A/B testing is a way to use data to inform your design decisions. The basic concept of A/B testing is that the data gathered from two or more designs are compared against the metrics of the existing design to prove a design hypothesis.

Before you begin A/B testing is it important to have the data from the existing design and know what you hope to achieve by implementing something new. If you want to improve read time on blog articles, you must first know the current read time.

The greater the risk, the greater the reward. By using A/B testing, you’re testing your ideas in front of a small amount of the site’s traffic. This way you can be sure that you are making the right choice. You can learn from every test you make and implement the results.

A/B testing can make you a smarter designer, as your new designs are proven by the data. A/B testing is a good way to learn from your design and which elements are yielding the desired results.

00:32 What is A/B testing?

08:38 Our experience of A/B testing

09:50 A/B testing: The basics

11:05 An example of A/B testing

15:10 A/B/C testing

17:27 The benefits of A/B testing

18:50 The results of Charli’s A/B test at Seva

21:20 A/B testing at Basecamp

24:00 When A/B testing comes up with surprising results

26:00 Know your reasons

28:20 A/B testing tools