Airlines are an extreme example when it comes to discriminating among customers for profit. Over the years, frequent-flier reward programs, which were launched to entice business travelers to book all their flights with the same airline, typically have become increasingly complex. Carriers created multiple tiers within their programs, offering their most frequent fliers the best perks such as preferred seating, more legroom, early boarding, and guaranteed overhead luggage space. Lower-tiered fliers and passengers who haven’t joined the frequent-flier program aren’t treated nearly as well; for example, they typically receive less-comfortable seat assignments unless they choose to pay extra. The airlines give business travelers, who are their main targets, enough protection and privilege even at middle loyalty tiers to make them oblivious to the indignities experienced by infrequent fliers. Indeed, the New York Times noted that “the opposite of rewarding a good customer is penalizing a bad one.” In the case of Delta Air Lines, the paper wrote, “in order to toss 10 or 11 [reward] miles at some travelers [its best customers] for every dollar they spend, Delta will have to do less for plenty of others on many of its routes.”1
The airline loyalty programs have had enormous influence on marketers’ overall efforts to use data to attract, learn about, and reward the best customers. Consultants have exhorted merchants outside the airline industry to discriminate between customers whose purchases indicate they will bring the firm profits over a number of years (a high lifetime value) and the others who just show up. Bain & Company loyalty consultant Fred Reichheld wrote in a letter to the editor in Harvard Business Review that “plenty of long-term customers—those who relentlessly cherry pick loss leader products, who treat front-line employees abusively . . . can’t be considered loyal.” He added, “If frontline workers are taught to distinguish profitable from unprofitable customers, and if those employees are rewarded for focusing jointly on earning profits today and treating profitable customers in ways that make them want to return, companies will be pleasantly surprised by the resulting improvements in growth and profits.”2
Several retail chain executives interviewed for this book suggested that the bluntness with which this sorting activity takes place in stores depends on the merchant’s target audience. Although luxury brands such as Louis Vuitton, Bergdorf Goodman, and Saks might well want the public to see them as exclusionary in order to cultivate elites, mid-tier merchants cannot be perceived as treating their lower-value customers the way that the airlines do. One department-store executive said he would rather try to persuade customers to move up the purchasing chain instead of making them uncomfortable or implying they should shop elsewhere. An executive with a major regional supermarket chain shares that view; rather than make life difficult for less-profitable shoppers, she said, her company tries to convert them to becoming increasingly loyal and, consequently, more consequential customers for them. “Cherry pickers exist,” she said, “but we don’t fire them. They are customers. Groups of folks in the company deal with such things, worry about loyalty now and beyond. There are certainly different types of programs [to reward different levels of loyalty]. If you use your [basic supermarket loyalty card] you will get the base level of savings. But if you use other programs, like gas . . . that can bring the customer more benefits.”3
The key to selling, executives agree, will increasingly be to know how to deal with individuals. Merchants need to know what messages to send to specific customers, whether store associates should interact with them (and, if so, for how long), and whether the store should offer specific customers discounts and, if so, for which products and for how much. To do this the store must have appropriate information about each shopper each time that person enters a digital or physical version of the store. “Retailers know they need to upgrade their technology portfolio to understand consumers’ complex path to purchase,” said a retailing consultant in 2014 at the National Retail Federation conference. “It’s critical for them to reach customers in new ways, and that can only happen if retailers gather and analyze customer data.” Macy’s chief marketing officer put the matter more bluntly. “We don’t need more customers,” he noted in 2012. “We need the customers to spend more time with us.”4
He meant that the merchant was attempting to engage shoppers in every way possible—the internet, any mobile device, and in the physical store, and he was particularly referring to the value of shoppers who interacted with more than one of these channels, as they spend more than those who adhere to just one. In an article discussing Target, the FierceMobileIT5 trade journal noted that “the multi-channel shopper is the prize, as customers who shop both in stores and online generate three times the sales compared to shoppers who only frequent brick-and-mortar stores, according to the retailer.” Target, Macy’s, and other chains have recognized that identifying and pursuing such high-value targets require highly specific data, and lots of it. “Analyzing data can help companies make precise decisions about everything, from crafting relevant offers for on-the-go consumers to displaying the right assortment of merchandise,” noted a retailing journalist who was covering the 2014 National Retail Federation conference, which was packed with merchants with strong physical footprints and digital sales platforms.6
The increasing focus on the individual was by no means unique to retailing. “Companies across the globe and from every industry are building teams to translate mountains of information into better understanding of their customers,” stated a 2014 Forrester report titled The Age of the Customer Requires a More Intelligent Enterprise. The title alluded to the potential knowledge and bargaining power shoppers could exercise in the age of the Web and mobile phones. “Your customers’ expectations are changing,” the report cautioned, “fueled by the constantly connected world and the mind-boggling speed of technology enablement,” and companies have to respond in kind. “Knowing your customers and quickly translating and applying that knowledge across the entire enterprise is no longer a competitive advantage, it’s a competitive necessity if you are to win, engage, and retain customers.” An “intelligent” business, it said, is one “in which customer knowledge is drawn from everywhere, created centrally, and shared across the entire enterprise, so all stakeholders can act upon it and measure the results.” Key to this approach is creating a unique identifier for each customer to “enable firms from industries as diverse as telecom, financial services, media, retail, and high-tech to avoid the agony and inefficiency of manually tracking, trending, and tying together customer interactions from disparate databases.” All this information should tie into “an automated system built on rules-based algorithms that trigger actions such as personal communication, offer optimization, and cross departmental notifications.” Such automation would speed the time it took to translate executive insight into action so as to “meet customer expectations.”7
A central question remained: What are the best ways to get such information without alienating customers? Although marketers had come up with surreptitious ways to create shopper profiles, not all of these would work in a selling situation. Consequently, many physical retailers began to use their loyalty programs to accomplish it. Traditionally stores used the programs to generate recurring purchases; now they also began to use them as bait to attract shoppers and encourage them to consider it perfectly normal and ordinary to give up information about themselves unselfconsciously. The shift has ramifications far outside physical aisles.
