162 14.9 Consumer Data from Private-Sector Sources
In addition to the syndicated research services, individual businesses are gathering a breath-taking amount of information about their own, and sometimes their competitors’, customers. Private-sector businesses have become major players in gathering and mining data about their customers. If you are reporting about a business or a trend or if you are doing strategic communications for one of these organizations, you will almost certainly want to ask about their customer data practices.
Here is one example: a major discount retailer used information willingly provided by customers from its “Baby Registry” and sales information from its customer loyalty programs (you sign up for special deals and notices in exchange for allowing the company to monitor your purchases) to identify a “profile” of female customers who were in their second trimester of pregnancy. When the retailer’s research staff crawled through millions of customer records, it became clear there there were about 25 products that, when purchased together, allowed them to assign shoppers a “pregnancy prediction” score.
Let’s say there is a 23-year-old shopper who bought, in March, a large jar of cocoa-butter lotion, a purse roomy enough to double as a diaper bag, zinc and magnesium supplements and a bright blue rug. According to the retailer’s interpretation of those data, there is an 87 percent change that shopper was pregnant with a delivery date in late August. Based on that information, the retailer could then send a coupon for related products and services or target advertising messages to her based on her “pregnancy score.” If you were doing advertising for this retailer, you can imagine how valuable this information could be. You can also imagine how disturbed many of the retailer’s customers would be to know they are being so profiled.
Such “profiling” is being done by companies based on every single thing we do in our virtual and “real” lives. Communications professionals are among those who are using such data to better reach us with information when, when and how we want it.
Here is another description of this “social profiling” from an article by Joseph Turow that appeared in The Atlantic magazine
Consider a fictional middle class family of two parents with three children who eat out a lot in fast-food restaurants. After a while the parents receive a continual flow of fast-food restaurant coupons. Data suggest the parents, let’s call them Larry and Rhonda, will consistently spend far more than the coupons’ value. Additional statistical evaluations of parents’ activities and discussions online and off may suggest that Larry and Rhonda and their children tend toward being overweight. The data, in turn, results in a small torrent of messages by marketers and publishers seeking to exploit these weight issues to increase attention or sales. Videos about dealing with overweight children, produced by a new type of company called content farms, begin to show up on parenting websites Rhonda frequents. When Larry goes online, he routinely receives articles about how fitness chains emphasize weight loss around the holidays. Ads for fitness firms and diet pills typically show up on the pages with those articles. One of Larry and Rhonda’s sons, who is 15 years old, is happy to find a text message on his phone that invites him to use a discount at an ice cream chain not too far from his house. One of their daughters, by contrast, is mortified when she receives texts inviting her to a diet program and an ad on her Facebook page inviting her to a clothing store for hip, oversized women. What’s more, people keep sending her Twitter messages about weight loss. In the meantime, both Larry and Rhonda are getting ads from check-cashing services and payday-loan companies. And Larry notices sourly on auto sites he visits that the main articles on the home page and the ads throughout feature entry-level and used models.
His bitterness only becomes more acute when he describes to his boss the down-market Web he has been seeing lately. Quite surprised, she tells him she has been to the same auto sites recently and has just the opposite impression: many of the articles are about the latest German cars, and one home-page ad even offered her a gift for test-driving one at a dealer near her home.
This scenario of individual and household profiling and media customization is quite possible today. Websites, advertisers, and a panoply of other companies are continuously assessing the activities, intentions, and backgrounds of virtually everyone online; even our social relationships and comments are being carefully and continuously analyzed. In broader and broader ways, computer- generated conclusions about who we are affect the media content – the streams of commercial messages, discount offers, information, news, and entertainment – each of us confronts.
This excerpt describes both the types of data that are being collected by private-sector institutions, and the practice of targeting specific types of messages based on what those data say about us. In fact, one popular online travel site that offers one-stop shopping for airline tickets, hotels and rental cars was exposed for showing searchers using a Mac computer pricier hotel options than those using more “down-market” models of computers. One of the pieces of data collected by online sites is the type of equipment the searcher is using to gain access. The assumption in this case was that if a user owned a Mac computer, they had deeper pockets and would be less likely to continue to search for less-expensive accommodations. Since the travel sites earn a “cut” of every reservation booked, they have an incentive to steer wealthier users away from the cheapest options.
Here is another example. We all are familiar with this scenario: we go to Google and do a search for information about, say, the best brand of athletic shoes for playing tennis. For many days after conducting that search, every other website we visit is suddenly showing us ads for athletic shoes. How does that happen? Is it a massive coincidence? Of course not. Google, and many other similar search sites, collects data about every action we take on its site. It then turns around and sells that data to advertisers, or offers to place ads on behalf of advertisers, when we do anything else or go anywhere else online.
Of course, many of us are now spending most of our online time using mobile devices (smartphone, tablets, “phablets” [phone-tablet hybrids]) rather than traditional computers. Services are now springing up to ensure that advertising messages delivered to mobile devices through individual tracking are as effectively targeted as they have been through websites on desktop and laptop computers. Again, these companies are tracking individual behavior on mobile devices, triangulating the data traces (“cookies”) we leave via those devices with those we leave on our desktop or laptop computer, and then making sure the targeted ads reach us via every device we use.
Especially for communications professionals, understanding these data practices of public- and private-sector institutions is a major obligation of doing their work. Strategic communicators need to know how to scrape, evaluate and use such data to effectively create and target ads and PR messages for their clients. Journalists need to understand how readers/viewers/listeners are moving through their news sites to better generate content that will attract news users.