How does an A/B test differ from a multivariate test?

In an A/B test, you only make one change to a variable while keeping all other variables the same. This allows you to isolate the effects of that specific change on the outcome being measured, whether it's click-through rates, conversion rates, or any other key performance indicator. By focusing solely on one element, A/B testing provides clear insights into which version performs better and why.

This approach is particularly useful for marketers and businesses who aim to refine their strategies based on evidence, as it facilitates a straightforward comparison between two variants. Making only one change, whether that be a headline, color scheme, or layout, ensures that the results are directly attributable to that single alteration, which simplifies analysis and helps in decision-making.

In contrast, multivariate tests examine the impact of multiple changes at once, which can complicate the analysis since it becomes difficult to determine which variable or combination of variables influenced the outcome. Consequently, A/B testing is often preferred for its simplicity and clarity in establishing cause and effect.