NPS Score Analysis Calculator
Calculate Net Promoter Score from survey data. Analyze promoter, passive, and detractor distributions with benchmarks and improvement modeling.
Product-Market Fit Score Calculator
Calculate your product-market fit score using the Sean Ellis test. Measure what percentage of users would be "very disappointed" without your product.
Would miss the product deeply
Would miss it a bit
Wouldn't care much
Already disengaged
Product-Market Fit Score
28.33%
Approaching fit
0%20%40%60%100%
PMF Score⧉
28.33%
85 of 300 respondents
Total Responses⧉
300
Survey sample size
Gap to 40%⧉
35 more VD needed
29.17% of SD responses
Verdict⧉
Not Yet
Sean Ellis benchmark: 40%
Response Distribution
Very Disappointed85 (28.33%)
28.33%
Core advocates — your most passionate users
Somewhat Disappointed120 (40.00%)
40.00%
See value but not yet essential
Not Disappointed60 (20.00%)
20.00%
Low engagement or finding alternatives
No Longer Use35 (11.67%)
Churned or inactive users
Path to 40%: Converting "Somewhat" to "Very" Disappointed
| % of SD Converted | Users Converted | New PMF Score | Meets 40%? |
|---|---|---|---|
| 5% | 6 | 30.33% | ❌ No |
| 10% | 12 | 32.33% | ❌ No |
| 15% | 18 | 34.33% | ❌ No |
| 20% | 24 | 36.33% | ❌ No |
| 30% | 36 | 40.33% | ✅ Yes |
| 50% | 60 | 48.33% | ✅ Yes |
Benchmarks
You: 28.33%
Superhuman (peak) (58%)
Strong PMF threshold (40%)
Approaching PMF (30%)
Early stage average (20%)
Planning notes, formulas, and examples
About the Product-Market Fit Score Calculator
The product-market fit (PMF) score, popularized by Sean Ellis, measures how essential your product is to users by asking one simple question: "How would you feel if you could no longer use this product?" Users respond with one of four options: Very Disappointed, Somewhat Disappointed, Not Disappointed, or No Longer Use. The percentage who answer "Very Disappointed" is your PMF score.
Ellis's research across hundreds of startups found that companies where 40% or more of users say they'd be "very disappointed" consistently achieve strong growth. Below 40%, products typically struggle to retain users and grow sustainably. This 40% threshold has become the gold standard for measuring product-market fit in the startup ecosystem.
This calculator analyzes your survey responses across all four categories, computes your PMF score, benchmarks it against the 40% threshold, and provides segment-level analysis. It also models how shifting users between response categories would affect your overall score — helping you identify where to focus product improvements.
When This Page Helps
The PMF score is the simplest and most actionable measure of product-market fit. This calculator takes your survey responses, computes the score, benchmarks against the 40% threshold, and models improvement scenarios. Use it before and after product changes to track fit over time, or segment by user type to find where your product resonates most.
How to Use the Inputs
- Survey your users: "How would you feel if you could no longer use [product]?"
- Enter the number of responses for each category: Very Disappointed, Somewhat Disappointed, Not Disappointed, No Longer Use.
- Review your PMF score (percentage of "Very Disappointed" responses).
- Examine the distribution visualization and benchmark comparison.
- Use the improvement modeling to set targets for shifting user sentiment.
Formula used
PMF Score (%) = (Very Disappointed Responses ÷ Total Responses) × 100
The 40% Threshold:
≥ 40% = Strong product-market fit
25–39% = Approaching fit, needs work
< 25% = Not yet at product-market fitExample Calculation
Result: PMF Score = 28.3%
With 300 total responses and 85 "Very Disappointed," the PMF score is 85 ÷ 300 × 100 = 28.3%. This is below the 40% threshold, suggesting the product is approaching but hasn't yet achieved strong product-market fit. Focus on converting the 120 "Somewhat Disappointed" users to "Very Disappointed" through deeper feature engagement and personalization.
Tips & Best Practices
- Survey users who have experienced core value — new users may not have formed strong opinions yet.
- Aim for at least 100 responses for statistically meaningful results.
- The 40% threshold is a guideline, not a magic number; track trends over time.
- Segment results by user type, plan tier, or acquisition channel to find your strongest PMF segments.
- Focus on converting "Somewhat Disappointed" users to "Very Disappointed" — they're closest to being passionate advocates.
- Re-survey quarterly to track PMF trends as your product evolves.
- Don't survey churned users — focus on active users who have experienced the product.
The 40% Benchmark
Sean Ellis's research established 40% as the threshold for product-market fit. Companies like Slack, Superhuman, and Notion explicitly tracked and optimized for this metric during their growth phases. Superhuman famously built their entire product development process around systematically increasing their PMF score from 22% to above 58% by deeply understanding what "Very Disappointed" users valued most.
Segmenting PMF Analysis
Aggregate PMF scores can mask important variation. A 35% overall score might include a segment of power users at 65% and casual users at 15%. By identifying the segments with highest PMF, you can double down on those users and either expand the segment or replicate the value proposition. This is the core of the "find your 40%" strategy.
From Measurement to Action
The PMF survey is most powerful when combined with qualitative follow-ups. Ask "Very Disappointed" users what they love most. Ask "Somewhat Disappointed" users what would make the product essential. Ask "Not Disappointed" users why they don't find it essential. These qualitative insights, combined with the quantitative PMF score, create a clear product development roadmap.
Sources & Methodology
Last updated:
Frequently Asked Questions
The Sean Ellis test (or PMF survey) asks users a single question: "How would you feel if you could no longer use this product?" with four options: Very Disappointed, Somewhat Disappointed, Not Disappointed, or I No Longer Use It. The percentage who say "Very Disappointed" is the PMF score. Sean Ellis found that products where ≥40% choose "Very Disappointed" achieve sustainable growth.
Sean Ellis analyzed data from hundreds of startups and found that 40% was the tipping point. Below 40%, products struggled to grow and retain users. Above 40%, products consistently achieved strong retention and organic growth. It's not a hard rule but a well-validated benchmark across many SaaS companies and consumer products.
Ellis recommends at least 40 responses, but 100+ provides more statistically reliable results. For segment-level analysis, aim for 30+ responses per segment. The key is surveying users who have truly experienced your product's core value, not brand-new users who haven't formed opinions.
If your score is below 40%, focus on the "Somewhat Disappointed" segment. They see value but aren't passionate yet. Ask follow-up questions to understand what would make them "Very Disappointed" to lose the product. Double down on the features and use cases that your "Very Disappointed" users love most.
Measure quarterly or after significant product changes. Track the trend over time rather than fixating on any single measurement. A rising score indicates improving fit, even if you haven't hit 40% yet. Sudden drops may indicate that recent changes have moved the product away from core value.
Absolutely. While the PMF survey is popular with startups, established products benefit from tracking PMF over time and across segments. It can reveal that PMF varies significantly by user type, geography, or use case, helping guide product strategy and resource allocation.
Both measure customer sentiment, but differently. PMF score measures essentiality ("would you miss this?"), while NPS measures recommendation likelihood. Products can have high NPS but low PMF (nice-to-have but not essential) or vice versa. Using both provides a more complete picture of customer sentiment.
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