1. What is A/B Testing Facebook Ads?

In other words, you essentially set aside your gut feeling as to which kind of creative, ad copy or targeting will work for your Facebook ad campaign and let the audience decide instead, based on their reaction and feedback. Rather than choosing to show your audience a video ad over an image ad because, well, everyone out there claims that videos are trending now, you put both versions in front of them and see how they respond to them after a certain amount of time.

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The purpose of A/B testing your Facebook ads is not only to increase your conversions by using the best performing version, but also to gain valuable insight into your potential buyers’ behavior and use this insight across all your other marketing campaigns. 

2. Which Elements of Your Facebook Ads Should You A/B Test?

Theoretically, you can test any element you want, from the color of a CTA to audience age or gender. It all depends on your hypothesis – that is, the conversion problem you’ve identified, the potential solution you have come up with and how that change would positively impact the conversion problem.  

Suppose you have identified that your ad has a high impression rate and therefore the click-through rate is low. As a result, you build a hypothesis which states that if you change your CTA text, the CTR will increase. Now you need to test and validate this hypothesis, don’t you? To achieve this, you A/B test one variable – CTA copy – while leaving all other variables the same. If the second version of the CTA wins over the original one, then your hypothesis is proved to be true. 

You might choose to A/B test your Facebook ad campaigns from the very beginning, when you’re yet to have any real idea as to what best resonates with your audience in general. Therefore, every ad campaign you run can be A/B tested – you can test audiences, ad copies, ad formats or ad designs until you find your winning set of variables. 

The split testing elements fall under the following categories: 

• Creative (variables to test: ad design, headline, ad copy, CTA copy or design, etc.)
• Delivery Optimization (variables to test: delivery optimisation type, bid strategy or delivery type)
• Audience (variables to test: audience age, gender, interests, saved audience vs custom audience, custom audience vs lookalike audience, etc.)
• Placement (variables to test: automatic placements vs edit placements, desktop vs mobile, etc.)

Here are some A/B testing ideas for you to get inspired and start your next test.

 13 Smart Ways to Split Test Your Facebook Ads 

3. How to A/B Test Facebook Ads – Manually or Automatically? 

Not long ago, when Facebook ads were just picking up steam, advertisers had no other option when it came to A/B testing than to do it manually. They would manually duplicate the control ad multiple times, just changing one variable, and then check the metrics like conversion rate, CPA or ROAS to determine which version performed best.

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Understandably, manual A/B testing had its limitations; apart from being time-consuming and messy, there was also a risk that audiences would overlap, thus skewing data. In later years, some tools were created which solved these limitations and automated the whole process. In 2017, Facebook also natively released its Split Testing feature to allow advertisers to accurately test different components of their campaigns and obtain easy-to-understand results.

Now you can select which ad element you want to split test, then you are prompted to test up to 5 versions of your chosen variable, schedule your test duration and, at the end, obtain an accurate report on the test performance. To conduct accurate tests, Facebook organizes the structure to be one ad per ad set so that the audiences do not overlap and provides an option to choose between even split and weighted split of the budget.

4. When Should You Start to A/B Test Your Facebook Ads?

You can start A/B testing your Facebook ads at any time, whether you’re just starting your business promotion and want to collect as many insights as possible or are stuck in the middle and want to improve your results. 

5. Should You Test One Variable at a Time or Conduct Multivariate Testing?

All sources recommend that you test one variable at a time when A/B testing Facebook ads. Even Facebook’s native split testing tool doesn’t allow you to select more than one variable when testing: for example, you can’t test both creatives and audiences within one campaign because you won’t be able to figure out what change affected the results. However, you can test up to 5 versions of the same variable. 

But what if you’re ready to launch yourself into more complex experiments and want to test all combinations of audiences, creatives and placements within one campaign? While it would be a real headache to run multivariate testing on Facebook Ads Manager, there are some easy-to-use third party tools out there like Adscook that resolve this issue. 

Adscook’s A/B testing feature allows you to conduct multivariate testing with ease. You can use all combinations of audiences, ad images, copies, devices, etc., and find the best converting ads. Let’s say you want to test two different audiences, three different creatives and two different placements – 2x3x2. Adscook will automatically generate 12 ad variations using all the possible combinations and help you find your best-performing set of variables. Want to see it in action? Sign up now and start 30-day free trial with Adscook.

