How to test bike delivery?

You are a data scientist at a food-delivery marketplace. The company is considering launching a **bicycle courier delivery option** in selected cities. Design a data-driven approach to evaluate this launch. Please address the following: 1. **Why might bike delivery be worth considering?** Discuss potential business, customer, courier, and operational benefits versus existing delivery modes such as cars or scooters. 2. **What factors should be considered before launching or testing it?** Include marketplace effects, city density, delivery distance, terrain, weather, order mix, courier supply, parking, safety, regulatory constraints, and possible cannibalization of existing courier modes. 3. **What metrics would you use?** Define a north-star metric, supporting operational metrics, and guardrail metrics. Explain tradeoffs among speed, cost, fulfillment, quality, courier economics, and safety. 4. **What type of experiment would you run?** Explain the most appropriate experimentation design for a two-sided marketplace, including the unit of randomization, experiment duration, segmentation, and how you would handle interference between treatment and control. 5. **How would you decide whether to scale the launch?** Describe how you would interpret results, account for confounding factors such as weather and time of day, and make a go / no-go recommendation.