A/B tests, which are also known as a split test. A/B testing is basically an experiment that will help determine which variation of an online experiment performs better by presenting every version of your test to users ant random and see which ones do better.
Split testing ultimately helps avoid unnecessary risks by allowing your to target your resources for maximum effect ad efficiency.
Over at Search Engine Journal, a user asked, “How do you set up a split test? Do you recommend only testing one variable (ie. creative or copy or where the ads are placed)? Anything else you think could be help to go from 0>1 would be awesome!”
In SEJ’s post, they describe what split tests are, give tips for structuring them, and how to evaluate and act upon them.