A/B Testing Ideas for Paid Social Media Ads

As marketers, data should be the foundation behind every decision made for clients.  

A house can’t stand without a strong base and the same applies to a marketing strategy. Without data guiding decisions, time and money is wasted, and you’ll end up with less than desirable test results. 
 
On a web page or a landing page, it’s easy to try different colors, copy and layout to see what performs best. In fact, one of the most famous examples is when Google tried out 40 different shades of blue to land on the blue that you now see in Gmail and across its homepage.  

On various social platforms like Facebook, Twitter, Instagram and LinkedIn, you can A/B test different versions of your paid social media ads to see what resonates with your audiences. In fact, a/b testing your ads can help you make content marketing and advertising decisions in real-time! 

What is A/B Testing? 

A/B testing can also be referred to as split testing or multivariate testing. It allows you to test two or more variables and determine a winner based on an end goal, usually conversion rate. Instead of just guessing which content might perform best, A/B testing on paid social media will give you the best bang for your buck and give you insights to help shape future online strategies. 

A/B Testing Basics: 

• Before A/B testing, decide what key performance indicators (KPIs) are most important to you. By forming a hypothesis, testing it and making decisions based on statistical significance, you'll make smarter decisions related to your goals.  
• A/B test your ads by changing one variable at a time so you know what is and isn’t working. On a web page, this could be a button color, but on paid social media ads, it could be a call-to-action or click throughs from a link.  
• Retest audiences as user experience can change based on your audience sample size over time. 

Types of paid social A/B tests to try:  

Copy: This is one of the most common A/B tests and probably one of the easiest to start testing. The text in your ad is worth A/B testing as audiences will respond to varied language which means your success may vary.  

• Other copy tests to consider:
  • Post length: Shorter captions versus longer vs bullet points 
  • Post style: Which will perform better--a question? A statement? A statistic? 
  • Use of emojis 
             

Version A: 1,034 likes; 56,407 impressions

Version B: 418 likes; 16,954 impressions 

Above is an example of a/b ads and test results that we did for a client. The only thing different between these two is the text. These paid social media ads ran for 1 week with the same budget, cost per result, image and sample size. You can see how the likes and impressions of Version A outperformed Version B strictly based on copy alone. Why is that? The copy in Ad A is more focused on building rapport and community while copy for Ad B focused on the client and what they can provide to the customer. 

Images: Split testing media can also be a great way to test what visually resonates or deters your audience. For example: will ads with people in them outperform a staged or landscape image? Will GIFs perform better on Twitter than static images? Will images with brighter colors outperform those with dark colors? Which will perform better for an ecommerce paid social media ad? A single product shot or a styled shot? These are all options that you can A/B test and the data will give you more insight.  
Headlines: If your headlines aren’t attention-grabbing, your users may not even read your ad and scroll right by it. Try experimenting with active language instead of a question.   
Call-to-Action (CTA): Each ad should have only one call-to-action. Whether it’s “visit” or “shop now,” your CTA button wording in your paid social media ads is another component to test. 
Various Ad Formats: Experiment with carousel, videos, single image ads, or other formats. Different paid social media ad types will have varied results based on your target audience and the content you are promoting. 
Audience Targeting: Test a sample size by using a variety of filtering characteristics which might give you some of the best data test results. Multivariate testing on audiences might look like: 

• City/State/Zip Codes
• Countries
• Gender
• Education Level
• Interests/Hobbies
• Groups
• Behaviors 

Placement: Where will your ad appear? On a story? In the feed? On the right side bar on a desktop? 
Day and Time: When are your paid social media ads performing best? 
Device type: Any patterns here? 

A/B testing gives you the ability to experiment and optimize your paid social media ads so that you’re getting the best results and ROI possible. Remember, you should be setting a hypothesis that you can either prove or disprove based on conversion rates and your KPIs. As you continue to run A/B tests online, you’ll continue to gather more data to use in future targeting paid social media targeting efforts.