ARF Social Media Insights: Can Social Media Effectively Track Influence? - Lynne d Johnson - MediaBizBloggers
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Published: July 7, 2010 at 02:40 AM GMT
Last Updated: July 7, 2010 at 02:40 AM GMT
By Lynne d Johnson
There's an ongoing debate about whether influence can be tracked via social media. At its core, the issue revolves around the lack of a common definition for influence, especially when we're talking about social media. I'm on the side of quality over quantity, where influence is more about overall impact than the number of followers or fans, or even the number of clicks. There are definitely instances where quantity will trump quality every time, and in the advertising business those instances happen far more often because we measure things by understanding their ROI. But is social media helping us shift away from that kind of thinking?
I'm at a crossroads with this, because the current work that the ARF is doing with the ANA and WOMMA is to create a social media measurement guideline for the industry. For the ARF's stake in this project, I'm advocating heavily to build off the work of Razorfish's Social Influence Marketing Score and Altimeter's Social Marketing Analytics.
With the first, it's possible to look at both the online and offline share of voice (reach of conversations) that a brand has, along with sentiment or likability for the brand (positive, negative, and neutral mentions) to determine the brand's SIM Score. With this model, you can also determine the SIM Score for an overall industry, say auto or financial. Primarily, the SIM Score is an accounting of your brand health: think of it as your social influence market share. And in this regard, it helps a brand to realize the impact of influence on brand affinity. It's a viable framework, given what it sets out to achieve.
On the other hand, Altimeter and Web Analytics Demystified have developed a framework which considers social media measurement meaning different things to different people—and for different reasons—and that no one social media analysis solution works as a one size fits all solution. Their framework looks at a number of KPIs that correspond to specific business objectives, including "Fostering Dialog," "Promoting Advocacy," "Facilitating Support," and "Spurring Innovation." For each KPI, such as "Share of Voice," "Advocate Influence," "Satisfaction Score," and "Sentiment Ratio," there is a numerical model that gets us closer to determining an ROI for its related business objective. A successful social media strategy can't happen without starting from the point of planning to reach a specific objective.
On the surface, both of these frameworks make total sense and lend credence to the idea that there is a method for determining influence through social media. And as social media changes daily and smartphones and portable devices become the major ways that people participate and share likes and dislikes, other metrics will certainly come into play. But together, for now, these two models get to the heart of the quantitative side of social media. But how can we understand or determine the qualitative side of social media?
Since it's the realm of the fuzzy stuff, it's often left to researchers who study consumer insights and behaviors. Yet for marketers this stuff is important too: It's not solely about understanding how many clicks an A-list influencer can drive, but also why that specific influencer drives so many clicks. If we're looking only at clicks, then we're looking at social media much in the very same way that we've been looking at all of digital media. Those older models can't explain the phenomenon of someone (or a brand) with a smaller pool of followers getting more clicks on a link than one with a larger pool? Is it the value of what that person has shared that makes a difference? Is it the trust level that person (or brand) has garnered? When we talk about how influence, word-of-mouth, and sharability are outpacing display advertising and even search, how can we view them through exactly the same lenses that we do display or SEO or SEM. Nielsen and Facebook have recently taught us that in understanding the value of earned media, we need to move beyond this sort of thinking.
Social media is becoming the space where we look closer at relationships and actions to determine behaviors. It's the stuff that scientist Albert-Laszlo Barabasi tried to teach us in Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science and Everyday Life. It's the stuff the Yahoo! Principal Research Scientist, Duncan J. Watts, explains in his body of work and in his groundbreaking book, Six Degrees: The Science of a Connected Age. In these offerings we find that influence is an outgrowth of the strength of relationships and connections.
And this brings me back to my crossroads. While I strongly believe that numerical data can tell us the story of social media, I strongly believe that it can only tell us part of the story. For instance, a recent post, "How Fast Company Confused Ego With Influence," written by Amber Naslund, Director of Community for Radian6, questions the methodology of the magazine's website experiment to find the most influential person online. She writes:
"To me, influence isn't about popularity. Or even reach. It's about the trust, authority, and presence to drive relevant actions within your community that create something of substance."
In this experiment, the magazine's Influence Project will determine influence based upon clicks to a unique link created when a participant creates a profile. So the experiment measures how many people check out the profile, as well as how many people create their own profiles based upon the referral. Sure it's a social experiment that monitors clicking behaviors, but what Naslund asks is whether tracking linking/clicking behaviors is the equivalent of measuring or monitoring influence.
I don't think we're talking about a wrong way of looking at influence, but we could be looking at only one side of the equation. In measuring social media, we have to listen, observe, and study to understand who the real influencers are. Perhaps an influencer's influence isn't driven online, but offline. Here's where Razorfish's SIM Score (or perhaps Altimeter's Social Marketing Framework) can help us capture--along with the aid of engagement in a private community, an interview or survey--the offline component.
There are also instances of people being influenced, but not clicking. A blog post or tweet may influence a purchasing decision with no blog post comment left behind, or no follower or retweet to track. What Naslund's argument also bears to light is that we should think about separating influence from virability/viralness when we're measuring influence in terms of social media. Generating buzz and going viral won't always create influence. Many social media failures (here and here) generated a lot of buzz (and sometimes even a lot of social media activity) that eventually reflected poorly on the brand.
Quantity and quality can both make influence happen, sometimes together and sometimes separately. Let's consider what Geoff Livingston writes in his post, "The History of Influencer Theory on the Social Web,"
"So who's right? Where's influence, the uber-connected one percenter, trust agent, free agent? Or the person who lights the spark within his/her community of 150? Well, both are."
Both the A-list social media influencer and the niche community influencer can create impact (and influence) for your brand. But it's really those who tech blogger Robert Scoble once called passionates that will drive your brand advocacy. In that case, it's not always about how many people they're telling your story to but the actual stories themselves that they are telling about your brand—the ones that are engaging and in turn driving more people to tell your brand's story. That's real influence. And that's where quality and quantity converge. It's a blueprint for how companies should think about developing relationships with their consumers and potential consumers, as well as how they should think about measuring those relationships.
Lynne d Johnson is SVP, Social Media for the Advertising Research Foundation. She can be reached at lynne@thearf.org and on Twitter: @lynneluvah.
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