Metrics question
What are your solutions to reduce the car cancellation rate on the Uber waiting page?
- Uber
- Metrics
- Medium
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What this question tests
Tests diagnosing and reducing cancellations during a specific high-anxiety moment in the ride flow, the waiting page.
How to approach it
- Clarify what's driving cancellations: long wait time, surge pricing surprise, driver behavior (wrong direction, no movement), or rider changing their mind.
- Segment cancellations by who cancels, rider or driver, since the fix differs; also segment by wait-time bucket.
- Propose rider-side fixes: more accurate live ETA, proactive notification if ETA worsens, and a one-tap reason survey on cancel to close the data loop.
- Propose driver-side fixes: better routing to reduce actual wait time, and reducing driver-side cancellations via incentive changes for long pickups.
- Define success as cancellation rate reduction segmented by cause, and completed-ride rate as the guardrail this shouldn't come at the cost of.
What a strong answer includes
- Separates rider-initiated from driver-initiated cancellations, since interviewers expect you to recognize this is a two-sided problem.
- Proposes a cancel-reason survey as a cheap, high-leverage fix that also generates data for future diagnosis.
- Uses an illustrative number, e.g. assume cancellations spike when ETA exceeds 7 minutes, to justify a proactive-notification threshold.
- Ties the fix to a broader guardrail, completed-ride rate, so cancellations aren't reduced by just hiding the cancel button.
Common mistakes
- Proposing a single fix without first segmenting who cancels and why.
- Focusing only on rider experience and ignoring driver-side cancellation causes.
Likely follow-up questions
- How would you use the cancel-reason data to prioritize fixes?
- What would you do differently in a market with a driver-supply shortage?
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More questions from Uber
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