Help users assess and achieve product-market fit. Use when someone is trying to determine if they have PMF, measuring user engagement and retention, running…
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.
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