Insights, frameworks and stories about finding Product-Market Fit
Insights, frameworks and stories about finding Product-Market Fit
Early signups give you powerful signals about what matters to users, and I use those first interactions to spot the few who already behave like long‑term champions. These early patterns help me refine onboarding, highlight sticky features, and focus development…
A healthy retention curve shows how quickly new users find repeat value, and it exposes the exact points where your product strengthens or loses engagement. I use it to see whether early activation sticks, whether long‑term value compounds, and how…
TL;DR Dive deeper in this topic with AI: ChatGPT Perplexity Grok Why PMF levels matter When you name the level you’re at, you stop comparing your seed-stage app to a unicorn’s metrics and start setting the right goals for the…
Early-stage founders often feel stuck: growth is choppy, word‑of‑mouth is weak, and users try the product but don’t come back—leaving you wondering if you’ve hit product-market fit or just a briefly exciting launch. TL;DR Dive deeper in this topic with…
Early-stage founders often chase growth, but the real signal of Product-Market Fit hides in your retention data. When your curve flattens, you’ve found users who can’t live without your product. Learn how to track retention, spot your ideal customers, and use early user data to reach PMF faster.
If you ask founders how they knew they got Product-Marktet Fit, most often they tell you: “I just felt it”. That’s great for them, but not usefull for you if you are desperately looking for signals of PMF. TL;DR Dive…
When you are building a new product or service, it is important to quickly learn if you are building a vitamin or a painkiller. The 40% rule for product‑market fit is a simple way to cut the noise and get…