Lean Analytics
Choose and audit startup metrics using Croll and Yoskovitz''s "Lean Analytics".
Install
npx skills add wondelai/skills --skill lean-analytics -g -a claude-code -y- Repository
- wondelai/skills2.6k
- Category
- Business
- Updated
- 2mo ago
- License
- MIT
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- No, instructions only
What it does
Choose and audit startup metrics using Croll and Yoskovitz''s "Lean Analytics". Use when the user mentions "what metrics should we track", "KPIs", "north star metric", "One Metric That Matters (OMTM)", "vanity metrics", "analytics dashboard", "DAU/MAU", "churn benchmark", or "measure product-market fit". Also trigger when choosing metrics for a startup or feature, auditing a dashboard for vanity metrics, setting metric targets and baselines, or instrumenting a product by business model and stage. Covers good-vs-vanity metrics, the One Metric That Matters, metrics by business model, the five startup stages, and benchmarks. For the build-measure-learn loop, see lean-startup. For fixing activation and retention, see improve-retention.
Lean Analytics
A data discipline for startups distilled from Alistair Croll and Benjamin Yoskovitz's Lean Analytics: separate metrics that change decisions from numbers that merely flatter, then point the whole company at the One Metric That Matters for your business model and stage. Use it to choose metrics, audit dashboards, set targets, and plan instrumentation.
Core Principle
Focus on the one metric that matters right now, everything else is noise that feels like progress. Startups die from lack of focus more often than lack of data. The discipline is knowing your business model, knowing your stage, and tracking the single number that tells you whether the riskiest part of the business is working. A metric earns attention only if it changes what you do next.
Scoring
Goal: 10/10. Rate metric choices, dashboards, and instrumentation plans 0-10 against these principles. Report the current score and the specific changes needed to reach 10/10.
- 9-10: One OMTM matched to model and stage, paired counter-metric, a line in the sand with a pre-committed miss response, cohorted and segmented data
- 7-8: Mostly actionable ratios and a plausible OMTM, but no explicit target, weak cohorting, or too many "key" metrics
- 5-6: Actionable and vanity metrics mixed; dashboard exists but rarely changes a decision; model and stage never named
- 3-4: Vanity metrics dominate, totals, cumulative charts, blended averages; metrics copied from other companies
- 0-2: No instrumentation, or numbers chosen to impress investors rather than drive decisions
