The Power of Habit – Why We Do What We Do in Life and Business

instance, provides every new mother with a gift bag containing samples of hair gel, face wash, shaving cream, an energy bar, shampoo, and a soft-cotton T-shirt. Inside are coupons for an online photo service, hand soap, and a local gym. There are also samples of diapers and baby lotions, but they’re lost among the nonbaby supplies. In 580 hospitals across the United States, new mothers get gifts from the Walt Disney Company, which in 2010 started a division specifically aimed at marketing to the parents of infants. Procter & Gamble, Fisher-Price, and other firms have similar giveaway programs. Disney estimates the North American new baby market is worth $36.3 billion a year. [202]

But for companies such as Target, approaching new moms in the maternity ward is, in some senses, too late. By then, they’re already on everyone else’s radar screen. Target didn’t want to compete with Disney and Procter & Gamble; they wanted to beat them. Target’s goal was to start marketing to parents before the baby arrived-which is why Andrew Pole’s colleagues approached him that day to ask about building a pregnancy-prediction algorithm. If they could identify expecting mothers as early as their second trimester, they could capture them before anyone else.

The only problem was that figuring out which customers are pregnant is harder than it seems. Target had a baby shower registry, and that helped identify some pregnant women-and what’s more, all those soon-to-be mothers willingly handed over valuable information, like their due dates, that let the company know when to send them coupons for prenatal vitamins or diapers. But only a fraction of Target’s pregnant customers used the registry.

Then there were other customers who executives suspected were pregnant because they purchased maternity clothing, nursery furniture, and boxes of diapers. Suspecting and knowing, however, are two different things. How do you know whether someone buying diapers is pregnant or buying a gift for a pregnant friend? What’s more, timing matters. A coupon that’s useful a month before the due date might get put in the trash a few weeks after the baby arrives.

Pole started working on the problem by scouring the information in Target’s baby shower registry, which let him observe how the average woman’s shopping habits changed as her due date approached. The registry was like a laboratory where he could test hunches. Each expectant mother handed over her name, her spouse’s name, and her due date. Target’s data warehouse could link that information to the family’s Guest IDs. As a result, whenever one of these women purchased something in a store or online, Pole, using the due date the woman provided, could plot the trimester in which the purchase occurred. Before long, he was picking up patterns.

Expectant mothers, he discovered, shopped in fairly predictable ways. Take, for example, lotions. Lots of people buy lotion, but a Target data analyst noticed that women on the baby registry were buying unusually large quantities of unscented lotion around the beginning of their second trimester. Another analyst noted that sometime in the first twenty weeks, many pregnant women loaded up on vitamins, such as calcium, magnesium, and zinc. Lots of shoppers purchase soap and cotton balls every month, but when someone suddenly starts buying lots of scent-free soap and cotton balls, in addition to hand sanitizers and an astounding number of washcloths, all at once, a few months after buying lotions and magnesium and zinc, it signals they are getting close to their delivery date.

As Pole’s computer program crawled through the data, he was able to identify about twenty-five different products that, when analyzed together, allowed him to, in a sense, peer inside a woman’s womb. Most important, he could guess what trimester she was in-and estimate her due date-so Target could send her coupons when she was on the brink of making new purchases. By the time Pole was done, his program could assign almost any regular shopper a “pregnancy prediction” score.

Jenny Ward, a twenty-three-year-old in Atlanta who bought cocoa butter lotion, a purse large enough to double as a diaper bag, zinc, magnesium, and a bright blue rug? There’s an 87 percent chance that she’s pregnant and that her delivery date is sometime in late August. [203] Liz Alter in Brooklyn, a thirty-five-year-old who purchased five packs of washcloths, a bottle of “sensitive skin” laundry detergent, baggy jeans, vitamins containing DHA, and a slew of moisturizers? She’s got a 96 percent chance of pregnancy, and she’ll probably give birth in early May. Caitlin Pike, a thirty-nine-year-old in San Francisco who purchased a $250 stroller, but nothing else? She’s probably buying for a friend’s baby shower. Besides, her demographic data shows she got divorced two years ago.

Pole applied his program to every shopper in Target’s database. When it was done, he had a list of hundreds of thousands of women who were likely to be pregnant that Target could inundate with advertisements for diapers, lotions, cribs, wipes, and maternity clothing at times when their shopping habits were particularly flexible. If a fraction of those women or their husbands started doing their shopping at Target, it would add millions to the company’s bottom line.

Then, just as this advertising avalanche was about to begin, someone within the marketing department asked a question: How are women going to react when they figure out how much Target knows?

“If we send someone a catalog and say, ‘Congratulations on your first child!’ and they’ve never told us they’re pregnant, that’s going to make some people uncomfortable,” Pole told me. “We are very conservative about compliance with all privacy laws. But even if you’re following the law, you can do things where people get queasy.”

There’s good reason for such worries. About a year after Pole created his pregnancy prediction model, a man walked into a Minnesota Target and demanded to see the manager. He was clutching an advertisement. He was very angry.

“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 gazing into their mothers’ eyes.

The manager apologized profusely, and then called, a few days later, to apologize again.

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.” He took a deep breath. “She’s due in August. I owe you an apology.”

Target is not the only firm to have raised concerns among consumers. Other companies have been attacked for using data in far less intrusive ways. In 2011, for instance, a New York resident sued McDonald’s, CBS, Mazda, and Microsoft, alleging those companies’ advertising agency monitored people’s Internet usage to profile their buying habits. [204] There are ongoing class action lawsuits in California against Target, Walmart, Victoria’s Secret, and other retail chains for asking customers to give their zip codes when they use credit cards, and then using that information to ferret out their mailing addresses. [205]

Using data to predict a woman’s pregnancy, Pole and his colleagues knew, was a potential public relations disaster. So how could they get their advertisements into expectant mothers’ hands without making it appear they were spying on them? How do you take advantage of someone’s habits without letting them know you’re studying every detail of their lives?¹

II.

In the summer of 2003, a promotion executive at Arista Records named Steve Bartels began calling up radio DJs to tell them about a new song he was certain they would love. It was called “Hey Ya!” by the hip-hop group OutKast.

“Hey Ya!” was an upbeat fusion of funk, rock, and hip-hop with a dollop of Big Band swing, from one of the most popular bands on earth. It sounded like nothing else on the radio. “It made the hair on my arms stand up the first time I heard it,” Bartels told me. “It sounded like a hit, like the kind of song you’d be hearing at bar mitzvahs and proms for years.” Around the Arista offices, executives sang the chorus-“shake it like a Polaroid picture”-to one another in the hallways. This song, they all agreed, is going to be huge.

That certainty wasn’t based solely on intuition. At the time, the record business was undergoing