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A man enters a Target in Minneapolis, expressing his frustration over baby clothes and crib coupons his teenage daughter received. “Are you trying to encourage her to become pregnant?” he questions a store manager. Little did he know, his daughter was indeed expecting. Target’s marketing-prediction model had become so refined that it could accurately discern the inner workings of her body before her own family had any inkling of the news. This anecdote, recounted by Charles Duhigg in The New York Times back in 2012, has since become one of the most notorious tales of the digital age. And rightfully so – it transforms a mundane consequence of digital marketing strategy into a gripping personal-privacy mystery with high stakes. It captivates audiences by tickling their conspiratorial fears that companies, thanks to the data we unwittingly share, can unearth our deepest secrets.
However, the reality is not quite as sensational. Target did not precisely predict the girl’s pregnancy or divulge it to her father. Admittedly, the teenager’s secret may have been exposed, but mostly because she couldn’t deny the accuracy of Target’s advertising mechanism. Target didn’t really “predict” anything – the retailer simply sent personalized marketing based on algorithms that suggested products a specific customer might be interested in. But for consumers unfamiliar with retailers amassing copious amounts of data about their lives, it felt like a prediction, just as many other targeted ads do in the online realm. There is a tendency to attribute savvy and even mystical intelligence to consumer data, as if large companies possess Minority Report-style clairvoyants capable of unveiling our most intimate thoughts before we even conceive of them.
Unfortunately, the reality is far more disconcerting. Retail companies amass vast quantities of incredibly sensitive data, including demographic information, geographic location, visited websites, frequented brick-and-mortar stores, owned products, perused products, searched products, and even products they suspect you may have considered but ultimately decided against purchasing. They do all this not simply to predict your future behavior, but to manipulate it.
In marketing, segmentation refers to dividing customers into distinct groups based on shared characteristics in order to tailor appeals to them. While segmentation has always been somewhat artificial, it used to correspond to genuine categories or identities, such as soccer moms or gamers. Over time, these segments have become increasingly precise and specific, to the point where retailers now have enough data to create a segment exclusively for each individual. It’s not just about targeting you; it’s about targeting you at this very moment in time. They personalize marketing messages for unique individuals at specific points in their lives.
You might be wondering, why should this concern you? If stores can offer the best deals on the most relevant products to you, why not let them do it? However, you may not even know which products are truly relevant anymore. Customizing offerings and prices to increasingly smaller customer segments is undeniably effective; it causes people to change their shopping habits, to the advantage of stores and their data-hungry machines. It gives retailers the power to exploit your private information to separate you from your money. The erosion of retail privacy warrants concern not solely because these stores could unearth or expose your secrets based on the data they collect about you. It’s the fact that they can employ this data to influence your purchasing behavior so effectively that they can reshape your desires.
Until about a century ago, sellers possessed a similar power, albeit in a different manner. To purchase goods like rice, fabric, or automobiles, one had to haggle. This allowed sellers to maximize profit based on their perception of what customers were willing to pay. It also gave them the ability to reward or punish customers based on how they appeared, such as their gender, race, or religion. Consequently, people bought the goods that sellers allowed them to buy. However, the advent of department stores and grocery chains disrupted this power dynamic. Efficiency triumphed over maximizing individual sales. John Wanamaker, who purportedly invented price tags for his eponymous department stores, saw this shift not only as a matter of retail fairness but also as an issue of eternal salvation. If everyone was equal in the eyes of God, everyone should be equal in terms of pricing.
Communications scholar Joseph Turow from the University of Pennsylvania refers to this transition to fixed pricing, popularized around the turn of the century, as the “democratic era of shopping.” The concept was democratic in the sense that people’s purchases became separated from their identities. While identity could influence desire, theoretically everyone had access to the same goods at the same prices. Companies didn’t care much about who you were, as long as you bought their products.
However, all of that changed with the emergence of a previously unknown computer technology that quickly became ubiquitous. You may have assumed I was referring to the internet, but you’re jumping ahead. I’m talking about the Universal Product Code (UPC) – the barcode found on bags of chips, underwear, curtain rod finials, and nearly every other consumer product available in stores or online. The very first item equipped with a barcode, a pack of Juicy Fruit gum, was scanned just after the summer solstice in 1974.
Barcodes revolutionized retail by enhancing inventory tracking and streamlining reordering processes. However, they also severed the connection between price and product. Price tags, once affixed to each can of beans, transitioned to store shelves and became more easily alterable. Stores soon realized that barcodes could be employed to trace customers’ purchases and influence their buying behavior.
Thus began the age of data collection in retail. Preferred-customer programs, identifiable through scannable membership cards and tags just like UPC codes, allowed retailers to link specific individuals with the products they purchased. Wanamaker’s idea of one price before God gradually faded away, replaced by preferred prices for loyal customers willing to surrender their purchasing data.
Retailers also recognized that data could drive innovative forms of direct marketing. They began extending tailored offers based on customers’ purchasing patterns. These custom coupons created a fog surrounding who received the best deals and why. Receiving a discount on sport-scented deodorant after buying Pepsi Max might reflect a shrewd deduction of a customer’s preferences based on data, or it could simply be a random guess. Regardless, individuals were offered special prices based on the perception the seller had of them, derived from the extensive data they had collected. And this notion held influence: Perhaps I am indeed the kind of person who prefers sport-scented products.
When the internet entered the commercial realm in the 1990s, things took a turn for the worse. By that point, retailers had already been collecting, storing, and utilizing consumer data for some time. The web promised the ultimate marketing treasure trove. In the physical world, marketers couldn’t determine whether an advertisement on the side of a bus influenced behavior. Conversely, online, they could trace customers from the moment they saw an ad to the moment they made a purchase. Retailers began gathering and connecting even more information about their customers. They monitored browsing history, not just purchase history. They tracked location through computer network addresses. They employed data breadcrumbs known as “cookies” to follow users across various website visits. Later on, cookies enabled tracking across the entire internet ecosystem.
Smartphones provided stores with even more refined customer information, enabling novel forms of in-store surveillance that most people remain oblivious to. Small radio transmitters, akin to mousetraps in size, called beacons, interact with apps on users’ phones and precisely track their locations within a store, granting retailers detailed insights into the products that capture their attention. Combining this information with other data they’ve collected or acquired from third parties, stores can paint a vivid picture of who customers are and what they may be enticed to purchase at any given moment. In theory, you could linger in the cereal aisle, opt for whole grain options, and subsequently receive a mobile ad offering a 10% discount on Lucky Charms, accompanied by a reminder that they are just one part of a balanced breakfast.
Furthermore, retailers have begun experimenting with facial and voice recognition technologies in stores, providing yet another means of tracking customer behavior. In-store Wi-Fi assists in overcoming signal interference caused by concrete and steel construction, but it also allows stores to collect email addresses and monitor browsing activity,…
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