Stop Guessing, Start Testing: The Hypothesis Hack You Need

Ever feel like your A/B tests are more “spin the wheel” than “science experiment”?

Picture this: You just ran a test. The results are in. Drumroll, please… and it’s a meh. No actionable insights. No champagne-popping. Just a slide that says, “We’ll get them next time.”

Let me let you in on a secret: The problem isn’t the test—it’s the hypothesis.

In this newsletter, I’m breaking down how to create hypotheses so clear, they could land their own TED Talk. Stick around—you’ll never look at testing the same way again.

What’s a Hypothesis, Anyway?

Let’s cut to the chase: A hypothesis isn’t just a fancy guess. It’s a statement you can test, backed by logic and evidence. Think of it as your A/B test’s GPS—if it’s vague, you’re lost.

🚫 Bad Hypothesis: "Changing the button color will improve clicks."
✅ Great Hypothesis: "If we change the button color to red, users will perceive it as urgent, leading to a 10% increase in clicks over two weeks."

Why it works: It’s specific, measurable, and tied to human behavior.

Framework #1: The “If, Then, Because” Formula

This one’s simple but powerful. Let’s build it out:

• If we change X...

• Then we expect Y...

• Because of Z.

Example:
“If we reduce the form fields from 10 to 5, then we’ll increase sign-ups by 20% because users find long forms overwhelming.”

This format not only keeps you honest but also gives your boss fewer reasons to say, “But, why?”

Framework #2: The SMART Hypothesis

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