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These A/B Testing Mistakes Could Be Screwing Up Your Campaign Data

Posted by Jennifer Dragon on November 16, 2018 at 11:10 AM

AB testing messing upIn the endless quest to optimize marketing campaigns and ensure you're squeezing every drop of ROI out of your efforts, A/B testing is a must-have tool. With this approach to testing variables in marketing campaigns, brands can gain valuable insights into what works best for their customers in terms of driving engagement and conversions.

But there's a right way to conduct this testing, and there are a lot of A/B testing mistakes to avoid in the process. If you're new to A/B testing and want to make sure you're getting good data from these efforts, make sure you avoid these three common testing mistakes.

You're Testing Too Many Variables at Once

It's the biggest, most obvious mistake you can make, but it's one that businesses keep making over and over again. A/B testing only works when you're able to isolate one variable — a headline in an email, or the photo attached to social media content — and test two versions to see which one gets better results. When you change multiple variables at once, it becomes difficult, and often impossible, to attribute those differences in performance to one variable over the other.

As SEMrush points out, this mistake happens when marketers are too eager and impatient to make improvements to their campaigns. But just remember that patience is a virtue, and if you try to rush things along too fast, you'll end up ruining your data and having no insights to guide your strategy.

Plan on Multiple Rounds

Once you figure out which call to action is the most effective, move on to other variables in your ad. Run further tests to check out the background color, another for imagery and another for headline. One test will not tell you what you need to know. It's a laborious process but you really can dramatically improve results so it's absolutely worth the effort.

The Results Within the Results

It could be that you find that certain headlines, imagery, etc resonate with a particular one of your targets more than the others – this is significant. The quest shouldn't be for a one-size-fits-all approach. It's a great idea to have ads tailored to each of your audience segments. Use your A/B testing results to help segment your creative by target. You will not only learn about your ad creative, but you will also find insights that can be used in all of your marketing efforts.

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