Running quick landing page tests or A/B tests without a clear hypothesis may seem like experimentation, but it doesn’t provide true validation of your assumptions. For example, imagine you're launching a fitness app and create a landing page to see if people are interested. You get some sign-ups, but without a clear goal, it’s hard to know what those sign-ups mean. Did users sign up because of your app’s core features, the design, or just curiosity?

Instead, a better approach is to identify a key assumption that needs testing, like "Users will sign up for the app because they value personalized workout plans." Now, you can design an experiment focused on this assumption — perhaps by offering two versions of a landing page, one highlighting personalized plans and another promoting general workouts. With clear data and goals, you’ll get more meaningful insights, helping you validate your assumption and guiding your next steps.^[1]