What if you used a popular research method to optimize your marketing strategy so that it resonates with your audience? Even small changes, like rewording your headline, can make a big difference in customer engagement.
A/B testing is the process of sending two versions of the same marketing asset to two separate groups and analyzing which performs better. This ensures that your digital marketing assets have the most impact on your audience.
Through A/B testing, or split testing, you can experiment with almost any marketing element and examine the impact that a single variable has on your audience a control test, in which no changes have been made to the asset and a variable test, in which the new element is introduced. This helps you understand which ones appeal the most to your buyers and which ones turn them away.
For example, group A receives your email newsletter with the current layout, and group B receives the email newsletter with a new layout. By examining the click-through rate of each group, you can determine which layout is more engaging to your audience.
In addition to improving marketing assets, A/B testing provides valuable customer insights. Determining unique traits and buyer preferences within your audience enables you to continue tailoring and improving your marketing assets for the best results. This will make your marketing campaigns more efficient in the future, as you are already aware of what will get the best results.
In this illustration, the old version is text-heavy but still fails to hold the reader’s attention. In the improved version, based on multiple rounds of A/B testing, the copy is tighter and more engaging, the headline is stronger and an interactive poll has been added to the side.
Randomize your sample audience so it reflects your audience as accurately as possible, and make sure your sample size is large enough and your tests last long enough to be statistically significant. Exact parameters depend on several variables, but this sample size calculator can provide some guidance. Be careful at this stage, because any issues in your sample will render the results of your test null.
For the most accurate results, isolate the single variable that you are changing and only test that. If there are a number of variables you want to test, conduct a different experiment for each variable. This lets you properly gauge the effect a single variable has on your audience. You should also conduct the control test and the variable test at the same time. The goal is to eliminate all possible influence on the results aside from the variable.
Before testing, set a clear goal of what you would like to discover. Analyze the results of the test and decide if they are significant enough to adjust your strategy or if a new variable needs to be tested. Customer polls or surveys may provide further information on why something does or doesn’t work.
A/B testing lets you optimize your digital marketing assets by testing one variable at a time and applying the most successful variation to your future marketing. It also provides insights into your customers that can help you continue to tailor your marketing strategies for greater customer engagement.