# Product-market fit Product-market fit is when a product meets a real need for a specific group of customers well enough that they keep using it, pay for it, and tell others, so growth starts to come from demand rather than pushing. Also called: PMF, Product market fit, Market fit. ## In short - Product-market fit means a **specific group of people** needs the product and keeps using it. - The clearest signal is retention that flattens: a steady share of users who keep coming back. - It is found by narrowing, not widening: one user, one problem, one job done well. - Fit is not permanent. Markets move, and it has to be kept as well as found. ## What product-market fit means The term was popularized by investor Marc Andreessen in a 2007 essay, where he described it as being in a good market with a product that can satisfy that market. In practice, founders describe it by how it feels. Before fit, every sale is a push. After it, customers come in through word of mouth, usage grows without heavy prompting, and the team struggles to keep up with demand. Fit is always with a particular market. A product can fit one group of users very well and another not at all. That is why the most useful question is not whether you have fit, but with whom. ## Signs you have it, and signs you do not **Diagram: Before and after product-market fit.** **Not yet** - Retention keeps falling toward zero - Sales need long, hard persuasion - Feedback is polite but vague - Growth stops when spending stops **Finding fit** - Retention levels off for a clear group - New users arrive by referral - Users complain when something breaks - Customers ask for more, and pay _No single number proves fit. Several signals pointing the same way, for the same group of users, is the evidence._ A telling sign is how people react when the product fails. If an outage brings a wave of messages, people depend on it. If nobody notices, they do not. Choie spends the final week of every build watching real people use the launched product and fixing what gets in their way. That week cannot prove fit, but it clears away the friction that would otherwise hide these signals. ## How to measure it Two measures are widely used, and they work best together. - **Cohort retention.** Track groups of users by start date and see whether the [retention](https://www.choie.co/glossary/user-retention) curve flattens. A flat curve means some people found lasting value. - **The Sean Ellis test.** Ask active users how they would feel if they could no longer use the product: very disappointed, somewhat disappointed, or not disappointed. Growth adviser Sean Ellis proposed 40 percent or more answering very disappointed as a benchmark for fit. - **Organic growth and revenue.** Referrals, repeat purchases, and expansion within accounts all show that demand comes from the product, not from your effort alone. > **Read who is very disappointed.** The people who would be very disappointed tell you who the product is really for. Narrowing to them, and building for their needs, is often how fit is reached. ## How to get there Most products reach fit by learning in loops: pick a specific user and problem, build the smallest thing that solves it, watch what happens, and adjust. [Product discovery](https://www.choie.co/glossary/product-discovery) and [user research](https://www.choie.co/glossary/user-research) choose the starting point. An [MVP](https://www.choie.co/glossary/mvp) puts something real in front of people. [Product analytics](https://www.choie.co/glossary/product-analytics) and conversations show what to change. The speed of each loop matters. A team that can try a meaningful change every week learns many times faster than one that ships every quarter. That is the reasoning behind Choie's shape of work: a one-week prototype for $4,900, a first release in four to six weeks with a new live link every Friday, and monthly work where something meaningful ships every week. ## Common mistakes - **Scaling before fit.** Spending heavily on growth when retention is still falling to zero fills a leaking bucket. - **Confusing interest with fit.** Waitlist sign-ups and compliments are encouraging, but they are not repeat usage. - **Serving everyone.** Adding features for every kind of user dilutes the product for the users who love it most. - **Declaring victory once.** Fit can erode as competitors arrive or needs change. Keep watching the signals. ## Common questions ### How do you know if you have product-market fit? Look for several signals together: retention that levels off, users who would be very disappointed without the product, growth through referrals, and customers who pay and ask for more. One good month is not enough. ### What is the Sean Ellis test? A survey question asking users how they would feel if they could no longer use the product. Sean Ellis suggested that when 40 percent or more say very disappointed, the product is likely to have found fit. ### Can an MVP have product-market fit? It can show early signs of it with a narrow group of users. More often, the MVP is the first step in learning what fit would require, and the product changes several times before it is found. Choie's best-fit [first release](/services/mvp-development) has one primary user and one critical workflow, and that narrowness also makes the signals easier to read. ### How long does it take to find product-market fit? It varies widely, from months to years. Teams that ship and learn in short cycles, and stay focused on one group of users, tend to get there sooner. Related: [Minimum viable product (MVP)](https://www.choie.co/glossary/mvp), [User retention](https://www.choie.co/glossary/user-retention), [Product discovery](https://www.choie.co/glossary/product-discovery), [User research](https://www.choie.co/glossary/user-research), [Product analytics](https://www.choie.co/glossary/product-analytics). HTML: https://www.choie.co/glossary/product-market-fit