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Jan 10, 2023 • 2 min read

5 tips to implement A/B testing in your social media campaigns

A/B testing on social media campaigns

Running A/B testing on social media campaigns is one of the most effective ways to optimize your results. Your goal with those campaigns can range from increasing visibility to driving engagement or improving customer service. A very revealing fact is that optimizing the presence in social networks helps to generate rapid and constant growth. According to a survey by Sprout Social, more than 80% of consumers would buy from the companies they follow on social media. Reason why online marketing should contemplate the networks constantly.




What is AB testing?

A/B testing, also known as A/B testing, is a technique used to compare two versions or variants of an element, whether a content, product, or service, to determine which of them offers better results. Although modern A/B testing has advanced significantly, its origin dates back almost a century.


The first documented test was performed by statistician Ronald Fisher, in agricultural experiments. However, it took several decades before marketing specialists began using these tests to evaluate and optimize direct response campaigns. In the beginning, A/B testing was manual, which involved a slow and tedious process. However, today, thanks to technology, it is possible to perform A / B tests in real time and easily, even in social media campaigns.


The main objective of A/B testing is to obtain accurate, data-driven information about which variant or version produces better results in terms of impact, response, or conversion. By comparing two variants, different elements can be measured and evaluated, such as content, layout, formatting, or call to action. And, really, any other relevant aspect to achieve the objectives of the campaign.


When implementing A/B testing in social media campaigns, it is essential to follow a proper methodology. Our first key tip is to test a single variation at a time for clear and reliable results. For example, if you want to evaluate which display and video ads generate the best results, it’s important to keep your audience demographics constant. In this way, you can identify the specific elements that impact the performance of the ads and make informed decisions based on the results obtained.


The implementation of A/B testing in social media campaigns has significantly evolved thanks to automation and the availability of specialized tools. Today, it is possible to perform these tests quickly and efficiently, allowing marketers to gain valuable insights to optimize their strategies and obtain better results on social networks.




Why should you implement A/B tests?

Implementing A/B testing in your social media campaigns offers a few significant benefits.  One of the main reasons to do this is to better understand your audience. By running A/B tests and comparing different variants, you can gain deeper insight into what type of content, tone, style, or approach resonates best with your target audience. This provides you with valuable information to adapt your strategies and create more relevant and engaging content.


As a result, by better understanding your audience through A/B testing, you can optimize your social media marketing efforts. When you identify which variants generate better results, you can direct your resources and efforts toward the most effective strategies. This allows you to maximize the return on investment and obtain better results in terms of visibility, engagement, and conversions.


In addition, A/B testing is not limited only to the content of your campaigns. You can also use these tools to evaluate products or services before they are launched. By conducting proofs of concept or prototypes, you can measure your audience’s response and make informed decisions based on the results. This reduces the risk of launching something that is not well received and helps you adjust and improve your products or services before they are introduced to the market.


A/B testing is a continuous process of optimization. Once you’ve done your first test to determine the right social networks, it’s important to keep experimenting with new variants. Your audience preferences and social media trends can change over time, so it’s critical to stay current and adapt your strategies accordingly. A/B testing gives you the opportunity to constantly improve and stay on top of your audience’s changing preferences.


Since each social media platform has its own audience and distinctive features. Our second advice is to identify where your target audience is to focus your efforts on those specific platforms. This will optimize your social media presence and help you more effectively reach your target audience.



What can be tested through A/B testing in social media campaigns

There are no restrictions on what can be A/B tested in social media campaigns. You can apply this approach to any idea, product, or service you are promoting. However, it is crucial that in each test you only vary one element at a time to gain valuable and accurate information about its impact on your results.




