SEO and Marketing Terms: A/B Testing
A/B testing is a marketing experiment where two versions of a webpage, email, or ad are shown to randomly assigned test groups. Although changing one thing at a time isn’t a die-hard requirement, it does help isolate the change’s effect. For example, testing a call-to-action button color, headline wording, or choice of image might improve conversion rates, but if you change all three at once, you don’t know which one made the difference.
When a test is created, success should be measured against a predefined primary metric that matches your goal. If you want more people to click on the Buy Now button, that’s the thing you track. Click-through rates, conversion rates, and bounce rates are just a few metrics you might measure to determine which version performs better. Other metrics might be engagement time if you want to know whether people spend longer on the page, or scroll depth if you want to see how far down they read.
Tests can provide a variety of information. You may find that changing a button color reduces clicks, or changing the wording of a headline apparently made no meaningful difference (or, at least, that the test didn’t establish a reliable difference). You may also find that changing the header image increased conversions by 5%.
A/B testing is a classic method of conversion optimization, but you need to make sure you can collect enough data to evaluate a change reliably. You need to decide your changes, detail what counts as success, set your benchmarks, design your tests, and run them.
Once you’ve collected enough data, compare the results against your primary metric. But don’t crown a winner just because one version has a higher number. Sometimes the difference is real, and sometimes it’s just statistical noise.
