In February 2012, the New York Times investigated some of Target’s data mining practices. What it found was both scary and interesting. It seems that by scouring through its data, Target can profile you as a consumer all in an effort to better serve you by offering promotions and discounts on products you can actually use. Sounds good, doesn’t it? After all, who doesn’t want to save money when they shop at Target? Well, it’s not always as wonderful as it sounds. Here’s what the NYT found out:
“[Target statistician Andrew Pole] 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.
As Pole’s computers crawled through the data, he was able to identify about 25 products that, when analyzed together, allowed him to assign each shopper a ‘pregnancy prediction’ score. More important, he could also estimate her due date to within a small window, so Target could send coupons timed to very specific stages of her pregnancy.”
Here’s where the story takes an interesting turn. An angry man went into a Target outside of Minneapolis, demanding to talk to a manager:
“‘My daughter got this in the mail!’ he said. ‘She’s still in high school, and you’re sending her coupons for baby clothes and cribs? Are you trying to encourage her to get pregnant?’
The manager didn’t have any idea what the man was talking about. He looked at the mailer. Sure enough, it was addressed to the man’s daughter and contained advertisements for maternity clothing, nursery furniture and pictures of smiling infants. The manager apologized and then called a few days later to apologize again. On the phone, though, the father was somewhat abashed. ‘I had a talk with my daughter,’ he said. ‘It turns out there’s been some activities in my house I haven’t been completely aware of. She’s due in August. I owe you an apology.'”
What this case reveals, of course, is the troublesome nature of data mining. It seems fairly innocent; that is, until someone’s privacy is violated in a big way. I’m certain that Target didn’t intend for anyone to find out that their daughter was pregnant the hard way. Regardless, it points to the need for information technology experts to think about how they’re using data and what the possible ramifications are. To me, that’s the real lesson of this case––we should pause to reflect on what we do and who might be affected. Unfortunately, there never seems to be enough time to do that. And therein lies the challenge: how to do the right thing when reflection isn’t always possible.
Source: forbes.com, nytimes.com, geekwire.com
Media Ethics Report 