Retailers in the early twenty-first century are adopting a new perspective in customer analysis that goes beyond traditional classifications of people based on a small set of categories such as demographic (gender, annual salary, etc.) or lifestyle (hunters, skiers, people who eat out a lot, etc.). Though these classifications remain important, there is a new emphasis on gathering behavioral and attitudinal information in order to predict how specific people will respond to various shopping situations. Indeed, practitioners in fields such as advertising, health care, political analysis, and insurance have been increasingly accepting that learning as much as possible about individuals will lead to accurate predictions of their behaviors. Genetic research has contributed to this new mindset. When the Human Genome Project published the first human DNA blueprint in 2000, “scientists promised that the age of personalized medicine had arrived.”8 Although the technology has yet to deliver on this promise, hope remains that improved whole-genome sequencing techniques will ultimately usher in a new health care era. A Los Angeles Times article noted that “what they learn will enable doctors to warn their patients of their genetic vulnerabilities, allowing patients, in turn, to take steps to reduce their risk.”9 At the same time, firms such as AncestryDNA (the genetics division of Ancestry.com) reflected and encouraged public fascination with genetics in their marketing efforts. “This service combines advanced DNA science with the world’s largest online family history resource to predict your genetic ethnicity and help you find new family connections,” explained the AncestryDNA website.10
Retailers adopted geneticists’ fixation on the individual but focused on more realistic avenues for collecting data. They turned to the work of actuaries, statisticians, accountants, engineers, and computer scientists who were building disciplines aimed at calculating the probability of knowing individuals’ actions based on social characteristics (such as age, ethnicity, gender, race, membership in an organization) and behaviors (such as driving habits, web-surfing habits, vacation destinations). A century ago the concept of probability “was relevant to practically only two types of people: to professional gamblers—and actuaries. Another profession which has integrated the concept of probability increasingly since the middle of this century is that of accountants.” But in recent years, “the concept of probability has become a universal way of thinking which is incorporated in all aspects of our life.”11 By 2010 computer-analytics specialists had attached that idea to tracking the minutiae of people’s everyday activities—“the little data breadcrumbs that you leave behind you as you move around in the world,” as MIT computer science professor Alex Pentland put it.12 Catalina Marketing used a different metaphor: “Like fingerprints, every shopper’s profile is unique in the assortment of products they buy each year.”13 The work of zeroing in on patterns linked to the fingerprint bread crumbs typically involved complex mathematical tools with labels such as data mining, logistic regression, and cloud computing.14 It attracted many different types of companies. A 2011 study forecast their phenomenal growth, including the need for 1.5 million managers and data experts by 2018.15
A 2013 report from the Gartner information technology consultants celebrated the rise of this analytical class. It predicted that within five years businesses would be able to identify and follow individuals through apps on mobile phones, home appliances, cars, and wearable devices. Gartner identified four stages in the evolution of these activities: “Sync Me,” “See Me,” “Know Me,” and “Be Me.” Sync Me and See Me “are well underway,” it said, referring to the increasing tendency of customers to connect several devices and the increasing ability of businesses to follow them across these technologies. Surveilling people across their digital and physical worlds would lead to such in-depth profiling that businesses would create intimate models of an individual’s behaviors and dispositions regarding their consumption patterns and preferences, and would ultimately enable firms to anticipate customers’ needs and actions.16 The report added that when a shopper can be identified via the information gleaned through connected devices such as location, app-usage tracking, customer demographic data, and behavior history analysis, “it will be easier to target the right advertisement at the right moment, or send the precise redeemable coupon when people are at the right location, at the right time of day, generating a higher return on marketing campaigns than before.”17 The report seemed to echo Google chairman Eric Schmidt’s comment that the information Google has collected on individuals enables the company to know “roughly who you are, roughly what you care about, roughly who your friends are”—to the extent that it can give insightful suggestions about what individuals should do next in specific locations.18
As to the challenge of collecting customer data, the internet set a precedent that physical retailing is now trying to imitate regarding the tracing of customer behavior. From the dawn of Web commerce in the mid-1990s marketers learned a lot about shoppers, and mostly without their direct approval or knowledge. The basic Web tracking mechanism, the cookie, was developed in 1994 solely to address the issue of identifying individual shoppers so they could purchase more than one item in the same transaction. Marketers learned quickly that such a mechanism could do much more, and an entire industry has since grown up around the ability to tag people, follow their movements from website to website, sometimes connect them to personally identifiable information (name, address, phone number), and build information profiles about them based on their digital travels and, often, their offline lifestyles.19 People have willingly provided personal information about themselves by creating accounts at sites of interest, but most of the time they have scarcely considered the ramifications of sharing such data. Surveys show that Americans have had little understanding of the specific ways in which tracking takes place or of the general lack of government regulations overseeing such surveillance.20
Americans’ ignorance has been no different when it comes to the mobile phone. Especially after the iPhone’s 2007 release, advertising and retailing executives considered it a necessity to track people via their smartphones in addition to following them on their home computers—and to pursue them from one device to another. However, a cookie cannot follow someone across platforms; it can’t even follow someone using different browsers on the same platform. In addition, while a smartphone’s Web browser such as Safari or Chrome can accept cookies, apps cannot. Marketers were flummoxed. “When companies lack a central notion of customer identity, each channel and the system creates a new identity,” noted a report from the Janrain marketing consultancy. “When identities are [isolated], companies all together lack the ability to plan, optimize, and measure the customer journey across devices, channels and systems.”21
