A/B (Split) vs. Multivariate Testing

Landing page design takes into account many elements including layout, text, images, color, calls to action and more. How do you know which style or placement works better for increasing engagement, and ultimately, conversion rates? Testing – either A/B (split) or multivariate. But what’s the difference?

graphic of ab testing and multivariate

A/B (Split)

A/B testing (also known as split testing) is a test method where your audience is split – two different versions of your landing page are served, with the difference generally being one element. Testing one variable at a time provides reliable data more quickly (without requiring a high number of visitors). If more people sign up for your offer when the CTA button is blue vs. red – you’re on the path to optimization! The difference could also be two radically different page designs tested against each other. The impact of the page as a whole would be measured in this case, as opposed to the individual elements.

Test both versions simultaneously – long enough to produce useful data (the length of time will depend on the traffic your site gets). The greater the number of variables tested, the harder it will be to evaluate which one is responsible for the difference in performance.

Multivariate

Multivariate testing uses the same concept as A/B testing – sending visitors to different versions of a page – but a higher number of variables are tested simultaneously. The purpose is to measure the effectiveness of each combination on the end goal. An example of a combination to test could be form length, type of CTA (text vs. image), and headline text. The most successful design will be evident once enough data has been compiled. Insights may also be made as to which elements of the site visitors interact with more favorably.

This method of testing is best used with sites that have high daily levels of traffic and conversions. The greater the number of variations that need to be tested, the longer it will take to produce reliable data.

Conclusion

Experiments that are well thought out, with a commitment to the process of redesign and testing, can result in big improvements to landing pages and increased conversion rates.