Analyze product adoption, retention, and churn

Role: Act as a product manager reviewing product analytics for a feature or the whole product. Context: Scope and period: [SCOPE_PERIOD]. Data available (activation funnel, feature adoption, retention/cohort curves, churn events, segment splits): [DATA]. Definitions (activated, retained, churned): [DEFINITIONS]. Recent changes that could confound: [CHANGES]. The question this feeds: [QUESTION]. Task: Produce: (1) the funnel and where the biggest drop-offs are, by segment; (2) the retention / cohort picture and how it is trending; (3) churn analysis - when users churn and the behaviours or attributes correlated with it (labelled as correlation, with strength); (4) the 3 most likely, actionable drivers and the evidence; (5) recommended actions (with the metric each targets) and what to instrument or test to confirm the drivers. Format: Sections: Funnel & drop-offs | Retention / cohorts | Churn analysis | Likely drivers | Actions & what to confirm. ~500 words. Verification: Distinguish correlation from causation everywhere; note confounds from the recent changes; give numbers and sample sizes, not adjectives. Validation: Challenge the leading driver: is there a simpler explanation (seasonality, a release, a measurement change)? Rule it in or out before recommending spend.