The best solution seemed to be what data scientists call the deterministic approach, meaning the shopper has to register separately for both the website and the app. Facebook and Target are businesses that operate this way. Say a Target customer logs into the company’s app and website every time he or she uses a device (or the software remembers the person). The tracking, the analytics, and the profiling can then take place in the background, out of the person’s awareness. Under this system, the company would recognize the individual no matter which of the person’s devices was used. Even if a shopper doesn’t sign in on every device, it might be possible to determine the person’s connection to all of them by encouraging the individual to offer personal information when visiting a website or using an app on a device not yet linked to that individual. As that personal disclosure takes place, the merchant can make a permanent connection between the shopper’s identity and the device ID. A common tactic for unmasking people, according to Janrain, is “to offer a discount code on a next purchase if an anonymous site visitor would provide an email address and opts in to future email marketing campaigns. Consumer brands frequently run sweepstakes and other contest promotions to the same end, and many product manufacturers incentivize otherwise anonymous buyers to provide contact and demographic information through warranty registrations.”22
But what if a retailer wants to learn about people who have never logged in to its app or website? Beginning in 2007, analytics firms launched a cavalcade of new technologies to follow these and all other individuals across devices, often without their being aware of it. The approaches they use are called probabilistic (as opposed to deterministic) identification because when firms don’t have log-ins to work with, they have to use predictive methods to recognize when a person using one device is the same one who is using another. Tapad is a company that does that. It analyzes the IDs and IP addresses of millions of devices to identify their geographical locations and then looks for patterns: are a laptop, tablet, and a smartphone using the same internet connection? Are the web-browsing patterns similar? Do the devices “wake up” at the same time? Do they “sleep” at the same time? The greater the number of “yes” answers to these questions, the more likely that the devices connect to the same user. Although accurate analysis might seem improbable,23 independent tests suggest a higher than 90 percent accuracy rate in predicting common owners.24
Tapad also matches its tracked phones, tablets, laptops, and desktops with devices that database firms such as BlueKai and eXelate follow with cookies and other tags. Tapad purchases information from these companies and uses all the information it has gathered to create individual profiles, which it then sells to marketers for targeting with personalized messages.25 Surprisingly, Tapad doesn’t try to match device owners with information that can identify them offline, such as name, home address, phone number. It also doesn’t permit clients to use its technology for tracking people’s activities within areas of less than one mile or to send people ads based on precise locations without their explicit consent. “Time to get precise (without getting personal),” the firm tells potential clients on its home page.26
In contrast, plenty of cross-device tracking firms do help retailers and other marketers connect behavioral data with personal identities. Janrain does this through social network log-ins, in which people register and sign in to a website or app with their passwords from one of the social networks to which they belong. Janrain claims that “more than half of people” worldwide use their social network log-ins for this purpose, with 81 percent going through Facebook or Google+. This method is certainly convenient, as people don’t have to take the time to register on sites or apps requiring users to set up an account; the social network password enables them to bypass the process altogether. But in so doing, the social network logging them in can record this activity. Moreover, these “social log-in identity providers,” like Facebook and Google, enable the site or app owner to identify each person by name as well as “select specific pieces of customer data that go beyond the basic name and verified email address to include elements like a customer’s birthday, Likes, relationship status, photos, and friends’ lists, to name a few.” And the social network updates the data every time a person logs in again. “Your customers simply select their preferred social identity from Facebook, Twitter, or other networks,” noted Janrain in its promotional literature, “and choose whether to share some of their information with you.” Logging in to the same retailer on various devices using the same social log-in presents a persistent identity that enables retailers to compile extensive amounts of information on individual shopper behavior.27
In recent years privacy advocates have convinced Facebook, Google+, and other social platforms to notify their users about the personal data they give away when they log in with their social accounts. In 2015 Facebook began to allow members to specify data they don’t want to share when logging in to a site or app. A Janrain report noted that “some consumers are discouraged from using social log-in when the personal data requested seems excessive for or irrelevant to the intended transaction.” To allay such concerns, it said, the retailer should ask the social media site to transfer only the data that will allow the retailer to recognize the individual. But once that basic material pertaining to identity has crossed the threshold, the data floodgates would be open. At that point, Janrain advised retailers, “build a supplemental strategy to collect everything else [about each person].”28 The company listed a range of sources that merchants can consult to collect “everything else,” including email service providers; gaming, e-commerce, and online chat and commenting platforms; “social signals/social listening” services such as Twitter, Facebook, and YouTube; rating and review platforms for those who offer opinions on products, services, or companies; and on-site behavioral analytics.29
