by Eric Weiss and Koen Pauwels, based on the paper by Peters, Chen, Kaplan and Ognibeni in Journal of Interactive Marketing
Rising social media ad spend has topped $40 billion in the US in 2020, and keeping a pulse is both important and challenging for companies. The structure of social media diverges from that of traditional media, however, and therefore metrics pertaining to marketing on social media must reflect such differences. “Social Media Metrics – A Framework and Guidelines for Managing Social Media” creates both a theoretical framework to understand the nuances of social media, as well as nine proposed guidelines which direct managers to better encapsulate the success and failure of social media campaigns.
Key social media elements are motive, content, network structure, and social roles and interactions. Motives are the reason users engage with social media. Users hope to gain intellectual value such as creative expression or uncertainty reduction. Users also seek social value; to socialize, dominate, and/or personally identify themselves. Lasty, due to the nature of social media’s self-governance, users gain cultural value by partaking in social media. Most users report only one of these three motivations. Below are two current dashboards by HubSpot and Sendible.
Content has three general attributes, quality, valence, and volume. Each of these aspects make content worthwhile to consume from the user perspective. Content quality includes vividness, interactivity, and its corresponding domain. Content valence is the emotion and tonality of messaging. Lastly, content volume allows for a brand to stay relevant in social media.
Network structure is defined by its size, connectivity, distribution, and segmentation. The degree of locality or the magnitude of the actors in the social media is its size, while how divided the network is determines its segmentation. How actors connect over the media, including homophily and multiplex connections define the connectivity of the network structure, and importantly the strength of ties between users is the network structure’s distribution.
Social roles and interactions are the final elements of social media. Users, through networking, sharing, expressing, and gaming, are constantly defining and redefining their social roles on social media. Accordingly, how these actors interact with each other is also constantly shifting to reflect their attempt to augment their social standing. Visualized below are the elements of social media and their interplay.
From this proposed framework, nine guidelines follow to quantify social media marketing activity through effective use of dashboards and their metrics. First, dashboard focus must transition from ‘control’ to ‘influence.’ Brands are just another actor in the egalitarian space of social media, with their marketing success mostly public information and communication between consumer and the company being bi-directional. So, if the content of a brand does not fit the motives of the immediately linked actors, it won’t be read, altered, or worse yet, shared. “In essence, sustained reach cannot be bought like in traditional media.” Brands must have the ability to measure listening to consumers in these bi-directional channels as well. This first guideline shifts traditional focus on controlling messaging to mass markets to transparent communication to influential consumers.
Secondly, dashboard attention should shift from states to processes and distributions. Rather than detecting the presence of links between actors, the intensity or dynamic of these is more important. Growth or decline metrics should be paired with those conveying possible feedback loops, potentially leading to dead-weight inactive users.
Third, divergence should augment convergence in social media dashboards. Certain brands may thrive on the adversity it receives on social media due to its differentiation. Besides measuring the sentiment of consumers, it is key to understand who expressed this sentiment and in what context. To this end, contingency keywords can classify the context of consumer sentiment.
Fourth, quality is more important than quantity. Measures of quantity work well for traditional media, however, mass “dead likes” are counterproductive in social media. Ranking and classifying levels of engagement has been captured in social media dashboards such as in BuzzRank displayed below at the time of paper writing.
Fifth, marketers should be aware of transparent and feed-back prone metrics. Users quickly learn about how brands evaluate their influence across social media and will be tempted to game the system. Visualized below is one such influence tracker by EdgeRank.
Sixth, metrics in dashboards should be counterbalanced. While traditional media metrics like purchase intent or awareness could encapsulate environments on their own, social media metrics must be as dynamic as the structure they wish to summarize. Easily gamed metrics should be balanced with secondary metrics that penalize against gaming and fake accounts. In terms of quality and quantity, metrics should encompass both states, in addition to dynamic and heterogeneity of the network structure. As social media inherently evolves, metrics must be regularly rebalanced as well.
Seventh, dashboards must convey the generalities and specifics of social media. Metrics should capture the nuances of different mediums, such as Twitters’ asymmetric nature (I can follow you without you following me) compared to the symmetry found in Facebook. Users employing multiple social media accounts may experience spill-over effects as well. There is no silver bullet; no single metric can summarize one social medium, so varying metrics across the micro-, meso-, and macro-levels should be utilized. Lastly, we should track varying levels of observed engagement, as expressed previously via BuzzRank.
Eighth, brands must shift their attention from urgency to importance. Social media are living organisms which evolve constantly and deviate wildly. Firms must stomach these deviations in a “corridor of confidence” where a predefined amount of evolution on social media platforms should be tolerated. Humans, especially managers, have the tendency to ‘react to what moves’ instead of what is important, which could move slower over time. Instead of chasing changes, leaders such as Jeff Bezos and Warren Buffet instead look at the future with the question: “What’s not going to change in the next ten years?” Academics have a similar perspective, due to the long research and review process before journal publication, so collaboration with them would assist a company’s long-term vision.
Ninth, dashboards should reflect a balance of pragmatism and theory. Brands must not allow pragmatism to create apathy in creating metrics and corresponding dashboards. Metrics can be a waste of time if they prevail simply because they are at hand or easily quantified. Changes to metrics should have clear managerial implications, ideally in a closed-loop fashion e.g. ‘If awareness drops by more than 5%, increase brand building ads by 20% until awareness is back within a percentage point of the target value’ .
Let’s wrap up and show all nine guidelines in one picture: