Product design question
How would you design a food delivery app?
- Microsoft
- Product design
- Easy
Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.
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What this question tests
Whether the candidate can design a three-sided marketplace, balancing eater, restaurant, and driver needs in a coherent MVP.
How to approach it
- Identify the three users: eaters wanting fast, reliable delivery, restaurants wanting order volume without high commission burden, and drivers wanting fair, predictable earnings.
- Name the core pain points: eaters want accurate ETAs, restaurants want low fees and manageable order volume, drivers want efficient routing and fair pay.
- Prioritize the core loop first: search and order for eaters, order management for restaurants, and dispatch and routing for drivers, before secondary features.
- Propose an MVP flow: browse nearby restaurants, place an order with an accurate ETA, restaurant confirms and prepares, driver is dispatched and routed efficiently.
- Define success per side: eater order completion and repeat rate, restaurant order volume and net revenue after fees, driver earnings per hour and acceptance rate.
What a strong answer includes
- Addresses all three sides of the marketplace explicitly rather than designing only for the eater.
- Prioritizes the core transactional loop over secondary features like loyalty programs or social sharing for a first version.
- Defines a distinct success metric for each side, showing the marketplace only works if all three are healthy simultaneously.
Common mistakes
- Designing only the eater-facing app and ignoring restaurant and driver needs.
- Adding secondary features before the core three-sided loop is solid.
Likely follow-up questions
- How would you balance driver pay against restaurant commission and eater delivery fees?
- What would you cut for a first launch in a single city?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 7: AI UX and human oversight: design for a system that is wrong sometimes
- Chapter 14: Get the job: the AI PM interview loop