A/B testing, also known as split testing, informs the social media marketer which advertisement or promotion text is more effective.  A/B testing involves comparing two versions of a social media post to determine which one does a better job in achieving an objective, which can be higher audience engagement, reach, click-through rates (CTR), conversions or any other promotional success metric.

Before addressing the step-by-step approach to A/B testing, knowing what to get out of it will enable thinking backwards from the end goal, to ensure that you get the most out of the testing process.  Are you testing for higher engagement, conversions, or another metric?  For a starting point, we will focus on CTR.

A/B testing enables greater social media impact

Why is A/B testing important for a social media marketer?  A/B testing enables data-driven decisioning over promotional effectiveness, and aims to provide a clear pathway forward to achieve better results.  It enables content creators to determine which types of content (e.g., images, videos, text) resonate best with their audiences, and by testing different variations of content, key drivers for higher engagement, click-through rates, and conversions can be better understood. 

This understanding comes from obtaining insights about your audience’s preferences and behavior.  You can test different messaging or creative approaches to see what appeals most to your target demographic, helping you refine your content strategy.  For paid social media advertising in particular, A/B testing is crucial to refining ad copy, images, targeting options, and ad formats, to ensure maximum financial return on the promotional budget.

Beyond just the financial results, A/B testing can help to optimize the user experience by testing different layouts, navigation options, or call-to-action buttons, and in this way can lead to higher user engagement and conversion rates.  Most importantly, by testing variations of landing pages or lead generation forms linked from social media, you can optimize lead generation and ultimately improve revenue from online offers. 

A/B testing is not just about format.  Timing and scheduling can also be tested, to determine the optimal times and days to post content.  This ensures that your posts reach your audience when they are most active and likely to engage.

A/B testing is an iterative process, enabling a virtuous cycle of continuous learning on the part of the social media promoter, and provides an empirical basis through which to refine social media content and promotional strategies.  Slight improvements over time can generate meaningful differences over the long run, which will give you and your business a competitive social media landscape.  Through this process, you will discover innovative approaches that differentiate your brand and messaging from others in your industry.

The steps to conducting an A/B test

1. Choose a Variable to Test:  Decide on the element you want to test. This could be the headline, image, call-to-action (CTA), posting time, caption, or any other aspect of the post.
2. Create Variations:  Create two versions of the social media post, keeping everything the same except for the variable you’re testing. For example, if you’re testing the headline, use the same image, caption, and CTA in both versions.
3. Determine Your Sample Size:  Decide how many users or followers you want to include in the test.  Ideally, it should be a statistically significant sample size to ensure accurate results.  Statistical sampling is a topic for another day, but if your audience size is small, then aim to divide the samples evenly.  Keep the variations limited and focused – but with significant differences to test – so that the outcome can be clearly understood.  If the sampling is small, then keep in mind that the results, due to random factors over which you have no control, may show a small enough difference that you cannot fully determine which version is better. 
4. Randomize the Audience:  Split your sample audience randomly into two groups.  The groups should be similar in terms of demographics and other relevant factors.
5. Schedule the Posts:  Schedule the two versions of the posts to go live at the same time. This minimizes the impact of external factors like time of day (unless you are testing for differences in posting times, in which case your promotional text would be the same, and the only variable difference is in the timing). 
6. Monitor Engagement:  Track the engagement metrics for both versions of the post. This could include likes, comments, shares, clicks, conversions, or any other relevant metrics. 
7. Analyze the Results:  After the posts have been live for a sufficient amount of time, analyze the results. Compare the performance of the two versions to see which one achieved your desired outcome. 

Improving insights from A/B testing

While the steps to conducting an A/B test are straightforward, the art is in the application of Insights and in identifying the winning elements of your test to improve engagement and results.  To enable better insights and to accurately attribute the results to a specific variable, ensure that you’re testing only one element at a time.  Testing multiple variables in one test can make it challenging to identify which element led to the change in performance.  As noted above, this is especially important if your audience size is small (less than 50 viewers). 

Conducting an A/B test is only the first step in achieving sustainable improvement over time.  A/B testing is an ongoing process.  Continuously test and refine your content based on the results you gather, and to develop a better understanding of what resonates with your audience.  By systematically testing different elements, you can refine your strategies and improve your social media engagement, reach, and conversions.

You can “up your game” with A/B testing with a broad range of testing tools.  Start with your own social media management platform, which frequently provides A/B testing features and key engagement metrics to track your success.  These tools can help you set up and manage A/B tests more efficiently.

A/B testing tools to improve analysis

Here are some tools that you may use:

• Google Optimize is a user-friendly tool that allows you to create A/B tests and multivariate tests.  The advantage of using this tool is that It integrates well with Google Analytics.
• Optimizely is a robust experimentation platform that offers A/B testing, multivariate testing, and personalization features. It’s suitable for both web-based platforms and mobile apps.
• VWO offers A/B testing and split URL testing. It includes a visual editor for making changes without coding knowledge.
• Unbounce is primarily designed for landing page optimization and A/B testing.  It offers drag-and-drop functionality for creating landing pages and experiments.
• Convert is an optimization tool that supports A/B testing and facilitates split URL testing. It also includes advanced targeting and personalization options.
• Crazy Egg is a more advanced tool for A/B testing which also provides a heatmap function and user session recordings. It’s focused on improving user experience and conversion rates.
• Adobe Target is part of the Adobe Marketing Cloud and offers A/B testing, personalization, and targeted content delivery.
• Split.io specializes in feature flagging and experimentation for software and product development. It is optimized for testing new features and changes.
• Apptimize is aimed at mobile app optimization and A/B testing. It includes support for improving user experiences within mobile applications.
• Other applications for consideration include HubSpot (own marketing platform), Leanplum (mobile-focused), Webflow (includes web design tools), Kameleoon  and Omniconvert (both with AI-driven experimentation).

The choice of the aforementioned tools will be driven by your own platform focus, as many of these are specialized for either web-based or mobile-based content.  Other key drivers are your budget, level of technical expertise and ability to integrate these with your existing platform. 

While these tools can provide insights and facilitate large scale testing, A/B testing does not require complex tools to start out, but rather, only your ability to collect and analyze the resulting data.  The power of A/B testing is taking the guesswork out of marketing decisions. Instead of relying on intuition or assumptions (which are usually good for a starting point), you make better decisions over time based on real world data, leading to more effective and efficient marketing strategies.  By systematically testing different elements of their campaigns, marketers can optimize their efforts and adapt to the ever-changing dynamics of social media platforms.