The Null Device

Predictive analytics and the hidden manipulators

The New York Times has a fascinating article about how retail companies use data mining and carefully targeted coupons to analyse and influence the spending habits of consumers, without the consumers getting wise to what's happening and resisting:
Almost every major retailer, from grocery chains to investment banks to the U.S. Postal Service, has a “predictive analytics” department devoted to understanding not just consumers’ shopping habits but also their personal habits, so as to more efficiently market to them. “But Target has always been one of the smartest at this,” says Eric Siegel, a consultant and the chairman of a conference called Predictive Analytics World. “We’re living through a golden age of behavioral research. It’s amazing how much we can figure out about how people think now.”
A specific case the article describes is that of finding new parents-to-be, who will soon be in a position of having to form new spending habits, and doing so before the competition can identify them from public information; which is to say, inferring from statistical information whether a customer is likely to be pregnant, and at which stage, and then subtly manipulating her spending through the various milestones of her child's development:
The only problem is that identifying pregnant customers is harder than it sounds. Target has a baby-shower registry, and Pole started there, observing how shopping habits changed as a woman approached her due date, which women on the registry had willingly disclosed. He ran test after test, analyzing the data, and before long some useful patterns emerged. Lotions, for example. Lots of people buy lotion, but one of Pole’s colleagues noticed that women on the baby registry were buying larger quantities of unscented lotion around the beginning of their second trimester. Another analyst noted that sometime in the first 20 weeks, pregnant women loaded up on supplements like calcium, magnesium and zinc. Many shoppers purchase soap and cotton balls, but when someone suddenly starts buying lots of scent-free soap and extra-big bags of cotton balls, in addition to hand sanitizers and washcloths, it signals they could be getting close to their delivery date.
One Target employee I spoke to provided a hypothetical example. Take a fictional Target shopper named Jenny Ward, who is 23, lives in Atlanta and in March bought cocoa-butter lotion, a purse large enough to double as a diaper bag, zinc and magnesium supplements and a bright blue rug. There’s, say, an 87 percent chance that she’s pregnant and that her delivery date is sometime in late August. What’s more, because of the data attached to her Guest ID number, Target knows how to trigger Jenny’s habits. They know that if she receives a coupon via e-mail, it will most likely cue her to buy online. They know that if she receives an ad in the mail on Friday, she frequently uses it on a weekend trip to the store. And they know that if they reward her with a printed receipt that entitles her to a free cup of Starbucks coffee, she’ll use it when she comes back again.
The uncanny accuracy of the algorithm is demonstrated by an anecdote about an angry father storming into a Target store demanding why they had sent his teenaged daughter coupons for nappies and prams, and then, some time later, returning to apologise, having discovered that she had, in fact, become pregnant.

Of course, there is the small issue of how to use this wealth of information in a plausibly deniable sense, without being obviously creepy. People, after all, tend to react badly to being surreptitiously watched and manipulated, especially so when deeply personal matters are involved:

“With the pregnancy products, though, we learned that some women react badly,” the executive said. “Then we started mixing in all these ads for things we knew pregnant women would never buy, so the baby ads looked random. We’d put an ad for a lawn mower next to diapers. We’d put a coupon for wineglasses next to infant clothes. That way, it looked like all the products were chosen by chance. And we found out that as long as a pregnant woman thinks she hasn’t been spied on, she’ll use the coupons. She just assumes that everyone else on her block got the same mailer for diapers and cribs. As long as we don’t spook her, it works.”

There are no comments yet on "Predictive analytics and the hidden manipulators"