Behavioral data shows every sign of serving as currency in what is rapidly becoming a world culture of information technology. For digital marketers, the benefit of data-collection can be summed up as a single concept: "insight."
Devout clerics used to argue how many angels could dance on the head of a pin. Some say it’s a certainty that one day, all the knowledge in all the world should fit on one. The world in a grain of sand – or silicon: this awaits us. And the insights we might gain from this concentration of knowledge seem limitless.
Information about everything from the wingspan of the largest insect to the sequence of buttons I have clicked on a website or an app will continue to be stacked like so many sheaves of wheat for the thresher. Behavioral data shows every sign of serving as currency in what is rapidly becoming a world culture of information technology.
For digital marketers, the benefit of data-collection can be summed up as a single concept: “insight.”
We may imagine our clicks and bits and bytes are ephemeral. But even as we forget the last email we sent, our online activity is recorded and, with increasingly rare exception, not merely kept, but ogled, prodded, poked, matched, calculated, combined, compared, and transmogrified into those increasingly precious insights.
Behavioral science is old. How many loaves to bake for Saturnalia? How many nickel cigars to put by for the week before Easter? The provident merchant would know this and more, else find his belongings out on the cobblestones one day.
How did the merchant happen upon these insights? By looking at data. The old-fashioned way was to write consumption data into a day-ledger and in a scene reminiscent of Dickens, have a scrivener copy the data over to a table so that comparisons might be made. Today those scriveners are ghosts in the machine, and we can make comparisons of comparisons never before possible.
And so we come to the modern practice of attempting to understand the customer in all her myriad complexity as she seeks the best deal on a flight to Aruba. Can it be a worthy goal to make the procurement of that flight easier, more foolproof, less time-consuming? And as worthy to study how one might offer a traveler the rental of a car upon arrival? How about a hotel? Not just a hotel, but the right hotel, one she’s more likely to book; as well as the additional deal for rum drinks and a show? What about scuba? Yes, if you know she bought goggles on another site not long ago.
Is this unrelenting collection of data entirely needed? No. The Internet – that is to say, the “http” protocol, html, and the browser – would easily function without it. But you’d have to do without Google, for instance. And probably Amazon. And probably without all but the labors of enthusiasts posting scans of old car manuals labeled with plain blue links. For even such basic provender as a simple site design might be not so pretty, had the developers never bothered to find out which designs prompted a more predictable (and market-desirable) response. Which design we seemed to “like” better based on how we clicked through it. Which one made the phone ring. And the cash register, too.
The creation of better user experiences (“UXP,” as the experts call it) is not founded in altruism. It’s anchored to the bedrock of commerce and the need to drive increasing revenue at a lower transaction cost per advertising dollar. And the common denominator in all commercial digital endeavors is measurability.
Ad-targeting (and content optimization) can be defined as the act of showing you the right offer at the right time in the hope that, having studied your behavioral patterns with enough acuity, your next click may in some way be influenced to the marketer’s benefit. Pattern recognition typically is achieved by the concatenation and automated study of usage details about you, as your work inside the confines of your addressable device – desktop, tablet, or mobile. What do you search for – and select once found? What types of sites have you visited, and what did you buy when you were there? What did you “like” on Facebook?
“Big Data” is the pool out of which emerges a coupon for a home improvement superstore if you have been looking at refinancing rates. Digital analytics is the manner in which Big Data is turned into actionable insights – resulting in that ad from the Home Depot. With the data so available, the algorithms so powerful, and the stakes ever more dizzyingly high, is it any wonder the breadcrumbs of data you leave behind as you pick your way through the online forest are gathered up behind you by search engines, analytics tools, and databases? Entirely separate but quite as fascinating is the fact that the record of your activity becomes the property of the tracking party. Finders keepers!
However, while the appetite for data may be rapacious, the outcome is often no more damnable than if a real proprietor at a real store remembered that you liked your bagel with butter, not cream cheese, and your coffee light and sweet – saving you time on your way to the office.
The darker side to information gathering goes to the Snowden-like revelations about government spying, but that is not what marketers spend their time doing. Instead, they spend their time gathering as much information as they can, always hoping for that precious nugget of data that gives them an opportunity to interact in a way that will result in your clicking, seeing, calling, or buying. The Internet would survive without digital analytics, but it would look very different – and would be a good deal less robust, useful, or interesting. Digital analytics keep digital media much more interesting to both the user and the publisher than otherwise.