Retailers who want still more information about their customers, including statistics that can potentially identify shoppers on their sites and apps on different devices, can buy it from data brokers such as Acxiom and Experian, which by the mid-2010s had put together their own ways of tracking individuals across digital devices. In 2013 Acxiom introduced a system that gathers information continually on approximately seven hundred million identifiable individuals using three sources: Fortune 100 companies’ records of people who “purchased something or signed up for a mailing list or some kind of offer”; “every data attribute you could gather publicly about consumers from public records”; and its own cross-device cookie-like system that can identify an individual across many digital properties and gives Acxiom “access to the last 30 days of behavior on more than one billion consumers.”30 Acxiom executive Phil Mui claimed that “for every consumer we have more than 5,000 attributes of customer data.” Joe Mandese, editor in chief of the online industry publication MediaPost, asked Mui and Acxiom CEO and president Scott Howe about the seemingly “creepy” nature of the company’s aggressive quantification of individuals. He reported that the two executives viewed their work as “just a fact of modern consumer life, and all Acxiom is trying to do is make it more scientific so that the data works the way it should, friction is taken out of the process for marketers and agencies, and consumers—at least—get the most relevant offers and messages targeted at them.” Indeed, Mui boasted that Axciom can actually predict individuals’ future shopping behaviors based on the demographic information and the off- and online purchase data the company has compiled. “We know what your propensity is to buy a handbag,” he said. “We know what your propensity is to go on vacation or use a loyalty card.”31
Despite the enormous and still-growing capability of companies to gather data from various devices so they can identify and market to consumers, retailers remained concerned about accomplishing the same with shoppers strolling through the aisles of their physical stores. These shoppers have to be explicitly willing to be identified if a human sales associate or a computer-driven point-of-sale machine is to recognize them and follow their actions. There is also the matter of encouraging customers to make sure the location tracking (Bluetooth, Wi-Fi) functions are activated on their phone, as well as to download the retailer’s app. High-profile privacy issues concerning National Security Agency surveillance and “creepy stalking” by marketers have prompted many Americans—approximately 35 percent, accordingly to a 2013 Pew Research report—to turn off their phone’s Bluetooth capability.32
Retailers argue people don’t have the antipathy toward tracking that critics claim they do. Some observers have declared the situation a “privacy paradox”33—meaning that, the New York Times noted, “normally sane people have inconsistent and contradictory impulses and opinions when it comes to their safeguarding their own private information.”34 A March 2015 Accenture consulting firm survey found that people felt strongly about controlling access to their personal information. Fully 90 percent of the survey participants said that, if given the option, they would limit access to certain types of personal data and would stop retailers from selling their information to third parties. In addition, 88 percent wanted to be able to approve how their data was used. But Accenture also found contradictions among the people in its sample: while nearly 60 percent of consumers wanted to receive promotions and discounts, just 20 percent approved of retailers knowing their current location so that the retailers could tailor those offers.35
An Accenture representative underscored the importance of gathering data about shoppers despite their reluctance. “Addressing the complex requirements of U.S. consumers is challenging because they are conflicted on the issue,” he noted. Yet he went on to state that “personalization is a critical capability for retailers to master.” The solution, Accenture suggested, lies in persuading shoppers to see the situation in terms of trade-offs. “If retailers approach and market personalization as a value exchange, and are transparent in how the data will be used, consumers will likely be more willing to engage and trade their personal data.”36 In reality, large retailers have yet to express such an interest in transparency and assume instead that their customers want personalization and will willingly exchange their data for relevant offers and good buys. Forrester marketing consultant company mirrored this view in a report that suggested ways to reach goals regarding shopper data but didn’t mention a need to let people in on how the information about them would be used. Forrester offered its own pragmatic formula: “Provide services that customers find useful and get back data on product use and customer affinities.”37
Physical retailers see cultivating loyalty as a way to encourage customers’ allegiance to services they consider useful. Retailers crave the kind of allegiance that will compel customers to identify themselves and to turn on their Bluetooth or Wi-Fi when they walk into a store because they think these actions can help them even if they are not sure exactly how. More generally retailers hope loyalty will trump wariness so that shoppers will suppress any data concerns and happily give out information about themselves—and will do so across multiple platforms, and will offer far more facts about themselves than they might even realize. Retailers especially hope they will be able to reinforce this relationship with the most desirable of those customers, encouraging them to implicitly accept and trust what the company does with all their personal data.
The intense competition accompanying the rise of online selling helped catalyze retailers to create “loyalty” programs that offer incentives for customers to return. Whether the programs retailers set in motion to accomplish this goal truly constitute loyalty depends on one’s definition of the term. Many have questioned whether this word accurately describes a customer’s repeated purchases at a store to accumulate points toward a gift. Bribery might be a better term, though the amount returned to the customer is typically quite small—often just 2 percent. In academic circles some have explained a person’s repeat visits to a store in response to loyalty points as a merchant’s attempt to imitate the behavioral psychologist B. F. Skinner, who conducted experiments with animals using food as a reward to encourage specific behaviors. To apply this methodology to retail shopping, the customer learns the habit of returning “first through short-term ‘points pressure’ and then through long-term ‘rewarded behavior’ that results from the reinforcement of behavioral learning by gratification” from those loyalty points.38 Many agreed that a successful stimulus-response regime could encourage loyalty, but they did not think that the goal should merely be to get customers to return. After all, buying things might have little to do with adding value to a retailer’s bottom line; for example, customers who buy only deeply discounted sale items provide little benefit to a retailer.
