Multivariate testing

While A/B testing compares two versions, multivariate testing examines multiple variables simultaneously.^[1] Think of an e-commerce product page where you want to test both the Buy Now button color (blue vs. green) and its label (”Buy Now” vs. “Purchase”). Instead of running two separate A/B tests, multivariate testing shows all possible combinations.

A multivariate test for just these two elements creates four variations: blue button with “Buy Now,” blue with “Purchase,” green with “Buy Now,” and green with “Purchase.” This approach helps identify not just which elements perform better individually, but also how they interact. For example, green might work better with “Buy Now” while blue performs better with “Purchase.”

The trade-off is sample size — each added variable multiplies the required visitors. With our example's 4 variations, you need 4 times as many visitors as a simple A/B test to reach statistical significance. This means multivariate tests work best on high-traffic pages where you can gather enough data within a reasonable timeframe.