data-analysis-standard

# 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] ``` --- ## Funnel Analysis Structure | Stage | Metric | Current | Benchmark/Target | Drop-off % | Notes | |---|---|---|---|---|---| | [Top of funnel] | [Users] | [N] | [N] | — | | | [Step 2] | [Users] | [N] | [N] | [X%] | | | [Step 3] | [Users] | [N] | [N] | [X%] | | | [Conversion] | [U...