Bain consultants Fred Reichheld and Phil Schefter believe that loyalty must involve focusing on “repeat purchases among a core of profitable customers.”39 Retailers tend to accept this view, yet they typically consider emotional attachment to be a crucial aspect of customer loyalty. Emilie Kroner, who heads consumer markets organization engagement at dunnhumby, a retailing consultant, observed in 2013 that “emotional loyalty to a brand is becoming more and more important” to merchants.40 Bond Brand Loyalty, a creator of loyalty programs, declared in 2014 that “it’s time for brands to look beyond [customers accumulating rewards] points to establish deep, meaningful relationships, even bonds, with their customers in ways that are engaging, emotionally rich, and brand aligned.”41 Such affective links are important, Bond Brand suggested, because they can help facilitate the collection of individual customer data: emotional loyalty results in higher trust and, consequently, a willingness on the part of program members to offer up personal information. Marketers then send out personalized messages built on this data, resulting in “likely . . . incremental business results.”42 Some believe that engaging shoppers in games as part of loyalty programs (what the industry calls “gamification”) is effective in encouraging emotional connections. Ayan Sen, senior manager for the marketing consultant company Peppers & Rogers Group, suggested that shoppers value this aspect of rewards programs nearly as much as they do protection and prestige. “Gamifying the engagement platform helps customers enjoy the activities that earn them rewards,” Sen wrote. “With a typical tiered loyalty program, many consumers don’t get close enough to the top rewards, so they lose interest.”43 The president of loyalty marketer Points agreed, noting that the aim of “modern gamification” is to create “a relationship of exchange where consumers are challenged and incentivized to share more of themselves: their time, their attention, their information, and ultimately their loyalty.”44
Merchants with physical stores see emotionally driven loyalty programs as a way to address their need for in-store data collection in the face of widespread public opposition toward surveillance, offering program members protection, privilege, and games in exchange for willingly providing the store with information about themselves. Retailers and their consultants believe that the data collected in this way allows them to create increasingly relevant messages. Wanting relevant messages, shoppers will accept location tracking and keep on Wi-Fi and/or Bluetooth and/or offer up their mobile phone numbers. Under this same relevance-through-personalization banner, the stores can make their customers complicit in their own data releases without describing the particulars of profiling and differential treatment lest the customers get annoyed or balk. It’s a classic technique of misdirection: hype the benefits of a relevant brand experience using the traditional emotional carrots of privilege and protection. Garnish it every now and then with the fun of gaming that in-store technologies can offer. And quietly, even surreptitiously, gather, store, and analyze all the data that go along with these activities.
The Janrain consultancy suggested to retailers in a report that they offer loyalty members the privilege of “first-to-know” promotions and other members-only offers not only to encourage shoppers to identify themselves, but also to motivate them “to return again and again and offer up more first-party data or engage in behaviors that help brands identify them as advocates or influencers.”45 Discrimination was an integral part of the process. “Not all customers are created equal—and not all segments are, either,” the company noted in a second report. “Segmentation should always be in support of maximizing customer value and response rate, and ultimately return. If your analysis of customer identity data reveals segments that are disengaged, or have never demonstrated a target behavior or conversion, focus on creating compelling content for your other more high-value segments first.”46
Cosmetic chain Ulta Beauty exemplifies the new approach to customer loyalty programs. Founded in 1990, the company currently operates nearly eight hundred stores nationally, selling both inexpensive and high-end brands. According to an analysis cited in Investor’s Business Daily, Ulta’s target customer in the mid-2010s is an upscale woman in her early thirties, with a household income of about $75,000. The company has grown steadily, by approximately 10 percent each year, and its success has been attributed to many factors.47 An article in Investor’s Business Daily suggested that customers are drawn to Ulta particularly because of its leisurely ambiance. “Salespeople aren’t on commission so they’re not breathing down your neck,” the article said. Another analyst attributed Ulta’s success to aggressive promoting of high-brand awareness, including its marketing efforts on Ellen DeGeneres’s television show. “A loyalty program, new products and the perception that it’s a ‘destination shop’ help pull customers to the store,” he asserted. “They know how to incubate new brands through their merchandising program. That’s what women are looking for. They’re looking for ‘the new thing I can show off to my friends.’”48 Another pointed to Ulta’s one-stop shopping experience. Before Ulta, he noted, women had to travel around to beauty stores, department stores, and mass retailers to make all their makeup and fragrance purchases. He suggested that Ulta allows them to short-circuit that journey, even to the point of having salons at the back of its stores that offer hair, skin, and brow services. He also contended that Ulta can hold its own against Amazon’s online “Beauty Bar” collection because “most women go online to see what’s hot but prefer going to brick-and-mortar stores. They want to see the makeup and smell the fragrance.” A Wells Fargo prognosticator remained unconvinced, however, that a niche physical store can be adequately protected from the two nemeses of retailing. “At the pace at which Amazon and Wal-Mart are innovating, if you’re great you’ve got to be supergreat tomorrow and unbelievably great a day later.”49
One way the chain attempts to remain competitive in the new shopping universe is to offer thousands of its products on its website, where shoppers can also engage in live, interactive chats with fashion experts, see photos of celebrities using Ulta products, and view photos as well as so-called haul videos of products customers have purchased.50 (Many of these features, especially the photos, are also available on Facebook, Pinterest, Twitter, and Instagram.) Although the company promotes these extras to add credibility, authority, and authenticity, its larger aim, noted Ulta’s chief marketing officer, centers on enticing high-value customers. Like many retailers, the chain has found that this group encompasses shoppers who cross the chain’s virtual and physical boundaries. “Our best guests,” the marketing chief said, “are the ones that are using our physical stores as well as our e-commerce business and then ultimately using our [salon] services—a trifecta that works well for us.”51
That “trifecta”—along with its associated marketing tools involving smartphones, guest services, direct mail, online and in-store activities, email, and social media—is the fundamental source for the data that fuels Ulta’s “Ultamate Rewards” loyalty program. It encompasses a fifteen-million-member database that contains customers’ unique preferences so the company can “target the conversation” to individual shoppers. Individuals can become members through signing up directly for an account or logging in through Facebook or Google+; these social log-ins are a particular data boon for the retailer because Ulta might then be able to learn the names of the member’s friends. On its website Ulta emphasizes that membership in its reward program “has its privileges.” The program’s rules are a bit tricky, and they have changed more than once. Not surprisingly, they are set up to encourage customers to spend more when they make purchases. The description glosses over the rather small standard discount the program offers and instead encourages members to earn double and triple points on specific products “or on your entire purchase during special bonus days.” If shoppers spend $400 within a calendar year, their points don’t expire. Moreover, in mimicking airline loyalty programs, customers who reach this “platinum” status receive a higher reward ratio: 1.25 points (rather than 1 point) for every dollar spent. Consequently, this group can receive discounts more quickly than lower-spending members, and it aims to encourage high-value customers to spend to keep their special status.
