The principles behind A/B testing and multivariate testing are similar. Both options involve testing variations of a webpage to see which will generate more conversions. Conversions don’t just have to be a lead or a sale. You can also measure micro conversions tied to visitor behavior, such as watching a product video, scrolling further down a page or adding an item to cart.
Multivariate website testing strategies involve testing different combinations of elements on a website to find the best performing design. For example, you can test different combinations of text, images, and colors to see which version of the website will get more visitors or lead to more sales.
For example, let’s say you want to test different headlines and images together to see which combination encourages users to click into a product category. If you’re doing multivariate testing, you might come up with three versions of the headline and two versions of the image you’d like to test. An A/B testing tool that allows for multivariate testing would allow you to test the six possible combinations at once to see which performs better.
Multivariate testing can be faster than A/B testing if you’re looking to test multiple combinations of elements. It can also help you understand how different aspects of your site work together to influence visitor behavior.
The downside to multivariate testing is that more traffic is needed to get a statistically significant test result because of the number of variations. It can also be resource intensive to come up with multivariate testing ideas and generate the website elements you want to test.
To learn more about multivariate testing, check out this guide from Optimizely.