Digital display advertising is great. It allows you to show potential customers more than just a few words. It is this style of advertising that tends to better engage viewers. However, creating an effective display ad is not always the easiest thing to do. Sure, it has become A LOT easier to actually create the ads, thanks to the online freelance community who use sites such as fiverr.com and elance.com, but it often takes more than one version of an ad to find the most effective one. One way to go about finding the most effective ad is to test it against other versions of the same ad.
There are two common testing methods that are used religiously within the digital advertising community: A/B and Multivariate. A/B testing is pretty self-explanatory. You choose one variable within an ad, and change the way it looks, reads, or interacts with the viewer. Once you select your variable, you can run the ads at the same time, in the same places, and see which one gets more clicks. Multivariate testing, on the other hand, is the process of testing multiple combinations of variables across many ads to help produce more complex results. These tests are often run by very large companies that have the capital and manpower to create, run, and interpret the data these tests yield. For most ad campaigns, A/B testing is just as effective in determining which ad generates more interest and interaction.
When conducting an A/B test with display ads, almost every aspect of the ad can be a variable. Here are a few of the most common variables our customers use:
Ad Design: Test which colors, images, and ad size works best.
Ad Copy: Try different verbiage and style of writing.
Ad CTA: CTA or Call to Action buttons can make a big difference. Find out if position, color, and size make a difference.
Ad Targeting and Ad Networks: Use different ad networks and behavioral categories to find out where your audience is interacting with your ads.
Ad testing can be the difference between a good and a great campaign. By understanding how your audience interacts with your ads and where they interact with them, you can develop a better ad, which will lead to a better ROI. To learn more about the next step of A/B testing, the actual test, click here. In this article, Alexandria Mancini covers the actual testing process, as well as when you can expect your test to yield actionable results.
