Gravity7: Social Interaction Design SxD By Adrian Chan

I’m pleased that the Bain company conducted research into social media users. Honestly and with earnest affirmation. However, the types they found among us users beg a few questions. And I should state up front that I have my own set of social media personality types — so what follows is admittedly biased if not critical.

First of all, these are a weird amalgam of market segment categories and user types. Blow up the image and you will see that Fact finders “skew male and older.” I guess this is the guy who sits on his blackberry at the airport dialing in facts and bookmarking them for later pre-purchase reference. He is almost by definition not a social butterfly, even though he might in fact be a trusted source of “facts found and saved” among friends.

Bain writes in its research report:

Our research has identified 10 segments of social consumers. Members of these segments frequent different social media platforms and prefer different types of content and engagement models. For example, companies such as Disney, Wal-Mart and Mattel, who target “moms,” will find they are disproportionately “Social Butterflies” and “Social Gamers.” A key demographic on Facebook, “moms” as a group spend significant amounts of time playing social games. Companies such as Nestlé have found ways to embed their brands into the games that moms play online. For example, the company allows users to grow ingredients of its Stouffer’s brand prepared meals within the FarmVille game. It engages with key customers in the right platform, and with the content those customers find compelling. Alternatively, companies looking to capture the online attention of the “Young and Mobile” will reach them through micro-blogs and location-based games, making the most of the platforms that are popular with this segment. As the social media ecosystem continues to evolve, it will likely further fragment, making consumer segmentation—and tailored social media approaches—even more important for success.

Never mind the categories for a minute. Clearly they leave a lot to be desired (connectors? inviters? pundits? thought leaders? critics? wikipedians? moderators? hashtaggers?) Who are these people? Both this description and the chart would suggest that these are real people — people found online and accounted for. That’s a bit strange. Our use of “user types” has, at least in the fields of design, UX, IxD, etc, at best served as a heuristic: a means of communicating with and to clients who belongs to a target market or is a target user.

Look at the categories, and the residual types we’ve used for the past decade are in there: the soccer mom, the butterfly, the gamer… You might think that these are life stages. That they are stages of technology use in life life stages. And you wouldn’t be far from the mark, for indeed, these are types combining conventional market segmentation and technology adoption stages.

How accurate can they then possibly be? And if they were somehow plausible facsimiles of actual users, how likely is it that they’re the same as they have been for, oh, as long as online marketing has been around?

These aren’t real people. They’re not even real categories. They are categories used to describe either a market and its segments, or technology adoption, in language familiar and reasonably commonsensical.

But in fact moms use instagram. Gamers get their facts down. Butterflies enjoy games. Blog readers tweet. And so on. You can’t describe a person generically and also capture their individual qualities. To describe people in the abstract by what appear to be qualities, then, is misleading. The name is neither a good description of who the person is, nor adequate to describing their behaviors and motives.

Seeing as in social media use, the grail for marketing is to close the distance between the brand/business and consumer, these kinds of reductive categorizations ought to be done away with as soon as they have served the purpose of framing the marketing opportunities and challenges. Move past the generalizations instead to a consumer’s interests, activities, and behaviors. Interests are motivated. Activities are habitual. Behaviors are observable.

And in the age of communication, when so much of the world of information has been socialized, by means of socializing tools, why bother with abstractions? Especially if they aren’t even good ones.

I suspect that we’re moving, slowly, to a world of mediated commerce. A world in which market segmentation and to some degree traditional marketing itself will be replaced by the real time and dynamic pricing and sales made possible by social data. Data specific to individuals and their relationships. This is a big data problem, and will take innovation to solve, and partnerships to leverage.

I question the categories used in this research and wonder whether or not research truly found these types of people, or simply confirmed what it already believed to be the case. I don’t think people actually vary in their behavior on social tools in this way. I think people’s communication styles and competencies vary, and that these more strongly govern or inform their use of social tools. Some develop an extended presence and ego; care-take a reputation; craft expertise; edit and contribute to what they believe is true and right; find distraction; hunt and mine; share and reciprocate; comment and plus one socially; and so on. It’s a newish medium and no old set of segments or categories captures how people use today’s social tools, and in particular how they relate to the content they create.

At risk with these kinds of broad consumer categories is that they substitute for what consumers are actually doing. That they offer up proxy explanations for why consumers like, identify, choose, and do. That they inform strategy that perpetuates a sense of ownership and control (over the consumer and his/her consumption), because they name the un-nameable, define the ineffable, and capture the ephemeral.

I would advise marketers to learn something from those of us at the user experience end of the equation. We too, have to anticipate what people do. But we know we have to frame it in terms of interaction and experience: how and why and what users do with each other. We learned a while back that it’s not up to us to control or define their experiences.