# Measuring Pmf

Help users objectively assess where their product stands on the PMF spectrum by...

- Repository: https://github.com/RefoundAI/lenny-skills (1456 stars)
- Category: Marketing
- License: MIT
- Last updated: 2026-07-16
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add RefoundAI/lenny-skills --skill measuring-pmf -g -a claude-code -y`
Codex: `npx skills add RefoundAI/lenny-skills --skill measuring-pmf -g -a codex -y`
Cursor: `npx skills add RefoundAI/lenny-skills --skill measuring-pmf -g -a cursor -y`
Gemini CLI: `npx skills add RefoundAI/lenny-skills --skill measuring-pmf -g -a gemini-cli -y`

## Description

Help users objectively assess where their product stands on the PMF spectrum by triangulating qualitative feedback, quantitative retention benchmarks, and organic growth signals.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Measuring Product-Market Fit

Transition from pushing your product to feeling the market pull it out of you.

Help the user with measuring product-market fit using insights from 16 guests and posts across Lenny's Podcast and Newsletter.

## How to Help

1. **Diagnose the current stage** - Determine where the user is on the journey from pre-product validation to scalable growth.
2. **Apply quantitative benchmarks** - Evaluate cohort retention and Sean Ellis scores against industry standards.
3. **Analyze market pull** - Identify signals of organic demand versus founder-led momentum.
4. **Iterate based on feedback** - Help prioritize roadmap changes that specifically drive toward retention for the most passionate users.

## Core Principles

### Standardize Quantitative Validation
Jag Duggal: "We rarely scale a project, a product we've launched, until we know the Sean Ellis score and we know that it's hit a threshold that we find really compelling."

Use an objective threshold like the Sean Ellis score to validate fit before scaling. Set a strict target of at least 40 percent of users feeling very disappointed if the product disappeared.

### Look for Urgent Feedback
Raaz Herzberg: "We really felt the type of questions change, right? Silly. The call sounded like, again, "How are you pricing this, or when can we start doing a POV?" I think naturally, as human beings, you have a bias to look for affirmation, versus a bias for what you don't want to hear."

True fit is revealed when customer feedback shifts from polite interest to urgent, practical questions about pricing and implementation. Treat generic interest as a negative signal.

### Listen Selectively
Rahul Vohra: "You have to deliberately not act on the feedback of many of your early users, and this is at the same time as listening to people intensely and building what people want."

The rest: https://github.com/RefoundAI/lenny-skills/blob/HEAD/skills/measuring-pmf/SKILL.md