##### Scenario A mobile app is redesigned, but the new version is only adopted by users who choose to upgrade; the team needs to measure performance impact. ##### Question Without a forced A/B test, how would you estimate the causal impact of the redesign? How would you define comparable treatment and control groups of ‘new-version’ and ‘old-version’ users? Which user features beyond engagement/behavior would you include to ensure similarity? What statistical or causal-inference methods would you apply, and how would you validate assumptions? ##### Hints Discuss propensity scores, matching, weighting, diff-in-diff, covariate balance checks, sensitivity analyses.