Analytics is a fluid process.
It’s all about going from one thing to the next, searching for patterns and other meaningful information gathered from the analysis of data.
The less glamorous side of social media, analytics isn’t what comes to mind when I tell people what I do for work. A significant portion of my role involves sifting through data and poring over spreadsheets. The process is time consuming and tedious, but it’s a process I’ve grown to appreciate. I think of analytics as the bloodstream of a social strategy, existing beneath the surface yet always pulsing, always driving forward — an indication of the vitality of your brand.
“The price of light is less than the cost of darkness.” Arthur C. Nielsen
From Darkness To Light
You know the feeling: You’re trying to find your way across a dark room, carefully placing one foot in front of the other. You think your’e right on track and then ouch! you stub your toe. That stubbed toe is kind of like the byproduct of an ill-advised social strategy. To create content in the absence of a data-driven approach is to practice social media negligently — it hurts. The price you’ll pay for not knowing where your brand is positioned is much less than the price it costs to analyze the data. In my case, the price is energy and time. The mental shift from content creation to data analysis isn’t an easy one, and it takes true effort to navigate back and forth. Time is critical to the accuracy of the data. The more time it takes me to get to the spreadsheet, the higher the likelihood of me having to manually calculate figures in order to maintain precise data from the start of the month to its end. But the energy and time is a small price to pay, because the light informs our strategy and illuminates strengths and weaknesses in the way we approach social media.
From Investment To Return
A popular metric in the business world, the ROI (Return On Investment) is a flexible, simplistic model of effectiveness. The formula is this: (Gain from Investment) – (Cost of Investment) / (Cost of Investment). Yet despite its versatility, I find ROI to be a difficult formula to calculate for social media. What exactly constitutes a “return” in the realm of social media? And how do you measure that return? Sometimes the return is as straightforward as a link referral. But other times? I think the return is simply a feeling. In my role, our team wants current students to feel welcomed, appreciated, and proud. We want prospective students to feel like this institution could be the new place where they feel like they belong. How do you quantify that? What’s the numerical value of a relationship between brand and consumer?
Determining a set of KPIs (Key Performance Indicators) will shed at least some light on the success or failure of your initiatives. Some popular social media KPIs are explained below:
- Reach: The unique number of people who received impressions of a page post. Reach is less than impressions since one person can see multiple impressions.
- Impressions: The number of times a post from your page is displayed, whether the post is clicked or not. People may see multiple impressions of the same post. For example, someone might see a page update in News Feed once, and then a second time if their friend shares it.
- Engagement: The measurement of how much fans are interacting with the Page. Engagement indicates how well you are connecting with your social community and how well your content is received. It is also the basis for the Edge Rank algorithm.
- Growth Rate: The increase in the number of fans in a given period. It’s recommended to look at a longer period of time to compensate for unique effects.
- Sentiment: The mood of fans on a post. To determine this, comments are analyzed and put in categories such as positive, neutral, and negative. The result is a quotient such as “75% positive.”
From Data To Design
As humans, we’re visual creatures. According to the Social Science Research Network, 65% of humans are visual learners. Passing the spreadsheet of data up the chain in our division would be a waste of time for anyone trying to decipher meaning without fully immersing themselves in the data. So I turn the data into design.
Imagine I told you that we experienced a “174% increase from 2014 to 2015 going from 14,917 avg. reach per post to 40,929.” That’s a pretty hefty cognitive load. But a visualization of the same information translates at a much faster, more efficient rate. The circles to the right represent that very same increase in reach without the mental effort to comprehend.
The fun part of social analytics is that you’re still telling stories. You’re uncovering patterns that determine which direction you’re headed.
Below is an example of how a person could take the same dataset and tell two entirely different stories.
This visualization of follower counts would indicate that Facebook is clearly the platform that should absorb the majority of our team’s time and energy. Clearly, it boasts the largest number of followers and would therefore be the most powerful platform. Right?
The next visual portrays the growth rate across the same three platforms. In this story, Instagram is clearly cast as the lead role, and Facebook appears to only be an extra.
Examining both visuals together, we can see the way the same dataset can tell different stories. To base our efforts solely on a follower could would be remiss, because we’d be missing the fact that Instagram is a rapidly growing platform for our organization.
From Surface To Core
Social media can come across in a very surface level way. People think our job is to play around on Facebook all day. Consumers scroll through their feeds and may or may not interact with a piece of content that we very deliberately published at a certain time, with certain text, and with a certain framework. Take our Best Teacher Awards post, for example. On the surface, the photo did not perform well, receiving only around 25% of the amount of likes that we would typically expect for a photo. I noticed, however, that the photo had a significantly high number of impressions. Despite a low number of likes, the photo got a high number of comments. With this information, we can uncover the idea that Instagram’s algorithm gives preference to comments.
Just recently, I found myself hurrying back to the office after a meeting. I bypassed the sidewalk and cut through the Monfort Quad to save some time. I looked down and noticed I was following a well-trodden path that had become worn into the grass over time. I wasn’t following the pathway that was designed for me to use. I was analyzing data — in this case, time — to get to my destination in the most efficient way. Social media analytics is a lot like that path. We often know where we want to be — more followers, more sales, more engagement. But we don’t always know where we’re at. Spending time with analytics sheds light on where you are so you can determine the most effective pathway to get you to your destination. These pathways are the patterns we’re digging for in the data. Just like sidewalks are developed by design, social media strategies are often developed out of habit or tradition: “Because that’s the way we’ve always done things.” But our challenge is to accept that our strategies are ever evolving, shifting along with trends and generations, and the only way for us to emerge from the darkness is to invest in the price of light.