How to know if you've got product-market fit

Lenny Rachitsky compiles the most concrete and actionable definitions of product-market fit (PMF) from leading investors, founders, and operators, organized into signals before a product exists and signals after launch. The core argument is that PMF is vague for most people, so it helps to watch for specific, measurable evidence such as retention curves that flatten, high organic growth, and customers who would be very disappointed if the product disappeared. He also highlights efficiency measures like CAC below LTV and the burn multiple, which show whether the market is pulling the product or the company is pushing it. The piece matters because it gives product builders a checklist for judging whether they have actually found PMF and a set of guides for finding it.

01Key takeaways

• Ask potential customers to pay, even before the product exists, since money down is the strongest early signal of interest.
• Plot retention cohorts over time; if the curve flattens, a group of users is finding durable value.
• Survey users on how disappointed they would be without the product and treat over 40% very disappointed as a strong PMF sign.
• Track organic and direct acquisition; if most new accounts arrive without paid push, users are recommending the product themselves.
• Make sure customer acquisition cost stays below the lifetime value of each customer before scaling spend.
• Treat product-market fit as something that shifts with competition and markets, so keep checking the signals over time.

02Key sections

Pre-product signals

Before a product is built, strong interest appears as visible excitement from users and willingness to pay, even before the product exists. Pre-sales and invoices are presented as the clearest early signal.

Retention and cohort curves

Post-launch, a retention curve that flattens over time indicates that a group of users finds lasting value. Cohort analysis and comparisons with benchmarks help set the right target for a given product type.

Survey and free-trial tests

The Sean Ellis survey asks how disappointed users would be without the product, with over 40% answering very disappointed as a PMF threshold. Enterprise teams can pull a trial at its end and see whether customers push back.

Organic growth and efficiency

Word of mouth, direct traffic, and unprompted recommendations indicate that users love the product enough to spread it. Efficiency metrics such as burn multiple, sales yield, and CAC below LTV show growth that the market is pulling.

Customer behavior and guides

Customers grabbing the product, usage that persists despite bugs, and demand that outpaces supply are all taken as signs of PMF. The piece closes with recommended guides on how to find PMF and a reminder that it is an ongoing state, not a single moment.

03From the post

““The only thing that matters is getting to product-market fit.” —Marc Andreessen I’ve noticed that most people (including myself) have only a vague grasp on what product-market fit actually is. And even fewer people are going after it in a systematic way. For my own benefit if nothing else, last year I began collecting the best descriptions of PMF that I could find across Twitter, podcasts, books, and blog posts. Below, I’ve put together my favorite (and most actionable) definitions of product/market fit, broken up into pre-product and post-product, and sorted from the most concrete to least concrete. I’ve also added my favorite guides for finding PMF. If you’ve come across anything better, or have gone through this journey yourself and have a story to share, I’d love to hear it. Lenny's Newsletter is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. What to look for Pre-Product 1. Visible excitement “The real metric for both consumer apps and enterprise is — do someone’s pupils dilate when they use your stuff?…”

04Frameworks mentioned

Summary and takeaways written by PM Atlas; quotes are short excerpts. © the original author.