What is that A/B testing?
Oh, thanks for asking.
A/B testing simply means that you create two versions of your ad, which are the exact same thing aside from one aspect. We will get to these aspects in a minutes, but just to give you an amuse bouche – it can be the text of the ad (body or headline), banner image, target audience and more.
These two ads are sent to different audiences (which we will also talk about soon), and their results help us determine which ad works better. Some sort of a digital focus group, if you will. Just to make sure it’s clear, we’ll give an example:
You have an ad, however not sure what the button should say. You and your colleagues are debating between two versions. So what do you do? Make both, of course. Then you send them to different people and see which version is more engaging and comes up with better results.
How to do it?
There are a few guidelines to do it right, in a way that will bring concrete results, which can give us essential real information for the future as well.
- One variable – the ads should be completely similar, with only one difference. This perhaps is the most important aspect of the testing. If you test both different color and text, how will you know which made the difference? Did ad A convert better than B because the text was more persuasive, or because the picture caught their sight and the liked it, and didn’t even bother to read the text?
- Audience – 5 people are not sufficient to determine what works and what not. For such a test, you need to reach a large enough audience to achieve good results. However, when doing so, make sure not to overlap with another campaign that might be live. If a person will see two different ads for the same app, the result might be biased.
- Time frame – the general conception for a test’s time frame is not fewer than 4 days, and up to 14 days. This is enough time to assess the numbers, however remember that this is only a test and not the actual campaign, so you’d want to end it in time so you can get to the real deal.
- Budget – every aspect of such a test on social networks comes with its cost. On the one hand, I would recommend not to spare in expenses to achieve the best results. However, remember it’s just a test! Save money for the real campaign you intend to run, after you have the results of you’re A/B test. The minimum amount for a split test on Facebook is $800, so you can start with that and control your expenses.
What to actually test?
Now it’s time to get serious!
Which aspects of your campaign you want to test? Here are a few possibilities:
- Ad components – you are going live with an ad – should it be red or green? Should the title say “Learn more” or “sign up”? These are aspects that can prove crucial for an ad, and you can try two versions and see which works best. However – as written before – make sure to only test one component at a time! If you are not sure about several aspects you can run multiple tests, but not simultaneously.
- Age groups – is you product better for youth or adults? You can see which age group reacts better for it with the testing. This aspect can give you also deeper insights to your product, and not only to the specific ad you are testing. Don’t forget to find appropriate age groups – don’t advertise an app for baby food to pensioners.
- States/countries – who responds better to your ad – Americans or Australians? East coast or mid-west? You can test this simply by targeting two groups who live in the different places and see which reacts better. Note! In this scenario you need to send the same ad exactly to both groups!
A/B testing on Facebook
So, you’ve decided what you wanted to test, how, created your ads and everything is ready. Now what? Facebook offers many tools to perform A/B testing, also known as Split Test. Each tool is flexible and can be used wisely and differently for any app, taking into consideration time, budget and more.
One example can be found in a recent campaign we ran in December of 2017, in which we tested the buttons. While the difference between “Sign up” vs “Learn More” may seems small and insignificant, the results were conclusive – one ad worked better than the other, and by far. Now, that does not mean the other ad was wrong, just that for this specific ad of that exact product – one CTA works better. That’s the importance of split testing.
Here are a couple of tools we regularly use when split testing on Facebook:
- Auto/Manual Bid – ever wondered which method delivers the best results? Facebook bid types allows you to test different methods of optimization. This tool enables you to decide if you want Facebook to run your ads automatically, or if you prefer to manually control them.
- Lookalike – with this advanced tool by Facebook, you can target people who are more likely to install your app. Facebook creates a broad list of potential users, based on similar characteristics to current users, and allows you to adjust the exposure percentage, i.e. how wide/narrow your targeted audience will be. You can try different exposure rates and determine which works best for you.
While the concept of A/B testing exists in digital ad marketing for many years, finally Facebook created a simple & friendly tool for advertiser to run experiments conveniently with what they call split testing.