Facebook A/B Testing

Posted by Cindy Le on

facebook a/b testing

Marketing a business in this digital age may often seem daunting, but in reality, digitization makes marketing easier than ever, especially with tools like Facebook’s split testing. Previously it was extremely difficult to analyze which of your advertisement was gathering the most profit for you, and which one needed to be stopped. Let us teach you the basics of A/B testing and how it can greatly benefit your business!

What exactly is A/B testing?

Split testing or A/B testing is a Facebook Advertising feature that collects statistics on your different advertisement tests and compares them against each other to find out which of them yielded a benefit for your strategy and which one was inefficient.

A/B testing gives accurate results and is easy to implement. Furthermore, it can be used for testing anything, whether it’s determining which images/creatives work best, to which call to action plan attracts a greater audience, etc.

A/B testing is a very important tool for marketers. It has proven to greatly increase ROI, often in the 10x range, and not only that, but it helps businesses determine what their target audience prefers to see as well as how different variations like color schemes and images affect the consumer response to ads.

Steps to take for the most successful Facebook A/B testing:

1. Test a single variable:

It is very easy to get carried away with split testing, creating vastly different ads and then comparing them to each other. That makes it difficult for you to determine which factor contributed towards the success of that advertisement.

Instead, when creating an A/B test, your ads should be almost identical to each other with the exception of one major variable. Doing so will make analyzing which creative strategy was the most successful for you, easier.

2. Use multiple ad sets:

There are two ways to place an ad on Facebook - you can either place all your ad variations within one ad set, or you can place them under separate ad set. Going the ‘separate’ route is the better choice as this gives a more comprehensive comparison which makes it easier to clearly identify which ad is more successful.

3. Use the right audience:

Ideally, you should have a large enough audience for these tests, which are demographically accurate for your marketing campaign. If your target audience is too small, you will not be able to gather the most accurate representation.

However, make sure that the audience you are using for these tests is different than your other Facebook campaigns, or it might lead to biased results.

4. Set the most accurate time duration:

When creating a split test, you must always remember that you need to give just enough time for your ad test to run so that it reaches your intended audience. But it shouldn’t carried out for such a long time that it becomes repetitive and a waste to your budget.

The ideal time duration your ad test should run for lies between 4-14 days, after which you should have enough results to make your conclusions.

5. Create a budget:

Before you start creating ad tests, allocate a proper, well-thought out budget. Ad testing can easily get very costly if it’s not handled efficiently.

Therefore, always plan ahead, and be prepared for your estimated budget to exceed as well once your ad tests start rolling.

6. Stop the losing ads:

As time goes by, you will be able to easily identify which of the ad tests are winning and which are losing. Once you have identified those, you should stop the ads which didn’t gather the success other ads did, as continuing them would just be a burden on your budget as you work to grow your business.

Keep removing the ads which aren’t winning until you end up with the final ad which performed the best in you’re A/B testing, and use your newfound learnings to strategize your future marketing strategies.

Wrapping It Up

Knowing the proper way to use the Facebook A/B testing tool can offer a lot of benefits to your growth. However, remember to be patient when it comes to collecting proper data and learning from trial-and-error.


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1 comment


  • Very cool info… more please ;)

    Dune on

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