Brandwashed (36 page)

Why were the credit card companies so aggressively going after these young customers? Simple. These students, with their meager incomes, irresponsible spending habits, and high credit limits (thanks to the fact that many of them opened joint accounts with their parents), are cash cows for these banks. According to student lending company Sallie Mae, in 2008 seniors graduated from college with a median credit card debt of more than $4,100, and six years ago, before the recession, the “collegiate affinity market” represented a more than $6 billion credit card debt portfolio.
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Oh, and don’t be fooled: credit card companies
love
it when students max out their cards; in fact, so long as students don’t default on what they owe, this is most credit card companies’ covert goal. Moreover, as Ohio State University researchers found, not only are first-time college-age cardholders eager to buy stuff on credit, but they’re apt to hang on to that particular card for up to fifteen years. No wonder Bank of America’s FIA Card Service Unit outspends its
competitors by 288 percent to entice college students to sign up for its card, according to the Federal Reserve Board of Governors.

What’s most valuable about these customers from a data-mining perspective is that, to prevent these young spenders from falling off the bank’s radar once they graduate, every single one of these affinity agreements requires colleges to provide students’ and graduates’ personal data, including names, phone numbers, and addresses.
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T
he loyalty card is another sneaky yet powerful tool companies use to turn every intimate detail about our lives into marketing gold. Today the average person carries around fifteen so-called
loyalty cards, now being issued by every retailer under the sun, from your local drugstore to Staples to Best Buy to Starbucks. Yet most of us forget we’ve even signed up for all these loyalty schemes. In a study I once conducted in the UK, when I asked a group of middle-aged females how many loyalty programs they belonged to, most were able to recall only half (and when, to jog their memories, I asked them to empty their wallets, most were shocked by the number of cards that fell out). So what’s so bad about loyalty cards, you might be wondering? Isn’t the whole point of them to
save
me money? No, not exactly. Sure, the language and terminology that retailers use in talking about these programs—“reward card,” “loyalty program,” “preferred customer savings”—may make you feel sort of special, or may even lead you to believe that these programs are about rewarding you, loyal customer, with money-saving offers. Well, they aren’t. The reason these clever programs exist isn’t to save you fifty cents here, fifty cents there, as their marketers and advertisers would have you believe. Loyalty programs exist for one simple and rather shifty purpose: to try to persuade you to buy
more
. In fact, each time you sign up for a store’s loyalty program, what you are actually doing is giving the store explicit permission to collect, aggregate, summarize, and crunch unparalleled amounts of information about you, your family, your habits, and your interests—all of which data miners then turn around and use to craft marketing and advertising entreaties too perfect,
too persuasive, and too uncannily targeted to your individual psychology and lifestyle to resist. One study about
Safeway, the supermarket chain, sums up the technique neatly: “Safeway . . . has turned itself into an information broker. The supermarket purchases demographic data directly from its customers by offering them discounts in return for using a Safeway savings club card. In order to obtain the card, shoppers voluntarily divulge personal information that is later used in predictive modeling.”
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In other words, each time we hand the clerk that colorful little card we keep on our key ring, we’re swapping our privacy for a twenty-five-cent savings here, a dollar off there, maybe the occasional buy-two-get-one-free deal.

Have you ever found yourself standing behind someone in the checkout line at the grocery store, trying to figure out who she is based on her purchases? Let’s say she’s buying a package of garlic chicken Lean Cuisine and a six-pack of Diet Coke.
Okay,
you tell yourself,
she probably lives alone and is dieting.
Next she sets down a bottle of high-end shampoo and conditioner.
She’s brand and beauty conscious,
you note,
and probably makes a good living.
Also in her basket are a can of Lysol with bleach and a bottle of Purell, so you figure she’s germ-conscious. Then she surprises you by pulling out a home blood-pressure kit.
Does she have an elderly parent living at home?
you wonder.
Or is she in iffy health herself?
You file this last observation away, awaiting later confirmation.

