Look at your phone. Go on, look at it. What is it?
It’s a clock. It’s a text-messaging glass slab. It’s a dynamically updating map/tracking device. It’s a ticket. It’s a late-night magazine. It’s an alarm clock. It’s a camera, photo album and publishing platform. It’s a gaming device, newsfeed(s), and a tether keeping work with you 24 hours a day.
Your laptop: it’s forty tabs open at once, word processing documents, music libraries (if you’re old), an EVEN BETTER gaming device, a TV and movie-watching platform, an audio editing suite, and, uh, other forms of entertainment.
You use these devices for dozens of different purposes, out of convenience and functional capacities. What I want you to think about is who you are in each of those purposes, and for whom you are in those purposes.
One of the most intriguing findings from my dissertation research (read it! become a member of a tiny club!) lo these four years ago was the degree to which students segregated audiences by medium. As I put it, they “use different communications technologies in their interactions with social, familial and academic audiences, in part as a manner of combatting the context collapse taking place on social network sites and mediated communications generally.” More directly: they talked to their friends via text message and Facebook message, called their parents on the phone, and only and ever talked to their professors in person and via email. That was, as they say, interesting, and something worthy of further study.
Well: I didn’t. But while the particular practices have shifted in the intervening time, these behaviors are no less intriguing or worthy of study and contemplation.
Cross-medium behavioral research is rare for a number of reasons. It’s expensive, difficult, time-consuming, methodologically fraught, ethically fraught. But I think the main limiting factor is that in any given moment, the incentives for any organization or individual performing research is to answer their central questions, as quickly/cheaply as possible. For an advertising firm: how did a given campaign deliver on KPIs as promised to the client? For an academic researcher: how does X behavior impact on my hopefully-tenure-securing line of research? For a membership organization: what were the A/B test results on a fundraising solicitation?
And to be crystal clear, this is NOT a problem solved by “Big Data.” Few but the most world-spanning organizations have the capacity to iteratively formulate hypotheses, expand data collection across boundaries, and act on findings. And the evidence suggests that even those world-spanning organizations don’t really know what to do with their endless reams of data. But, really, that’s neither here nor there: if you aren’t inside one of the world’s larger walled gardens of behavioral data, you’re still left with the same question. Namely: just who are your users, and who (and when, and how) are you to your users?
One of the foremost issues is attention. There are two ways of looking at attention: as something to maintain, and as something to be acquired. From your perspective, dear reader, you of course want to maintain sustained attention – on relationships, on work, on engaging culture. An advertiser, on the other hand, wants to capture your attention. Chartbeat – which makes a fantastic suite of products for publishers, that I’ve used and enjoyed – is part of a tech vanguard that recognizes this. As they put it:
Online publishers know clicks don’t always reflect content quality.
But research shows more time spent paying attention to content does.
Advertisers know click-through rates don’t matter for display or paid content.
Research shows 2 things matter for getting a brand’s message across: the ad creative and the amount of time someone spends with it.
The Attention Web is about optimizing for your audience’s true attention.
From their perspective, attention equals quality, and a shift to focusing on quantifying attention means better quality content (oh and also more clients). It’s a compelling thesis – but then, it is your attention that they’re selling, to advertisers. Others are more interested in selling your attention to, well, you:
As our computing devices have become smaller, faster, and more pervasive, they have also become more distracting. The numbers are compelling: Americans spend 11 hours per day on digital devices, workers are digitally interrupted every 10.5 minutes, with interruptions costing the U.S. economy an estimated $650 Billion per year. That’s a lot of distraction.
Device makers have largely turned a blind eye to this issue, building distractions in to the very devices we need for work. We address this challenge with tools that simply and effectively reduce digital distractions. Our software interrupts the habitual cycle of distraction associated with social media, streaming sites, and games.
Attention is basically an adversarial dynamic: your devices and the advertiser-supported content therein yelling at you while you struggle to maintain concentration. Many or most of us are in this stage of managing our relationships with digital communicative prostheses – a struggle. It’s not a struggle without benefits, but nor is it one without costs – study after study shows the costs to both productivity and personal health and well-being of a consistently-interrupted existence.
A central part of this struggle is creating a hierarchy – either explicit or implicit – of attention. When do you respond to a text message? It depends when you receive it, and from whom. Do you return an email? Again: who sent it, work or personal, when did it get received? And then: what do you read, or listen to? That also depends – how did you get there? A link from a friend, an immediately-forgotten source on your social media timeline, through a series of unreproducible clicks? The depth, length, and quality of the attention devoted depends on all these factors and more – but I believe it’s impossible to understand the meaning of a given interaction without looking at how these hierarchies are created.