With the daily bombardment of social media that a consumer is exposed to, it’s hard not to wonder: is more really better? That is, if the goal is viewer engagement with one’s content, is there an optimum number of daily posts?
Crash course in social media analytics
The first step in answering this question is discovering whether higher levels of posting on social media are really associated with higher levels of content engagement. The methodology is relatively straightforward and involves a simple correlation. For this blog, we’ll focus on Twitter because of its simple post format: a tweet. The best way to dissect this question is to examine the association between number of tweets in a day and the number of engagements on those days. Engagements can be defined in any way you choose, depending on what’s meaningful for your company. They can be all encompassing, or just include the big three (retweets, replies, favorites). In doing this analysis, there are a few things to keep in mind:
First, the more data you have, the more accurate your results will be. While it may be tempting to snag just a week’s worth of tweets, there are many factors that could influence just one week’s worth of data such as seasonality or a recent campaign. To control for this, an ideal data set would include at least a full year’s worth of tweets. The more data you have, the more representative your analysis will be.
Second, you must account for the unbalanced nature of your data. It is likely that in looking at your data set you will have several days with 5 tweets but maybe only 1 day with 20 tweets. To reconcile this imbalance, you will need to average the number of total engagements on the days with multiple instances of x number of tweets. For example, if you have two separate days where you posted 5 tweets where one elicited 30 engagements and the other elicited 40 engagements you would average the two engagement levels to say that on average, a day with 5 tweets is associated with 35 engagements.
Finally, keep in mind that the association you will see from this analysis is only a correlation and does not show cause. If you’ve ever taken an introductory statistics course, I am sure the phrase “correlation does not equal causation!” was ingrained into your mind like a tattoo. Well, this analysis is no exception. If you’re new to the analytics game, let me explain this commonly used quote: When comparing two variables, we are simply observing events that have occurred naturally, and we aren’t controlling the number of tweets or the number of responses they elicit. While this provides useful information about what is going on in the world around us, it does not allow us to say that x number of tweets directly will cause y number of engagements.
So is every tweet as efficient as the last?
In doing this analysis, you may find the association that I did: the more tweets there are, generally the more engagements you will have. This is not a surprising result; sheer volume of tweets encourages a higher volume of interaction with those tweets.
However, this is assuming that your tweeting resources are unlimited and that you have a room full of minions waiting to pump out the next tweet. For many of us, this simply isn’t the case. In these instances, it is important to consider the efficiency of a tweet. That is to say, if your resources for tweeting are limited, at what point does your next tweet elicit fewer engagements than the previous tweet?
To answer this question, some modifications must be made to our data. Our end goal here is to examine engagement per tweet. In order to calculate this number we must divide our total engagement by the number of tweets in that given day. For example if we have a day where 1 tweet was made and there were 30 engagements, we will have 30 engagements per tweet. However, if we sample a day where 2 tweets are posted and there are 30 engagements. We would find ourselves with only 15 engagements per tweet.
In mapping this out, your graph is more likely to appear as a bell curve than your previous graph of total engagements. The top of that curve will tell you the most efficient number of tweets per day for your company. We can’t give you a straight answer on what’s right for your company — because the most efficient number of tweets will be different for every business.
Again, these numbers are only an association and don’t account for seasonality or events such as a sale. During these times, it may be more worth spending a little more time to push out a few extra tweets.
There you have it! Just like that you can begin assessing the most efficient practices for your social media posting. Happy tweeting!
