Just Another Lab Mouse: Choosing Social Media Metrics that Matter
by Tory Martin
Social media has become a tool of nearly incalculable value to nonprofits and their causes. Channels like Facebook, Twitter, and Instagram offer a cost-effective way for us to reach the people we serve, the communities we hope to shape, and the donors and volunteers we rely on for so much. Yet beyond the fact that we know we need to be on social media, it’s hard to know what else we can and ought to measure about the impact of our digital presence. Which social media metrics matter?
As with so many questions, the answer to this one is “it depends.” The data you collect and analyze should reflect your institution’s goals, and you should know what you intend to do with that data once you have it.1 That’s where “data-driven decision making” begins, no matter the project. Start by establishing your goals — are you trying to raise awareness for your programs? To mobilize voters? To attract local attention to a community problem? — and then set about identifying the metrics that will tell you whether or not you’re accomplishing that goal.
Your evaluation should also recognize the unique environment of social media. Unlike traditional media, wherein communication is often one-way and controlled by the content distributor, social media is multi-lateral and user-directed. As Kay Peters et al note, “In social media, brands and their managers are just equal actors in the network. A frequently used analogy is the transformation of brand managers from a lab scientist into just another lab mouse.” The best social media users are both proactive and reactive, both beginning conversations and joining them.
This unique environment, however, provides its own limitless opportunities for gathering good data and using it to improve your strategies. You just might have to adjust the way you think about measurement. For traditional media, “snapshot” data like circulation and viewership provide an in-the-moment understanding of an organization’s reach. Social media, however, is best understood as an ever-changing web of players and actions, and it has to be measured as such.2
For instance, it’s certainly important to pay attention to the number of followers you have — especially when you’re just starting out on a platform. But what’s more informative for your efforts is whether and how that number moves. Is your rate of growth increasing? Holding steady? Declining? Taking the time to calculate your movement will give you a better sense of whether your strategy is working.
This kinetic mix of people and content should actually feel fairly familiar. Nonprofit engagement techniques often rely on the notion of “donor centricity:” framing communications around the donor’s experience and role in accomplishing an organization’s mission. Social media is no different — in fact, its networked nature is perhaps the most pure form of a donor-centric communications strategy. Users’ social media activity is driven by what Donna L. Hoffman and Marek Fodor (2010) call the “4c’s: connections, creation, consumption, and control.” These are the ways your audience — all audiences — engage on social media, and if you can find a way to understand and harness the motivating power of these drivers, your strategy will succeed. But how to quantify these user actions?
Relevant Metrics for Social Media Applications Organized by Key Social Media Objectives3 is a very useful table to help social media managers identify key metrics from different platforms that can be used to tally progress towards a particular communications goal. The way you measure and value any of these metrics (e.g. the number of shares, comments, or submissions) will depend heavily on what you’re trying to accomplish, but they’ll give you some sense of how you’re doing. Comparing them to industry averages (you can find M+R’s report on benchmarks here), and your own patterns over time, will help.
But there’s a final step that’s key to all of this: you have to use what you learn. IBM estimates that every day our world generates 2.5 quintillion bytes of data — a practically inconceivable number that we could never hope to fully utilize.4 But within that larger bucket there are smaller buckets, sets of data that we can use to evaluate our progress and adjust course. Once you’ve identified your goal, use your data to help you make adjustments to your strategy, to reach the people who will be your most active audience members, and to connect them to the mission-focused content and engagement opportunities they seek.
Nancy Baym (2013) reminds us that even the best social media strategies come with a caveat: those interactions that are most meaningful aren’t always quantifiable. “In a time when data appear to be so self-evident and big data seem to hold such promise of truth,” she writes, “it has never been more essential to remind ourselves what data are not seen, and what cannot be measured.”5 In philanthropy, we know that much of our greatest impact happens within and over the course of individual lives, and we may never hear about the true differences we make. It’s hard to measure the impact and effectiveness of a social media strategy that is intended to do more than merely draw customers and clicks. How should we quantify the impact of #WomensMarch or #MeToo, for instance, on the next generation of women political candidates or aspiring executives? That metric may never be known. Yet it is to our benefit to use the data we do know to drive the impact we may never be aware of.
Tory Martin is the director of communications and engagement here at the Johnson Center, where she partners with her colleagues on the senior leadership team to identify, implement, support, and promote the Johnson Center’s strategic priorities and vision for a world powered by smart, adaptive, and effective philanthropy. Read more about Tory here.
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- Petersen, J. (2018). Data to what end?. 11 Trends in Philanthropy for 2018, 11–12. Retrieved from http://johnsoncenter.org/wp-content/uploads/2017/12/11-Trends-for-2018-Report-FOR-WEB.pdf
- Peters, K., Chen, Y., Kaplan, A. M., Ognibeni, B., & Pauwels, K. (2013). Social Media Metrics – A Framework and Guidelines for Managing Social Media. Journal of Interactive Media, 27(4), 281–298. Retrieved from https://www.sciencedirect.com/science/article/pii/S109499681300042X
- Hoffman, D. L., & Fodor, M. (2010). Can you measure the ROI of your social media marketing? MIT Sloan Management Review, 52(1), 41–49. Retrieved from http://search.proquest.com.ezproxy.gvsu.edu/docview/757349606
- Jacobson, R. (2013, April 24). IBM. Retrieved from IBM Consumer Products Industry Blog: https://www.ibm.com/blogs/insights-on-business/consumer-products/2-5-quintillion-bytes-of-data-created-every-day-how-does-cpg-retail-manage-it/
- Baym, N. K. (2013, October 7). Data not seen: the uses and shortcomings of social media metrics. First Monday, 18(10). Retrieved from https://journals.uic.edu/ojs/index.php/fm/article/view/4873