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A/B Test

Definition

A/B Testing, also known as a split test, is a method used to compare two versions of a marketing asset (webpage, ad, email, ect.)  with one varying element, to determine which performs better. With A/B Testing, half of your audience is shown the original version of your asset (version A) and the other half of your audience is shown the modified version (version B).  As your audience is served either version A or version B, their engagement levels are measured and collected. With this data, you can determine which version performed better and make careful, informed changes to your user experiences and/or designs.  A/B testing can help you determine which words, phrases, images, videos, and other elements work best when targeting your audience.

A/B Testing Process:

1. Identify goals:

What are you trying to achieve by conducting A/B testing?  Goals can be anything from generating more organic traffic to increasing product purchases and email signups. 

2: Choose what you want to test:

Determine what single element you would like to test to see how it impacts performance.  The variable you choose to change could be related to your design, wording, or layout. Make sure you choose a variable that relates to what you are trying to achieve in your goals.  For example, if your goal is to generate more organic traffic, focus on an element that will impact SEO.

3. Create variations:

You can make your desired change using A/B testing software.  This change might be switching the background color, swapping the order of elements, or changing the headline.  Be sure that you are only changing one variable so that you can evaluate exactly how effective that change is.

4: Run experiment:

Split your audience as equally and randomly as possible.  Your audience should be randomly assigned to either version A or version B and their interaction with these versions should be measured.

5: Analyze data:

Compare the measurements of audiences’ engagement levels with the two versions to determine which performed better.  If there is a significant difference in the two versions, then take action based on your results.