What do I need to use Retention Analysis?

Product and business model; Current retention metrics; Segment to analyse; Key question to answer; Available data.

Is Retention Analysis free to use?

Yes — run it free in the browser playground (no API key needed for the sponsored trial, or bring any provider key), or install it into Claude Code, Cursor, ChatGPT and more via npx pm-claude-skills. MIT-licensed and open source.

Retention Analysis

Q: How do I know the Retention Analysis output is good?

The skill verifies itself against its own quality checks: Retention curve shape is diagnosed (flattening vs trending to zero = PMF vs onboarding); Cohorts are segmented before analysis (not all users lumped together); "Aha moment" correlation is identified or flagged as unknown; Interventions are specific (not "improve onboarding").

🟢 Production-Ready🕐 updated 2026-07-14 🔷 SkillSpec L3 pm-analytics

Structure a retention analysis, churn investigation, or engagement deep-dive for any product team. Use when asked to analyse user retention, investigate churn, measure DAU/MAU, or build a retention improvement plan. Produces a retention snapshot with root cause hypotheses, aha-moment correlation, and prioritised interventions.

📚 Based on Cohort retention analysis (Reforge / Brian Balfour)

▶ Run it free — no key needed 📝 Grade your existing draft View SKILL.md ↗

What to give it

▸Product and business model — SaaS / consumer app / marketplace / other

▸Current retention metrics — D1, D7, D30 if available

▸Segment to analyse — all users / paid / free / a specific cohort

▸Key question to answer — why is retention dropping? what drives retention?

▸Available data — analytics events, churn surveys, interview notes

✅ The bar it holds itself to

Every skill in this library self-verifies — these are this skill's own quality checks, straight from its definition.

✓Retention curve shape is diagnosed (flattening vs trending to zero = PMF vs onboarding)

✓Cohorts are segmented before analysis (not all users lumped together)

✓"Aha moment" correlation is identified or flagged as unknown

✓Interventions are specific (not "improve onboarding")

✓Churned user interviews are recommended (not just data analysis)

✓Monitoring plan includes an alert threshold

⚠️ What it refuses to do

Do not recommend "improve onboarding" without specifying what specific step to change and why

Do not analyse retention without segmenting by cohort — aggregate retention curves hide cohort-specific patterns

Do not treat DAU/MAU below 5% as a retention problem — at that level, it is a product-market fit problem

Do not skip qualitative research — churned user interviews reveal reasons that quantitative data cannot

Do not set a monitoring alert without specifying the threshold that triggers it

Install

npx pm-claude-skills add --agent claude   # or codex · cursor · gemini · hermes
# or one-line MCP (every skill, any client):
claude mcp add pm-skills -- npx -y pm-claude-skills-mcp

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💬 Discussion

Retention Analysis is one of 1078 open-source professional AI agent skills — all SkillSpec L3. Try them all in the browser · ⭐ Star on GitHub · Browse the full catalog