6. What’s the Ideal Budget for Facebook A/B Testing?

The budget for your A/B testing campaign largely depends on how many versions you are testing. The more versions there are, the more budget you should allocate because you will need a sufficient number of impressions and conversions to determine the winning ad. 

However, if you’re just starting out and don’t yet have enough data, you can always call on Facebook and use the recommended budget it provides. 

But if you want to take control of your budget, here is a simple formula to help you calculate your ideal A/B testing budget:

Average CPC x No. of Variations x Conversions Needed

Suppose that your product average cost per conversion is $5, your number of split testing variations is 3, and your number of conversions needed is at least 50-100 per ad variation. This gives the following result:

5 x 3 x 100 = 1,500

In this case, you’ll need a budget of $1,500 to run a successful A/B testing campaign. If you choose to spend your budget daily, it will be spread across the number of days you have set. For example, if you’ve set the duration at 10 days, your daily budget will be $150.

7. What’s the Ideal Time Frame for Your Facebook A/B Testing Campaign?

The recommended time frame is at least 1 day and no more than 30 days because one day is not a sufficient amount of time for Facebook to learn the data and come up with conclusive results, while 30+ days would simply be a waste of your budget as it is more than enough time for Facebook to identify the winning version and conclude the testing.

If you’re not sure about the ideal duration for your A/B testing, it’s always safe to start at 4 days. However, it all depends on your business and audience size, so think about your own circumstances carefully and don’t just blindly follow this recommendation if you know that the buying process for your product is longer.

8. What’s About Audience Size?

Another question linked to Facebook A/B testing is how large your audience should be in order for your campaign to run successfully. If you are targeting a very niche audience, such as women aged 25-30, living in London and interested in luxury jewelry, your audience might be very small if you were planning to conduct many tests.

You need to remember that the audience is split among all versions and if it’s too small, the reach will be low and the spend will be high accordingly. In this case, therefore, avoid testing many versions, or otherwise increase your audience size for more effective testing. As a rule of thumb, an efficient size per audience is between 200k-1MM. 

Another thing to keep in mind is to make sure not to use the test audience in other campaigns so as to avoid audience overlap and gain accurate results.

9. How is the Winning Ad Set or Ad Determined?

Facebook determines the winning ad or ad set by comparing the cost per result for each one based on your campaign objective. It also provides a confidence level that shows how likely it is that the ad would perform in the same way if you ran the test again. Therefore, the cost per result and confidence level combine to determine the winning version. 

If you’re using Facebook’s Split Testing tool, you will see the test results in the Ads Manager reporting table; the winner will have a star icon next to it. You will also receive a report via email, which details the results (the number of times your ad set or ad got the result associated with your campaign objective), cost and amount spent.

10. What Actions Should You Take after Reviewing the Facebook A/B Test Results?

So, you’ve successfully split tested your ad campaign and determined the winner, but now what? What are the next steps to help you to get the most out of the testing results? Here are some post-testing strategies that will help you further improve on your results and reap more benefits.

#1. Reactivate the winning ad

Once the winning version is determined, the campaign stops running and so too does your winning ad. You can reactivate it straight from Ads Manager, but be aware that Facebook will restart its learning phase if you keep the ad paused for longer than 7 days.

#2. Create a new ad from the winning ad set with an increased budget

This is one of the most successful Facebook ad scaling tactics. However, make sure to avoid making big budget increases; otherwise, this will cause an ad set to re-enter the learning phase. It’s advisable to increase your budget by no more than 15%-20%. You can even go further and make incremental increases every 3-4 days.

#3. Continue testing to refine your advertising strategy further

Let’s assume you were A/B testing an image vs video and the video emerged as the winner. Now you can narrow down the testing within the video, for example by testing the video value proposition, its CTA and so on. You can target the same video at different audiences to see which best resonates with your video, or test it on different placements. There are plenty of ways to play around and experiment with testing and hit the bullseye.

Final Thoughts

We hope this post answered your basic questions on Facebook A/B testing and will help you take your experiments further. 

Do you have a specific question that we haven’t addressed here? Please feel free to share it with us in the comments below. 

The post How to A/B Test Facebook Ads in the Right Way appeared first on Adscook Blog.

Split tests answer your questions using data rather than guesswork and provide you with new, sometimes unexpected insights that can improve your overall marketing strategy.

Set an image against a video and see how your audience responds to each one, or test whether your product resonates better with a male or female audience.

