Product Market Fit Questions and Survey Template (Free Download)

The most used product-market fit question is this one: "How would you feel if you could no longer use this product?" You send it to your users, they pick very disappointed, somewhat disappointed, or not disappointed. If 40 % or more pick very disappointed, you have product-market fit. That is the bar Sean Ellis set after testing the question at around 100 startups, and it's the answer you searched for. The survey grades what you already built, nothing more. The questions that decide whether you ever get a good grade come earlier, and they're about the customer's problem, not your product. This page has both.

Where you are	The question that matters	What you do with the answer
Nothing built yet	What did you do the last time this problem came up?	Write your headline in their words
First users	Can I see what my 30 users actually do?	Set up tracking and user calls before any survey
Paying customers	How would you feel if you could no longer use it?	Score it, sort it by benefit, cut what nobody asked for

The product-market fit survey: the questions everyone searches for

The product-market fit survey is one scored question plus four open ones. Sean Ellis wrote the scored question while running growth at Dropbox and LogMeIn, and Rahul Vohra used the open ones at Superhuman to turn a 22 % score into 58 % within three quarters (First Round Review, 2018).

1. How would you feel if you could no longer use [product]?
   • Very disappointed
   • Somewhat disappointed
   • Not disappointed
   • I no longer use it
2. What type of person do you think would benefit most from [product]?
   • Open answer
3. What is the main benefit you get from [product]?
   • Open answer
4. What would you use instead if [product] were no longer available?
   • Open answer
5. How can we improve [product] for you?
   • Open answer

Questions 2 to 5 have no fixed answers. People write a sentence or two in their own words, and those sentences are what you sort the scores by later.

Send it only to people who used the product at least twice in the last two weeks. That was Vohra's rule, and it matters more than the wording. Everyone else answers from memory, and memory is polite.

40 % "very disappointed" means fit. What to do below 40 % is a longer story, and it lives in my PMF framework guide, including the segmentation trick that got Superhuman from 22 to 58.

Download the 21 questions and the survey template

The file below has the five survey questions with answer options, a scoring sheet, and the 16 questions around them: seven to ask people before you build, seven to ask yourself at first users, two for the step back once customers pay.

The answer you want, and the answer you need

A survey tells you whether people like what you built. The real product-market fit question is what problem the customer wakes up with, and you ask it before you write a line of code.

I am not a fan of these surveys, and I say that on a page about them. My rule as a founder coach: if I have to go to a customer and ask whether they like my product, something already went wrong. The time to understand the customer is before building, and it has to be enough time that what I build solves a problem they actually have.

No customer wakes up in the morning thinking "I would love to log in faster with Google sign-in today." Plenty of companies build exactly that, put it in the release notes, and call it a feature. The customer wakes up stressed about something else entirely. The whole game is whether you know what.

Nothing built yet: seven questions about the problem

Before a line of code, the product-market fit questions are about the customer's day. What they did the last time the problem showed up. What it cost them. What they already tried and why they stopped. What happens if nothing changes for a year. Who else feels it. How they describe it to a colleague. What they would do with the time if it went away.

Seven questions, five to ten people, and you never mention your idea. The method behind this is product discovery, and the interview craft is in my customer discovery guide. This page only needs the questions and the test that follows them.

The test is your headline. In September 2026 I looked at a mentoring platform. Their homepage said "First-hand advice from top creators." Sounds great. Now picture the person this is for: someone in a job who wants the promotion, who has stress with their boss and stress with their team, who wants to grow into a leader. That person wakes up thinking about the meeting at ten, and "first-hand advice from top creators" is nowhere in that head.

A headline that comes out of the seven questions names the pain and the result. Russell Brunson's Expert Secrets has the shape I use: the result, then the fear it removes. "Lose weight in 30 days without changing what you eat." You can read a startup's customer understanding off its homepage in ten seconds, and most of the time that is where it ends.

First users: what you need before any survey means anything

A product-market fit survey at 30 users measures nothing if you cannot see what those 30 users do. The setup comes first: which features each user touched this week, how long a session lasts, how often they come back, where they leave, the bug rate, the open rate on your mails, a screen recording tool like Hotjar or Microsoft Clarity, and a user call at least twice a month.

Most early products I see have none of this. In 2026, with AI, building got fast and measuring did not. A founder ships a feature in an afternoon and has no idea a week later whether anyone opened it. That is the basic equipment for evaluating fit, and without it every survey score is a guess with a percent sign.

The reason is the difference between leading and lagging indicators, which I explain in the Lean Analytics guide. Usage, return rate and interviews tell you what is about to happen. Revenue, churn and the survey score tell you what already happened. Founders stare at the lagging ones and skip the leading ones, and then the survey surprises them.

Paying customers: the step back

When revenue already answers "do they like us", the product-market fit question changes to "what do they actually need", and the answer is usually somewhere nobody asked.

One of the last founders who came to me put it like this: "We built a big platform. At the start we were strong with it. Now the competition is far more specialised and we don't know how to position ourselves anymore." A B2B software startup, paying customers, real revenue. What I see in that situation, more often than not, is a feature graveyard: a lot started, nothing planned through to the end, and the question "how do we go on, everyone else is faster and better than us." They were on the right track at the start. Then FOMO pulled them off it. Instead of going deeper on the track they had, they chased what the others were building, and lost the track.

What we did was a step back. We talked to customers, and not in the "do you like us" way, because revenue had already answered that. We ran customer research on what they actually needed. The answer was a place the founders had never looked: their customers ran their whole working day inside one tool nobody had asked about, and the product lived next to it instead of in it. The direction that came out of the research was to bring the product into that tool, with AI doing the repetitive part, instead of adding another feature beside it.

Two questions do that step back for you, and they are in the template: which one problem did the first customers pay us for, in their words, and what have we built since then that nobody asked for.

How to read the survey answers

Count "very disappointed" only among people who used the product in the last two weeks, then segment by the benefit they name. The share against everyone who ever signed up is a vanity number.

Group the "very disappointed" answers by question 3, the main benefit. The biggest group is your core segment, and its share of "very disappointed" is your real score. Then group the "somewhat disappointed" answers by question 5: what would move them to "very"? Build that. Ignore the "not disappointed" group entirely; Vohra's team did, and that is the part most founders cannot bring themselves to do.

Signs of product-market fit outside the survey look like this: users come back without a reminder mail, they describe the product to others in the words you would have chosen, and the "what would you use instead" answers are "nothing" or a spreadsheet. Below 40 or so responses, read the survey as a set of interviews, not as a score.

Product-market fit questions for AI products and SaaS

The questions are the same for an AI product or a SaaS; what changes is the timing. An AI product gets built in days now, so the problem questions get skipped and the tracking never happens. Founders arrive at the survey with 200 sign-ups, 12 active users and no idea which of the two groups they are asking. Run the seven problem questions before the prompt, set up the tracking before the launch post, and send the survey to the 12, not the 200. If the 12 are not there yet, how to get your first customers is the page before this one.

If you have paying customers and the score is below the bar, that is the conversation I have most often as a founder coach. If you want to compare your score with other founders first, the Product Bakery community is where I do that.