Corporate, or organizational, surveillance can take a lot of forms, including watching customers, competitors, or the basic operating environment (environmental scanning). Given this volume’s emphasis on privacy, this entry focuses generally on surveillance of customers, including privacy and other concerns raised by the expansion of such surveillance.
Organizations watching customers is a phenomenon with a long history. Previously, surveillance often took the form of observation studies. Observation studies, taking place in public where individuals know or should know that they could potentially be objects of scrutiny, were usually not controversial. Techniques were as simple as noting automobiles or pedestrians passing by for a traffic count or tracking a shopper’s path through a store. Ethical problems arose only in situations where customers would have a reasonable expectation of privacy (e.g., changing rooms).
One of the first applications of loyalty programs to detailed customer observation was the UK grocer Tesco’s clubcard program, created with assistance from dunnhumby. The clubcard tracks customer purchases as well as responses to targeted offers delivered to individual members. With a membership in the millions and even more potential individual promotional offers, the program demonstrated the power of individualized knowledge of each customer.
A similar program was instituted by Harrah’s (now Caesar’s) casinos. The True Rewards card collects information on hotel stays, restaurant purchases, show attendance, and gaming activity. By the turn of the 21st century, the firm had the capability to make targeted offers to customers (whatever drew them to the casinos more frequently: e.g., free/discounted shows, free/discounted rooms, cash for gambling) and had even moved into yield management in pricing, with different offers for different customers and situations, much like the airlines do. Even more recently, the firm has started tracking gambling activity. Money is loaded on the reward cards and monitored (players insert cards at specific tables) so the casinos know what games are played, for how long, how much is bet, who won or lost, and other such precise data. Activity is tracked down to the level of casino managers meeting the best customers at the door after a bad night with a check that will make them feel better (and return sooner).
These trends have been expanded with even more detailed database construction in online environments. Online retailer amazon.com has an ability to not only track online purchases and response to offers but also record search histories, from where the customer comes as well as other sites visited, and even equipment used. Orbitz, for example, received substantial publicity when it was found that the firm was reordering hotel listings depending on the type of computer used to visit the site. Apple Mac users were shown more expensive properties at the top of their listings than were PC users. Use of Internet sites also comes with customer agreements—sometimes explicit and sometimes implicit. So customers are well aware that surveillance may be occurring, but they may not be fully informed of its breadth and depth.
Even more recently, with big data capabilities, firms have been able to further expand their surveillance activity and subsequent analytical processes. Big data usually refers to the ability of organizations to obtain massive amounts of data when conducting day-to-day activities, including operations, transactions, and communication (e.g., social media). Big drops in the cost of data storage and computer processing power have made it cost-effective to take in, hold, and analyze all of these data. Firms are using this capability to divide customers into increasingly specific subsegments, discover buying patterns (e.g., what products are bought together), and find other, even more precise, analytical insights. An individual fitting a specific demographic profile, for example, might be determined to be 3% more likely to buy a product than another, fitting a different profile. Since the finding is based on analyzing the full population of customers, there is no statistical doubt—targeting all such customers should result in a bump in sales.
In a related example, a Target store manager received a complaint from a customer whose teenage daughter had received a targeted mail concerning pregnancy products. Some days later, the store manager called back to apologize more fully and found that the daughter was, indeed, pregnant. In explaining the episode, Target noted that it had built a model, based on purchase of around 25 products, that could predict pregnancy with a high degree of probability. The store had known that the girl was pregnant before her father did, perhaps even before she did.
This incursion into customers’ personal lives begins to raise some important questions about how far these surveillance capabilities should go. The collected records are fairly mundane, but through analysis, personal insights can be drawn as well. These trends have been taken even further as some online firms have started conducting experiments on customers. Once again, the intentions aren’t necessarily objectionable: to better determine customer needs and wants so as to better satisfy them. But also once again, the capability can be taken a stretch too far.
In summer 2014, Facebook owned up to conducting experiments on customers. It turned out that the practice was quite prevalent, and to a great extent, most experiments were aimed at improving service (companies change packaging or prices all the time, experimenting with response). But the experiment that was drawing publicity was changing the nature of members’ newsfeeds from positive to negative, something that had the potential to influence their mental states. OKCupid weighed in on the controversy by noting that it also conducted experiments, sometimes even recommending matches that weren’t accurate according to its established algorithm, essentially changing the product offering. Once again, the question was raised as to whether activities based on the surveillance databases had been taken to an inappropriate level.
The danger with these modern capabilities are that marketing or other initiatives take the information considerably beyond the level customers expected when they agreed to yield the data—if they explicitly agreed at all. Furthermore, firms are now capable of combining databases. So proprietary databases with identified customers who willingly give up their information can be combined with other databases that customers may have expected to be kept anonymous. In such cases, matching up details in the databases allows data miners to attach the anonymous data to an identifiable customer, by name. The power of contemporary data analysis lets organizations take surveillance in directions far beyond what customers agreed to or what could have reasonably been expected to anticipate when they gave permission for collection. If the customer never explicitly gives permission, of course, the concerns are magnified.
Although much current customer surveillance is justified by better serving customer needs and recognition that individuals willingly turn over the information, the use of such data has moved far beyond just serving needs and into areas customers never anticipated when yielding the information. Usually, this is harmless, but there is growing evidence of the potential for considerable abuse of privacy as these new tools are more aggressively employed.
G. Scott Erickson
See also Ethics ; Information Security ; Privacy ; Privacy, Right to
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