An Introduction To A/B Testing

A/B Testing isn’t a new term. In fact, many canny marketers and designers are using it at this very moment to obtain valuable insight regarding visitor behavior and to improve website conversion rate. Unfortunately, A/B Testing still remains in the dark for most online marketers and web designers. The technique is still underrated as opposed to comparably valued methods like SEO.

Definition Of A/B Testing

A/B Testing (also known as Split Testing) is a website optimisation technique that involves sending half your users to one version of a page, and the other half to another, and watching the web analytics to see which one is more effective in getting them to do what you want them to do (for example, sign up for a user account).

Multivariant and Split Testing With Google Website Optimizer

Multivariant and Split Testing With Google Website Optimizer

To improve your website conversion rates using A/B Testing, you must first learn and master the technique. While there are different means to test alterations made to a website, none of these methods are easier and simpler as A/B Testing. However, it is important to realize that A/B Testing isn’t suitable for each and every website, regardless of its diverse positive attributes. In fact, it is advised by experts that you should first identify if it is the proper Testing strategy to employ for the corresponding circumstances you are working with.

Benefits Of A/B Testing

As a technique, A/B Testing is highly useful when it comes to testing alternative variations in your website like, for example, different types of buttons utilized for call to action, alternative images or headlines. It can also be used to evaluate the impact that trade association logos and icons have on generating user trust. However, other parts of your website that are not included in the above recommendations can still benefit.

Still, take note that it ultimately relies upon the amount of alterations that you are planning to introduce to your website. A/B Testing is ideal to evaluate one alteration from the current user interface. If you plan to introduce more than one alteration, then Multivariate data analysis a fitter testing methodology to employ.