What is a cost-effective way to improve important KPI’s that are impacting the growth of your organization, or brand? A/B testing.
What is an A/B Test?
A/B testing is the study of the relationship between independent variables, and dependent variables. For example, let’s say you were curious if the color of your webpage font was impacting your conversion rate. You can test this. the practice of showing 2 variants of the same webpage to different segments of website visitors at the same time and comparing which variation drives more conversions. The one that gives higher conversions wins!
How Do I Run the Test?
You may have run an A/B test before and not have even known it! Have you ever sent two identical emails to someone, and changed only one variable in the email?
Create a variation based on your hypothesis, and A/B test it against the existing version. Calculate the test duration keeping in mind your monthly visitors, current conversion rate, and the expected change in the conversion rate. (Use our Bayesian Calculator here.)
That’s A/B testing
An A/B test starts with the altering of a single variable, like the color of the font, the style of a font, etc. Once you’ve set up your tests, all you have to do is study the data from each test to see which test performs better: A, or B. For example, let’s say you want to test how an image on your website is perceived by your audience. To conduct an A/B test, you would use two different images on your website, and see which image your audience responds better to.
If test B performs better than test A, then you know your hypothesis is true. But if test A, the controlled test, performs better than test B, the changed variable, you’d have the data to conclude that your hypothesis was false.
To better understand A/B tests, see the infographic below, brought to you by Spire Digital: