Data-mining – a Holy Grail for the business of the future

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How many loyalty cards do you have in your wallet? Their purpose is not just for companies to send you irrelevant offers but also so they learn about your shopping habbits – what you like, need and what offers would please you most. Some companies are doing better than others but the American retailer Target seems to be in a league of their own as they figured out a way to look into people’s stomachs and find weather they are pregnant or not.

Timing is of Essence
One study from Duke University cited in a New York Times article estimated that “habits, rather than conscious decision-making, shape 45 percent of the choices we make every day”. There are, however some moments in people’s lives when changes shake old routines. One of those moments is the awaiting and preparation for a child birth, when parents to be need to buy loads of new stuff. This is when their shopping habits and brand loyalties are up for the taking.

Timing however is of essence as the baby shopping habits start to form around the end of the first trimester, long before the baby is registered in the public records or it became visible that the woman is pregnant.

The problem for Target is that while it sells everything from milk, toys and clothing to furniture and TVs, many people will only buy from the store certain types of products and the rest from other shops. For pressed parents the goal is to make Target a one stop shop. Sounds good but shopping habits are difficult to change. Target knew however that if they could get parents to buy diapers from them, they could capture their customer loyalty for years and get them to buy loads of other stuff as well – from milk and orange juice to stuffed animals and DVDs.

Data-mining discoveries
Charles Duhigg outlines in a New York Times article what Target found with the data mining. They assign every customer a Guest ID number, linked to their credit card, name or e-mail. This ID becomes a storage of data for everything they have bought and any demographic information that Target has collected or bought. The statistical team looked at the historical buying data for all the ladies who had signed up for Target baby registries in the past. After some tests a number of patterns started to emerge – women on the baby registry were buying larger quantities of unscented lotion around the beginning of their second trimester; pregnant women loaded up on supplements like calcium, magnesium and zinc at some point during the first 20 weeks. Whilst many people buy soap and cotton balls, when someone suddenly starts buying loads of scent-free soap and extra-big bags of cotton balls, in addition to hand sanitizers and washcloths, it signals that they might be getting close to their delivery date. The data mining allowed the Target team to identify about 25 products, on the basis of which they could assign a “pregnancy prediction” score to each woman and even predict the delivery date within a small window.

Don’t spook customers
Armed with that information the Target marketing team started to send customers coupons timed to very specific stages of the pregnancy. However as Target soon found out, the fact they knew such intimate information could spook customers. In his article Duhigg shares an anecdote — so good that it sounds made up — that conveys how eerily accurate the targeting is. The father of a girl went into a Target store demanding to speak 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.”

Target learned the lesson and started adding in ads for things pregnant women would never buy, so the baby ads look random e.g. a coupon for wineglasses next to kids’ cloths and a lawn mower next to diapers. This way people would think that everyone one the street got the same offers.

Arms race to hire Statisticians
Companies like Target, Amazon, eBay are leading the way in personalising the ads for their customers and are setting a new norm. We recently spoke with the customers of a charge card company and they were expecting the company to be able to send them personalised offers as it had their spend data but the company wasn’t utilising it in this way. As it becomes increasingly easier for companies to track their customers spending whether it’s done online, via their credit or loyalty card or by buying a panel of consumer data, companies may find themselves in a race to hire statisticians.
There is also the learning from Tesco’s (UK’s largest supermarket chain) Big Price Drop fiasco over the Christmas festive season last year. Under “The Big Price Drop” Tesco would invest £500m in cutting prices across the board. But, to fund this, it had to end its generous double discounts Club Card scheme. This essentially meant that Tesco, which has the highest market share, would not reward its most loyal customers who use their club cards throughout the year with special vouchers but instead will “reward” everyone the same way with a highly perceptual price drop at a season when everyone else also runs special offers. In the end Tesco got his worst Christmas in years and the initiative gained the name “The Big Price Flop”. The learning however is that using the data from the clubcards to send vouchers to customers for products that would fit customers’ needs and would bring them to the shop to buy everything else they need might be a much better strategy than simply reducing the prices across the whole.

Key to beat Showrooming
Data-mining could also prove a powerful tool to beat the showrooming trend in which consumers visit a retailer to check a product and then buy it online where it is cheaper. This puts brick-and-mortar retailers such as WallMart, Target, Best Buy in a less advantageous position to online retailers such as Amazon. As Anne Zybowski, director of retail insights for Kantar, puts it cited in a WSJ article: “Offering people personalized prices through their mobile device may be the most effective way to beat showrooming”. Thus Target is sending daily-deal alerts and exclusive discount coupons to its customers’ mobile phones. UK retailer Sports Direct is also sending daily deals to its customer base via e-mail.

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