What is A/B testing?
A/B testing is also called split testing. It is a method where you create two versions of a landing page and make changes to the elements you want to optimize in one of the versions. When you run an A/B test, the traffic to the specific page is split and distributed between the two different versions. You then analyze which of the versions generates the highest number of desired actions related to what you have changed.
By testing one element at a time in each version, you can see whether the original page delivers the best results, or if the modified version has led to higher performance. Once you see which version performs best, you can select a winner and implement the changes that delivered the strongest results.
What can be A/B tested?
You can test most elements on your website. The most important thing when it comes to A/B testing is to only test one thing at a time. If you evaluate several changes in the same test, you will never know which of the changes led to better results.
Among other things, you can test:
- Headlines
- Text
- CTA buttons
- Images
- Breadcrumbs at the top of the landing page
- Design elements
- Forms
- Navigation on the page
Summary
By A/B testing different elements on your website, you will gain statistics on which variant your visitors respond best to. You can test every element on the page and identify which ones drive higher conversions and engagement.
Frequently Asked Questions
What is the definition of A/B testing?
A/B tests are experiments where you test two different variations of a single element within the same time period. A/B tests direct half of the traffic to the landing page to each of the two versions. This way, you can identify which variant delivers the best results.
Why use A/B testing?
A/B testing is a relatively safe way to test specific elements on your website without risking your existing conversion rate. By A/B testing your page, you make it more user-friendly, can reduce the share of users who take no action on the landing page, and increase the quality of the traffic coming to the page.
