Introduction to A/B Testing

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Introduction to A/B Testing

What is A/B Testing

A/B Testing is a method wherein 2 versions of a web page or a landing page is tested by sending outimage-11-walteranalytics to each test subjects an equal amount of traffic. The winner is decided by the number of conversion it generates.

A/B Testing is not limited to websites. You can also test ads and emails.

Importance of A/B Testing

  1. A/B testing reveals your user’s behaviour and reaction. With this in mind, you can change your layout, content or design according to how the users respond and eventually convert.
  2. A/B testing before undergoing a redesigning saves you time and effort you could have allotted to actually optimising your conversion rate.
  3. A/B testing gives you actionable data from comparisons, test and collected data through continuous testing.
  4. Designing, redesigning and arranging the layout is better done with data driven results from A/B testing instead of grasping at straws with guesswork.

Click here to read “Top A/B Testing Mistakes”

Is it necessary to test? Can we just emulate the test results of others?

While it is ideal to take the effort to do A/B testing, other organisations see fit to copy tests which proved successful to other websites. What most do not know is that there are many factors to consider such as the industry, the type of market and the website design. What works for one does not necessarily work the same for others.

When and What to Test

Testing should be done whenever you make a change to website to see if that particular change will impact your business goals and to what extent.

Changes that will impact your conversion goal should be the priority to test. If your goal is to convert visitors into subscribers, then it’s only logical to test your sign up or conversion forms.

Click here to read “How to Run an A/B Test with Google Analytics”

How does Multivariate Testing Differ from A/B Testing?

A/B Testing and Multivariate Testing are practices which have only come about with the advent of image-12-walteranalyticsinternet marketing. In traditional marketing – billboard, television – it can take extended periods of time to see any real results, and these results are often not directly attributable. We’ll touch on this a bit later, but the point here is that in digital marketing, it is possible to immediately see the results of any changes made to the campaign content. You are able to see whether your audience responds better to different changes in layout, website copy, colours, animations, graphics, forms, video content and other elements.

In A/B testing, version A is the control and version B is the test. The two versions are identical in purpose except that the designs are different with the intention of testing the behaviour of users and how they react to each of the designs. The elements from control A are compared to the elements in test B. This way, you’ll have better understanding of how to optimise your pages, ads or email campaigns.

Multivariate testing is simply this same test, but with more versions and more variance.

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