Problem
Scenario
You work on a ride-sharing marketplace and are testing a new pricing change. Early results suggest more completed trips, but there is concern that the change may have pulled demand forward from later hours instead of creating net new demand. You need to distinguish true demand lift from timing shifts.
Question
How would you analyze whether the pricing change increased demand or just shifted when trips happened? Explain how you would design and evaluate the experiment so you can separate incremental demand from temporal substitution.
What This Tests
- Choosing a primary metric that captures net demand, not just in-window lift
- Selecting a randomization scheme robust to marketplace interference
- Setting MDE and sample size with explicit assumptions
- Using guardrails and diagnosing timing-shift behavior
Practicing as: Product Growth Analyst interview at UberHi, I'll play your Uber interviewer for the Product Growth Analyst role. Candidates describe these interviews as mixed and moderately difficult, so expect me to be professional and fair. Take your time with the question above and answer like we're in the room.
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