loyalty points on a spin, when the workflow processes the spin result, then the user's loyalty points balance increases by the exact bonus amount within 2 seconds and the updated balance is visible in the account dashboard.
Complimentary Item Addition Verification
Given a user wins a complimentary side item, when the order is updated, then the complimentary item is automatically added to the order summary and kitchen ticket with the correct quantity and zero additional charge.
Discount Application Confirmation
Given a user wins a percentage or fixed-amount discount, when the order total is calculated at checkout, then the discount is applied correctly to reduce the order total, the new total is displayed to the user, and loyalty points are adjusted accordingly.
Promo Code Issuance and Uniqueness Check
Given a user is awarded a promo code, when the code is generated, then a unique 10-character alphanumeric code is created, delivered to the user's notification center, and the code is valid for a single redemption before its expiration date.
Error Handling and Rollback Assurance
Given any failure occurs during perk application (e.g., database error or service timeout), when the workflow detects the error, then all changes made during the transaction are rolled back to the previous state, an error is logged, and the user receives an error notification within 3 seconds.
Animations and Feedback Integration
"As a customer, I want fun animations and clear feedback during and after the spin so that the experience feels exciting and accessible."
Description

Implement engaging animations, sound effects, and visual feedback tied to the spin wheel interaction. Include pre-spin loading animation, realistic wheel rotation physics, celebratory confetti or banner for wins, and graceful messaging for ‘better luck next time.’ Ensure accessibility by providing alternative text and adjusting animations for reduced-motion preferences.

Acceptance Criteria
Pre-Spin Loading Animation Display
Given the user initiates the spin, when the spin button is tapped, then a loading animation appears within 0.5 seconds and remains visible until the wheel is fully initialized without blocking further interaction.
Realistic Wheel Rotation During Spin
Given the wheel is loaded, when the user taps ‘Spin’, then the wheel rotates with smooth acceleration and deceleration over 3–5 seconds and comes to rest on a valid segment reflective of the earned perk.
Celebratory Effect on Winning Outcome
Given the spin lands on a winning perk, when the wheel stops, then confetti animation overlays the screen for at least 2 seconds accompanied by a celebratory sound effect and a banner displays the perk name.
Gracious Feedback for Non-Winning Spin
Given the spin results in no prize, when the wheel stops, then a “Better luck next time” message appears within 1 second with a subtle fade-in animation and a neutral tone sound effect.
Reduced-Motion Accessible Animations
Given the user has enabled reduced-motion preferences, when any spin-related animation is triggered, then animations are replaced by static transitions or minimal motion and alternative text is provided for each visual feedback.
Admin Configuration Dashboard
"As a restaurant owner, I want to configure available perks and their probabilities in an admin dashboard so that I can tailor promotions to my customers’ preferences."
Description

Extend the restaurant owner’s admin console with a dedicated interface for configuring the spin wheel. Owners should be able to define available perks, set individual segment probabilities, schedule active spin periods, set per-user spin limits, and preview the wheel layout. Changes must validate input and be versioned for rollback.

Acceptance Criteria
Add New Perk Segment
Given the restaurant owner is on the spin wheel configuration page, when they click “Add Segment” and input a perk name, reward type, description, and probability percentage, then the new segment appears in the segment list with the exact input values and the wheel preview updates to include the new segment.
Adjust Segment Probability
Given existing segments total probability equals 100%, when the owner edits a segment’s probability to a new value, then the system validates that the sum of all segment probabilities does not exceed 100% and displays an error if it does.
Schedule Spin Availability Period
Given the owner defines a spin activation start date/time and end date/time, when they save the schedule, then the system accepts only non-overlapping, future date ranges and displays confirmation of the scheduled period.
Set User Spin Limit
Given the owner specifies a maximum spins-per-user per day, when they enter a numeric limit and save, then the configuration enforces that users cannot spin more times than the set limit within a 24-hour window.
Preview Spin Wheel Configuration
Given the owner has configured multiple segments with labels, colors, and probabilities, when they open the preview pane, then the wheel graphic accurately displays each segment’s label, color, and relative size proportional to its probability.
Version Control and Rollback
Given any change to the spin wheel configuration is saved, when the owner views the version history, then each saved version shows a timestamp and user, and selecting “Rollback” restores the wheel to that version’s exact settings.
Spin Analytics and Reporting
"As a product manager, I want to view analytics on spin usage and reward redemptions so that I can measure engagement and adjust configurations for maximum ROI."
Description

