A/B Testing vs Multivariate Testing: What's the Difference?

A/B testing compares two versions of a single element - subject line A versus subject line B, one call-to-action colour versus another - changing just that one variable to isolate its individual effect on the outcome.

Multivariate testing tests multiple elements at once in combination - subject line, header image, and call-to-action text all varying simultaneously - measuring which specific combination of choices performs best, not just which single change helps.

A/B testing is simpler to run and needs far less traffic to reach a statistically meaningful result, because it's only comparing two options on one variable. Multivariate testing can reveal interaction effects a series of individual A/B tests would miss entirely - a headline that only performs well paired with a specific image, for instance - but it needs substantially more volume to reach significance across every combination being tested, which makes it impractical for campaigns without a large enough audience to support it.