The retailer’s additional goal of learning as much as it can about customers and reaching them across digital and physical domains may or may not be evident in the postal mailings, emails, app coupons, website offerings, Facebook blandishments, and other marketing materials program members encounter. Members are probably completely unaware of other aspects of data gathering that are explained in the small print of the Ulta privacy policy. If they do take the time to wade through these notices they might be startled to learn that Ulta:
• claims the right to buy information about its members from third-party sources (often database firms) to incorporate into its existing member profiles;
• uses cookies and similar elements to follow members’ activities on its sites and in emails as well as to infer their interests by tracking members’ visits to non-Ulta sites;
• allows authorized advertising networks to collect data about its members while they’re visiting the Ulta site;
• tracks members’ locations via their mobile devices without requesting explicit permission (unless members turn off that feature on their devices);
• collects members’ comments and other input regarding “a product review, question, or other information” on the Ulta website; and
• allows “third-party social media widgets such as buttons or similar mechanisms” from Facebook, Twitter, Pinterest, YouTube, and FourSquare to collect information about members as well as to place trackers on members’ devices.
Although Ulta collects much information about its shoppers online and via its app, Ulta’s marketing director emphasized in 2015 that his company’s goal is for them to shop primarily in the store, and to have “a personal and fun experience” as they do it.52 To help facilitate this, the company has instituted what it calls a “clientelling” tool—an iPad that provides clerks with immediate access to every bit of information the store has compiled on any individual customer. Once the employee has identified a customer, the clerk can “review her purchase history, understand what her beauty concerns are, and target the right product to address those concerns.” The associate can also enter the customer’s brand preferences. All that information can lead to personalized offers as well as “targeted invites” to in-store events.53
Sephora, an Ulta competitor, which likewise collects information on its customers from their activities via the internet, mobile devices, and in-store, has a different focus. It installed beacons in all its locations in 2015, and smartphones that have downloaded the company’s app can capture the beacon transmissions, which send notifications of promotions in specific areas of the store. The app also outlines in-store services, and shoppers can also use it to review previous purchases as well as to check their current balance for the company’s rewards program. In-store shoppers who have checked their balance to find that they’re just a few dollars short of earning their next reward often shop accordingly and buy a bit more to make sure they’re eligible for their next reward once they complete that day’s transaction. Johnna Marcus, Sephora’s director of mobile and digital store marketing, said that the balance-checking function of the app is one of its most popular features.54
No matter the merchant, rewards programs have much in common with game playing—following rules, accumulating points, obtaining prizes. To be sure, industry reports suggest that such game-like activities can help keep customers interested in the merchant—“prime the loyalty pump,” says an executive at the marketing consultant Pepper and Rogers—by informing them about products, stimulating their use of more services, and encouraging them to talk about the company with others through social media.55 For the retailers involved, the fun elements help sew together each customer’s purchase and preference data from the merchants’ digital online, mobile, and physical platforms. In 2015 Sephora extended the game-like approach beyond its rewards program to an in-store “augmented reality image scanning” activity. Customers who spot “Scan to Watch” signs in the store are urged to point their phones at the signs and “unlock content (such as exclusive videos).”56 The signs also encourage shoppers to use the company’s app as a tool as they shop—which also means that the store’s customer-tracking beacons will be capturing data on its customers as they shop.
While many, if not most, loyalty programs can offer real value to shoppers, their unstated aim is also to train people to give up personal data willingly. shopkick, which pioneered ultrasonic and Bluetooth technologies to follow customers through stores and encourage them to interact with the retailer and provide personal information, has made capturing all sorts of data with little transparency an integral part of its business model. In an uncharacteristically frank reflection, a Best Buy representative said her company signed up with shopkick to “find new ways to bring people into our stores through the use of mobile technology, but more importantly, [to] know when they [individually identified shoppers] come into our store.”57 For shoppers shopkick emphasizes the rewards they can earn by scanning goods with the shopkick app and by purchasing products. According to the online magazine TechCrunch, an important part of shopkick’s success came from introducing “a level of ‘gamification’ to the shopping experience.” But the company’s privacy policy makes clear that it reserves the right to store, analyze, and use for profiling and “tailored” targeting virtually all the information it can gather on its users. The company also maintains the right to purchase information on shoppers from data brokers as well as to gather information that shoppers provide retailers “in the course of using their services.” shopkick further reserves the right to share any of this personal information with merchants so long as shoppers give shopkick their various merchant reward program account numbers (which many do out of convenience to simplify awards transactions), or identify themselves as a shopkick member (to earn points) when they make a purchase from a shopkick-related store. Only those customers who bother to wade through the privacy policy can learn of these conditions, as shopkick does not otherwise mention them. And although shopkick won’t share shopper information among its retailer clients—for example, it won’t tell Best Buy what a customer bought at Macy’s—it does compile all that data for itself and maintains the right to use it to analyze shopping behaviors and target shoppers with ads accordingly.
