Split testing
Split testing, also known as A/B testing or multivariate testing, is a method used in pay-per-click (PPC) advertising to determine the most effective version of an advertisement or website element by comparing two or more variations.
This technique allows marketers to make data-driven decisions about which version of an ad or website element will perform best with a target audience.
How split testing works
Split testing works by randomly dividing a target audience into two or more groups and showing each group a different version of the ad or website element being tested. The performance of each variation is then measured and compared to determine which version is more effective.
For example, a marketer might want to test the effectiveness of two different versions of a landing page for a PPC campaign. One version of the landing page might have a strong call to action, while the other version might have a more subtle call to action.
The marketer would then split the target audience into two groups and show each group one of the two versions of the landing page. The marketer could then measure the performance of each version by looking at metrics such as conversion rate and cost per conversion.
Split testing can be used to test a wide range of elements, including ad copy, images, call to action buttons, and more. It is a valuable tool for PPC marketers because it allows them to make informed decisions about which elements are most effective at driving conversions.