What is a product-market fit (PMF) survey?
A PMF survey asks users how they would feel if they could no longer use your product, and the share who answer “Very disappointed” is your PMF score. It shows how many users rely on the product enough to miss it, and its follow-up questions show why.
Product-market fit in one question
A product-market fit survey, often called the Sean Ellis test after its author, rests on one question: “How would you feel if you could no longer use the product?” Users pick “Very disappointed”, “Somewhat disappointed” or “Not disappointed”, and many surveys add an answer for people who no longer use it.
The question asks about loss instead of liking, which makes a polite answer harder to give. A user who would only be somewhat disappointed has alternatives in mind, and one who would be very disappointed depends on what the product does. The share in that last group is the PMF score.
Startups and product teams use it to judge whether a product is ready to grow, to find the users who get the most from it and to learn what those users value. It works best beside usage and retention numbers, since the survey measures how users feel and the numbers measure what they do.
- Measures
- How many users would miss the product
- Answers
- Very, somewhat or not disappointed
- Score
- The share of Very disappointed answers
- Asked of
- Users who have used the product recently
- Also called
- The Sean Ellis test
The product-market fit question
Keep the wording close to the original so your results stay comparable over time, and keep the answers in the same order. The answer for people who no longer use the product keeps former users out of the score, since they can't judge what losing it would mean.
How to calculate the PMF score
Leave out the answers from people who no longer use the product, then divide the number of “Very disappointed” answers by the rest and multiply by 100.
The test's author suggested 40% as a rule of thumb: when at least 40% of users would be very disappointed, the product has likely found its fit. Treat the line as a guide, since the result depends a great deal on who you ask.
PMF score = Very disappointed ÷ (all answers − no longer use it) × 100
A score of 40% or more is the test's usual sign of fit. Below that, the follow-up answers show what to change.
A PMF survey example
Say 400 users answer. 30 say they no longer use the product and are left out, which leaves 370. Of those, 148 would be very disappointed, 150 somewhat disappointed and 72 not disappointed.
148 of 370 is 40%, right on the usual line. Next, read what the 148 say they get from the product, and what the 150 in the middle would need before they depend on it.
- Very disappointed
- 148 answers, 40%
- Somewhat disappointed
- 150 answers, 41%
- Not disappointed
- 72 answers, 19%
- No longer use it
- 30 answers, left out
- PMF score
- 148 ÷ 370 = 40%
Who to ask, and when
Ask people who have used the product enough to judge it, and recently enough to remember. A common rule is users who used the core of the product at least twice in the last two weeks. Brand-new sign-ups and long-gone customers both blur the result.
- Active users who have reached the main feature at least once
- People who signed up a few weeks ago or more
- Paying and free users counted apart, so each group gets its own score
- The same kind of users again every few months, or after a big change
Follow-up questions that explain the score
The score says how many users would miss the product. The open questions after it say who they are and why, which often guides the next step better than the number itself.
- “What is the main benefit you get from the product?”
- “What type of people do you think would benefit most from the product?”
- “What would you use instead if the product were no longer available?”
- “How can the product be improved for you?”
Running a PMF survey in Usertick
Start from the Product-market fit template. It asks the Sean Ellis question with four answers, ends the survey for people who no longer use the product with a logic rule, and follows with open questions on alternatives, who would benefit most, the main benefit and what to improve. Send it by email, show it in your web app, or share it by link.
To reach the right users in a web app, show the survey to returning visitors with a minimum number of visits on every plan. From Starter, you can also show it only to signed-in users whose traits match, such as their plan, passed to Usertick with identify.
Results draws the question as a donut with each answer's share and count. Select “Very disappointed” and the whole page narrows to those users, so their answers to the benefit question sit on their own, each filed by theme and sentiment.
Mistakes to avoid with a PMF survey
Small choices that keep the results useful.
- 01
Asking brand-new sign-ups
People who have barely tried the product can't say whether they would miss it. Wait until they have used it a few times.
- 02
Counting former users in the score
People who no longer use the product pull the score down for the wrong reason. Give them their own answer and leave them out.
- 03
Changing the wording
“Would you be sad to lose the product?” is a different question with a different result. Keep the original wording to compare over time.
- 04
Stopping at the number
The score alone doesn't say what to build. Read the benefit answers from the very disappointed users and shape the product around what they value.
Frequently asked questions
The question and the 40% line come from Sean Ellis, which is why the survey is often called the Sean Ellis test. Treat the line as a rule of thumb for your own trend, since who you ask moves the result a lot.
Enough that a handful can't swing the share. With 40 answers, each one is worth 2.5 points, so check the margin of error before you act on a result close to the line.
Every few months, or after a large change to the product or its pricing. Ask the same kind of users each time so the scores stay comparable.
Read what the very disappointed users value and who they are, then focus the product and its marketing on people like them. Asking the same kind of users again after the changes shows whether the share moved.
Yes. A Usertick website survey runs in a web app, and identify passes the signed-in user, so each answer carries who gave it. From Starter, user traits can limit the survey to active users.
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