Metrics question
How would you go about building a marketplace app for finding available parking spots?
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
Tests two-sided marketplace metric design for a spatial, real-time inventory problem.
How to approach it
- Clarify the model: private or underused parking spots, driveways, empty lots, listed by owners and booked by drivers needing a spot.
- Set the core marketplace health metric as liquidity, the ratio of available listed spots to searching drivers in a given area and time window.
- Build supporting metrics: listing activation rate for spot owners, search-to-booking conversion rate for drivers, and average time to find a match.
- Add trust and reliability guardrails: no-show rate by either owners or drivers, and dispute or complaint rate.
- Segment by area density, dense downtown areas near event venues will have very different liquidity dynamics than suburban neighborhoods.
What a strong answer includes
- Centers liquidity as the core two-sided marketplace metric, the right framing for a spatial inventory problem.
- Names a specific reliability guardrail, no-show rate, critical for a marketplace built on real physical commitments.
- Segments by geographic density, recognizing this marketplace behaves very differently across different area types.
Common mistakes
- Measuring only total listings or total bookings without a true liquidity or match-rate metric.
- Ignoring no-show and reliability risk, a major trust barrier for a marketplace involving physical commitments.
Likely follow-up questions
- How would you bootstrap supply in a new area with no existing spot listings?
- How would you handle a driver arriving to find the spot already occupied?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 2: Data fluency: SQL, logs, and reading the truth yourself
- Chapter 14: Get the job: the AI PM interview loop