How A/B Testing Works
A/B testing involves creating two versions of the same marketing content that differs by just one variable. Marketing content that can be tested includes:
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The different content is then displayed to different groups and their behavior is analyzed. Based on that information, content can be changed to increase conversions or participation with the brand, the content, or the website.
Changes can include the design of a landing page, the call to action, or the content. It is important to change just one thing at a time, to determine what is changing the conversions.
Benefits of A/B Testing
A/B testing takes time, but it is relatively affordable, and it ensures website optimization and marketing tactics come from data-informed decisions. By measuring the actual impact of the changes during an A/B test, marketing strategies can be used that will boost instead of hinder engagement.
A few examples of the benefits of split testing include:
- Testing different blog titles can increase the number of people who visit the site.
- Testing different CTAs can increase the number of people who click on them.
- The bounce rate can be reduced by modifying the appearance and functionality of a website
- A different approach to product descriptions may be able to lower cart abandonment at an e-store
Even failed A/B testing can influence the marketing strategy. They can reveal things that are done right in the current website copy, and they can provide future tests with various variables that can be changed.
Tips for conducting split testing
Choose a marketing area that will provide the most insight. For example, a high traffic area with a high bounce rate is a good place to start because it will generate a lot of data. Decide on the changes that will be made, and identify the type of data that will be collected to know if the changes are successful.
In order for split testing to be successful, only one variable should be changed at a time. It ensures that the one specific change can be measured and its impact determined. For example, when testing a different landing page color, the content on both landing pages should be kept exactly the same. Once an effective color has been identified, a new A/B test can be created that involves keeping the landing pages the same color, with a different call to action used on each page. Make sure there is a plan in place to analyze the results of A/B testing. Software makes crunching the numbers easier, and it can determine if there is a statistically significant difference between the two tested items.