This article will review A/B testing and its use in digital marketing. You can take a look at this article on setting up an A/B test campaign in Creatopy. Keep in mind that this feature is available through the Ad delivery and optimization addon, which can be acquired if you have a Pro or Plus subscription. If you wish to learn more about the characteristics of our subscription plans and available add-ons, please visit this page.
What is it?
A/B testing in digital marketing compares two versions of a creative to determine which one performs better. The purpose of A/B testing is to optimize conversion rates and improve the effectiveness of digital marketing campaigns by identifying the most effective version of a page or element. By testing just one element at a time, marketers can determine what specific changes lead to better performance and use that knowledge to improve future campaigns.
How does it work?
Start by defining what you want to achieve with your ad, whether it's more clicks, conversions, or impressions. Once you have your goals in mind, create two versions of your ad that differ in one specific variable, such as the headline, call to action, or image. Use your DSP of choice to show each ad version to your target audience to measure which performs better. You can check how each creative performs regarding clicks, impressions, and CTR during and after the test is complete from the listing area through the side-panel view. Deciding a winner requires an 85% probability of a creative winning the test in a repeated situation. So, when one of your creatives reaches 85% probability, the test ends, and that creative becomes the winner continuing to be served and running your ads. You can end the A/B test whenever you want and manually select a winner or none.
- Testing only one variable at a time will help you isolate the impact of each change and get more accurate results.
- Evaluate and prioritize ideas with the highest impact based on their potential to have a significant effect or result.
- Use the top-performing setup for non-tested elements to help maintain consistency in the campaign and ensure that it is aligned with the brand's messaging and values.
- Creating new campaigns for A/B tests is a best practice in digital marketing that can help to ensure accurate and reliable results and lead to more effective and efficient campaigns.
- Define the test's metrics and how to define success to set realistic expectations for the A/B test and measure the effectiveness of each version of the campaign consistently and objectively.
- Setting the right A/B testing budget can ensure that the test is conducted properly and that the results are relevant and helpful in making informed decisions about the campaign, which will lead to better performance and more efficient use of resources.
- Allow the test to run its course to gather reliable data and draw accurate conclusions about the performance of each version of the campaign.
- Applying new findings to existing campaigns can improve performance and more effective digital marketing strategies.
- Track and document your A/B tests to provide valuable insights and improve the overall performance of campaigns.
- Adopt an "always be testing" mindset to stay ahead of the competition and continuously improve the effectiveness of your digital marketing strategies over time.