Assigning numbers—meaningful numbers—to our work with social media is not an easy task. Setting measurable goals helps us get there, but there are always decisions to make about the numbers. Which set of numbers tells us what we want to know? How do we manipulate data to get the full (or relevant) story? And then, what do we do when our goals aren’t all that clear or measurable?
A New Perspective
I have a confession to make. I’ve long been touting the necessity of goal-driven social media strategy facilitated by meaningful measurement. Yet, in my own role as a social media manager, I find it incredibly challenging to define concrete and measurable goals. I live in a world without access to the data or the resources I want, at least in my immediate reach. The result has been a set of very broad goals for my university’s social media efforts. I tell others (I’ve told you!) that it’s not enough to aim for community growth or engagement; and this is the very thing I am working toward. Controversy? Maybe not.
Yesterday, while pulling together my latest version of a quarterly social media report, I made two decisions.
- We can/should be striving for more than community growth and engagement, but there is value there.
- By examining the behavior and preferences of our communities, we gain valuable insight that can shape content strategy across channels.
Resolved as such, I set out to create a report that would tell me what my community cares about. Instead of reporting on the past as a measure of success, I reported on the past as a resource for the future.
I’ve spent a lot of time trying to pinpoint which tactics yield the best results. Much work went into analyzing the time of day or media type that saw the largest reach, how many posts or tweets in a day affected follower counts, etc. No more. This makes no sense. From here on out, I am choosing to believe that good conversations will make for good interactions. Good content will lead to higher engagement and happier communities.
A New Report
I want to know which conversations and topics are getting traction across networks so I might understand what matters to our audiences. My new report serves to answer the following questions: What topics, regardless of the type of post, are resulting in the most impressions, reach, and interaction? Are topics received similarly across social networks?
To get these answers, I couldn’t rely on standard-format reports or spreadsheets. My examination of topic interest was limited to Facebook and Twitter, and I used numbers provided by Facebook Insights, Bitly, and SocialPing. Below is a general list of steps for creating this sort of topic-focused report.
- For Facebook, export Facebook Insights data for the desired date range (page-level and post-level)
- Define a set of topic categories
- In Facebook’s post-level data spreadsheet, the “Key Metrics” tab, insert a column and assign a topic category to each post within the date range
- After posts are categorized by topic, average the numbers for Lifetime Post Total Reach, Lifetime Post Total Impressions, and Lifetime Post Consumers (total of values divided by number of posts)
- Graph averages by topic category for Facebook
- For Twitter, extract click-through rates for tweeted links from Bitly or a URL shortener of your choice (I copied and pasted Bitly’s stat information to a spreadsheet, which meant much reformatting and moving cells around)
- Assign topic categories to the tweets/links
- After tweeted links are categorized by topic, average the numbers of clicks for each
- Graph averages by topic category for Twitter
- Compare data and graphs to identify trends
In my case, the data showed that regardless of the social network, the best-received topics were consistent. Armed with this information, I can make better choices about which content I should share in the future, and which conversations my community wants to be part of.
This report, as always, will probably evolve in some way. In the future, I may need to adjust or better define the topic categories I assign. I may find a way to apply this categorization to Instagram or blog posts. Or maybe I’ll get my hands on the data I need to dig into lead conversion or campaign analytics. For now, I’m optimistic about how this set of data will guide future content strategy. No more social-media-report guilt.