First Data Corporation, a major credit card payment processor, has blended its primary function with managing rewards programs for smaller businesses that otherwise aren’t set up to operate one.58 Using beacon technology, merchants are notified when rewards shoppers open the First Data’s Perka app upon entering a store; the notification includes the customer’s name, a photo, and most recent transaction at that business. Shoppers may appreciate a personalized greeting and offers that result from their presence being announced, but they likely are unaware that all the personal information that the app gathers on them in the process is shared with many sources outside that particular store. Perka’s privacy policy is even broader than shopkick’s in terms of allowing outside firms to purchase access to individual shopper data. Because customers use the app at any number of associated small- and medium-size businesses, Perka can harvest enormous amounts of information about the shoppers who use the app and visit the websites of these merchants. Based on a customer’s initial registration when downloading the app, and on subsequent behavioral tracking as the customer uses the app, shopper profiles are built around “personal data such as your name, birthday and email address, any transaction history, and could include a photograph.” First Data mines “geographic location details” both outdoors (via GPS and Wi-Fi) and inside stores (via Bluetooth) so shoppers can be sent “relevant and appropriate offers.”59 While it shares just transaction-specific data with the merchant making the sale—and not the extensive personal information the company has compiled—First Data also sells access to third-party advertisers “to serve advertisements regarding goods and services” based on customers’ activities on Perka-associated websites as well as on other websites (which are monitored via cookie-like trackers).60
Merchants who use Perka are generally aware that they are not in full control of their customer relationships, and this concern at least partly explains why large retailers release their own apps even as they also work with outside loyalty trackers such as shopkick, and proximity ad networks such as inMarket. Several people interviewed for this book pointed out that the premier retailer Macy’s, which employs shopkick’s perimeter-and-beacon app, also fields its own app. The retailer values shopkick’s ability to help bring desirable customers into the store and assist Macy’s in identifying them, but at the same time it doesn’t want an outside technology firm to have complete control over its customer data. Unlike shopkick’s app, the Macy’s app is not an explicit attempt to encourage shopper loyalty. Its dominant focus is on encouraging omnichannel shopping at Macy’s either remotely or inside a Macy’s store. The app invites product searches via text messages, product ID information obtained online, a smartphone-generated photo of the product, or the item’s barcode scan. Neither logging in to an existing account nor registering for a new account is necessary to access these or many other of the app’s functions, so any tracking that occurs under those conditions is anonymous. However, the app does encourage users to set up an account and create a personal profile. When shoppers do register the app, Macy’s can match the personal information they have provided, such as name, birth date, and physical address, with information obtained about them from shopkick and other sources.
Many apps often offer features such as ease, special offers, and game-like activities, which entice shoppers to accept smartphone settings that link their device with cellular, Wi-Fi, Bluetooth, and other technologies while enabling retailers to track individuals walking toward, through, or away from their physical locations and gather additional valuable information as they do so. A few examples:
• Old Navy and some other retailers use sweepstakes offers distributed in widely broadcast anonymous text messages as a way to begin collecting personal data. Once a cell phone user opts in and provides the requested personal information, a company can “start to develop the data set you need as a marketer to actually deliver personalization,” said an executive who was familiar with Old Navy’s digital-marketing agency and who requested anonymity to be interviewed for this book.61 “The consumer texts in, and there’s a prompt that responds. It says, ‘Are you sure you want to join? Reply yes.’ And some companies will say ‘Reply yes and include your birthday’ as the next validation. Once the consumer has opted in, now that mobile number is in your database, and you can link that number with your CRM [customer relation management] system.”
• Although Walmart doesn’t have a traditional loyalty program, it has nevertheless gathered personal data on its customers by asking them to register on its website and app and by using credit card information that customers provide during a purchase. In 2015 the giant retailer introduced a new vehicle by which it could identify individual customers: under its “Savings Catcher” program, shoppers submit the prices of goods they’ve bought by scanning a barcode on their purchase receipt using the Walmart app (they can also input the barcode number by hand on the company’s website). Walmart says it then compares the prices against those listed by its competitors in the past month and will issue a credit for any difference in the form of a Walmart gift card.62 To participate, customers need to identify themselves, whether they either already have an account or paid cash for the transaction. Walmart can then connect this information with other purchases a customer has made. The program also encourages customers to download the Walmart app to simplify access, and those who do so can then also be tracked by beacons when they shop in the physical store.
• Target’s popular app helps shoppers aggregate discounts, compare Target coupons with those of other retailers (and possibly receive lower prices as a result), find products in the aisles via an interactive map, and check an item’s availability. But between the app and other ways customers interact with the retailer, according to the firm’s privacy policy, Target and its “service providers” use “cookies, web beacons, and other technologies” to record just about every such action it can, and by every means—“online, in store, mobile, etc.”63 The phone app also connects to inMarket’s beacon technology for further data collection.64 Target’s privacy policy for its app states that the chain buys additional information from third parties and shares this data with its subsidiaries and affiliates, as well as with other companies “for their marketing purposes.”65 Target’s main privacy policy adds that “if we are able to identify you as a Target guest, we may . . . link your activity on our website to your activity in a Target store. . . . This allows us to provide you with a personalized activity regardless of how you interact with us.”66
Target is one of the few companies that present a separate privacy policy for their app, as most use one policy to cover all aspects of their business. This variation notwithstanding, privacy policies in general often mask rather than reveal firms’ handling of customers’ personal data. shopkick’s long, complex privacy policy is typical; it uses terms such as non-personally identifiable information, affiliated partners, API calls, and psychographic data without defining them or providing any explanation.67 Ulta’s privacy policy is likewise characteristic in that it doesn’t explain how it profiles people based on the information it gathers or how the data translate into what it calls “special offers and personalized content.”68 Privacy policies also often seem contradictory when they describe their data-sharing activities. For example, in one section the Safeway supermarket chain privacy policy states, “We do not sell, rent, lease, share or disclose personal information to any non-related companies or third parties without your consent,” except for certain narrow business purposes like filling orders. But in another section the policy notes that it allows “third parties to serve ads on our websites.” It also says that the company shares personal data from cookies with the third parties. Marketers are well aware that the information those third parties collect in this manner enables them to easily identify the names and other personal information pertaining to Safeway customers. And because the supermarket chain charges the marketers for serving the ads, indirectly at least Safeway does “sell . . . personal information.”69 Attorneys representing various marketing organizations acknowledge privately that these policies are not written for public consumption. Rather they are arcane documents that provide the retailer with legal protection, so they mention everything the merchant does to learn about its shoppers but without revealing specifics that might enlighten competitors or stir up the general public.
