What is A/B or split testing?
A/B testing or split testing, as it’s also known, is a great way to take the guesswork out of your digital marketing efforts.
Split testing, commonly referred to as A/B testing, allows marketers to compare two different versions of creative, such as advertisements or landing pages for example. The two versions are the control (the original) and the variation — to determine which performs better, with the goal of boosting conversions or the desired objective.
Why perform A/B or split testing?
By doing this we allow for carefully thought out tests or hypotheses for our advertising creative or our website to learn more about our audiences and user behavior and to be able to speak to them with relevance.
The ad layout within Google’s platform gives a lot of opportunity for testing and optimization: headline (1 or 2), description, path (1 or 2), landing page, CTA, prices, offers, etc.
Before you can start testing, you need something specific to test. We recommend that you start small. Once you’re comfortable creating variants and experiments, you can expand the scope of your testing. You can perform A/B testing not only just on the ad units in Google Ads but on your website and landing pages.
Before creating your first experience you need to identify a problem, then create a hypothesis (backed up by data, of course) about what you can alter to improve it.
What’s the problem that you want to solve? Have conversions dropped off? Has your traffic patterns changed? Has your demographics shifted? A close examination of trends in your Google Analytics behavior reports is a great place to start.
Once you’ve identified a problem, solicit opinions from people you work with or clients that you have a good relation with about the cause of the problem. Use this feedback to form your hypothesis, an educated guess that you’ll validate or invalidate with experimentation.
“Changing the color of the ‘Add to cart’ button from blue to green will increase revenue by 10 percent.”
After you’ve identified a problem (low conversions), and worked on a hypothesis (changing the button color) you’re ready to test your hypothesis on your website.