Whatever you choose to do, there are so many aspects of Facebook ads that can be tested and improved. 

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Are you short of ideas when it comes to Facebook A/B testing? If so, we’re here to equip you with a list of ideas, ranging from target audience to ad design and beyond. You could test one idea out at a time or embark on more interesting multivariate testing and try different combinations all at once. 

Facebook Split Testing Ideas for Your Audience

Can you ever be 100% sure that you’ve found your ideal audience and that this audience is what dictates your advertising strategy in all respects? Finding your ideal audience is an ongoing process and if you ever stop testing, you’re simply passing up an opportunity to delve deeper and find a hidden treasure.

Here are some ideas to help you test your audience and find the most profitable one.

Audience testing is conducted on ad set level either manually or automatically with Facebook split testing or a third-party tool. 

1. Split Test Two or More Interests/Demographics/Behaviors

Is there an aspect or characteristic of your target audience that you’re not sure about and want to test?

As an example, let’s look at the age range of your audience. You can create up to 5 audience variations changing only the age variable while leaving the other variables the same.

Play the same way with other aspects, like gender, location, interest, relationship status, or behavior patterns, and gradually you’ll manage to narrow down your ideal audience type.

Perhaps you’ve already defined two or more buyer personas for your business and now want to check which group  your product resonates with most? This is where split testing comes in.

Create two or more cold audiences that are relevant to your buyer personas in terms of demographic and interests and set them against each other to determine the winner.

By doing this, you’ll be able to make data-driven decisions and distribute your efforts accordingly, whether that means increasing your budget for the winning buyer persona, improving product features for that specific group, or indeed anything else.  

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Adscook provides an easy-to-use and flexible multivariate A/B testing feature that will save you valuable time and help you organize your work. Instead of having to manually change one audience variable every time, you can now set all variations (locations, languages, age, gender, or interests) within one window, and create all possible combinations. Join Adscook now and publish 100s of variations with a single click.

2. Test Different Custom Audiences

Custom audiences are by far the best-performing audience type as they include people who have already interacted with your brand in some way or other – perhaps they  visited your website, subscribed to a newsletter, added a product to their cart, made a purchase or just liked your Facebook page.

Custom audiences are also the most cost-effective.

Attracting a new customer is five times more expensive than keeping an existing one. 

You can create a custom audience by using different sources like your website, customer list, app activity, Facebook page likes or video views. This variety makes it possible for you to experiment with multiple retargeting tests.

• Test the audiences of specific web pages – some pages on your website may be almost equal in value and A/B testing their viewers may offer you valuable insights into your business and lead to better results in the future. For example, if you sell software products, you can split test viewers of your pricing page vs viewers of your case study page or if your business is in  ecommerce, you can experiment with the audience for your wish list vs the audience for your add to cart. If you want to gain valuable insight into your content, go ahead and split test by topic or compare your gated content pieces to determine which one performs best. 

• Split test different customer segments – depending on your business type, you’re likely to segment your customer base. Imagine that a new product category is added and you want to test your customers’ reaction first. The best way to do this is by showing the same ad to different customer segments and measuring the results. 

• Split test video viewers – Facebook also allows you to create custom audiences from video viewers on Facebook or Instagram. You can take advantage of this feature to try different options. Retarget and split test the viewers of different videos on your Facebook page or split test people who have watched at least 25% of your video vs people who have watched at least 95% of it. 

3. 1% vs. 5% vs. 10% Lookalike Audiences

When creating a lookalike audience, you can select an audience size ranging from 1% to 10%, where 1% consists of people who are most similar to your existing customer base. As the percentage increases, the audience becomes broader.

If a 1% lookalike audience is most likely to buy from you, then why test it versus broader audiences, you might ask? The reason is that, if used very frequently, your most similar 1% audience might get exhausted and begin to show declining results. If this happens, you can then start experimenting with broader audiences.

Facebook Split Testing Ideas for Your Ad Creative

Ad creative is the most fun part of your Facebook split testing. You can’t make just one video or write just one passage of ad copy and then sit back and wait to see amazing results – there’s always a better design and better copy that might beat your previous results. That’s why, when it comes to ad creative, you should always split test two or more versions. Here are some ideas to help you get started.

