Multivariate Testing vs A/B Testing

A/B testing is a method of website optimization that involves testing two versions of a website. One version is shown to half the number of visitors, while the other is shown to the other half. Conversion rates are compared to determine which version outperforms the others.

A/B Testing Use Cases

One of the most common uses of A/B testing is to test two very different page designs against each other. For example, one page might have a call to action in text while another omits all text and instead has an advertisement on the top bar. A/B testing is also very useful if you have 2 variations of copy, an image or location of a CTA on your website and you want to see which one is best. Rather than guessing, an A/B test allows you to actually determine which version drives conversions.

Pros Of A/B Testing

One of the main pros of A/B testing is that it’s fast. We strongly encourage you to split your traffic into a few separate test groups. Splitting traffic into more than three or four segments would make it hard to finish a test since you would require high volumes of traffic to get results from the test.

A/B testing is also a great starting point for experimentation since it’s simple to do and can test the impact of a small change. It can quickly demonstrate how small changes can lead to measurable gains in conversion rates and increases in revenue for a business.

Cons Of A/B Testing

A/B testing is a powerful tool that can prove extremely useful to e-commerce optimization. However, it can be used as a standalone test only and does not reveal any information about the interaction between variables on a single page.

Multivariate Testing

A multivariate test is similar to an A/B test, but is more accurate and shows much more information about how different variables interact with one another. The purpose of a multivariate test is to determine the differences between each combination of variables.

Once a page has enough traffic to run the test, the data from each variation is compared to determine which design elements have the most positive or negative impact on visitors' behavior.

The most common example of multivariate testing is a page on which several elements are up for debate. You can run a multivariate test on this page by creating two different lengths of sign-up form, three different headlines, and two footers. Then, you would split up traffic to all the various possible combinations of those elements. The more variations, the longer this test will take.

Once the test is complete, the variables from each variation are compared to see what had the best results regarding its relationship with the other variations on your page resulting in the best outcome of elements put together.

Pros Of Multivariate Testing

Multivariate testing is a powerful way to help you hone design efforts by analyzing the elements of the page where they will have the most impact. This can be an especially useful tool when designing landing pages, for example. By comparing various designs and applying data-driven insight, multivariate testing helps you better optimize future campaigns.

Cons Of Multivariate Testing

The biggest limitation of multivariate testing is the number of possible combinations. Too many variables can make a test a challenge to run and means it might take a long time to complete. Even a site with a lot of traffic might find that it can take time to test different combinations and scenarios.

To Sum It All Up

A/B and multivariate tests are both powerful tools that complement each other. Both help you optimize your site and are useful for experimentation.

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