Build reporting capabilities that track and visualize key metrics such as total spins, win distribution, redemption rates, and per-perk performance. Integrate with the existing analytics dashboard, allow filtering by date range and restaurant location, and export data for deeper analysis. Ensure real-time updates and historical data retention.

Acceptance Criteria
Total Spins Count Visualization
Given a selected date range and restaurant location, when the analytics dashboard loads, then it displays the total number of wheel spins matching the selection and the displayed count matches the database records.
Win Distribution Visualization
Given a selected date range and restaurant location, when viewing the analytics dashboard, then it presents a breakdown of spin outcomes with counts and percentages for each prize type, and the values align with stored spin data.
Redemption Rate Tracking
Given a selected date range and restaurant location, when inspecting the dashboard, then it calculates and displays the percentage of spins that resulted in redeemed perks and the rate matches manual calculations over the filtered dataset.
Per-Perk Performance Metrics
Given applied filters, when accessing the analytics section, then the dashboard lists each perk type with awarded count, redeemed count, and redemption rate per perk, and all metrics correspond to the filtered spin records.
Filter Spin Data by Date Range and Location
Given the date range and location filters, when the user applies or clears a filter, then all analytics metrics on the dashboard update in real time to reflect only the spins within the selected parameters.
Export Spin Analytics Data
Given applied filters for date range and location, when the user initiates a data export, then the system generates and downloads a CSV file containing all displayed metrics with correct headers and data matching the dashboard view.

Tier Tracker

Visualizes your progress toward loyalty tiers with a dynamic progress bar and clear milestones—letting you see at a glance how close you are to earning higher-level benefits like VIP pricing, priority pickups, and anniversary gifts.

Requirements

Real-time Data Synchronization
"As a loyalty program member, I want my spending and order updates to reflect instantly in my tier progress so that I always see up-to-date information about how close I am to earning new benefits."
Description

Ensure that order and spending data used to calculate loyalty tier progress is synchronized in real-time between the order management system and the Tier Tracker dashboard, minimizing delays or discrepancies. This involves implementing API endpoints or message queue integrations that push updates immediately upon order completion, updating the user’s progress metrics within seconds. The requirement enhances data accuracy, improves user trust in the loyalty system, and supports timely milestone notifications.

Acceptance Criteria
Order Completion Sync Updates User Progress
Given an order is marked completed in the order management system, when the system pushes the update, then the Tier Tracker dashboard reflects the updated spending and tier progress within 5 seconds with no discrepancies.
Manual Refresh Reflects Latest Progress
Given a user has not opened the Tier Tracker dashboard for over a minute, when they manually refresh the page, then the dashboard fetches and displays the current spending and tier progress matching the order management system within 3 seconds.
Network Interruption Resilience
Given a temporary network interruption during data synchronization, when connectivity is restored, then the system automatically retries and synchronizes all pending order updates within 10 seconds without data loss or duplication.
Bulk Order Processing in Peak Hours
Given multiple orders complete simultaneously during peak traffic, when the message queue processes the batch, then the Tier Tracker updates cumulative spending and progress accurately within 10 seconds per batch, maintaining correct ordering and totals.
Tier Milestone Notification Trigger
Given a user crosses a loyalty tier threshold upon an order completion, when the updated spending is synchronized, then the system triggers the in-app milestone notification within 3 seconds and displays the new tier status correctly.
Dynamic Progress Bar
"As a loyalty program member, I want to see a visual progress indicator so that I can quickly understand how much more I need to spend to reach the next tier and unlock rewards."
Description

Display a dynamic, interactive progress bar on the user’s loyalty dashboard that visually represents current progress toward the next loyalty tier. The bar should update in real time, use color coding to indicate completed versus remaining progress, and adapt responsively to different screen sizes. This feature boosts user engagement by making progress easy to track at a glance and motivating further participation in the loyalty program.

