Product Analytics

Analytics for product teams: usage, engagement, retention, and feature adoption. Focus on what users do inside the product.

Key metrics

• DAU / MAU — Daily and monthly active users; stickiness ratio
• Retention — D1, D7, D30; cohort retention curves
• Engagement — Sessions, time in product, events per user
• Feature adoption — % of users using a feature; time to first use
• Funnel conversion — Step-by-step drop-off through key flows

Event-based analysis

• Events — User actions (clicks, views, completions) with properties
• Funnels — Conversion through a sequence of events
• Paths — What users do before or after a key action
• Segments — Cohorts by behavior, acquisition, or attributes

Retention and cohorts

• Cohort retention — Retention by signup week or acquisition source
• Churn — When and why users stop coming back
• Reactivation — Re-engagement of dormant users

Common analyses

• Retention curves by cohort and segment
• Funnel analysis for signup, onboarding, or conversion
• Feature adoption and usage over time
• Power-user identification and behavior patterns

Tools

Amplitude, Mixpanel, Heap, Pendo, PostHog — event-based product analytics. Often paired with a data warehouse for deeper SQL analysis.