A-B testing

What does A-B testing stand for?

A-B testing, also known as split testing, refers to a randomized experimentation process wherein two or more versions of a variable (web page, page element, etc.) are shown to different segments of website visitors at the same time to determine which version leaves the maximum impact and drive business metrics.

Examples 

• Perhaps you want to see if moving a certain call-to-action (CTA) button to the top of your homepage instead of keeping it in the sidebar will improve its click-through rate.

To A/B test this theory, you’d create another, alternative web page that uses the new CTA placement. The existing design with the sidebar CTA — or the “control” — is Version A. Version B with the CTA at the top is the “challenger.” Then, you’d test these two versions by showing each of them to a predetermined percentage of site visitors. Ideally, the percentage of visitors seeing either version is the same.

• If you want to compare a set of ads using A-B testing, then you need to compare ads with similar usage for the same audience and channels.

Setting up Google Optimization

Now let’s start listening to AB tests. We will use Google Optimize.

• We created a new account. Just enter the name and accept the agreement.
• Next, we need to create an optimization project. The project is, in fact, an AB test that we are going to conduct.
• Pay attention to several options for AB tests. In the case of a simple content substitution on the page, select “A / B experiment”, but if the experiment requires the participation of a developer, you can select an experiment with redirection and use GET parameters to transfer some users to one version of the page, and some to another.
• The first thing we do is add a new option.
• Next, we need to change the page according to our hypothesis. To do this, Google Optimize has a special constructor, which is available when you click on the “Change” button.When clicked, the page editor opens, where you can change almost everything. Images, button colors, texts, blocks, etc.
• After changing the page, click “Finish” in the upper right corner.
• Now you need to set up the experiment conditions by selecting the conditions (in our case, this is a page view, but you can add additional ones, for example, going to a page with a specific UTM tag so that the test is only for visitors, for example, Google Ads). Then link your Google Analytics account (it is through this system that the effectiveness of the experiment will be tracked) and select the purpose of the experiment.
• Note that you can also add an additional target. This is very useful if you have a global goal, for example, to increase the number of orders, but there is also an intermediate one – switching to a product card, for example. In this case, you will be able to track whether the number of views of the product card has increased and whether this has a negative impact on the overall conversion to an order on the site.

Now it remains only to add a special optimization code to the site and run the experiment by clicking the “OK” button at the top of the screen.

The optimization code that needs to be added to the site can be found on the project page, which displays all the created experiments.

• In addition, Google recommends adding special code that temporarily hides the page (and displays a white screen instead) so that users do not see the substitution process. This code is not required.

The code looks like this:

<!– Anti-flicker snippet (recommended)  –>

<style>.async-hide { opacity: 0 !important} </style>

<script>(function(a,s,y,n,c,h,i,d,e){s.className+=’ ‘+y;h.start=1*new Date;

h.end=i=function(){s.className=s.className.replace(RegExp(‘ ?’+y),”)};

(a[n]=a[n]||[]).hide=h;setTimeout(function(){i();h.end=null},c);h.timeout=c;

})(window,document.documentElement,’async-hide’,’dataLayer’,4000,

{‘CONTAINER_ID’:true});</script>

Please note that you need to add it above the experiment code, and with the help of a piece “‘dataLayer’,4000” – you can adjust the number of millises.

Test results

Test results can be viewed both in Google Analytics (Behavior-Experiments), or directly in Google Optimize reports.