product-analytics
Use when defining product KPIs, building metric dashboards, running cohort or retention analysis, or interpreting feature adoption trends across product stages.
Profile →npx skills add alirezarezvani/claude-skills --skill product-analytics --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Product Analytics Define, track, and interpret product metrics across discovery, growth, and mature product stages. ## When To Use Use this skill for: - Metric framework selection (AARRR, North Star, HEART) - KPI definition by product stage (pre-PMF, growth, mature) - Dashboard design and metric hierarchy - Cohort and retention analysis - Feature adoption and funnel interpretation ## Workflow 1. Select metric framework - AARRR for growth loops and funnel visibility - North Star for cross-functional strategic alignment - HEART for UX quality and user experience measurement 2. Define stage-appropriate KPIs - Pre-PMF: activation, early retention, qualitative success - Growth: acquisition efficiency, expansion, conversion velocity - Mature: retention depth, revenue quality, operational efficiency 3. Design dashboard layers - Executive layer: 5-7 directional metrics - Product health layer: acquisition, activation, retention, engagement - Feature layer: adoption, depth, repeat usage, outcome correlation 4. Run cohort + retention analysis - Segment by signup cohort or feature exposure cohort - Compare retention curves, not single-point snapshots - Identify inflection points around onboa
- When To Use
- Workflow
- KPI Guidance By Stage
- Pre-PMF
- Growth
- Mature
- Dashboard Design Principles
- Cohort Analysis Method
- Retention Curve Interpretation
- Anti-Patterns
- Tooling
- scripts/metricscalculator.py
- Cross-References
Retention analysis python3 scripts/metrics_calculator.py retention events.csv python3 scripts/metrics_calculator.py retention events.csv --format json Cohort matrix python3 scripts/metrics_calculator.py cohort events.csv --cohort-grain month python3 scripts/metrics_calculator.py cohort events.csv --cohort-grain week --format json Funnel conversion python3 scripts/metrics_calculator.py funnel funnel.csv --stages visit,signup,activate,pay python3 scripts/metrics_calculator.py funnel funnel.csv --stages visit,signup,activate,pay --format json
What does the product-analytics skill do?
Use when defining product KPIs, building metric dashboards, running cohort or retention analysis, or interpreting feature adoption trends across product stages.
How do I install it?
Run `npx skills add alirezarezvani/claude-skills --skill product-analytics --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From alirezarezvani/claude-skills, a repository with 23,791 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.