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.