A/B split testing, A/B testing, split testing… different names for the same concept. In this text, we will refer to it as A/B testing.
At its core, A/B testing is a way to compare how different versions of something perform against each other. It’s commonly used on websites and apps. Often, A/B testing is closely connected to conversion optimization.
What performs best: variant A or variant B?
If you run an online store, a very common example is testing which color of the purchase button performs best. In other words, which version leads to the highest conversion rate?
The purchase button is the classic example, but A/B testing is also used to find out which email subject line works best, which product image performs better, and much more.
How to run an A/b split test
When you create an A/B test, you first come up with a hypothesis.
For example:
Product image A will lead to a higher conversion rate than product image B.
Then, you set up the test on your website so that half of your visitors see version A and the other half see version B.
Once you have tested enough users and collected sufficient data, you can decide which version performs best. If you use software like Optimizely, it will automatically stop the test when there is enough data to determine a winner.
Why you should always run split tests
Conversion optimization is an ongoing process that never stops. There will always be elements you can adjust to get the most out of your visitors or advertising budget.
This means that almost anything can be A/B tested.
The most important thing to remember when running A/B tests is to only change one variable at a time. That way, you know exactly which change caused the result of the test.
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