Numbersense: How to Use Big Data to Your Advantage by Kaiser Fung

Author:Kaiser Fung [Fung, Kaiser]
Language: eng
Format: mobi
Publisher: McGraw-Hill
Published: 2013-06-19T14:00:00+00:00

Why Do Marketers Send You Mixed Messages?

The mass retailer Target, with the famed red bull’s-eye logo, made the front page of New York Times Magazine in 2012 with an eye-catching—to others, appalling—application of customer targeting. The journalist Charles Duhigg describes the working of a statistical model that predicts if a female customer is in the second trimester of pregnancy:

Take a fictional Target shopper named Jenny Ward, who is 23, 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 … [The marketers at Target] 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. And they know that if they reward her with a printed receipt that entitles her to a free cup of Starbucks coffee, she’ll use it when she comes back again.

Marketers have marked pregnancy as one of the few life events that cause women to alter their shopping habits, and if Target beats other retailers to the chase—by jumping in front of the barrage of deals that bombard these women once the birth records become public—Target could steal market share from its competitors. According to Duhigg’s informant, Target achieved a remarkable spurt in the sales of baby products after deploying a marketing program to reach women predicted to be pregnant.

This type of predictive technology benefits from Big Data—the construction of gargantuan databases that record every trivial interaction between a customer and a business. Chris Anderson, the former editor-in-chief of Wired magazine, once argued that when data become plentiful, every detail is exposed, nothing needs explaining, and theory is passé. Are we entering such a world? Is this world as scary as it sounds? As more and more companies invest in targeting machinery, it is imperative that we learn what they are doing, and how they are doing it. How accurate are Target’s predictions? Something about information technologies causes reporters to lose their bearing, and so it is with the practice of customer targeting: Does the substance justify the hype?

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