Mastering A/B Testing for Your Social Media Ads

How did companies like Bannersnack increase their sign-ups by 25%, Turum-Burum boost their client’s conversion rates by 54.68%, and Clarins achieve higher basket page views and transactions, rising by 2.41% and 0.37% respectively. These companies were able to see such impactful results through mastering A/B testing in their social media ads!

What is A/B Testing on Social Media

Also known as split testing, A/B testing is when a brand intentionally tests subtle differences in their social media content to see which version yields the best results from their target audience.

Giving an example, imagine you’re a hiking boot brand running an ad on your Facebook page to promote your brand-new waterproof boots. In ad #1, your featured image is of a woman standing at the peak of a mountain wearing her waterproof boots, with your company logo at the top-right corner. In ad #2, the content is exactly mirrored, except you add the text, “Where will your boots take you next?” Essentially, the goal is to create two minimally altered versions of the same ad for two different target audiences, giving you the opportunity to see which ad performs better.

What Do You Want Your A/B Testing to Do For You?

Before running A/B tests for your social media ads, it is paramount to figure out your goals and identify what you want to see improvement in. Are you trying to increase conversion rates or decrease your bounce rates? Some other highly relevant metrics you may want to consider for your tests include:

• Click-Through (CTR): Shows the percentage of clicks on your links or, in this case, your ad.
• Abandonment Rate: The measure of users who leave your page midway through the conversion process.
• Retention Rate: The percentage of users who return to a specific page or website after a certain period.
• Revenue: Gives you the chance to uncover your customer’s buying patterns and lets you see how they respond to your messages.
• …and many more

There is no one-size-fits-all metric to test. Ultimately, whatever metrics are the most relevant to your brand’s social media ad campaign can help you and the most meaningful insights.

Interpret Your Results

Let’s return to our hiking boot example from What is A/B Testing on Social Media. After we’ve chosen what metrics we want to focus on, in our case, let’s say we’ve picked the click-through rate, and after we’ve made the two variants of our brand-new hiking boot social media ads, it’s time to run our A/B tests! Once that is all said and done, what exactly happens next?

There are three ways we can do this! They include basic analysis, secondary metrics analysis, and audience breakdown analysis.

Basic Analysis

According to Barbara Bartucz of OptiMonk, with basic analysis, you want to be certain that the results yielded from your A/B tests are statistically significant. This means that the results of your tests were not by chance and you want to see which of the two tests you ran gave you the best possible results.

Secondary Metrics Analysis

With secondary metrics analysis, you analyze more than just one metric to gain a better understanding of how your A/B testing went. For instance, if we see our click-through rate for one of our hiking ad variants (the one that had the text “Where will your boots take you next?” was low, secondary metrics analysis could allow us to see that the same ad had a lower bounce rate. This showcases that the ad variant wasn’t all for nothing and still provided valuable insights

Audience Breakdown Analysis

Lastly, audience breakdown analysis enables you to break your audience down into segments. The breakdown of your segments includes demographics (age, gender, marital status, etc.), psychographics (personality, values, lifestyle, etc.), geography (city, country, state/province, etc.), and your segment’s behavior (product use, loyalty, desired benefits, etc.). This method gives you critical insight into how these various groups within your target audience respond to your ad variations when A/B testing.

After You’ve Identified Your Results

Let’s go back to our initial goal: increasing the click-through rate for our hiking boot company’s social media ad. We’ll know if our ad variation performed well or not compared to our original ad based on our findings. If there wasn’t a huge difference between the two ads, you may choose to use your original ad’s design or keep testing other variations of the ad until you see improvements in the metric(s) you’ve picked. If however, you saw that one variation stood out to your target audience over the other, then definitely capitalize on this opportunity to promote your more successful ad variation.

What Not To Do When A/B Testing

Thus far, we’ve explored what metrics to consider before testing, how to run A/B tests, and how to interpret our results. However, there are some pitfalls that social media marketers should steer clear of. Common mistakes include:

● Not Appropriately Segmenting Your Audience: In our case, if you fail to segment your audience, you may focus on individuals who aren’t your main audience. The overall increased engagement is certainly a plus, but you may be missing out on opportunities with your intended audience.

● Forgetting to Involve Cross-Functional Departments in A/B Tests: The lack of unique perspectives on your A/B tests can lead your social media marketing team to miss out on amazing creative concepts that could strengthen your test’s overall results.

● Failing to Stay True to Your Brand’s Voice: As many brands want to increase their conversions (who wouldn’t?), it’s simple to stray from your brand’s voice. Many brands will focus solely on optimizing their content, in our case, social media ad campaigns, just to increase their conversions, ultimately getting off-course with their brand’s voice.

So, what if you do end up making one of the above mistakes? Don’t be too hard on yourself. Accept the error and use that as a learning opportunity to improve your future A/B testing.

Conclusion

Next time you’re struggling to obtain a higher CTR or retention rate, or trying to decrease your abandonment rate, consider using the magnificent benefits A/B testing can provide your brand’s social media marketing ad campaigns.

What has been your experience with A/B testing? Do you love it, hate it, or feel neutral about it? We’d love to hear your thoughts in the comments below!