Retailers continue to seek out new ways of combining data collection with benefits so that shoppers fixate on the perks and don’t stop to consider the behind-the-scenes activities that capture their personal information. Mobile wallets are among the newest such vehicles. A wallet is a default smartphone app that began as a means by which users could store and access items on their device such as retail coupons, airline boarding passes, and event tickets. It has since grown to include credit and debit cards, as well as retail rewards cards. Both Apple and Google offer a version of the app. But despite the availability of mobile payments from these and other entities as diverse as Amazon, PayPal, Alipay, and a consortium of retailers that includes Walmart, most Americans have yet to give up their plastic cards and paper currency and use their mobile phones instead to make their purchases. The competition for phone-payment supremacy among these companies is likely to be drawn out and messy.70
Battles among mobile payment providers aside, some marketing professionals believe that mobile wallets can serve as at least a partial replacement for individual retail apps. Although a retailer’s app can help the merchant by collecting customer information, encouraging their loyalty, tracking their locations, and sending them messages, many shoppers either never download the app or, when they have downloaded it, never turn it on. Mark Tack, vice president of marketing at Vibes, a mobile technology marketing company, noted that smartphone users access just five of their downloaded apps 80 percent of the time, and so retailers should change their strategy and tap into the mobile wallet platform already on the phone. “When you have that [wallet] app that is offered by the operating system, it sits on your phone, it’s just there,” he said. A report from the marketing consultant agency Forrester Research agreed, noting, “Marketing leaders will benefit from mobile wallets if they tie together loyalty programs, coupons, product discovery, gift cards, and promotions to create powerful and new brand experiences in the mobile moments of their customers.”71
Here is how the process can work, according to a Vibes executive who did not want to be named:72 a retailer can send emails or text messages with discount coupons to people who are customers or whose contact information the retailer bought from third parties. If the individuals open the messages on their smartphones and click on the coupons, they can deposit them into their phone’s mobile wallet for later use. These promotional items can incorporate a unique identifier, which, when combined with the geolocation functions of the smartphone, can result in the coupon or other offer automatically appearing on the phone’s lock screen as the shopper nears the store (or, with Wi-Fi or Bluetooth on, the location in the store) for which the offer is intended.73 Vibes performs these services for its retail clients, and, depending on the data analysis of the smartphone user, it also offers the option of altering the text—and even the discount amount—of the coupon once delivered, until the offer is redeemed or deleted. For example, Men’s Wearhouse (a Vibes client) can first send a coupon discounting the price of a pair of pants, then increase the discount or change the discount item to a sports jacket. The company can also increase the rewards points offered with the purchase, or present an offer to buy a gift card. (Interestingly, the hardware hasn’t quite caught up with the rest of the technology, as a smartphone’s barcode can’t always be read by a store’s scanner. Consequently, Vibes includes the numerical digits with the barcode so the clerk can key in the number by hand when this problem occurs.)74
This ability to change the value of a discount based on a company’s knowledge of an individual across space and time raises coupon personalization to a new level. Making the activity a common promotional tactic requires retailers to make loading retailer messages into a mobile wallet part of shoppers’ regular routines. That will involve encouraging them with help, special treatment, and gamelike entertainment around the smartphone. Another Vibes executive listed incentives such as loyalty points, rewards redemptions, and contests as ways to present “more opportunities for . . . consumers to save content to their mobile devices.” He said that email, text messages, the internet, apps, direct mail, and QR (quick response) codes all can be used to transmit these incentives to targeted individuals.75 And behind the scenes Vibes can tell “who has saved or deleted mobile wallet content” as well as “which [geographic] locations consumers save to their mobile wallet offers and loyalty cards.”76
Whatever the tools that marketers and retailers use to gather information on consumers so that they can be sold to more effectively, the main goal is to make the surveillance-and-selling scenario as smooth and as tension-free as possible. The companies discussed in this chapter—Ulta, Sephora, Old Navy, Men’s Wearhouse, Walmart, Target, and Safeway—each reflects the retail industry’s common practice of baiting consumers to gather data on them and then to obfuscate the process by presenting confounding privacy policies. Indeed, “frictionless” and “seamless” are current industry buzzwords for a process that doesn’t provoke people to stop and ask tough questions about the technologies influencing them. “By investing in mobile applications and frictionless digital payment tools that incorporate loyalty, coupons and rewards in-store,” said the global head of retail consultant Accenture, “retailers can provide a seamless bridge between customers’ online and offline experiences.”77 And a trade publication article on Target stressed that the retailer “plans to strengthen its data, analytics and technology capabilities to deliver more personalized digital experiences, loyalty programs and promotional offers.”78
Such a retailing environment raises some major questions: What does personalization really mean? What should personalized messages express? In an era where personalized information can yield tailored prices as well as other offers, what should the balance be? And in what direction is retailing headed as a result of personalization?