retention-analysis
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.
npx skills add mohitagw15856/pm-claude-skills --skill retention-analysis --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.
# Retention Analysis Skill Diagnose why users leave, identify what keeps them, and recommend specific, testable interventions — not vague "improve onboarding" suggestions. ## Retention Fundamentals **The retention curve has two components:** 1. **Steepness of initial drop** (D1–D7) — onboarding problem 2. **Long-term floor level** — product-market fit indicator A product with PMF has a retention curve that flattens. If it trends to zero, you have a PMF problem, not an onboarding problem. Name this distinction explicitly. --- ## Retention Metrics Definitions | Metric | Formula | What It Tells You | |---|---|---| | D1 Retention | Users who return on day 2 ÷ new users day 1 | Quality of first experience | | D7 Retention | Users active on day 8 ÷ users who joined 7 days ago | Early habit formation | | D30 Retention | Users active on day 31 ÷ users who joined 30 days ago | Product-market fit signal | | DAU/MAU Ratio | Daily active users ÷ monthly active users | Stickiness (>20% good, >50% excellent) | | Churn Rate | Users lost in period ÷ users at start of period | Monthly or annual | | Net Revenue Retention | MRR at end of period ÷ MRR at start (same cohort) | Revenue health including
- Retention Fundamentals
- Retention Metrics Definitions
- Retention Investigation Framework
- Step 1: Segment the problem
- Step 2: Find the inflection points
- Step 3: Identify the "aha moment" correlation
- Step 4: Qualify the churn
- Output Format
- Retention Analysis — [Product/Segment] — [Date]
- Required Inputs
- Deeper Materials
- Scoring Rubric (0–40)
- Quality Checks
- Anti-Patterns
What does the retention-analysis skill do?
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.
How do I install it?
Run `npx skills add mohitagw15856/pm-claude-skills --skill retention-analysis --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 mohitagw15856/pm-claude-skills, a repository with 1,255 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.