Product analytics answers what users do and why they churn — an event taxonomy designed before tooling, a warehouse-centric stack, and governance
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A versioned tracking plan: events named for user intent (order_submitted, report_shared), consistent properties, and review before anything ships — untended instrumentation becomes noise nobody trusts.
Capture (SDK/CDP) → warehouse as source of truth → product analytics for exploration, dashboards for the north-star tree — warehouse-centric beats tool-silo, and keeps you portable.
Activation funnels, retention cohorts, feature adoption depth, and path-to-churn signals — four lenses that answer most product questions asked all year.
PII discipline in events, definitions documented, and one owner for metric truth — the moment two dashboards disagree, analytics stops informing decisions.
Skipping the discipline this article describes until an incident, audit, or stalled project forces it — every practice above is cheaper adopted early than retrofitted under pressure.
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