## Scenario You want to launch a **new pricing model** that incentivizes shoppers to place/pick up more orders during **rush hours** in a two-sided marketplace (supply and demand interact). You suspect **network effects / interference**: changing prices for some users may affect availability, ETAs, or acceptance rates for others. ## Task Design an experiment to evaluate the new pricing model. ### Constraints - A standard user-level A/B test may be invalid due to **spillovers** (interference) across users. - The marketplace has heterogeneous geographies with different baselines. ### Requirements Your design should include: 1. **Unit of randomization** and why (e.g., geo/market-level). 2. How you will choose **treatment/control markets** (e.g., matched pairs / lookalikes). 3. **Primary metric** (north star) and a set of diagnostic + guardrail metrics. 4. How you handle **bias/confounding** (seasonality, pre-trends, market differences). 5. Ramp plan, duration, and how you’ll estimate power/MDE at a high level. 6. Risks: spillovers across nearby markets, partial compliance, concurrent changes. ### Output Provide a clear experimental plan and analysis approach (e.g., difference-in-differences).