Problem
Scenario
You are reviewing user engagement on a consumer app and notice that newer signup cohorts behave differently from older ones. A teammate suggests using cohort analysis to decide whether a recent product change improved engagement, while another suggests running an A/B test instead.
Question
What is the difference between cohort analysis and A/B testing? When would you use each, and why is an A/B test usually stronger for making causal product decisions?
What This Tests
- Ability to distinguish descriptive analysis from causal experimentation
- Understanding of hypothesis testing in product experiments
- Metric selection with primary metric and guardrails
- Basic sample-size reasoning for an A/B test
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