measuring-product-market-fit

SKILL.md

Framework-based assessment of product-market fit using signals from 46 product leaders.

Apply the Sean Ellis "very disappointed" survey as a leading PMF indicator, targeting 40% threshold before long-term retention data is available

Diagnose stage through retention curves, reference customer counts, and customer pull signals; distinguish between vanity metrics and genuine PMF evidence

Recognize PMF across four levels (nascent to extreme) with segment-specific fit; understand that PMF requires both product retention and scalable distribution

Flag common mistakes including launch spikes mistaken for PMF, premature scaling, and conflating market size with actual product-market fit

Measuring Product-Market Fit

Help the user assess and achieve product-market fit using frameworks from 46 product leaders.

How to Help

When the user asks about product-market fit:

Understand their stage - Ask how many customers they have, what their retention looks like, and what signals they're seeing (or not seeing)

Diagnose the situation - Determine if they're confusing vanity metrics with PMF, if they have PMF in a specific segment, or if they're clearly pre-PMF

Apply the right framework - Help them use the Sean Ellis survey, retention curves, or reference customer counts depending on their situation

Guide next steps - Help them decide whether to scale or continue iterating based on the evidence

Core Principles

Use the Sean Ellis "disappointment" survey

Sean Ellis: "How would you feel if you could no longer use this product? Very disappointed, somewhat disappointed, or not disappointed. If 40% say 'very disappointed,' you're on the right track." This is a leading indicator of PMF before long-term retention data is available. Focus on the "very disappointed" segment as your core value indicator.