Let’s say you’re planning a social media campaign and want to run an A/B test to determine which text variations generate the best results in terms of engagement and response from your audience. Here are some items you could try:

  • Text length: Create two versions of a post, one shorter and one longer. Both versions must convey the same message or content, but with different length. Then, publish each variant so that it’s only visible to different segments of your audience and analyze engagement metrics such as clicks, comments, and actions taken. This will allow you to determine which text length is considered most engaging and effective for your audience.
  • Publication styles: For example, create two versions of a post with a citation style in one and a question style in the other. Then, distribute the variants among different segments of your audience and evaluate the engagement generated. See which style of post gets the most responses, comments, or interactions. This test will help you understand which communication style best suits your audience and allows you to adjust your strategy accordingly.
  • Use of emojis: Emojis can add personality and expression to your posts. However, its effectiveness varies by audience. To test its impact, create two versions of a post, one with emojis and one without. It then distributes the variants to different segments and analyzes the responses. See if posts with emojis generate more engagement or if there is a preference based on demographic segments. This will allow you to determine if you should use emojis in your posts and who they are best targeting.
  • Tone and length of sentences: You can also test the tone and length of phrases used in your posts. Create two versions that convey the same message, but with different tones (for example, one more formal and one more casual) or with shorter sentences versus longer sentences. Then, distribute the variants and analyze the engagement generated by each one. This will help you understand which tone and sentence length resonates best with your audience.

Remember that it is important to keep only one item at a time in each A/B test. This way, you’ll be able to pinpoint which specific variation is responsible for any differences in results. Analyze the data and metrics collected during the test to make informed decisions about which approaches and text elements work best for your audience.




Let’s say you’re planning a social media campaign and want to run an A/B test to determine what type of visual content generates the best results in terms of engagement and response from your audience. Here’s how you might run an A/B test of visual content:

  • Comparing different images: To get started, select two or more different images to test in your posts. They can be regular images, infographics, GIFs, or other formats. Create different versions of your posts, keeping text and other elements constant, but changing images. Then, distribute these variants to different segments of your audience and analyze the engagement generated by each one. See if any particular magic generates more interaction, clicks or comments compared to the others. This will provide you with valuable insight into what kind of visually appealing images your followers prefer.
  • Experiment with different video elements: If you plan to use videos in your campaign, you can run A/B tests to determine which video elements have the greatest impact on engagement. For example, you can try different video lengths, from short clips to videos plus thergos.

Remember that each A/B test should keep all other elements constant, such as the text, the call to action, and the target audience. In this way, you will be able to identify precisely which specific variation is responsible for any differences in the results.

It’s important to note that although generally visual content, such as images and videos, tends to perform better than written content, this can vary depending on the audience. Therefore, our third piece of advice is not to take anything for granted. A data-driven approach through A/B testing is always preferable to making assumptions.




If you’re using different ad formats, such as still images, short videos, or carousels, you can run A/B tests to determine which one generates better results. For example, create two  identical ad versions, but with different formats. Then, show these variants to segments of your audience and analyze the performance of each in terms of clicks, impressions, conversions, or other relevant metrics. By now, you will have seen that the way of carrying out the test is always the same, although the elements vary.

Another variation you can try is ad copy. Experiment with different writing approaches, calls to action, and key messages in your ads. Create two versions of ads, keeping all other elements constant, but changing the copy. This test will allow you to understand what type of message and wording resonates best with your target audience .



Target Audience

If you have detailed demographics about your audience, you can run A/B tests to determine how different demographics respond to specific content. For example, create two versions of a similar post but targeting different demographics. Analyze the performance of each variant based on the response of each demographic. This will help you identify which content is most relevant to each group and allow you to tailor your campaigns to be more effective and personalized.

Another option is to test how your audience’s different interests or behaviors influence their response to a particular piece of content. For example, if you’re promoting sports and fitness-related products, you can create two versions of a post and target audience segments with different related interests, such as running or yoga. See which segment responds best and tailor your future campaigns to focus on the interests that drive the most engagement and conversions.




Our fourth tip is that, regardless of what you are going to try, always segment your audience. Thus, the data you obtain will be much more accurate and, therefore, more useful.

And the last tip is, if you are not familiar with A/B testing, it is advisable to seek the help of professionals who can guide you in the design and application of these tests in your social media campaigns. At Ideafoster, we will be happy to help you through this process.




Practical Example of A/B Testing in Social Networks for physical products

To illustrate even better how A/B testing works on social networks, let’s study a concrete (and absolutely fictitious) example related to a fictitious company called EcoFit. We will see how to follow many of the best tips we recommend to do your A/B tests.

EcoFit is a sportswear brand that sells its products mainly online. Your marketing team uses social media to promote your products and generate sales. They are interested in optimizing their Instagram posts to increase engagement and ultimately conversions.



