Step-by-Step Guide

How to Calculate Your PMF Score

Five steps to run the Sean Ellis product-market fit survey and interpret the result. Methodology, formula, and tips for product managers.

Last updated: April 2026

1
Identify your active users

The PMF score is only meaningful when answered by people who have used your product enough to form an opinion. Surveying anonymous signups or one-time visitors gives you noise.

›Define active before you send anything.
›Example eligibility rule: at least two sessions in the last 14 days. Adapt it to how often users need your product.
›Pull the matching list from your analytics or product database.
›Filter out internal and test accounts. Include trial users only if they have experienced enough of the product to answer.

Formula

Eligible respondents = users who have experienced the product’s core value

Pro tip: With a small user base, report the response count and uncertainty alongside the percentage. Qualitative answers can still help identify problems.

2
Send the Sean Ellis survey question

Use the Sean Ellis disappointment question consistently so you can compare results across survey runs.

›Lead with: "How would you feel if you could no longer use [product]?"
›Provide four answers: Very disappointed, Somewhat disappointed, Not disappointed, N/A.
›Add one open follow-up: "What would you use as an alternative?"
›Keep the survey to two questions to maximize completion rate.

Formula

Survey response set = answers from your active user cohort

Pro tip: More responses make the percentage less sensitive to individual answers. Report the count and avoid treating a small sample as proof of fit.

3
Segment your respondents

Choose the eligibility rule before analyzing responses. If N/A means the respondent no longer uses the product, report those answers separately and disclose that exclusion.

›Tag each response: very disappointed, somewhat, not disappointed, or N/A.
›Apply the eligibility rule and report any excluded N/A responses separately.
›Look at the very-disappointed group separately for qualitative insight.
›Read every very-disappointed follow-up answer.

Formula

Qualifying respondents = eligible answers after disclosed exclusions

Pro tip: Use follow-up answers to understand what very-disappointed users value. Test whether those themes also resonate with prospective customers.

4
Compute the percentage of very-disappointed users

The PMF score is the share of qualifying respondents who said they'd be very disappointed without your product. The formula is straightforward.

›Count the very-disappointed responses.
›Divide by qualifying respondents from step 3.
›Multiply by 100 and round to the nearest whole percentage.
›Example: 32 very-disappointed out of 80 qualifying = 40% PMF score.

Formula

PMF Score = (Very Disappointed responses / Qualifying responses) x 100%

Pro tip: Track the score by user segment. You may have strong fit with one persona and weak fit with another. The blended score can hide both signals.

5
Interpret against the 40% threshold

The 40% threshold is a heuristic from Sean Ellis’s startup work, described in Superhuman founder Rahul Vohra’s account. It is a useful comparison, not a definitive test of product-market fit.

›At or above 40% meets the survey heuristic; confirm it with retention and customer behavior.
›Below 40%, inspect the answers and differences between customer segments.
›A low score can prompt research into product value and audience fit; the percentage alone does not identify the cause.
›Use segmented scores to decide where to focus next.

Formula

Survey heuristic: 40% or more very disappointed; assess alongside behavior

Pro tip: 40% is a benchmark, not a guarantee. Pair the survey result with retention curves and word-of-mouth data before drawing conclusions.

Score Your Product-Market Fit

Use the PMF calculator to review the survey alongside retention, growth, and engagement. Its combined index is separate from the 40% survey heuristic.

Open Free PMF Calculator

Frequently Asked Questions

Who created the PMF score and where did the 40% benchmark come from?

Sean Ellis developed the disappointment survey heuristic. In his First Round Review account, Superhuman founder Rahul Vohra describes Ellis’s finding that 40% very disappointed helped distinguish startups with stronger traction. Treat it as a heuristic and inspect your own retention and customer behavior.

Why does the survey ask about disappointment instead of satisfaction?

The question asks how much users would miss the product. It measures dependence on its value from a different angle than satisfaction or recommendation questions; it does not eliminate survey bias.

How often should I run the PMF survey?

Once a quarter is a reasonable baseline. Run it more often if you've shipped a major change or pivoted positioning. Watch the trend across runs more than any single number.

Should I survey free users or only paying customers?

Survey users who have experienced the core value, and report free and paying segments separately where useful. Strong attachment among free users does not establish willingness to pay; investigate pricing, packaging, and market viability separately.

What if I run the survey and only get 30 responses?

You can report the percentage with the count, but treat it as uncertain. With 30 responses, one answer changes the result by about 3.3 percentage points. Read the follow-up answers and seek more evidence before making a major decision.

Sources

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