A genetic diagnostics machine was built to speed up patient diagnosis in hospitals. However, its biggest market turned out to be pharmaceutical companies needing to prove drug efficacy. This highlights how true product-market fit can be discovered accidentally in an adjacent, more lucrative market.
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Metrics can be misleading. The founder's true "aha" moment for product-market fit came from solving a complex, real-world problem posed by a skeptical expert during a live demo. When the product solved in seconds what took the customer's team two weeks, it provided undeniable proof of value in a high-stakes environment.
Treat your startup like a drug discovery experiment. A market's needs are like biological 'binding receptors'—they either exist or they don't. Marketing can raise awareness of your 'drug' (product), but it can't convince the body to grow new receptors. If you lack product-market fit, don't try to market your way out of it.
PMF isn't a one-time achievement. Market shifts, like new technology or major events, can render your existing model obsolete. Successful companies must be willing to disrupt themselves and find new PMF to stay relevant.
When a startup finally uncovers true customer demand, their existing product, built on assumptions, is often the wrong shape. The most common pattern is for these startups to burn down their initial codebase and rebuild from scratch to perfectly fit the newly discovered demand.
Technical founders often create a perfect solution to a real problem but still fail. That's because problem-solution fit is useless without product-market fit. An elegant solution that isn't plugged into the market—with the right GTM, pricing, and messaging—solves nothing in practice. It's unheard and unseen.
Sure's journey shows that PMF is not binary. The company achieved initial PMF with its prototype, then again with its first product, and again after its pivot. However, launching auto insurance with a major EV brand created a "literal rocket ship" moment that represented a completely different order of magnitude of PMF.
Initially building a tool for ML teams, they discovered the true pain point was creating AI-powered workflows for business users. This insight came from observing how first customers struggled with the infrastructure *around* their tool, not the tool itself.
After success in the affiliate network niche, Everflow expanded to direct brands. They discovered this seemingly similar market had different user personas (under-resourced marketers vs. entire teams) and needs (e.g., payment automation). This required significant product adaptation rather than a simple market expansion.
Product-market fit can be accidental. Even companies with millions in ARR may not initially understand *why* customers buy. They must retroactively apply frameworks to uncover the true demand drivers, which is critical for future growth, replication in new segments, and avoiding wrong turns.
A common misconception is that market size is fixed. However, as investor Alex Rampell notes, the market for a product executed exceptionally well can be orders of magnitude larger than for a merely adequate solution. Superior execution doesn't just capture a market; it dramatically expands it.
