Product-Market Fit Radar
PRODiagnose, measure, and visualize my startup's journey to product-market fit using the Sean Ellis test, retention cohorts, and multi-dimensional radar analysis.
Example Usage
“I’m building a B2B SaaS tool for legal document automation at the Seed stage. I just ran the Sean Ellis survey with 150 responses: 35 said ‘Very Disappointed’, 60 said ‘Somewhat Disappointed’, 55 said ‘Not Disappointed’. Calculate my PMF score, analyze what questions I should ask the ‘Somewhat Disappointed’ group to convert them, and generate a radar assessment of my current position.”
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Suggested Customization
| Description | Default | Your Value |
|---|---|---|
| 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.
Research Sources
This skill was built using research from these authoritative sources:
- 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