Most "do we have product-market fit?" debates go in circles because nobody's working from a list. One person points at a great sales month, another at churn, a third at a glowing review — and everyone's technically right, because PMF as a feeling can be argued forever. A checklist ends the argument. Either the box is ticked or it isn't.

So here's the whole thing: twelve boxes across three tiers. Work top to bottom — the signals tell you if you have fit, the evidence tells you whether to believe the signals, and the readiness tier tells you whether you've earned the right to pour fuel on it.

Tier 1 — The signals: do you actually have fit?

These three are the definition of product-market fit. Tick all three and you have real fit; miss one and you have something earlier.

☐ 1. At least 40% of engaged users would be "very disappointed" without you.
The Sean Ellis score — the single most predictive test. 40% is the benchmark.

☐ 2. Your retention curve flattens into a plateau.
A cohort that stops decaying and holds is the behavioral proof under the survey. Words say fit; retention proves it.

☐ 3. A rising share of new users arrives organically.
Word of mouth and referrals mean fit is generating its own demand — the hardest signal to fake.

Why three and not one? Because any single signal lies. A great score can come from superfans; great retention can be propped up by a tiny loyal niche; organic buzz can spike and fade. All three at once is very hard to fake — which is exactly the point of validating fit across independent signals.

Tier 2 — The evidence: is the signal trustworthy?

Ticking Tier 1 on flimsy data is how founders scale on a mirage. These four boxes make the signals believable.

☐ 4. The score comes from 100+ engaged respondents.
Below ~40 it's directional; 100+ makes it reliable.

☐ 5. You surveyed engaged users, not your whole list.
Who you ask matters as much as how many. Inactive users poison the number.

☐ 6. You've measured it more than once.
Fit is a trend, not a snapshot. One reading is an anecdote; a stable or rising line is evidence.

☐ 7. The score holds per segment.
A healthy blended number can hide a dying core carried by one great segment. Check fit inside each slice.

Tier 3 — Ready to scale: have you earned it?

Fit confirmed isn't the same as ready to pour money into growth. These five boxes separate "we have fit" from "we can scale it."

☐ 8. You can describe your ideal customer in one sentence.
Drawn from who your "very disappointed" users actually are — not who you hoped they'd be.

☐ 9. You know the main benefit in your users' own words.
Their language, from the survey, is your positioning.

☐ 10. Fit holds in the segment you're about to scale into.
Don't assume it travels. Confirm before you spend.

☐ 11. The unit economics work at your current fit.
Retention that plateaus above your payback period, not below it.

☐ 12. You have a way to keep measuring after you scale.
Fit decays; scaling stresses it. Keep the score on a dashboard so you catch drift early.

Three boxes prove you have product-market fit. The other nine stop you from betting the company on a number that only looked like fit.

How to read your ticks

Map your result onto the stages of product-market fit:

Tick the hardest boxes automatically

PMFtracker handles the whole first two tiers for you: it surveys engaged users, calculates your "very disappointed" score on a clean 100+ sample, tracks it over time, and breaks it down by segment — so the boxes that matter most tick themselves.

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Print the list, run it every quarter, and watch the boxes fill in. A checklist you re-run is the difference between "I think we have fit" and "here's exactly where we stand and what's left." The work of reaching fit gets a lot less mysterious when it's just a list of boxes to tick.

Keep the checklist current

Measure your PMF score, watch the trend, and see which boxes are ticked at a glance — instead of re-litigating "do we have fit?" every board meeting.

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