You already know that social moves fast. What worked for your brand a few months ago may not be relevant today. This is why social media managers thrive when they embrace a mindset of continual learning and development. Improving your social media marketing strategy requires frequent reevaluation and iteration, and running social media experiments is an essential part of the process.
Whenever you have a hypothesis, question or challenge related to your social media marketing strategy, social media experiments can provide actionable next steps. Their results provide concrete evidence to support your case for more resources or reasoning behind switching up your current content.
Social media experiments not only challenge your current strategy, but can also open opportunities to try something different—such as a new social media network or feature—and determine if it’s effective for your target audience. Experimentation can also reveal faster ways to reach your goals, help you avoid costly mistakes and uncover new information about your audience.
Grab your metaphorical safety goggles, lab coat and test tubes because in this article we’re going to walk through the steps for running and measuring successful social media experiments.
With these seven steps, you’ll be testing on social media with ease in no time:
Before you begin, you’ll need a basic understanding of the following:
Prioritize a hypothesis that will result in the biggest impact on your team’s top-level social media goals. Avoid running several tests at once because it can lead to inconclusive results, especially if you’re focused on managing organic social.
If you’re using Sprout, you can learn about your audiences and performance by channel through our cross-network reports (like the Post Performance Report) or competitor reports (like the Instagram Competitors Report).
To dive even deeper into understanding your audience, use Sprout’s Advanced Listening tools. With Listening, you can build queries to track and analyze social conversations, pin down trends and view consumer sentiments. Seeing the data behind what your audience is talking about and the content they engage with will help you formulate a hypothesis.
Now that you have a hypothesis, it’s time to select the type of social media experiment you will conduct to prove your theory.
There are two main types you can choose from: A/B testing and multivariable testing.
One of the most common types of social media experiments, an A/B test is an experiment where you change only one variable and keep everything else the same. These types of tests are an excellent way to pinpoint improvements that will make a measurable impact. Some common A/B tests on social include:
For example, if you wanted to test which content type is the most engaging on Instagram Stories, your team could test photo content against video content. The content type would change, but you would use the same caption and post at the same time and day of the week, one week apart.
Using Sprout, the Atlanta Hawks‘ social team tested a casual approach to videos at community events. A player shot a hand-held video that was compared to the performance of more produced social videos. The casual video format proved to be more successful and sharing the performance data was a major win for the social team.
As its name implies, multivariable testing alters two or three variables at once. However, since you’re experimenting with more elements, analyzing and interpreting data can be harder. You’ll also need a large audience to avoid skewing the test.
Some multivariable tests include:
Sprout’s social team conducted several multivariable tests to help develop our TikTok marketing strategy, as you’re about to read in the next step.
Establish the key metric you want to measure successful content against. This can include impressions, traffic to a particular page such as your brand’s website or a gated resource, and engagement metrics (Think: likes, clicks, comments or shares).
The channel you choose to conduct your experiment will depend on what you’re testing and the social media network you use the most to post that kind of content. Use your network-specific data to inform this decision. Read some of Sprout’s Insights resources to learn which content types perform the best on which platforms.
When our social team started testing TikTok, the main goal was to increase awareness among our target audiences. Accordingly, we selected impressions, video views, profile views and audience growth as key performance indicators.
Don’t fall into the common mistake of not defining a time frame for your social media experiment. Remember that social media strategy is a long game–give time for new initiatives to grow and develop.
Your reporting window depends on your budget, audience size and KPIs, but the most important factor is to reach statistical significance.
Statistical significance refers to the likelihood your test results are the outcome of a defined cause and not chance. To reach statistical significance, you’ll need a large sample size and a control. For example, a sample size of 1,000 is stronger than 100, and your control would be the piece of content you do not change.
Set a duration and look for statistical significance. What are the significance changes? After your testing period, consider optimizing content that didn’t work during that timeframe instead of hitting the breaks on posts that aren’t resonating immediately.
While experimenting with TikTok, the social team reported results after four months since there was enough data available to analyze. They also set a weekly update to our internal social dashboard to continue testing and learning, along with iterating strategy, if needed.
During the first four months, we discovered views for every TikTok remained consistent, with an average of 535 views per video. We were also able to confirm our thoughts/assumptions about the For You Page (FYP) and the TikTok algorithm—each consistently pushed out content to our target audience (social media specialists, managers, digital marketers, etc.).
If you’re using A/B testing, consider all of the elements of your content that could influence your test results to ensure you’re only testing one variable. Also select your control, which is the content that will not change. For example, if you’re testing images, make sure to not change the copy, audience, timing, etc.
In our social team’s multivariable TikTok experiments, they tested several variables including formats, themes and creative considerations like music, sounds and closed captions.
In the example below, 91% of views came from the FYP, 5% came from a personal profile view and 1% came from direct followers–confirming their hypothesis that the FYP and the algorithm were the key drivers pushing out content to our target audience.
If you use Sprout, you can use tagging to track the performance of your control and the test post.
Now it’s time to execute! Use Sprout’s Publishing tools to seamlessly plan, create, optimize and post your content for the experiment. For example, you can use Sprout’s ViralPost® technology to post at optimal send times.
Use the Tag Performance Report to organize, run and analyze your social media experiment results, including your paid campaigns.
Read our guide on creative testing for more tips and examples for conducting social media experiments.
Review the results of your experiment to identify new opportunities or add insights to your records.
If you’re trying to gain executive buy-in, especially for further testing or resources, you’ll need to communicate and create an effective data story to highlight why your company will benefit from your suggested next steps.
Using Sprout, you can easily access automated, presentation-ready reports to help illustrate your data story. Create custom reports, like this Facebook Performance Summary that includes impressions, engagements, post link clicks and publishing behavior for various content types:
Here’s a quick overview of the seven steps:
Good luck on your journey to embracing curiosity and thinking like a scientist—your social strategy will thank you.
This article is an excellent first step, but there’s so much more to learn about social media experiments. Step into the (virtual) lab yourself and get a hands-on experience, by signing up for a free trial.
Jamia Kenan is a Content Specialist for Sprout Social based in Atlanta, GA. When she’s not writing, you’ll find her talking about the Internet from the latest TikTok trends to NFTs and the metaverse. She also enjoys trying new restaurants, hiking and watching movies.
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