Besides merely selling information collected about individuals, businesses can benefit from consumer data in two other ways. One is that understanding a consumer’s preferences, income and lifestyle enables companies to advertise products the consumer is more likely to buy, thereby increasing the return per dollar on ads and other marketing materials. Second, firms can actively price discriminate, especially on online sales platforms where buyers cannot see the prices shown on the screen of other buyers.
Target, the multi-billion dollar merchandise retailer, is a fascinating example of a company exploiting data on its consumers to increase sales. Through extensive market research, Target found that shoppers tend to not buy everything they need at one store – shoppers buy groceries at the grocery store and toys at the toy store and visit Target only when they need particular items they associate with Target, such as detergent or toilet paper. But retailing companies typically sell everything from ready-made salads to swimsuits to pens and staplers. What Target wants is to convince customers that it is the only store they need.
Collecting information itself is not new, and Target has done so for decades. It assigns each shopper a unique code, known internally as the Guest ID number, that keeps tabs on everything he or she buys. Doing this follows the “revealed preference” theory put forward by economist Paul Samuelson, which holds that a seller can infer the preferences of consumers from their purchasing habits. Demographic information like age, marital status, number of kids, estimated salary, credit cards owned and websites visited is also linked to one’s Guest ID. On top of that, Target can buy data on ethnicity, job history, education, reading habits and political leanings.
What is new, however, is Target’s ability to combine that data with an understanding of behavioral science. Shopping is a habit for most people – we don’t think much about going to different places for different kinds of things – and habits are most likely to change when one is going through a life-changing event, such as marriage or childbirth. Marketers of retailers want to send specially designed ads to pregnant mothers in their second trimester, which is when they spend the most on new items such as prenatal vitamins and baby clothing. The idea is that by sending them numerous discount coupons that encourage the purchase of baby-related items, Target would entice potential mothers to buy everything they might have acquired from another retailer, from Target instead. Hence, for Target to beat other retailers, it is crucial that they get the information (i.e. that a customer is pregnant) as soon as possible ahead of their competitors, before the birth of the baby.
Furthermore, Target is aware that women may feel unpleasantly scrutinized in their reproductive decisions. Thus, in an even more devious method, it places its baby-and-mom-related ads and discount coupons next to innocuous items such as sofas, dishwashers or kitchen utensils. It is seems as though other, non-expecting households would have received the same offers, but those directed offers are in reality part of a greater marketing ploy.
Adopting the new strategies was a tremendous success. Between 2002 and 2010, Target’s revenues grew from $44 billion to $67 billion. Its maternity product sales skyrocketed. In sum, Target had managed to parse the information it had on its customers, figure out the best time to entice them to spend more at Target, and then capture their loyalty for time to come.
Not only does a company peeping into personal information backyards feel highly intrusive, but also what they do with the information is, while economically efficient, biased against the consumer . Businesses manipu late information to squeeze every penny a customer is potentially willing to pay. Take for example Staples, an office supply store, which displays different prices to different people after estimating their locations. If someone is further away from the nearest Staples store, the price is lower. In addition, Staples considers the customer’s distance from a rival store such as OfficeMax or Office Depot – if rival stores were within 20 miles or so, Staples’s website would show a discounted price.
Airlines also use a similar strategy. Plane tickets tend to be updated in real-time as seats disappear, and ticketing websites read customers’ browsing history to track spending habits and demographics, leading to price discrimination. For example, if airlines know that a customer has a relatively high income, they are likely to charge higher prices, because they know that the costumer is able to afford it and is unlikely to back out of the purchase. Perhaps the process is analogous to the difference in treatment that sellers in a store might give a customer in an expensive suit compared to a cash-strapped student: cut the student some slack and try to entice the expensive suit wearer to buy the most expensive thing in the store. Today, a computer does the screening and operates by algorithms and rules that make any human bargaining impossible. An automated system of discrimination between customers feels much more unfair compared to arbitrary exceptions, as customers are aware that price changes are part of a systematic scheme to charge the highest price possible, without any of the social niceties that one might find in a person-to-person sale.
By going through data to find out as much as possible about the customer’s preferences, businesses can capture as much of the consumer utility that, under the traditional single-price model, would have gone to the consumer. They can tailor prices to match every customer, charging higher prices to customers they know are more willing and able to pay more, thereby squeezing more dollars out per customer.
A lot of what the firms do with consumer information in order to increase their sales or profit margins is legal. While it may be difficult to agree on whether privacy is an inherent right, or to what extent these companies’ actions violate privacy, it is clear that customer information benefits firms more than it benefits consumers. Some argue that individuals should have a right to “sell” their personal information to companies. The problem is that there are very low barriers to access of information, and it is very difficult to protect one’s data from being read by others. Privacy options that allow for ad tracking on Facebook tend to be “opt out” rather than “opt in,” making it even easier for firms to track customer data. As a consumer, one should be wary about browser settings and what one shares online. For a business selling any sort of product, it appears that investing in data collection and analytics can generate massive returns.