pmf-survey

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.

pmprompt/claude-plugin-product-management333 installsMITSynced Aug 26

Works with

Claude CodeCursorCodex CLIGitHub CopilotGemini CLI
---
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.
license: MIT
---

## 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](https://pmprompt.com/blog/pm-ai-evals)
- [Pmf Survey](https://www.productcompass.pm/p/pmf-survey)

More General & Other skills

← All General & Other skills

Check your AI visibility

One URL in, a 0–100 score and the exact fixes out.

RUN THE CHECK

Browse all the tools

15 tools across six categories
13 of them never send your data anywhere

Free · No signup · No trial clock

SEE THE DIRECTORY