Marketing Communication Methods

How does this work in practice? If you've ever paid off an auto loan, you may have noticed a torrent of mail offers from car dealerships right around the five-year mark. They know, from your credit history, that you're nearly done paying off your car and you've had the vehicle for several years, so you might be interested in trading up for a newer model. Based on your geography and any voter registration information, you may be targeted during election season to participate via telephone in political polls and to receive "robocalls" from candidates and parties stomping for your vote.

Moving into the digital world, virtually any time you share an email address with an organization, it becomes part of a database to be used for future marketing. Although most organizations that engage in email marketing give the option of opting out, once you become a customer, it is easy for companies to justify continuing to contact you via email or text as part of the customer relationship you've established. As you continue to engage with the company, your behavior and any other information you share becomes part of the database record the company uses to segment and target you with offers it thinks will interest you.

Similarly, marketers use SMS (text) for marketing purposes, and direct marketing activity takes place in mobile apps, games, and Web sites. All of these tools use the data-rich mobile environment to capture information about consumers and turn it into productive marketing opportunities. QR codes, another direct-to-consumer mobile marketing tool, enable consumers to scan an image with a mobile phone that takes them to a Web site where they receive special information or offers.

 

A great illustration of how companies use consumer information for direct marketing purposes comes from a New York Times article that interviewed Andrew Pole, who conducts marketing analytics for the retailer Target. The article discusses how Target uses behavioral data and purchasing history to anticipate customers' needs and make them offers based on this information:

Target has a baby 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 twenty 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 twenty-five 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.

One Target employee I spoke to provided a hypothetical example. Take a fictional Target shopper named Jenny Ward, who is twenty-three, 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.

The article goes on to tell the well-documented story of an outraged father who went into his local Target to complain about the mailer his teenage daughter received from Target featuring coupons for infant clothing and baby furniture. He accused Target of encouraging is daughter to get pregnant. The customer-service employee he spoke with was apologetic but knew nothing about the mailer. When this employee phoned the father a few days later to apologize again, it emerged that the girl was, in fact, pregnant, and Target's marketing analytics had figured it out before her father did.