This kind of speculation, in a nutshell, is what data miners do, only thanks to all the sophisticated data-tracking technology and computer models they have at their disposal, these few purchases tell them a whole lot more about this woman than the naked eye ever could. How? Every time you or I use our loyalty card in a store, a record of what we’ve bought, how much of it, at what time of day, and at what price is sent to a data warehouse, where it is added to our digital folder (most companies and retailers with loyalty programs amass data continuously, then parse it into chunks that sum up our weekly, monthly, and yearly behavior. Then algorithms so complex they would make a math major’s head spin crunch all the data to come up with all kinds of interpretations of who we are and what we’re likely to buy (based on our own buying habits and those of millions of consumers similar to us). For example, when we use a loyalty card to buy groceries, we are being pegged by at
least one supermarket chain as one of six different customer profiles: a “Time Pressed Meat Eater,” a “Back to Nature Shopper,” a “Discriminating Leisure Shopper,” a “No-Nonsense Shopper,” a “One-Stop Socialite,” or a “Middle of the Road Shopper,”
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categories used to target us with specific deals and offers.

There’s no end to what this data can tell companies about what we’re likely to buy. If I buy yogurt and vitamins, the algorithms predict I am probably a good target for an invitation to join the new local gym that just opened up. If I buy ready-to-eat meals, the data shows it’s a sign that I’m a busy guy and more likely to use a coupon that’s delivered straight to my phone than one I have to clip from the newspaper or print from my in-box. If I suddenly start buying baby wipes and diapers, I’ve clearly recently experienced a life change that’s likely left me run down and tired and am statistically likely to jump at a special offer for a day at the spa.

It is by crunching these kinds of numbers that the data-mining industry has uncovered some even more surprising factoids: Did you know, for example, that at Walmart a shopper who buys a Barbie doll is 60 percent more likely to purchase one of three types of candy bars? Or that toothpaste is most often bought alongside canned tuna? Or that a customer who buys a lot of meat is likely to spend more money in a health-food store than a non-meat-eater?

Or what about the data that revealed to one Canadian grocery chain that customers who bought coconuts also tended to buy prepaid calling cards? At first, no one in store management could figure out what was going on. What could coconuts possibly have to do with calling cards? Finally it occurred to them that the store served a huge population of shoppers from the Caribbean islands and Asia, both of whose cuisines use coconuts in their cooking. Now it made perfect sense that these Caribbean and Asian shoppers were buying prepaid calling cards to check in with their extended families back home.

This is all well and good,
you might be thinking,
but how could that supermarket use this information to make more money off us?
Well, first and foremost, it could create what’s known in retail parlance as an “adjacency.” An adjacency is when a store positions two or more products next to each other that are seemingly unrelated but appeal to the same target
customer. This way, after that Jamaican shopper has picked out a coconut to cook with, she need only glance to her left to find the strategically placed display of prepaid phone cards and be reminded she owes Mom a call.

Often adjacencies make stores and companies money by offering us solutions to problems we didn’t even know we had. For example, imagine it’s mid-August and recent incoming data shows that a lot of people are buying frozen strawberry shortcake. Now, typically the ingredients for fresh, homemade strawberry shortcake—local strawberries, bottles of whipped cream, and pound cake—are located in three discrete aisles of the store. However, gleaning from the data that this particular demographic has a weakness for strawberry shortcake, the supermarket installs a stand-alone display of strawberries, whipped cream, and pound cake at the front of the store. Thus, the shopper enters the store, murmurs to herself,
Instant fresh dessert?
Why didn’t I think of that?
, and swooshes all three into her basket—costing herself about three times as much as a box of Sara Lee.

