Multivariate Testing

What Is Multivariate Testing?

While A/B tests compare individual elements, multivariate testing uncovers interactions between multiple variables. This is especially valuable for landing pages where the headline, image, and CTA button all jointly influence the conversion rate. You do need significantly more traffic for statistically reliable results.

Multivariate testing is a testing method in which multiple variables on a page are tested simultaneously — in contrast to A/B tests, which test only one variable. A multivariate test could, for example, test the headline, image, button text, and button color simultaneously with various combinations. This delivers insights faster but requires more traffic.

Technically, multivariate testing works by combining different variations of all tested elements. With 2 headlines, 2 images, 2 button texts, and 2 button colors, you get 2x2x2x2 = 16 different combinations. Each combination is shown to a portion of users and conversions are measured. Statistical significance is important — with too little traffic, results are unreliable. Google Optimize (discontinued) and other A/B testing tools like Convert or Unbounce enable multivariate tests.

In practice, you should only run multivariate tests with high traffic (at least 1,000 visitors per variation per day for statistically reliable results). With less traffic, A/B testing is more efficient. Use multivariate testing to discover interactions between elements — for example, a particular headline might perform especially well with a specific button text. Document all tests and their findings for future optimizations.