A/B Testing – Process
A/B Testing comprises of a set of processes that one must follow sequentially in order to arrive at a realistic conclusion. In this chapter, we will discuss in detail the steps of A/B Testing process that you can use to run tests on any web page −
Background research plays a critical role in A/B Testing. The first step is to find out the bounce rate of the website. This can be done with the help of several widely available background research tools like Google Analytics and others.
Data from Google Analytics can help you to find visitor behaviors on the websites. It is always advisable to collect enough data from the site. Try to find the pages with low conversion rates or high drop-off rates that can be further improved. Also calculate the number of visitors per day that are required to run this test on the website.
Set Business Goals
The next step is to set your business or conversion goals, which will help in understanding what the objective is. Once that is done, then you can find the metrics that determine whether or not a new version is more successful than its original version.
Once goal and metrics have been set for A/B Testing. The next step is to find ideas on how to improve the original version and how to make it better than the current version. Once you have a list of ideas, prioritize them in terms of expected impact and difficulty of implementation.
For example, one of the most effective thing is to add images to a site, which will help in reducing the bounce rate to some extent.
There are many A/B Testing tools in the market that has a visual editor to make these changes effectively. The key decision to perform A/B Testing successfully is by selecting the correct tool. Some of the most commonly available tools are −
- Visual Website optimizer (VWO)
- Google Content Experiments
There are different types of variations that can be applied to an object like using bullets, changing numbering of the key elements, changing the font and color, etc.
Running the Variations
Present all the variations of your website or app to the visitors. Their actions will be monitored for each and every variation. Furthermore, this visitor interaction for each variation is measured and compared to determine how a particular variation performs.
Once this experiment is completed, the next step is to analyze the results. A/B Testing tool will present the data from the experiment and will tell you the difference between the performance and efficiency of different versions of a web page. It will also show if there is a significant difference between variations with the help of mathematical methods and statistics.
For example, if the images on the web page have reduced the bounce rate, you can add in more images to increase the conversion. If you see no change in bounce rate because of this, go back to the previous step to create a new hypothesis/variation to perform a new test.