A/B Testing

A method of comparing two versions of a web page, email, or ad to determine which performs better based on a specific metric like conversions or clicks.

A/B testing (split testing) shows different versions of content to random audience segments and measures which version achieves better results. It replaces guesswork with data-driven decisions.

What to A/B Test

  • **Headlines and copy**: Different value propositions or wording
  • **CTAs**: Button text, color, size, placement
  • **Images and videos**: Hero images, product photos
  • **Pricing presentation**: Monthly vs annual, anchoring strategies
  • **Email subject lines**: Open rate optimization
  • **Page layouts**: Long-form vs short-form, sidebar vs no sidebar

Best Practices

  • Test one variable at a time for clear results
  • Run tests until you reach statistical significance (usually 95%+)
  • Ensure sufficient traffic — small sample sizes produce unreliable results
  • Document and share learnings across your team

FAQ

How long should I run an A/B test?

Until you reach statistical significance — typically at least 1-2 weeks and 100+ conversions per variant. Ending tests too early leads to false conclusions.

What's the difference between A/B testing and multivariate testing?

A/B testing compares two versions with one changed element. Multivariate testing changes multiple elements simultaneously to find the best combination, but requires much more traffic.