What retention benchmark should I actually aim for at pre-seed, and how do I know if my numbers are bad?
The short answer
There's no universal number: a daily-use consumer app lives or dies on D30 retention above 20 to 30 percent, while a B2B tool people open weekly is judged on month-2 logo retention closer to 85 to 90 percent. The honest signal is whether your retention curve flattens at all, a curve that keeps sliding toward zero means you have no product-market fit yet, no matter the headline number. Start by picking the right time window (daily, weekly, monthly) for how often your product is genuinely meant to be used, then compare cohorts against themselves over time, not against someone else's blog post.
Go deeper, your way
3 hand-picked resources, 3 link-checked. Pick how you want to dig in.
✍️ Essay
✓ Link checkedFreeIntermediate
Why we picked it
The real signal of product market fit is not a headline retention number, it is whether your cohort retention curve stops falling and flattens into a stable base of users who keep coming back. Andrew Chen is the canonical voice on this mental model, and he pairs the flattening curve with the power user smile so you can see where your sticky core actually lives. Read it as the frame for judging your own numbers, not as a pass/fail line.
Why we picked it
Once you know your curve should flatten, the next question is where it should flatten, and this piece answers it with concrete benchmark ranges by business type instead of hand-waving. Lenny pooled numbers from 20-plus growth leaders and investors, so you can put your own 6-month retention next to a real bar for your category. Treat the ranges as a starting point for judgment, not a pass-fail line, since a consumer social product and an enterprise SaaS live in completely different worlds.
The bar is category-specific: roughly 25% good / 45% great for consumer social, 40% / 70% for consumer subscription, and 70% / 90% for enterprise SaaS at 6 months.
Judge yourself against your own business type, not a global average. Comparing a marketplace to a SaaS number will just mislead you.
It also splits user retention from net revenue retention, a useful reminder that a subscription business can look flat on users while still growing revenue per account.
Why we picked it
Benchmarks only matter once you can plot your own cohorts and see whether your curve is flattening, and Amplitude's Retention Analysis chart does exactly that on real user data. Amplitude has a free Starter plan that covers basic retention and cohort analysis, so a pre-seed team can run this without spending anything. Start by wiring in a few key events, then read the curve shape the way the essays describe.
