A/B testing is designing two versions of an element and, by conducting a test, gather evidence of an empirical definition of which element is more successful at achieving a specific goal.
Typically, A is the current design (called the control), and B is the new design. You split your website traffic between these two versions and measure their performance using metrics that you care about (conversion rate, sales, bounce rate, etc.). In the end, you select the version that performs best.
You have to run more A/B tests and of course other kind of tests, e.g. Click test, Memory test, Yes/No Test etc. according to the business or user goals you would like to achieve.
There are many kind of online platforms where you could create your tests. A/B Testing is available in Google Analytics too.
You analyze and synthesize user data from Google Expriments to improve user experience and workflow of product feature. According to the data and outcomes, you will decide what to change in your design.
Benefits of these tests are that you will get a kind of "user approval" - you will know if user understand your design, features and if your goals are relevant or not.
On the following pages you will find examples of AB Testing, Click Test, Memory Test, AARRR Definition and changes I've done for the TASKLY Project Management Web App.
