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The Scientific Method for Growth

A/B testing isn't just about changing button colors. It's about applying scientific rigor to understand what drives user behavior and business outcomes.

Building Strong Hypotheses

Every test should start with a clear hypothesis:

"If we [make this change], then [this metric] will [increase/decrease] because [user behavior insight]."

Test Design Principles

1. Isolate Variables

Test one element at a time to understand what drives results.

2. Ensure Statistical Power

Calculate required sample sizes before starting. Don't call winners too early.

3. Account for External Factors

Consider seasonality, marketing campaigns, and product changes that might affect results.

What to Test

• Headlines and copy: Value propositions, CTAs, error messages
• Visual elements: Images, colors, layout, forms
• User flows: Onboarding steps, checkout process, feature discovery
• Timing: Email send times, notification frequency, trial length

Common Pitfalls to Avoid

• Testing without sufficient traffic
• Stopping tests too early
• Ignoring statistical significance
• Testing vanity metrics instead of business outcomes