# Solution Alignment Notes Treat the merchant complaint as a data signal to investigate. Balance merchant capacity, customer reliability, dasher wait time, and marketplace growth when recommending mitigations. --- ### 1) Triage: verify the issue and quantify impact Start by aligning on what “too much traffic” means operationally: - Max orders/hour the kitchen can handle - Staffing level by daypart - Whether the pain is from *order volume*, *order timing* (spikes), or *order complexity* Pull a before/after view (e.g., last 2 weeks vs prior 4 weeks) for that merchant (and comparable merchants): - Orders/hour by daypart; peakiness (P95 orders/hour) - Prep time (P50/P90) and variance - Merchant cancellation rate and reason codes - Late orders, refunds, missing items - Dasher wait time at store If merchant KPIs degraded at the same time volume spiked, the complaint is likely valid. ### 2) Diagnose root causes (common patterns) **A. Demand spike drivers** - Promotions, pricing changes, featured placement, search ranking changes - Local events or competitor outage **B. Capacity mismatch** - Merchant hours/availability inaccurate (store marked open while understaffed) - Menu item availability not updated (out-of-stock leading to substitutions/delays) **C. Incorrect operational parameters** - Prep-time settings too low → dashers arrive early and congestion builds - No effective throttling / order caps during peak **D. Marketplace spillovers** - Delivery radius too large bringing in extra demand - Reassignment/batching causing bursty arrivals at the merchant ### 3) Interventions (balance all sides) Pick the least invasive intervention that restores service quality. **Merchant-protecting controls** - **Order throttling / caps**: max orders per 15 minutes during peak. - **Busy mode** / dynamic prep times based on real-time backlog. - **Temporary pause** or reduced delivery radius during staffing shortages. - Improve menu management (auto-86 items when out-of-stock signals appear). **Consumer experience safeguards** - Update quoted ETAs and availability transparently instead of accepting orders that will fail. - If throttling reduces supply, ensure ranking/search reflects availability to reduce frustration. **Dasher experience safeguards** - If the merchant is congested, reduce early arrivals by delaying dispatch or improving ready-time prediction. **Operational partnership** - For top merchants, offer ops playbooks: staffing guidance for expected demand, peak-hour scheduling. ### 4) Measurement and monitoring **Primary success outcomes (merchant health):** - Merchant cancellation rate ↓ - Prep time P90 ↓ (or stabilizes) - Dasher wait time ↓ - Merchant satisfaction / complaint volume ↓ **Guardrails:** - Consumer conversion and completion rate (don’t over-throttle) - On-time delivery and refund rate - Merchant revenue (avoid unnecessary demand suppression) **Evaluation design:** - If rolling out throttling logic, do merchant-level A/B (or stepped-wedge rollout) because interference is localized. - Monitor for demand shifting to nearby merchants (good) vs overall demand loss (bad). ### 5) Recommendation Treat this as a service-quality risk: accept fewer orders but deliver them reliably. Implement short-term throttles and correct prep-time/availability settings immediately, while building a longer-term dynamic capacity model (predict max sustainable order rate by daypart) to prevent recurrence.