Strategy question
What pricing enhancements can we make to reduce driver rejections?
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What this question tests
Tests pricing strategy for a marketplace supply problem, connecting driver incentives to the specific trips they tend to reject.
How to approach it
- Clarify the problem: drivers reject requests they see as low value, short trips, low fares relative to distance, or requests heading away from high-demand areas.
- Segment rejected requests by trip characteristics, distance, fare, and destination zone, to find the pattern behind rejections.
- Propose fare adjustments that better reflect a trip's true cost to the driver, like a minimum fare floor for short trips and a destination-zone bonus for trips ending in low-demand areas.
- Add transparency, showing drivers estimated trip value before they decide, rather than a blind request they can only accept or reject.
- Define success as reduced rejection rate for previously low-acceptance trip types and stable or improved rider wait time.
What a strong answer includes
- Segments rejections by trip characteristics first, correctly identifying the pattern before proposing a fix.
- Names concrete pricing mechanisms, minimum fare floors and destination bonuses, tied directly to why drivers reject specific trip types.
- Adds pre-acceptance transparency, addressing driver decision-making directly rather than pricing alone.
Common mistakes
- Proposing a blanket fare increase without analyzing which specific trip types drivers actually reject.
- Ignoring driver-side transparency, since drivers reject partly due to uncertainty about a trip's true value.
Likely follow-up questions
- How would you avoid a minimum fare floor making short trips unprofitable for the platform?
- How would you balance rider fare increases against driver acceptance improvements?
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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 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 14: Get the job: the AI PM interview loop