Acceptance Criteria
Zero Progress Scenario
Given a user with zero loyalty points visits the dashboard, the progress bar displays a 0% fill with the remaining segment colored gray.
Mid-Tier Progress Update Scenario
Given a user has accumulated 50% of the points required for the next tier, the progress bar displays exactly 50% fill, with the completed portion in the primary tier color and the remaining portion in the secondary tier color.
Tier Achievement Real-Time Update Scenario
When a user completes an order that pushes their points above the next tier threshold, the progress bar animates from its previous fill level to 100% and then resets to 0% and retracks in the new tier color scheme within one second of order confirmation.
Responsive Display Scenario
When the dashboard is viewed on devices with viewport widths between 320px and 1920px, the progress bar scales responsively, maintaining full visibility of percentage labels and touch targets without horizontal scrolling or truncation.
Color Coding Accuracy Scenario
The completed portion of the progress bar uses #FF9900 and the remaining portion uses #E0E0E0, matching the approved design system, and passes a visual pixel-match test in the QA environment.
Tier Milestone Alerts
"As a loyalty program member, I want to receive notifications when I hit spending milestones or unlock a new tier so that I feel recognized and motivated to continue earning rewards."
Description

Implement real-time milestone alerts that notify users when they reach predefined spending thresholds or tier upgrades. Notifications should appear within the dashboard and optionally via push/email, highlighting the new tier benefits and any immediate reward eligibility. This requirement increases user satisfaction by celebrating achievements and encouraging continued engagement.

Acceptance Criteria
Dashboard Tier Upgrade Notification
Given a user’s total spend reaches the Bronze tier threshold, When the user logs into TableHop’s dashboard, Then an on-screen modal displays a congratulatory milestone alert indicating the Bronze tier has been unlocked along with the associated benefits.
Opt-in Push and Email Alerts
Given a user has enabled push and email notifications, When the user’s cumulative spending surpasses the Silver tier threshold, Then the system sends both a push notification to the user’s device and an email with details of the Silver tier benefits and any immediate rewards.
Immediate Reward Eligibility Highlight
Given a user achieves a new tier that includes an immediate reward, When the milestone alert is displayed, Then the alert prominently highlights the immediate reward and includes a call-to-action button to claim the reward in-app.
Real-time Alert Data Accuracy
Given a recent qualifying transaction, When the transaction is processed, Then the dashboard’s tier progress bar updates instantly and the milestone alert triggers without requiring a page refresh.
Notification Suppression for DND Mode
Given a user has enabled ‘Do Not Disturb’ hours in notification settings, When the user reaches a new tier during these hours, Then the milestone alert is queued and delivered once the DND window ends, and no notifications are sent during the suppressed period.
Benefit Details Overlay
"As a loyalty program member, I want to view the specific benefits of each tier within the progress interface so that I understand exactly what I’ll receive when I reach the next level."
Description

Provide an interactive overlay or pop-up that displays detailed information about the benefits associated with each loyalty tier. Users should be able to click on any tier milestone marker to view specific perks, eligibility criteria, and expiration details. Integrating this feature within the Tier Tracker ensures transparency and helps users understand the value of progressing through tiers.

