Measuring whether a feature worked is one of the most important feedback loops in product development. Without it, you're just shipping and hoping. But most teams get the timing wrong. They build the thing, launch it, then ask themselves how they'll know if it succeeded.
By that point, you've already lost. You'll find a metric that went up, declare victory, and move on. Confirmation bias is almost impossible to avoid when you're measuring success after the fact.
The fix is simple: write your hypothesis before you sketch a wireframe or write any code.
A hypothesis forces clarity. It documents what you believe to be true and what needs to happen to prove or disprove it. "We believe that adding a progress bar to onboarding will increase completion rates from 40% to 55% within two weeks of launch." That's specific. That's measurable. And crucially, it's written down before you've invested anything in the solution.
This matters even more at startups. When you have finite runway, the speed of your learning loop is a survival metric. Every feature that ships without a clear hypothesis is a missed opportunity to learn something. And every week spent building the wrong thing is a week you don't get back.
The best product teams I've worked with treat hypotheses as non-negotiable. No hypothesis, no build. It sounds rigid, but it actually speeds things up. You stop wasting time on features that nobody can explain the purpose of. You get direct, unbiased feedback on what's working. And you build a culture where learning matters more than shipping for shipping's sake.
Plan your feedback loop before you plan the feature.