Design a foundational product-market fit survey analysis

The Sean Ellis Score Is a Segmentation Question, Not a Pass/Fail

The 40% "very disappointed" threshold is the famous Sean Ellis PMF bar — but aggregate 40% is both rare and misleading without segmentation. Reforge's PMF research and SVPG's PMF writing both argue the correct analysis segments responses by usage, tenure, and use case: a core segment with >60% disappointment rate is stronger evidence than a 38% aggregate.

How the Design a foundational product-market fit survey analysis Prompt Works

The prompt segments PMF survey responses across four dimensions, identifies the core segment by disappointment rate, pattern-matches open-text, and produces a next-step decision (iterate / scale / pivot). The segment-level analysis is what turns a 38% aggregate from ambiguous into actionable.

When to Use It

• You ran a PMF survey and need to interpret the results.
• A PMF-like metric is below the bar and you need a next-step.
• A pivot is being debated and evidence from PMF data would inform it.
• A new PM is establishing PMF measurement.
• A board is asking "do we have PMF?"

Common Pitfalls

• Reading only aggregate score. Aggregate hides your PMF core. Segment or the result is unreliable.
• Ignoring open-text. The verbatim reasons contain the positioning language and the feature signal. Don't skip.
• Scaling before segment PMF is clear. Scaling without segment PMF burns acquisition dollars on wrong-fit cohorts.

Sources

• Assessing Product-Market Fit — Silicon Valley Product Group
• B2B Product-Market Fit — Reforge
• Product Strategy Overview — Silicon Valley Product Group
• Ten Principles of Product Teams — Silicon Valley Product Group