If you’re a regular customer of Target—or any major retailer—with a sophisticated point-of-sale and inventory-management system to predict the future needs of customers, you’ve probably been given a guest ID, typically a number tied to your credit card and your name, which records your data on everything that you’ve purchased in their stores. And, from this, these retailers can learn about broader consumer trends.
Tracking Customer Purchases
One of the things that Target noticed when it began tracking shopping data and behavior electronically was that women who registered for baby showers—in other words, women who had self-disclosed that they were pregnant—tended to buy larger amounts of unscented lotion, starting sometime around the beginning of their second trimester of pregnancy.
Presumably, this reflected something like heightened smell sensitivity, but the reason doesn’t matter for this discussion. What does matter is that the correlation of data gave Target an idea for marketing. Traditional practice was that a retailer would note that a woman was pregnant and then track her purchases.
Statisticians at Target put their computers to work, and as they massaged the data, they tried to reverse that practice. Company officials asked whether they could identify customers who were pregnant not from how they looked or what they said, but rather from what they purchased—and they could. The analysis identified about 25 products that were predictive of pregnancy.
The New York Times noted: ‘Taken together, these 25 products became the basis for statisticians to assign each shopper a pregnancy-prediction score, and to predict within a very narrow window exactly when each shopper’s due date was likely to be.’
This is a transcript from the video series The Surveillance State: Big Data, Freedom, and You. Watch it now, on Wondrium.
Data to Predict the Future?
In other words, Target could tell that a woman was probably pregnant and could even predict with some accuracy when she was due to deliver—sometime in, say, the first two weeks of September.
Armed with this information, Target issued coupons tied to the likelihood that a customer was pregnant and also to her probable stage of pregnancy. Of course, not all of the customers had publicly signaled or even disclosed their pregnancies, but from a marketing perspective, it seemed to be a genius strategy. To many customers, such unsolicited conclusions were intrusive.
An enterprising New York Times account into how commercial data brokers use big data analytics to sell goods found that the program led one angry and unsuspecting father to storm into a Target store and berate employees for sending his teenage daughter coupons for baby clothes and cribs. It turns out his daughter was pregnant—she just hadn’t told her dad yet.
Because Target’s predictive analytics were perceived as too creepy, the retailer made it less precise. So now, today, in a mailing with coupons for baby clothes, you might also find it combined with an offer for television sets.
Learn more about how our personal data Is the product.
Data Collection or Psychic Powers?
These sorts of predictive analytics are becoming an essential component of target advertising. Consider what the digital marketing company Quantcast says it can do with data. Let’s say that you’ve watched three videos on feng shui in the last 24 hours, read 12 articles on the health benefits of kale in the past week, and spent 9 hours in the past 3 weeks looking at the hot spots for social life in Portland—all this information quietly gathered and recorded by your mobile phone.
Mixing this bowl of seemingly random information along with other data, Quantcast says it can predict—with a reasonable degree of accuracy—that you are 30 times more likely to buy a juicer than the average person and that you are 14 times more likely than the average to purchase renters’ insurance. Their motto: “We’re not really psychic, but we’re pretty close.”
Welcome to the world of commercial data aggregators and analytics. Like government spy agencies, commercial data aggregators are involved in a form of surveillance. And some people think the commercial firms are more of a threat to privacy than the government.
Learn more about the Internet of Things.
Would You Choose Companies or Governments?
Before Edward Snowden released state secrets about U.S. government spying methods, if you had asked many people who they feared more, commercial data brokers or the government, they might have said commercial brokers.
One time, at the DefCon hacker convention in Las Vegas, visitors were asked who they feared more, Google or the National Security Agency? They responded: “Google”, by a two-to-one margin.
Of course, that was before Snowden. After the Snowden revelations, one suspects the result might be different given the controversies that resulted. Nonetheless, the story about the hackers at DefCon is indicative of the general unease with which some people view commercial data collection.
Commercial data aggregators are often the source of information that the government itself seeks to collect to analyze—from your telephone records to your web search activity. The government may buy this data or force the company to turn it over.
Common Questions about How Stores Predict the Future Needs of Customers
Tracking customer purchases helps companies know more about the specific customer making the purchase and more about the latest consumer trends. One of the goals is to predict the future needs of customers and to have them in stock when they ask for them.
Target tries predicting the future needs of customers so it can send them coupons to push them towards more purchases. The data they stored from previous purchases that pregnant women had made helped their system figure out what purchases are indicators of someone being pregnant.
Companies usually collect the same information that the government wants; maybe not to predict the future needs of customers, but they could certainly use the extra information. Since companies may be obliged by the law to hand over the information to the government, people are most afraid of companies surrendering to the government’s will.