Problem
Scenario
You are evaluating a product change on a feed or notification surface, but rollout was not randomized and adoption was correlated with user behavior. You still need to estimate whether the change caused a shift in outcomes rather than just reflecting selection or timing effects.
Question
How would you think about causal inference in a product setting when you can’t run a clean experiment?
What this tests
- Choosing a causal identification strategy in observational product data
- Using regression and time-based comparisons to reduce bias
- Explaining assumptions behind difference-in-differences
- Separating statistical evidence from causal credibility
Practicing as: Product Growth Analyst interview at QuoraHi, I'll play your Quora 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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