asankarasubramanian/pmf-survey
.cursor/skills/pmf-survey/SKILL.md
Use when asked to "PMF survey", "measure product-market fit", "40% rule", "Sean Ellis test", "Rahul Vohra method", or "how disappointed would you be". Helps quantify product-market fit and systematically improve it. The PMF Survey framework (created by Sean Ellis, popularized by Rahul Vohra at Superhuman) measures how disappointed users would be without your product and turns that data into a roadmap.
development
Updated Apr 16, 2026
$ install --global
skillsauthnpx skillsauth add asankarasubramanian/pm-alfred pmf-surveyInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- pmf-survey
- description:
- Use when asked to "PMF survey", "measure product-market fit", "40% rule", "Sean Ellis test", "Rahul Vohra method", or "how disappointed would you be". Helps quantify product-market fit and systematically improve it. The PMF Survey framework (created by Sean Ellis, popularized by Rahul Vohra at Superhuman) measures how disappointed users would be without your product and turns that data into a roadmap.
Domain Context
This skill implements a proven product management framework. The approach combines best practices from industry leaders and is designed for practical application in day-to-day PM work.
Input Requirements
- Context about your product, feature, or problem
- Relevant data, research, or constraints (recommended but optional)
- Clear articulation of what you're trying to achieve
PMF Survey (Product-Market Fit Survey)
What It Is
The PMF Survey is a method to measure and systematically improve product-market fit. The core insight: you can put a number on product-market fit, and you can use that number to write your roadmap.
The key question: "How would you feel if you could no longer use this product?"
- Very disappointed - "I'd be devastated. I need this."
- Somewhat disappointed - "I'd be bummed but I'd find something else."
- Not disappointed - "I wouldn't really care."
Sean Ellis discovered that companies with 40% or more "very disappointed" responses almost always grew successfully, while those under 40% struggled. This benchmark has held across thousands of companies.
Rahul Vohra at Superhuman took this further: he built an engine that uses survey responses to algorithmically generate a roadmap guaranteed to increase PMF score.
When to Use It
Use the PMF Survey when you need to:
- Quantify product-market fit before making major investment decisions
- Decide whether to pivot or double down
- Prioritize your roadmap based on what will actually move the needle
- Identify your best customer segment (who loves you most)
- Track PMF over time as you iterate
- Make the case to investors with data, not gut feeling
When Not to Use It
- You have fewer than 30 active users (sample too small)
- Users haven't had enough time to experience value (survey too early)
- The product is employer-mandated (users had no choice)
- You want to validate a hypothesis without building (use JTBD instead)
Resources
Articles:
- How Superhuman Built an Engine to Find Product-Market Fit by Rahul Vohra
Books:
- Hacking Growth by Sean Ellis
- The Lean Startup by Eric Ries
Further Reading
- Pm Ai Evals
- Pmf Survey
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