measuring-pmf

Assess product-market fit using retention benchmarks, surveys, and organic growth signals.

1.3k|169|Updated Jan 29, 2026
One-click install
npx skills add https://github.com/RefoundAI/lenny-skills --skill measuring-pmf
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: measuring-pmf
Source: https://github.com/RefoundAI/lenny-skills/tree/main/skills/measuring-pmf
Command: npx skills add https://github.com/RefoundAI/lenny-skills --skill measuring-pmf

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Founders and product teams struggle to objectively determine whether they have achieved product-market fit, often mistaking founder-led momentum, polite customer interest, or launch spikes for genuine market pull.

Core Features & Use Cases

  • Quantitative Benchmarking: Evaluate cohort retention curves, Sean Ellis survey scores, and burn multiples against industry standards for your business type.
  • Signal Diagnosis: Distinguish true market pull (urgent pricing questions, organic word-of-mouth) from false signals like investor enthusiasm and founder-driven deals.
  • Iteration Guidance: Identify which of four PMF problems you face (wrong product, distribution, onboarding, or audience) and what to fix.
  • Use Case: A B2B startup with 8 paying customers uses the skill to run a Sean Ellis survey, plot cohort retention, and determine whether to scale sales or keep iterating on the product.

Quick Start

Ask the assistant to assess whether your product has product-market fit based on your current retention data and customer feedback.

Frequently Asked Questions about measuring-pmf

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I measure product-market fit for my startup?

Measure product-market fit by triangulating three signals: cohort retention curves that flatten above zero, a Sean Ellis survey score of 40%+ users who would be very disappointed without the product, and sustained organic word-of-mouth growth rather than marketing-driven spikes.

What is a good Sean Ellis survey score for product-market fit?

A Sean Ellis score of 40% or more respondents answering 'very disappointed' if the product disappeared indicates product-market fit. Some teams set stricter thresholds of 50%, and scoring benchmarks may need adjustment for regional cultural biases in survey responses.

What are good retention benchmarks by business type?

Six-month retention benchmarks vary by model: consumer social is good at ~25% and great at ~45%, consumer SaaS is good at ~40% and great at ~70%, SMB SaaS is good at ~60% and great at ~80%, and enterprise SaaS is good at ~70% and great at ~90%.

How long does it take to find product-market fit?

The median time from idea to feeling product-market fit is roughly two years for B2B startups, including 9-18 months of iteration after launching a working product. Start worrying if two years pass without PMF signals, and seriously worry after three years.

How do I distinguish real market pull from false PMF signals?

Real market pull shows as urgent customer questions about pricing and implementation, organic growth without founder involvement, and customers paying before being asked. False signals include polite interest, investor checks, and deals closed through founders' personal relationships.

When should I scale after finding product-market fit?

Scale only after cohort retention curves flatten above zero and quantitative thresholds like the Sean Ellis score are met. Scaling headcount or marketing spend before retention stabilizes leads to high burn and eventual failure.