Some businesses are using the adjacency technique to turn even bigger profits. Take Marks & Spencer, the upscale English department store chain. A few years back, by parsing the data taken from loyalty cards, its management noticed that more and more of its customers were buying Indian-style dishware, followed by ready-to-eat Indian meals. When management realized that a large number of first- and second-generation Indians must have started shopping there, a lightbulb went off. Why not open a currency exchange office right there in the store? Then another thought occurred: why not sell a service organizing travel to these countries? Which is why the retailer partnered with Thomas Cook, the UK’s largest travel agency, to create the Marks & Spencer Travel Club, which offers holiday discounts as well as “loyalty points when you book your holiday using your M & S Credit Card.”
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But this isn’t all companies do with the information they compile from our loyalty cards. Not by a long shot. To truly see the volumes that even an innocent trip to the grocery store can tell a company about us, and what it then does with that knowledge, let’s take a quick trip to a regional grocery chain we’ll call Sparky’s.

First off, mind if I note right off the bat here that Sparky’s was
smart to position its front door on the right? That’s because data compiled from a study of two hundred stores reveals that shoppers who move counterclockwise spend two dollars more per trip than those who go in the opposite direction. Human beings are naturally more inclined to move to the left (because it’s easier to reach out with our right arms to grab whatever it is we need), so a right-side entryway is a subtle yet effective way to ensure a counterclockwise shopping flow. I might add here that Sparky’s was smart to outfit its store with oversize shopping baskets, as studies show that the bigger the shopping basket, the more likely we are to fill it to the brim.

After desperately making my way through the labyrinth of shelves, towers of products, and special displays looking for the apples, I find the Granny Smith apples and put five in my basket (I really only wanted three, but I saw the sign saying “buy four, get one free” and immediately fell for the classic ploy that author William Poundstone calls “
nonlinear
pricing,” meaning the store has upped the price of those four apples by 20 percent so I’m actually paying the exact same amount per apple even though I think I’m getting a bargain). My choice of organic apples tells Sparky’s database that I’m pretty well educated, make a good living, and am more likely to buy eco-friendly products. No surprises there.

Let’s pause once again. Notice how I had to navigate around numerous displays before I chanced upon the apples? It’s no coincidence. The more complex the navigation paths we’re asked to walk, the slower we walk, and the slower we walk, the more
stuff
we are exposed to . . . and tempted to buy. In order to combat the increasing sophistication of shoppers, many of whom have learned to arm themselves with shopping lists and make a beeline for what they want, more and more
supermarkets are mixing around groceries—or changing the location of items on a monthly basis—so it’s harder for us to find what we’re looking for. The result is that not only are we tempted by more products, but finding what we want becomes a game of sorts (remember the power of
games?), at the end of which we often reward ourselves for our hard work by buying something that wasn’t on our list.

Next, over by the pharmacy aisle, I pick up a package of Nicorette (even though I’ve never smoked; it’s just part of my little experiment). By my buying the Nicorette, Sparky’s is immediately able to establish that
I’m almost certainly between the ages of twenty-five and fifty-four and more likely to buy name-brand products over the generic or store-brand variety. Again, makes sense, right?

Next, just for fun, I buy a package of Jheri curl texturizer in the women’s hair-care section and a small box of Dora the Explorer Band-Aids. Now the store will make two fairly good assumptions about me: that I’m an African American female and that I have a child under the age of five—and am thus a good candidate for coupons and offers on those particular brands of everything from juice to breakfast cereals to cosmetics that the data miners have found to appeal to my demographic.

Tucked away at the rear of the store, so the pharmacists can keep a close watch on teenage boys, the condom display takes up half a shelf. Just for fun, I pick up a pack of neon, ribbed ones. Now I’m
confirming
to the data miners that I’m a woman (who just happens to be named Martin). Why? Because most people who buy
condoms are, in fact, female (note that the name of the section is “family planning,” which subtly targets the female of the household by implying that this is the section for the person who is generally in charge of schedules, date books, doctors’ appointments, and, yes, condom use). Incidentally, this is why nine tenths of the condoms for sale proudly exhibit the words “sensitive” and “thin,” two adjectives guaranteed to strike a chord with the contemporary woman.