A picture of me standing at a lectern, working on a laptop computer, on the stage of the FWD50 digital government conference

Hi! I’m Alistair. I write surprisingly useful books, run unexpectedly interesting events, & build things humans need for the future.

Interrupting gracefully

As we’ve seen, in an information-rich world, attention is a precious commodity. One reason Google is successful is that it has positioned itself as an exchange between money and attention—more attention gives you a better ranking, which means more money; paid ads buy you more attention.

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That means that in order to survive, you have to get someone’s attention. And for that, you need to be good at interrupting. You need to build graceful interruption into everything you build.

Interruption happens in three timeframes: before, during, and after someone realizes they have a need. Each is a specific use case for marketers.

When the customer’s already satisfying the need

Here’s a great example, by way of Jen Rubio, of Google changing an interface in order to keep you abreast of what’s going on.

A reservation by @jennifer from her email

Here, Google has parsed something that’s already underway for Jen—in this case, a coming hotel reservation—and made it easy for her to adjust that reservation. By parsing your email, they’ve added value, and made themselves the default tool for managing travel.

For another example, consider a commuter walking past a bus stop. If a travel application knew what time the next bus was coming, where you live, what meetings are in your calendar, and where you’re usually headed, it could notify you about how long you’d have to wait—and perhaps convince you to buy a bus ticket. You’re already in transit, but by gracefully interrupting with useful, contextual information, it can change your behavior.

At the moment of the question

The perfect form of interruption is answering a question. When someone asks something, if you respond, it’s not an interruption at all—it’s a response.

Search engines are ideally positioned to do this. When I ask for something, they can respond. But they need to strike a balance between value (giving me the right answer) and filthy lucre (giving me the answer from which they will gain the most.) They’re walking a fine line, and knowing when they’ve gone too far is a matter of constant optimization.

Before they know they need an answer

Amazon experiments a lot. One of the things they’re working on shipping you things before you know you need them. Predictive models mean we can anticipate a customer’s needs and respond to them before they’re manifested.

Phone carriers know this. They invest heavily in technology to predict customers who are about to churn, offering to sweeten the deal or send them a new handset in return for a contract renewal. But sometimes, prediction can go too far, as the much-cited example of Target anticipating a customer’s pregnancy before she’d told her family has demonstrated.

The field of predictive science is blossoming. There’s a resurgence of interest in data science, along with a torrent of data exhaust we can analyze and digital, one-to-one channels we can use to test things quickly. When I was discussing this with Joe Wilkinson a few weeks ago, he observed,

It would be the ultimate goal of most apps: knowing what someone wants, when they want it, and giving it to them before they ask.

It seems to me, though, that something like Watson needs to become a lot cheaper, and perhaps even smarter, for most apps to be able to do that. The best app wouldn’t even need your input for where you live or work.

At Strata last month, Sociometric Solutions’ Ben Waber presented a fascinating talk on sensing best practices. When your body is under stress, it produces cortisol. You can measure the amount of cortisol in saliva and see how stressed someone is. In one example, Ben looked at how a small device worn around the neck can detect stress through voice analysis—fifteen minutes before the stress shows up in saliva (which makes me wonder: Can office installations be far away?)

This is one reason why companies like Apple are so interested in biosensing. The more you can discover ambiently about your market—its location, its mood, its preferences, its health, the weather, its budget—the better you can anticipate its needs. If Apple owns the sensor that you need to anticipate demand, they’ll effectively be able to tax every microtransaction the way they do apps in the app store.

Benford’s Law, a variant on Clarke’s Law, says that “Any technology distinguishable from magic is insufficiently advanced.” Tomorrow’s smartest companies will figure out how to interrupt gracefully—not too creepy, with the right mix of value and commerce—and it’ll seem magical, like a prosthetic brain upgrade rather than a marketing pitch.

So what should you do?

When you’re creating new marketing campaigns, or designing new products, ask yourself three questions:

  • How can I gracefully interrupt something already in progress?
  • How do I become the place my target market goes to ask questions?
  • How do I anticipate needs without being creepy, based on my customers’ data exhaust?

This is more than a set of marketing techniques. As we come to rely on the devices and feeds around us, they will supplant many of our existing senses, much as we forgot our friends’ numbers when we got mobile phones. It’s a fundamental shift in the way brands and customers interact. Just cycle time trumps scale, so interruption beats promotion.

If you made it this far, here’s a video from Genconnect of Ben talking about devices that can measure how you’re feeling.