Acceptance Criteria
Tier Milestone Marker Click
Given the user is viewing the Tier Tracker, when they click on a specific tier milestone marker, then a benefit details overlay must appear centered on the screen within 300ms.
Benefit Overlay Content Accuracy
Given the benefit details overlay is displayed, then it must list all perks, eligibility criteria, and expiration dates for the selected tier exactly as defined in the design specification.
Benefit Expiration Visibility
Given the benefit details overlay is displayed, when a perk has an expiration date, then the expiration date must be shown in DD/MM/YYYY format and highlighted.
Closing Benefit Overlay
Given the benefit details overlay is open, when the user clicks the close icon or anywhere outside the overlay, then the overlay must close and return focus to the previously selected tier marker.
Mobile Responsiveness of Benefit Overlay
Given the user is on a mobile device, when they tap a tier milestone marker, then the benefit details overlay must open full-screen with scrollable content and a visible close button.
Tier Progress CTA and Recommendations
"As a loyalty program member, I want actionable suggestions that guide me toward my next tier so that I can make informed decisions and accelerate my progress."
Description

Add a contextual call-to-action (CTA) section beneath the progress bar that suggests personalized actions—such as recommended menu items or order amounts—to help users reach the next loyalty tier. The CTA should update dynamically based on current progress and user order history, providing tailored incentives like limited-time offers or bonus points opportunities.

Acceptance Criteria
Dynamic CTA Suggestions Display
Given a user viewing their loyalty tier progress bar, when their progress is below the next tier threshold, then a CTA section displaying suggested actions appears directly beneath the progress bar.
Menu Item Recommendation Accuracy
Given a user’s past order history, when generating CTA suggestions, then the system recommends menu items that the user has purchased before and are eligible for bonus points.
Limited-Time Offer Highlight
Given an active limited-time promotion, when the user’s progress triggers eligibility, then the CTA dynamically displays the promotion’s details and expiration date.
Bonus Points Promotion Trigger
Given a bonus points campaign, when the user places an order amount that qualifies, then the CTA suggests increasing the order amount to meet bonus point thresholds.
Responsive CTA Update on Order History Change
Given a user completes a new order, when the loyalty progress recalculates, then the CTA section updates in real-time to reflect the new progress and tailored recommendations.

Product Ideas

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

PlatePeek Preview

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Idea

SideNote Chat

Enable instant messaging between customers and kitchen staff for special requests or allergy alerts, cutting misorders by up to 50%.

Idea

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Offer biometric-secured, one-tap payment for preorders using saved preferences, slashing checkout time to under three seconds.

Idea

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Automatically apply loyalty credits after curbside pickups, unlocking personalized deals and gamified streak bonuses.

Idea

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Embed sensors in containers to monitor food temperature, sending alerts if meals drop below 140°F to maintain quality.

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Press Coverage

Imagined press coverage for this groundbreaking product concept.

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TableHop Introduces Urgent Ping to Eliminate Takeout Errors and Accelerate Curbside Service

