Also called A/B testing, this is a way to optimize your marketing efforts.
It’s all about testing what works best, and testing it within an isolated environment.
A Facebook Ads-related example is creating two different posts on your company’s Facebook page, and sponsoring both with the exact same budget, at the exact same time, and targeted at the exact same audience. Here, the only thing that can affect the performance of these two ads is the content of the posts. The result will probably be that one of the posts performs better than the other. Good to know, and some potential learning in that result.
You can narrow this test down in several ways, but one is to focus on the imagery of the posts. Use the exact same copy but two different pictures. Make everything else exactly the same, as in the last test. Now, the difference between the ads will only be in the imagery, and you’ll pretty soon see which image is more appealing to your target audience.
You may also split test on audience, say by creating different age segments, different interests, different gender, and so on. But when testing on target audience, be sure to keep the ads identical, so you don’t end up with a bunch of data that can’t tell you anything. The curse of big data right there.
PS. Duplicating and hiding Facebook posts for split testing is really efficient with Fanbooster Publisher.
We’d love to talk to you about split testing, so leave your contact here, and we’ll get back to you.