4. Test Single Image vs. Video  

Everyone is now talking about the indisputable  advantage of video ads compared to other formats. But does this mean that you should automatically use video ads without a second thought? No – you can’t prove that this is the right strategy for your business until you test it for yourself. You can show both a single image and a video with the same offer to your audience, compare the results and then establish which one works better for your product. 

McDonald’s experiments with single image vs. video testing while keeping its ad copy the same.

5. Test Single Image vs. Carousel Ads

While a single image allows you to show one shot of a product, multiple images let you tell a story and show the ins and outs of the product and its different uses.

eBags split tests its Mother Lode Weekender bag with a single image and a carousel ad showing the bag’s pockets, flexible ways of carrying it and other storage capabilities. 

6. Test Long Video vs Short Video  

Video length matters. If you show your audience both a long and a short video and then compare the results, you’ll gain some valuable insights into your audience’s attention span.

Here’s another example from eBags – one video explains all the aspects of the carry-on, like a laundry bag or wet/dry cubes, while the other focuses solely on its USB port. 

7. Test Ad Copy with Numbers vs. No Numbers

Using numbers in your ad copy can add credibility to your words and make the ad easier to digest. So, it’s worth testing this hypothesis and running an A/B test with numbers vs. no numbers.

Here’s an example from Zendesk, where one version of the advertising copy stresses the fact that a CSAT score of 95% can be achieved with Zendesk.

8. Test Different CTAs

As you know, when creating an ad creative, you’re prompted to choose from a list of CTAs, from the general, such as ‘Learn More’, to more specific, like ‘Book Now’. What sort of CTA will work best for your business and help you to generate more clicks? Should you just stick with one standard ‘Learn More’ CTA and not try any others? It’s a better idea to test all CTAs relevant to your offer and optimize your CTR.

Here’s an example from IPSY with ‘Learn More’ and ‘Sign Up’ CTA variations:

9. Ask a Question vs. Make a Statement

Should you use a question mark or a period in your ad copy? Question marks have already proven to be quite effective in advertising, as they question the problem faced by the audience and seek to solve it. But does this mean that you should give up on statements? No, because it’s perfectly possible that your audience will gravitate towards statements rather than questions. Split test your ad copy to check the hypothesis.

Here’s an example from HubSpot:

10. Test the Headline With and Without the Word “Free”

How powerful is the word “free” when it comes to Facebook advertising? People usually love free stuff so may instinctively click on ads that mention free products or services, but it’s possible that your target audience won’t necessarily trust someone who sells free things. So, to eliminate any guesswork, go ahead and A/B test your ad headline with the word “free” and without it. 

Here’s an example from HubSpot, advertising their free CRM. 

Facebook Split Testing Ideas for Your Ad Placement

Do you give equal time to each social media platform? Do you like to use all of the available platforms? Probably not. You might browse Instagram more often than your Facebook feed, or perhaps you prefer scrolling through your Facebook Mobile Feed rather than your Desktop Feed. Take all of this into account when advertising on Facebook and test which platforms your target audience likes to use most. There’s always hidden information just waiting to be discovered! 

11. Test Automatic Placements vs. Edit Placements

Facebook’s algorithm is becoming smarter every day, and it already has enough data to automatically put your ads in the places where they’re likely to perform best for your target audience.

However, if you know your audience inside out, down to the detail of the places they view most, you may feel a little skeptical about automatic placement. Just to end your doubts, you can A/B test your ads with automatic placement vs. choosing the placement yourself. 

12. Test Different Platforms

When advertising on Facebook, the following four platforms are available to you: Facebook, Audience Network, Instagram and Messenger. Each platform has its own relevant placements. To get a better idea of where your audience is most active, we suggest that you run tests on different placements and then use the results to determine where to allocate your budget. 

13. Test Different Devices

On Adscook, we also offer A/B testing for iOS and Android devices. This could be a great idea if you’re advertising an app and want to find out whether your best performing audience uses iOS or Android. 

To Sum Up…

A/B testing your Facebook ads is a must if you want to move to the next level and enter a more data-driven world of advertising. The list we’ve provided here is a great starting point – take an idea or two and start experimenting. 

If you already have experience with A/B testing, go ahead and share it in the comments below. We’d love to include it on our list. 

Haven’t tried multivariate testing yet? With Adscook, you can use all combinations of audiences, ad images, copies, devices, etc., and find your best converting ads. If this sounds interesting to you, come join Adscook and get 30-day free trial.

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