Imagined Press Article

CITY, STATE – 2025-07-29 – TableHop today announced the launch of Urgent Ping, a high-priority notification feature designed to drastically reduce takeout errors and speed up curbside handoffs for urban restaurants. Urgent Ping flags allergy alerts and critical special requests with visual cues on both the kitchen dashboard and customer devices, ensuring immediate attention and a flawless pickup experience. In the fast-paced world of urban takeout, even minor miscommunications can lead to dissatisfied customers and lost revenue. TableHop’s Urgent Ping addresses this challenge head-on by elevating urgent orders above the normal queue, triggering pulsating notifications and red banners on the kitchen dashboard. Simultaneously, customers receive a confirmation alert that their special requirements have been prioritized, providing peace of mind and setting clear expectations. “Errors in takeout orders erode trust and loyalty,” said Jordan Nguyen, CEO of TableHop. “With Urgent Ping, we’re giving restaurants the tools they need to tackle critical requests immediately and deliver a seamless experience every time. Families with allergies, dietary restrictions, or rush schedules can now feel confident that their needs won’t be overlooked.” How Urgent Ping Works • High-priority triggers: When a customer selects an allergy alert or a time-sensitive request, Urgent Ping automatically elevates that order. • Visual alert system: Flashing banners and color-coded indicators appear on the kitchen dashboard, drawing immediate attention. • Real-time customer confirmation: Customers receive push notifications confirming their request is flagged as urgent. • Integrated analytics: Restaurant managers can generate reports on flagged requests to refine staff training and menu offerings. Restaurant Impact Since pilot testing Urgent Ping in select markets, participating restaurateurs have reported a 45% decrease in order errors related to allergies and special requests. One early adopter, Marcella’s Kitchen in downtown Cityville, saw customer satisfaction scores rise from 82% to 96% within the first month of implementation. “Our guests appreciate knowing we take their dietary needs seriously,” said owner Marcella Ruiz. “Urgent Ping has been a game changer for our curbside business.” Customer Benefits • Families with allergies can predefine their needs and receive real-time confirmation, reducing anxiety around takeout options. • Busy commuters and time-sensitive patrons can flag rush-hour pickups to ensure their order is expedited. • First-time explorers gain confidence in TableHop’s reliability, helping convert one-time users into regular customers. Availability and Integration Urgent Ping is available immediately for all TableHop clients at no additional cost. Existing users can enable the feature via their dashboard settings, while new customers will have it activated by default. The feature seamlessly integrates with TableHop’s existing real-time dashboard, curbside arrival alerts, and request management modules, requiring no additional hardware or staffing adjustments. About TableHop TableHop empowers independent urban restaurant owners with a real-time order dashboard and instant curbside arrival alerts. By slashing takeout errors and wait times, TableHop helps restaurateurs reclaim profits and control their takeout experience while enabling families to order ahead, skip lines, and avoid third-party fees. Contact Information For media inquiries, please contact: Morgan Patel Director of Communications, TableHop Email: morgan.patel@tablehop.com Phone: (555) 123-4567 Website: www.tablehop.com

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TableHop Launches BioPay Unlock and AutoTender to Deliver Frictionless Payments

Imagined Press Article

CITY, STATE – 2025-07-29 – TableHop today unveiled two groundbreaking payment features—BioPay Unlock and AutoTender—designed to eliminate checkout friction for both first-time and loyal curbside customers. By harnessing device-native biometric authentication and intelligent payment routing, TableHop ensures transactions complete in under three seconds while automatically selecting the best payment method for maximum value. In a world where speed and convenience are non-negotiable, long checkout times and payment failures can undermine the customer experience and slow down order flow for busy restaurants. TableHop’s BioPay Unlock leverages Face ID, Touch ID, and other biometric protocols to provide a one-scan authorization process, while AutoTender analyzes order size, loyalty rewards, and past preferences to choose the optimal saved payment method. “Checkout should be the easiest part of any transaction,” said Riley Chen, Chief Technology Officer at TableHop. “By combining biometric security with AI-driven payment selection, we’re removing all barriers between customers and their meals. Restaurants benefit from faster turnover and fewer failed payments, and diners get in and out in seconds.” Feature Highlights BioPay Unlock • Device-native security: Utilizes existing biometric systems—Face ID, Touch ID—for instant payments. • Under-three-second checkout: Removes PINs and passwords, streamlining the process. • High-level encryption: Ensures all biometric data remains secure and confidential. AutoTender • Smart payment routing: Analyzes order details, loyalty credit balances, and rewards to pick the best payment option. • Real-time updates: Provides transparent confirmation of which card or wallet was used. • Configurable preferences: Allows customers to set fallback rules (e.g., always use credit first, then wallet). Restaurant and Customer Benefits • Faster turnover: Reduced checkout times allow restaurants to process more orders per hour. • Fewer declined transactions: AutoTender minimizes the risk of payment declines by selecting optimal funds. • Enhanced security: Biometric authentication decreases fraud and eliminates password fatigue. • Improved customer satisfaction: Seamless payments boost NPS scores and foster loyalty. Early Results During a beta trial with over 50 urban eateries, BioPay Unlock reduced average checkout time from 12 seconds to 2.5 seconds, while AutoTender decreased payment error rates by 38%. “Our curbside queue moves more smoothly than ever,” said Chef Daniel Morales of Riverside Bites. “Customers love the one-scan convenience, and we’re seeing repeat orders increase by 15%.” Availability Both BioPay Unlock and AutoTender are available immediately to all TableHop subscribers as part of the standard platform package. Activation requires a simple settings toggle; no additional integrations or fees are necessary. About TableHop TableHop equips independent urban restaurants with a real-time dashboard and instant curbside arrival alerts. By slashing takeout errors and wait times, TableHop allows restaurateurs to reclaim profits and deliver a superior pickup experience, turning first-time visitors into loyal regulars. Contact Information For further details or interview requests, reach out to: Alexandra Gomez Director of Marketing, TableHop Email: alexandra.gomez@tablehop.com Phone: (555) 987-6543 Website: www.tablehop.com

