PRD Template for Food Delivery Products

Example: "Average order-to-delivery time is 52 minutes, with 38% of delays caused by inaccurate restaurant prep time estimates. Couriers spend an average of 8.3 minutes waiting at restaurants for orders that are not ready, reducing their effective hourly earnings from $18 to $14.20. Customer satisfaction drops 12 percentage points for every 10 minutes beyond the estimated delivery time. 24% of customer support contacts are about delivery time — each contact costs $3.40 to resolve."

Example: "Primary: Reduce average order-to-delivery time from 52 to 38 minutes within 90 days. Restaurant: Reduce courier wait time at restaurant from 8.3 to under 3 minutes through improved prep time prediction. Courier: Increase average deliveries per hour from 2.1 to 2.8 without extending working hours. Unit economics: Maintain or improve contribution margin per order at $1.20. Guardrail: Food quality rating must not decrease below 4.2/5 average."

Example: "As a consumer, I want to see a real-time estimated delivery time that updates as my order progresses so that I can plan when to be available to receive the delivery. Acceptance criteria: ETA displayed immediately after order placement; ETA updates in real-time based on restaurant prep progress and courier location; push notification sent when courier is 5 minutes away; accuracy target: actual delivery within 5 minutes of displayed ETA for 80% of orders. As a courier, I want to see the order details and restaurant pickup instructions before I arrive so that I can go directly to the pickup counter without searching."

Example: "FR-1: Dispatch algorithm must assign couriers to orders within 30 seconds of restaurant accepting the order, optimizing for: estimated total delivery time, courier current location, courier active order load (max 2 concurrent), and restaurant prep time estimate. FR-2: Real-time tracking must show courier location with updates every 10 seconds and accuracy within 20 meters. FR-3: Dynamic prep time estimation using restaurant-specific historical data: average prep time by menu item category, current order queue depth, and time of day. FR-4: Order batching: system may assign 2 orders from the same restaurant to one courier if delivery addresses are within 1.5 km and combined delivery time is under 15 minutes above single-order time."

Example: "OP-1: Food safety — maximum time from restaurant handoff to customer delivery must not exceed 45 minutes; orders exceeding this threshold trigger automatic quality alert and customer notification. OP-2: Courier safety — app must not display new order notifications while courier is actively navigating (speed above 5 km/h); no in-app actions requiring text input during active navigation. OP-3: Restaurant food safety certification verification during onboarding — valid health department permit required. OP-4: Temperature-sensitive items (ice cream, sushi) must be flagged in dispatch to prioritize direct delivery without batching."

Example: "Delivery speed: Average order-to-delivery time. Baseline: 52 min. Target: 38 min. ETA accuracy: Percentage of deliveries within 5 min of estimated time. Baseline: 58%. Target: 80%. Consumer: Order satisfaction rating. Baseline: 4.1/5. Target: 4.4/5. Restaurant: Average courier wait time at restaurant. Baseline: 8.3 min. Target: under 3 min. Courier: Average deliveries per active hour. Baseline: 2.1. Target: 2.8. Economics: Contribution margin per order. Baseline: $1.20. Target: $1.50."

Example: "Phase 1 (Weeks 1-4): Core ordering, dispatch, and tracking. Milestone: End-to-end order flow working with 5 test restaurants. Phase 2 (Weeks 5-8): Prep time prediction and dynamic dispatch optimization. Milestone: Predicted prep time within 3 minutes of actual for 70% of orders. Phase 3 (Weeks 9-10): Restaurant onboarding portal and courier app. Milestone: 50 restaurants onboarded, 100 couriers activated. Phase 4 (Weeks 11-14): Soft launch in single market (1 city zone). Milestone: 500 completed orders with 4.0+ average rating. Phase 5 (Weeks 15-20): Market expansion to full city."

Example: "Risk: Peak demand overwhelms courier supply, leading to 60+ minute delivery times and mass cancellations. Likelihood: High (every Friday/Saturday evening). Impact: High. Mitigation: Dynamic pricing (surge) to attract more couriers during peak; order throttling when courier supply drops below 1:3 ratio; proactive customer communication about extended delivery times. Risk: Courier classified as employee rather than contractor by labor regulator. Likelihood: Medium. Impact: Critical (business model change). Mitigation: Ensure courier flexibility (choose hours, decline orders, multi-app); legal counsel on classification in each operating market."

Example: "Integration 1: Restaurant POS — Square, Toast, Clover direct integration for automatic order injection; fallback: tablet-based order acceptance. Integration 2: Mapping — Google Maps Platform for routing, ETA calculation, and geocoding. SLA: 99.99%. Integration 3: Stripe Connect — consumer payment, restaurant settlement, and courier payout with real-time split. Integration 4: Twilio — masked phone numbers for consumer-courier communication; SMS order status updates. Integration 5: Segment — event tracking for consumer funnel, conversion, and retention analysis."

Example: "Q1: Should we implement dynamic pricing (surge) during peak demand or maintain flat delivery fees? Surge improves courier supply but frustrates consumers. Decision owner: CEO. Needed by: Week 3. Q2: Should couriers be able to see the delivery tip amount before accepting an order? Transparency improves acceptance rate but may lead to cherry-picking. Decision owner: Head of Operations. Needed by: Week 2. Q3: What commission rate for restaurants? Industry ranges from 15-30% — lower rates attract more restaurants but hurt unit economics. Decision owner: Head of Partnerships. Needed by: Week 4."