Is Cohort 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.

Cohort Analysis

Q: What do I need to use Cohort Analysis?

Analysis goal; Product or feature; Cohort definition; Observation window; Key metric; Available data; Baseline or goal.

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

The skill verifies itself against its own quality checks: Run all checks before delivering output. Do not mark a check as passed unless it is verifiably true given the supplied data.; **Mutual exclusivity:** No user can appear in two cohorts — entry event and date boundaries are unambiguous; **Retention plateau:** The curve shows a visible plateau, or the analysis explicitly states the window is too short to confirm one; **LTV grounding:** LTV projections use observed retention and observed ARPU — not assumed figures.

🟢 Production-Ready🕐 updated 2026-07-14 ✅ 3.5/5 🔷 SkillSpec L3 pm-data

Structure a cohort analysis for retention, LTV, or behavioural patterns. Use when asked to run a cohort analysis, analyse retention by cohort, segment users by behaviour over time, or calculate lifetime value by acquisition period. Produces a complete cohort analysis framework with methodology, cohort definitions, retention curves, 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

▸Analysis goal

▸Product or feature

▸Cohort definition

▸Observation window

▸Key metric

▸Available data

▸Baseline or goal

✅ 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.

✓Run all checks before delivering output. Do not mark a check as passed unless it is verifiably true given the supplied data.

✓**Mutual exclusivity:** No user can appear in two cohorts — entry event and date boundaries are unambiguous

✓**Retention plateau:** The curve shows a visible plateau, or the analysis explicitly states the window is too short to confirm one

✓**LTV grounding:** LTV projections use observed retention and observed ARPU — not assumed figures

✓**Behavioural segments:** Mutually exclusive and collectively exhaustive — every user in scope falls into exactly one segment

✓**Minimum cohort size:** Any cohort below the reliability threshold is flagged and excluded from trend conclusions

✓**Churn signals:** All leading indicators listed are observable in production data, or explicitly marked as hypotheses

✓**Recommendations anchored:** Every recommendation references a specific finding — no free-floating growth advice

⚠️ What it refuses to do

Avoid these failure modes — they produce analysis that looks rigorous but cannot be trusted or acted upon.

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

Start with

Related skills

🔌 Embed this skill

Drop this on your blog, docs, or site — it renders a "Run this skill" card:

<div data-pm-skill="cohort-analysis"></div>
<script src="https://mohitagw15856.github.io/pm-claude-skills/embed.js" async></script>

💬 Discussion

Cohort Analysis is one of 1174 open-source professional AI agent skills — all SkillSpec L3. Try them all in the browser · ⭐ Star on GitHub · Browse the full catalog