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TableHop Unveils PlatePeek Preview and Freshness Ticker for Perfect Curbside Pickups

Imagined Press Article

CITY, STATE – 2025-07-29 – TableHop today announced the rollout of PlatePeek Preview and Freshness Ticker, two innovative features that give customers unprecedented visibility into their curbside orders before arrival. By enabling real-time dish photos and live freshness countdowns, TableHop ensures diners receive exactly what they expect—at peak quality. As curbside pickup becomes increasingly popular, customers often face uncertainty around portion sizes, presentation, and meal freshness. PlatePeek Preview addresses these concerns by scanning a QR code to display up-to-the-minute dish photos taken just before handoff. Freshness Ticker complements this by showing a live countdown of how long ago the dish was plated and its optimal consumption window. “Food quality and presentation are at the heart of every great restaurant,” said Priya Desai, Vice President of Product at TableHop. “With PlatePeek Preview and Freshness Ticker, we’re bringing the in-restaurant experience to the curbside lane. Customers can see their meal’s plating down to the last garnish, and know exactly when to arrive for the best taste.” PlatePeek Preview Details • QR-driven access: Diners scan a code on their order confirmation to view high-resolution images captured in the kitchen. • Multiple angles: Photos showcase each dish from three perspectives—overhead, side profile, and close-up—to give a complete visual. • Real-time updates: Images are refreshed every two minutes until pickup, reflecting any last-minute tweeks. Freshness Ticker Details • Live plating timer: Displays the minutes and seconds since plating, with color-coded indicators for peak, acceptable, and stale windows. • Customizable thresholds: Restaurants set their own optimal freshness timing for each menu item. • Arrival guidance: Suggests best pickup times to customers based on their ETA and the dish’s freshness. Restaurant and Customer Impact In pilot tests with ten independent urban eateries, PlatePeek Preview reduced order-change requests by 30% as customers confirmed details visually before pickup. Freshness Ticker improved on-time arrivals by 22%, since diners could see when their meal was at its freshest and time their departure accordingly. “Seeing the dish in advance gives our guests confidence, and the freshness timer makes sure they hit the sweet spot,” said Marcus Lee, owner of Elm Street Café. “We’ve noticed fewer complaints about cold fries or wilted greens, and an uptick in five-star reviews.” Availability and Integration PlatePeek Preview and Freshness Ticker are available immediately to all TableHop clients. Activation requires an update to the restaurant app, which is automatically deployed through TableHop’s cloud platform. Both features integrate seamlessly with existing curbside workflows and require no additional staff training. About TableHop TableHop empowers independent urban restaurant owners with a real-time order dashboard and instant curbside arrival alerts. By slashing takeout errors and wait times, TableHop helps restaurateurs reclaim profits and control the curbside experience—turning first-time visitors into lifelong regulars. Media Contact Taylor Rodriguez Public Relations Manager, TableHop Email: taylor.rodriguez@tablehop.com Phone: (555) 321-8901 Website: www.tablehop.com

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