What is product-market fit?

Written by Madalena Rugeroni, founder of Mazo · Updated 15 September 2026

Product-market fit (PMF) is the point at which a product satisfies a strong market demand: a clearly defined group of customers buys it, keeps using it and would be genuinely disappointed to lose it. In B2B SaaS the clearest evidence is a retention curve that flattens for a segment instead of declining towards zero.

Where the term comes from

Marc Andreessen's 2007 essay defined it plainly: "Product/market fit means being in a good market with a product that can satisfy that market."¹ Brian Balfour describes the same thing from the other side: the market pulls the product out of you.

How to measure product-market fit

Retention curves. Casey Winters' test: if a cohort's retention curve flattens at any level, you have fit for the segment that stayed. If it declines towards zero, you don't have fit for anyone yet. If it flattens and then decays, value was delivered but isn't durable.
The 40% survey. Sean Ellis asks users how they'd feel if they could no longer use the product; when more than 40% answer "very disappointed", that's his threshold for fit.^2,3
Pull in sales. Referrals, shorter sales cycles and prospects who arrive already knowing what they want.

Worked example

A fictional analytics tool has 60 paying customers across two segments. After six months:

E-commerce brands: of 30 customers, 18 are still active at month three and 17 at month six. The curve flattens.
Marketing agencies: of 30, 15 are active at month three and 4 at month six. The curve keeps falling.
A survey of active users: 46% of e-commerce users would be "very disappointed", 19% of agency users.

The company has fit with e-commerce brands, not agencies. The move is to reorient the ICP and positioning around e-commerce — not to add a marketing channel.

Why it matters from €0 to €1M ARR

Pre-revenue to 10 customers: you're searching. Focus on ICP, positioning and the job to be done; spend little.
10 to 50 customers: read cohort curves by segment. Fit usually shows up in one segment first.
50 customers to €1M ARR: once fit is clear, the search moves to a repeatable, scalable way to grow. David Skok's warning: spending scale-phase money while still searching is the classic fatal error.

Mazo's rule of thumb: read your retention cohort curves before anything else. If they flatten for one segment, you have fit there — rebuild your ICP around those customers. If they decline towards zero, no growth tactic will fix it; it's a product problem. Don't scale spend or hire sales before the curve flattens.

Common product-market fit mistakes

Mistaking sign-ups or launch-day buzz for fit. Retention is the evidence.
Averaging segments. A strong segment and a weak one blend into a curve that says "maybe".
Treating fit as permanent. Markets move; keep watching the curve.

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FAQ

How do you know if you have product-market fit?

Look at retention by cohort and segment: if the curve flattens instead of falling towards zero, you have fit for that segment. Sean Ellis's survey is a second check: over 40% of users saying they would be very disappointed without the product.

What is the Sean Ellis 40% test?

A survey asking users how they would feel if they could no longer use the product. If more than 40% answer "very disappointed", Sean Ellis considers that a sign of product-market fit.

Should I spend on growth before product-market fit?

Keep spending low. Before fit, money is best spent learning who retains and why. Scaling acquisition first mostly buys customers who leave.

Who wrote this

Madalena Rugeroni built Mazo. She's an ex-Googler, a startup advisor and investor, and runs a portfolio of internet companies. Before that, as Head of Growth at Amplemarket, she scaled a B2B SaaS to $10M ARR. LinkedIn

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Sources.

Definition of product/market fit: Marc Andreessen, "The Only Thing That Matters" (2007)
The 40% "very disappointed" threshold: First Round Review, "How Superhuman Built an Engine to Find Product Market Fit"
Sean Ellis on the survey: Sean Ellis, "Is Product/Market Fit Hiding in Your User Base?"

Operators and books referenced: Casey Winters (retention curves), Brian Balfour (four fits), David Skok (forEntrepreneurs). These are published methodologies credited to their authors; Mazo is not affiliated with or endorsed by them.