When you're talking about the social media strategy of your company and someone is wondering why you're treating any social aspect in a certain way, what are you saying?
a "Because we've always done it this way." (This one is a career killer, never say this.)
b "Because our audience seems to like it."
c "Because we've checked several strategies and found that one was by far the most effective in delivering against our goals."
If you thought that article will get you to answer "C" every time, you're correct! Wherever you have a strategy-related hunch, query, or challenge, social testing will help you produce valuable insights to support your next steps.
1 When you want to make a case that you need more video production budget, run a social media check of how different types of content work against your KPIs, such as views or interaction.
2 When you're trying to prove your audience's not reacting well to a buttoned up, corporate-sounding brand voice, checking copy written in various voices or playing with emojis included.
3 If you're wondering if raising your publishing cadence would increase traffic from social to your website but you don't have a lot of free time, then check it for a week and measure it to a regular week of operation.
Instead of worrying what could be and hoping for the best outcome, build a theory, check different social variables and search for rational and outcome-oriented insights to the data.
Getting started with social testing
The assessments on the social media are standardized and observable. We help you understand what works (and what doesn't work) for your company through a data-driven lens, instead of relying on blanket best practices or the metrics of other people. Although you're still looking at reporting on social media to see how your content, communication and publishing tactics are going, social media research helps you to define different variables and come away with a clear image of what will (or won't) drive your brand success.
Once you start checking, make sure you have some basic details down there. This includes:
an explanation of your company's overall objectives
Written details of your current social strategy, including your overall goals for each network
An explanation of your audiences per channel
An overview of current results A list of questions, hunches and ideas you would like to test
Reviewing these basic documents and your current results will help you find the most critical areas that need to be addressed while testing. You don't need to go from zero to check all at once— and actually running multiple tests at once, particularly if you're focusing on organic social, may actually lead to inconclusive outcomes.
Prioritizing the hypothesis that will have the biggest effect on the top-level goals of your team and your overall business objectives can help you check in a way that can make a significant difference for your company. With that in mind, let's talk about some popular vocabulary testing, review a few forms of testing and walk through how you can build your own.
Common testing terminology
When you lay the groundwork for social testing, understanding basic terminology for testing is critical. Below are some common words you're going to need to use.
Hypothesis: A hypothesis is an inference that you may use that as the starting point for evaluating social media. This is usually focused on minimal knowledge (you have some statistics or empirical proof, but not enough to know whether your argument is correct) and can be clearly proven or disproved by testing.
Variable: A variable is an entity or element that changes, or differs. A variable could be anything like the copy you use in social research, the imagery you pick or the time you post a message.
Control or controlled variable: A control variable, or a controlled one, remains the same in the analysis. The control is used as a point of reference to test the results of modifying the variable you are searching for.
Metric: A metric is a measurement norm in social testing which you use to gage tests. Examples may include interactions, contributions or clicks on a tweet.
Statistical significance: Statistical significance is the probability that the outcomes of the experiments are actually influenced by the variables you modify and not by chance. Developing a statistically meaningful test requires a large enough sample size (e.g. measuring a variable using 100 messages instead of 10) and a consistent control.
A/B testing
A / B checking is one of the most simple social media tests you can perform. Defining an A / B test is a test in which you change one variable and hold all the others the same. For instance, if you want to know what form of content results in the highest interaction on Instagram, you can check photo content vs. video content with the same caption or story copy, posted simultaneously on the same day of the week, a week away.
When modifying one variable in your posts, such as the type of content, you will compare the test results with each other. Yet two posts don't do a test— because there are so many variables involved in one social post, e.g., time of day, form of media, etc., you'd have to replicate this experiment with different content, change variables, multiple times, to get conclusive results.
The A / B test works best for single variables, as stated. If you're checking strategy against strategy or campaign against campaigning, you'll need to concentrate more on the variables you can monitor, so you can equate them with each other meaningfully. A / B testing will get you to a point of statistical significance but social testing is not ideal. Every single moment is special. For this reason, not only the science of research is involved, but also the art of perception, and this is on the creation of the social media manager.
Here are a few examples of A / B tests which you can run on social:
- Daytime: Monday at 8:00 a.m. Vs. 8:00 a.m. tuesday
- Types of content: video vs. a link
- Captions: long vs. short
- Copy: query vs. argument
- Images: illustration vs. photography
- If you want to go beyond a single variable test, that is where you want to look at multivariable tests.
How to run a social media test
Now that you know two ways to handle social media research, learning how to perform a test will be next. The execution of a social media test as mentioned below is achieved in five stages. On the first step, we're going to go into more depth so you know more about what you can play with.
- Decide what you want your theory to test and build on.
- Select test type: A / B, or multivariable.
- Determine the length of the test, the platform on which you want to test and any variables you need to monitor.
- Run the check.
- Analyze the performance, new ideas or next steps, and share them.
Conclusion
We have listed different ways to check on social media but there are more tons to play with. There are infinite possibilities as social media and customers grow with their own preferences and intricacies.
The planet is your oyster now that you learn the fundamentals of social research. Choose one aspect of your social strategy that wasn't going well, or a hunch that you're hoping to confirm, and build a test to get the answers you need to refine your method.
