In this age of analytics, marketers are data detectives. A/B testing can help resolve many of their quandaries related to online marketing.
But, first, what is A/B testing? It is a process in which you choose the best-performing version of a webpage, by randomly displaying different versions of your site to visitors and assessing the performance of each variant against a desired metric (such as clicks or sign-ups). You can test by tweaking one page element (such as headline, call to action, or image) at a time, or you can test changes to several page elements all at once (the latter is referred to as "multivariate testing"). Thus, when you use A/B testing, you are not flying blind. You're letting data drive your design choices and decisions. Think of A/B testing as "the scientific method meeting online marketing."
Not just for webpages, A/B testing use cases span email campaigns, banner ads, mobile apps, and other marketing scenarios in which even a small increase in conversion rate significantly moves the needle on business outcomes.
Strictly speaking, A/B testing techniques are not new. However, until a few years ago, the complexity of implementation meant that only companies with large teams of marketing analysts, data scientists, and developers were able to effectively use them in practice.