It takes less than 30 milliseconds to determine a web-user’s value to advertisers, apparently, which is either a marvel of engineering or a foreboding of a Kafkaesque future in which our lives are guided by all-knowing machines whose processes are beyond comprehension. Or both.
Or anyway, that’s the way The New York Times spins its dive into real-time bidding for digital advertising, an emerging industry in which practitioners dump a given web-user’s data into an algorithm, and the algorithm pumps out an approximation of what said user is worth to a given advertiser—all in the time it takes a web page to load.
Viewed through the prism of the Rubicon Project, an ad-sales platform that says 97 percent of U.S. internet users interact with its system each month, the process works something like this:
Most sites … compile data about their own visitors through member registration or by placing bits of computer code called cookies on people’s browsers to collect information about their online activities. To those first-party profiles, Rubicon typically adds details from third-party data aggregators, like BlueKai or eXelate, such as users’ sex and age, interests, estimated income range and past purchases. Finally, Rubicon applies its own analytics to estimate the fair market value of site visitors and the ad spaces they are available to see.
The whole process typically takes less than 30 milliseconds.
That’s great for advertisers sick of the inefficient “spray and pray” strategies they depended on for years. For consumer advocate-types, though, the real-time methods raise an old set of tensions: It’s great to get things for free, less great when we realize we’re paying by participating in an invisible market for information about ourselves.
Put it another way, it’s pretty innocuous when the systems are asserting different pricing on the respective page views from a high-net worth individual and a Chinese teenager, but maybe less so when a payday lender is putting its ads in front of the highly indebted?