Stop guessing at product-market fit.

Find out if people will pay for your idea before you build it.

Will people pay for my idea?

Most founders say they’re ‘close’ to product-market fit. Close is not a measurement. It’s a feeling, and feelings don’t tell you what to fix.

There are four signals that actually matter: how many people would be very disappointed without your product, whether your retention curve flattens, what your NPS reveals about your best customers, and how fast usage recovers after a churn spike. Each one is concrete. Each one points somewhere.

Getting these signals right changes the decisions you make next. You stop pouring budget into acquisition before retention is solved. You stop building features nobody asked for. You start knowing which customer segment to double down on.

By the numbers

40%
The Sean Ellis threshold — the share of users who must say ‘very disappointed’ for PMF to be real
4 signals
The metrics that together give a complete PMF picture: survey score, retention curve, NPS by segment, weekly active usage
1 segment
All it takes — a single segment that clears the 40% bar tells you exactly where to focus next
Most founders
Report making major product decisions without a defined PMF measurement framework in place

Everything between the goal and the result

The Sean Ellis 40% Benchmark

Ask your users: how disappointed would you be if this product disappeared? If 40% or more say ‘very disappointed,’ you have a meaningful PMF signal. Below 40%, the product is not yet essential to enough people.

Retention Curves as a PMF Signal

Plot retention over time. A curve that keeps falling to zero means you have a leaky bucket, not a product. A curve that flattens — even at 20% — means a core segment finds real value.

NPS vs PMF Surveys

NPS measures satisfaction. PMF surveys measure dependency. They answer different questions. Use NPS to track customer experience. Use PMF surveys to find out whether the product is irreplaceable.

Segment Before You Score

Your PMF score looks weak when you average across all users. Segment by use case, company size, or acquisition channel. A strong signal inside one segment is the direction the whole product should move.

When to Pivot vs Persevere

A PMF score below 40% is not a verdict. It is a map. If a specific segment scores above 40%, the pivot is repositioning — not rebuilding. If no segment clears the bar, the core value proposition needs rethinking.

The Measurement Framework

Run the PMF survey, plot your retention curve, calculate NPS by segment, and track weekly active usage. These four data points together tell you more than any single metric. One metric alone will mislead you.

How it works, step by step

PMF Survey Score
Your PMF score gives you a number, not a gut feeling. Decisions about budget and focus follow from data, not optimism.
Retention Curve
A flattening retention curve tells you which segment found the value. You build for them instead of guessing.
Segment Analysis
Segmented PMF data surfaces the one customer type that loves the product. Everything else gets deprioritized.
Pivot or Persevere
When the data is clear, the decision is clear. You stop cycling between doubt and false conviction.
PMF survey results dashboard showing percentage of very disappointed responses
40%

That is the share of surveyed users who must answer ‘very disappointed’ before PMF is considered real — and most early-stage products miss it on the first measurement.

<40%
Below threshold
40%+
PMF confirmed

What changes when you get this right

01

Your retention curve flattens instead of falling to zero.

02

One customer segment is clearly identified and your whole roadmap reflects it.

03

Budget goes to acquisition only after the retention problem is solved.

04

The pivot-or-persevere decision gets made on data, not founder fatigue.

05

Your PMF survey score climbs as the product narrows to what that segment actually needs.

06

Investors and partners see a product with a measurable signal, not a founder with a hunch.

Common questions

The answers founders ask before they commit time to building this.

What is the Sean Ellis test and why does 40% matter?

Sean Ellis developed a one-question survey: ‘How would you feel if you could no longer use this product?’ If 40% or more of respondents answer ‘very disappointed,’ the product has reached a meaningful level of dependency. Ellis validated this benchmark across hundreds of startups. Below 40%, the product is not yet essential to enough people to sustain organic growth.

How is a PMF survey different from NPS?

NPS measures satisfaction — whether a customer would recommend you. A PMF survey measures dependency — whether the product would be missed. A product can score well on NPS and still have weak PMF. They answer different questions and should not be substituted for each other.

What does a healthy retention curve look like?

A healthy retention curve flattens. Early churn is normal. The signal is whether the curve levels off at some point — even at 20% — rather than continuing to decline toward zero. A curve that flattens means a segment of users keeps coming back. That segment is your PMF signal.

What should I do if my PMF score is below 40%?

Segment your results before drawing conclusions. Average scores hide strong pockets. If a specific segment — by use case, company size, or channel — scores above 40%, reposition the product for that segment. If no segment clears the bar, the core value proposition needs rethinking, not just the messaging.

How do I run a PMF measurement sprint?

Run the one-question PMF survey to your active users, plot a retention cohort chart by signup month, calculate NPS broken out by segment, and track weekly active usage. Do all four in one sprint. One metric alone will give you a partial picture. The four together tell you what to do next.

Identify your Product-Market Fit.

Set your goal. Answer a few questions. CorZen turns it into a week-by-week plan you can run without guessing what comes next.

Plan my PMF sprint