Step 1: Define the experiment

To achieve their goal, they have decided to carry out an A/B testing to evaluate how the use of hashtags influences the interaction of their audience with publications. Its objective is to determine what type of hashtags generates greater participation by followers, specific or generic. We see, then, that only one element varies and that the entire A/B test will be carried out on that element.

  • Variation A: Use of Generic Hashtags: EcoFit creates posts on Instagram using generic hashtags related to sportswear and fitness in general. For example, #Fitness, #ModaDeportiva, #Salud, etc. These hashtags are widely popular and are used in a wide variety of sports-related publications.


  • Variation B: EcoFit decides to use brand-specific hashtags that they have created themselves, such as #EcoFitRun, #EcoFitStyle, and #EcoFitHealthy. These hashtags are designed to highlight the brand’s identity and its focus on sustainable sportswear and healthy lifestyle.


Step 2: Audience segmentation

To ensure accurate results, EcoFit decides to segment its audience into two groups, Group A and Group B. Each group is made up of followers with similar demographics, common interests, and previous levels of interaction with the brand that are also common.



Step 3: Run the experiment

For one month, EcoFit implements its A/B test to evaluate the impact of using generic and brand-specific hashtags on its Instagram posts.

Each post, reel and story is carefully scheduled to be published at the same time and day of the week for both groups, ensuring comparable conditions in terms of publication schedule and content.

Throughout the month, EcoFit meticulously records metrics such as likes, comments and shares on both variations. This will provide solid data to determine the effectiveness of each hashtag strategy on engaging your audience. This meticulously planned trial period will allow EcoFit to make informed decisions on  how to adjust its hashtag strategy to optimize its brand engagement and visibility on Instagram.



Step 4: Analysis of A/B testing results

EcoFit will analyze your A/B test results on hashtag usage as follows:

  1. Comparison of key metrics: including likes, comments, and shares in both variations (generic hashtags vs. brand-specific hashtags).
  2. Meaningful statistics: The brand will use data analysis tools to determine if differences in metrics are statistically significant. This will help discern whether the observed results are the result of a true difference in hashtag strategy or whether they could simply be random.
  3. Evaluate Total engagement: EcoFit will calculate the total engagement obtained in both variations during the trial period. This will include the sum of likes, comments, and shares in each group.
  4. Performance comparison by metric: this will allow you to identify if one hashtag strategy generated a higher number of likes, while the other had more comments, for example.
  5. Analysis of qualitative feedback: The company will pay attention to the feedback received in both variations to assess the quality and tone of the interaction. Qualitative comments provide valuable insights into how the audience responds to posts and hashtags used.
  6. Impact on audience growth: It will also be considered whether the use of generic or brand-specific hashtags had an impact on your audience growth during the trial period.
  7. Trends Throughout the Month: EcoFit will look at trends throughout the month, looking for possible changes in the effectiveness of hashtag strategies over time. This could reveal whether a strategy became more effective over time or whether its effectiveness decreased.



Decision making: the final step of A/B testing

Based on all these analyses, EcoFit will make informed decisions about whether to continue using generic, brand-specific hashtags, or a combination of both in its Instagram strategy. You could also decide to adjust the usage ratio of each hashtag type based on the results.

Of course, here is a final conclusion that emphasizes the complexity of the process of A/B testing in social networks and the recommendation of having professionals like Ideafoster



Conclusion: The Importance of Having a Professional A/B Testing Partner in Social Media

Throughout this practical example of A/B testing in social networks, we have analyzed the meticulous process that a company should follow to improve its strategy on Instagram. From the definition of the experiment to the segmentation of the audience and the careful execution of it, it is clear that A/B testing is a tool as powerful as it is complex.

Analyzing results, interpreting metrics, evaluating meaningful statistics, and making informed decisions all require knowledge and expertise in data analysis and digital marketing. This is where the direct help of professionals like Ideafoster can make all the difference.

The complexity of the data collected and the need to discern between meaningful and random results make having A/B testing experts critical. Ideafoster gives you the knowledge and experience to conduct effective A/B testing, interpret the results, and apply the findings to your social media marketing strategy. Contact us!

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