data-analysis-standard
Structure a product data analysis, metric deep-dive, funnel analysis, or cohort study. Use when asked to analyse product metrics, investigate a drop in conversion, explain a data change to stakeholders, or find the root cause of a metric movement. Produces a structured analysis with question, root cause, confidence level, and recommended action.
npx skills add mohitagw15856/pm-claude-skills --skill data-analysis-standard --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.
# Data Analysis Standard Skill Turn raw numbers into product decisions. Structure every analysis with a clear question, methodology, finding, and recommended action. ## Analysis Framework: The 4-Question Method Every analysis starts here: 1. **What changed?** (describe the metric and its movement) 2. **Why did it change?** (root cause — segment, funnel step, cohort, channel) 3. **So what?** (business or product impact) 4. **Now what?** (recommended action with confidence level) Never deliver data without answering all four. A chart with no narrative is not an analysis. --- ## Metric Triage Template Use when a metric has moved unexpectedly: ``` METRIC: [Name] MOVEMENT: [X% change over Y period] BASELINE: [What was normal] SEGMENTATION CHECK: - By platform (iOS / Android / Web)? - By user cohort (new / returning / power users)? - By acquisition channel? - By geography? - By plan/tier? ROOT CAUSE HYPOTHESIS: 1. [Most likely explanation] — Evidence: [data point] 2. [Alternative explanation] — Evidence: [data point] 3. [Ruling out] — Eliminated because: [reason] CONCLUSION: [Single sentence answer to "why did this change?"] CONFIDENCE: [High / Medium / Low] — based on [data available] `
- Analysis Framework: The 4-Question Method
- Metric Triage Template
- Funnel Analysis Structure
- Cohort Analysis Guidelines
- Stakeholder Analysis Output Format
- [Analysis Title] — [Date]
- Required Inputs
- Deeper Materials
- Scoring Rubric (0–40)
- Quality Checks
- Anti-Patterns
- Guidelines
What does the data-analysis-standard skill do?
Structure a product data analysis, metric deep-dive, funnel analysis, or cohort study. Use when asked to analyse product metrics, investigate a drop in conversion, explain a data change to stakeholders, or find the root cause of a metric movement. Produces a structured analysis with question, root cause, confidence level, and recommended action.
How do I install it?
Run `npx skills add mohitagw15856/pm-claude-skills --skill data-analysis-standard --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.