Before we delve into discussing how A/B testing is being used, let us, first of all, know its definition. A/B testing, which is also called split testing or bucket testing, is a method for testing which version of an ad, landing page or any other element of a marketing campaign performs better. If you must conduct an A/B test, just change one aspect of your campaign and run both variants, collecting data on performance. You can then implement the change that got better results.
You will really need A/B testing whenever tweaking an element of an online property or ad could enhance performance and aid you in achieving the campaign’s goal.
How to Do A/B Testing for Marketing Campaigns
So, how does one run A/B tests for their marketing campaigns? Here’s a basic process you can follow.
Determine which campaign elements you want to test: First, you need to make a decision on what to test. Look for landing pages, ads. Then, use web analytics and other research tools to create a hypothesis for why it is not performing well
Create two variations of that element: Immediately you decide what you want to test, choose or create the two variants. For instance, you might design two versions of a banner ad — one with an image and one without an image.
Establish a plan for measuring your results: Ensure you have a strategy in place for tracking the metrics of your campaigns. Try to figure out what indicators you’re measuring, whether that’s more sales, more newsletter signups, more comments on your Social Media posts or something else entirely.
Set a timeline for your test: Figure out how long you will run the test. Ensure your testing period isn’t too short or too long, because this can lead to inaccurate results.
Run the test: Now, it is time to run the test. Ensure you test one element at a time, so you know which element had an effect on the results.
Check your results and implement changes: Once your test has run for the predetermined amount of time, you will have your results. If your test didn’t produce conclusive results, adjust your hypothesis and run another one
Repeat the process: You can always use A/B testing over and over to continue to refine your marketing campaigns for even better performance. After your first test, run another with the next element on your prioritized list. This element can be part of the same item you just tested or part of another one. You should also repeat A/B testing as trends and customer preferences change over time
Implementing A/B Testing Results to Maximize Campaign Performance
The way in which you run your tests is crucial for getting accurate results, but what you do once you have your results is essential, too. You should implement the best-performing variant, but there are also other ways you can use your results to improve campaign performance. Here are a few tips for using your A/B test results.
Implement results across your site: Once you’ve applied what you’ve learned to the web page, email or ad you tested, try using it on other similar elements, too. If a red CTA button works better on one landing page, for example, it might also work better on another.
Track differences between audience segments: You can also drill down further into your test results to get even better insights. One of the best ways to do this is by looking at your results across various audience segments.
Use different elements across segments: Use what your tests teach you about your audience segments to create campaigns tailored to different kinds of customers.
Use results to inform future tests: Using the results of each test to perform future tests can help you work more efficiently and get better results. If you find your customers like videos, for example, you can try testing more videos in the future.
Archive your test results: Once you finish each test, make sure you archive the results in an organized way. Using a DMP can help with this. Saving this test data allows your knowledge to grow over time, helping you improve your marketing campaigns over the long term.