Ab Testing Design

A/B test design, experiment setup, variant design, and statistical analysis for designers.

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Ab Testing Design

Experiment Design

What to Test

  • High impact, easy to change: Copy, color, layout, CTA.
  • Clear hypothesis: "Changing the CTA from 'Sign Up' to 'Start Free Trial' will increase conversions because it communicates zero commitment."

What Not to Test

  • Preferences ("Do users prefer blue or green?").
  • Everything at once (test one variable).
  • Insignificant elements (button border-radius doesn't matter).

Variant Design

  • Control (A) = current experience.
  • Variant (B) = one change with a hypothesis.
  • Don't create wildly different variants (you won't know what caused the difference).

Statistical Rigor

  • Sample size calculator before starting.
  • Run for full weeks (not 2 days — behavior varies by day).
  • 95% confidence minimum before declaring a winner.
  • Watch for novelty effects (new things get more clicks initially).

Reporting

  • State the hypothesis.
  • Show the numbers (conversion rate, confidence interval).
  • State the winner with context.
  • Document learnings for future tests.

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