Product-Market Fit Radar
PROMesse und verbessere Product-Market Fit. Metriken, Signale und Aktionen für bessere Marktpassung.
Anwendungsbeispiel
Analysiere unsere Nutzerdaten und sag mir, ob wir Product-Market Fit erreicht haben.
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Anpassungsvorschläge
| Beschreibung | Standard | Dein Wert |
|---|---|---|
| My business model type affecting benchmark expectations | B2B SaaS | |
| Current funding/growth stage for context-appropriate advice | Seed | |
| Primary metric focus for the analysis | Retention | |
| My target customer segment for persona analysis | General | |
| How I'll provide data: Raw CSV, Summary Stats, or Qualitative | Summary |
Product-Market Fit Radar is a diagnostic and analytical framework that helps founders and product managers objectively measure their journey toward product-market fit. Instead of treating PMF as a gut-feeling milestone, this skill visualizes it as a spectrum across Retention, Satisfaction, Growth, and Economics dimensions—identifying exactly which part of the engine needs work.
Forschungsquellen
Dieser Skill wurde auf Basis von Forschung aus diesen maßgeblichen Quellen erstellt:
- Superhuman PMF Engine Gold standard framework by Rahul Vohra for measuring and systematically increasing PMF using the 40% rule
- Andrew Chen's Investor Metrics Detailed breakdown of retention curves, DAU/MAU ratios, and power user curves
- PostHog PMF Survey Guide Practical engineering-focused guide to implementing PMF surveys for B2B/B2C
- Lenny's Guide to PMF Comprehensive benchmarks and timelines for B2B vs Consumer apps
- YC Startup School: PMF Y Combinator's fundamental definitions and validation techniques
- Sean Ellis Test Official Official methodology for the 'How disappointed would you be?' survey
- Reforge Retention Series Advanced concepts on retention as the proxy for PMF
- a16z Growth Metrics Dictionary of growth metrics including Magic Number and Burn Multiples
- PostHog B2B SaaS Metrics Open-source definitions of B2B SaaS metrics tracking PMF
- Cohort Analysis Python Examples Python-based Jupyter notebooks for calculating retention cohorts