Before distributing your content on social media, implement stringent user testing. The A/B testing method is one of the best and easiest methods. This is when you test slight variations in your social media content by splitting your audience into two groups and showing them the same content with a different variant to determine what content best reaches your audience.
A/B testing helps determine what specifically works for your social media platforms, as it provides insight into your audience's preferences, allowing you to make more informed decisions regarding your social media content. It also helps decipher the differences between particular sections of your audience and their preferences depending on which social media platform they are following you on. A/B testing will help you better understand your followers' preferences across all of your social platforms. Additionally, using the A/B testing method allows you to use the free data that social media platforms provide to make data-based decisions, making it one of the most cost-effective ways to perform user testing.
To perform an A/B test, create two versions of one piece of content, with changes to a single variant. Release the versions to two similarly sized audiences and analyze which performs better over a specified period. The following are some variants for testing within your content:
- Text length
- Writing style
- Emoji usage
- Tone of voice
- Hashtags (multiple hashtags versus a single hashtag, which hashtags result in the best engagement and hashtag placement within the messaging, e.g. at the beginning, the end or in the middle)
- Call to action
Remember to only test one element at a time! Testing multiple elements in the same A/B test will yield unreliable results because you will not know which element had the most significant impact on your audience; however, multivariant testing is possible. The main difference is that A/B testing focuses on two variables, while multivariate is 2+ variables. Use multivariant testing only if you have significant website traffic as you need enough data to test all variables accurately.
Check with your unit to ensure there are no further local policies or guidelines for this task.
Implement your A/B test by following the steps below:
Make your goal when A/B testing your social media content SMART
— specific, measurable, achievable, relevant and time-bound. Some common goals when A/B testing are:
- Increased traffic
- Higher conversion rates
- Lower bounce rates
- Enhanced product images
Select a timeframe for how long the test will last, ensuring you choose a timeframe that will yield meaningful data. Release your A/B test at the same time of the day unless you are testing how your content reaches your audience at different times.
It is also imperative to understand your audience. Your audience cares about themselves, so make sure they are the focal point of the content you post. Some questions you can ask are:
- Does my audience prefer still images or video?
- Does my audience respond differently to different tones of voice when posting content?
- Does my audience prefer short posts or long posts?
- Does my audience respond better to hashtags over text?
Refrain from measuring what you know you cannot change or what you do not want to change in your messaging. It is critical that the metrics you choose align with a goal or mission objectives, but do not be afraid to challenge assumptions!
First, you need to identify what content element to test. Then determine what will be your control message and the message with the variant, and compose both messages.
Let's say we want to A/B test some social media content with the goal of increasing traffic to our social platforms and deciphering whether our audience prefers content with images or video. The example below shows an A/B test for image content. The first post's content is the control, which is a still image, while the second post contains a video. Notice that the only element that changes from the control to the variant is the image to video; the language of the post and everything else stays the same.
Split your audience into two same-sized groups and show one group the control message and the other the message with the variant. Manually split your audiences into two groups and release the control content to one group and the variant content to the other.
Additionally, you can use the A/B testing tools provided by the social platforms you are using. For example, Facebook Ads Manager, X Ads (formerly Twitter) and Google Ads all provide the user organized A/B testing tools to assist in splitting your audience and releasing content.
Remember, when in doubt, check with your local command's protocols. Once you post your content, it lives on the internet forever. Some bots take screenshots of every public post, so even quick deletions last forever.
Monitor how each group reacts to the messaging. Track and document your findings to determine which content approach performs better. Continue to closely monitor the data until your timeframe for the test ends. Things to monitor:
- Engagement rate
Remember that raw data itself is meaningless. Learning the basic of statistics will help you make sense of the data. Analyze the data by converting raw data into useful information, then use this information to determine whether you have accomplished your objective set at the beginning of the test. You can calculate the statistical significance to determine the results were not random. Additionally, use the information learned to make data-based decisions to optimize your social media content and strategy in the future. If you do not reach your goal, do not fret! Continue to test other variants within the content until you reach your goal.
If one variation is outperforming the other, you have a winner! Complete your test by disabling the losing variation in your A/B testing tool or disabling the post. Before disabling, make sure you are in compliance with all social media guidelines, policies and procedures. If neither variation yields significant results, the variant you tested did not have an impact, and therefore, your test is inconclusive. When this happens, select the control as the winner or run another test with a different variant. Use failed data to help you figure out a new iteration on your new test.
The example below shows how well our control post performed versus the post with the variant. The post with the variant is outperforming the control post with more likes, shares and positive engagement.
- The Control (test A) received 14 likes, 22 shares and negative-toned comments.
- The Variant (test B) received 101 likes, 209 shares and encouraging and supportive comments.
The variant clearly outperformed the control. So, moving forward, you would disable the losing variation in your A/B testing tool or disable the post and release the variant content to your entire audience.
Share the results of your tests with everyone who needs to know. This will help you create a library of best practices for your messaging. Consider creating a social media performance report
and use the data you gathered to make actionable decisions
. Additionally, update your social media strategy
with your A/B testing procedures and lessons learned as appropriate.
Don't stop here! It is essential to continue testing different elements of your content to optimize your social media messaging and maximize your social media performance. You can set a new goal, or your winning post can now be the control and you can select a different variant to test.
There are endless possibilities, but it is vital to continually test the content you share on social media. For example, you can reuse the image and post text from the variant test above and create a new A/B test to gain insight into hashtags on the same platform, such as their placement within the post or the types of hashtags used.