• Identify and prioritize riskiest assumptions.


• Design minimal experiments that generate learning.


• Execute tests quickly with constrained resources.


• Make go/no-go decisions based on evidence.

• Validated or invalidated key assumptions.


• Evidence-based go/no-go decisions.


• Reduced risk before significant investment.

Making assumptions explicit is key. Teams operate on hidden assumptions. Force every "obviously" and "everyone knows" into a hypothesis. You can't test what you can't see.

Enforce test design discipline. Teams often want to build more than the minimum. "While we're building the landing page, let's add features..." No. Build only what's needed to test the hypothesis. Extra features muddy the signal.

Define success upfront. Set success criteria before running the test. "70% complete signup" or "10% email conversion." Otherwise, you might rationalize success regardless of results. Clear metrics prevent bias.

Real users are essential. Testing with coworkers, friends, or hypothetical users teaches nothing. You need actual target users in realistic contexts. If you can't access real users, the test is useless.

Acting on results is the hardest part. Teams rationalize away invalidated hypotheses. "Users didn't understand our test" or "We just need to explain it better." Sometimes that's true, but often it's denial. Be honest about what you learned. I've seen teams ignore clear evidence, and it always backfires.