by Adam Tanner
The software is predictive, which means it is not always right. Both Stirista and Ethnic Technologies said their software would likely wrongly guess that Barack Obama would be a Muslim of Kenyan extraction. Stirista predicted that I would be Western European, “typically English or German.” They were a few countries off, and missed the Italian half of my heritage, obscured when my mother, with an Italian surname, married my father. It suspected that American Name Society president Donna Lillian was of Irish ancestry. She does have some Irish, but also English, Scottish, and a dash of Native American heritage.
Political campaigns also increasingly use ethnic data. “In politics it’s like marketing on steroids. So you’ve got a one-day sale where you have to get all the shoppers to the store,” says John Phillips, CEO of Aristotle, which uses personal data to help US and foreign candidates. “Political marketing based on ethnicity or nationality is increasingly important.” He cites campaigns in India, Mexico, Tunisia, and elsewhere where nationals living abroad are a vital source of both donations and millions of votes.
Although Gupta is open about his business, many selling and using the data are reluctant to reveal much about racial targeting. Sinisi of Ethnic Technologies spoke at the 2013 DMA convention, but her CEO and other officials have declined to answer subsequent questions. The president of List Service Direct, a rival company, emotionally shooed me away at the DMA convention in Las Vegas in 2012, saying he had been unfairly portrayed as a racist in the past. He did not return later calls and emails.
“When you look at certain ethnic populations and their kind of negative historical experiences with the majority treatment of the minority, there is no surprise that there are some sensitivities,” says Andy Bagnall, executive vice president of strategic direction at Prime Access, an advertising agency specializing in multicultural health-care marketing. “Something that we are very aware of as an agency and the industry is aware of as well is the delicate dance that we play when it comes to hyper-targeting, especially based on ethnicity, because we never want to come across as ‘Big Brotherish.’”
Daniel Ocner, director of strategic marketing and development at multicultural marketing agency MediaMorphosis, says companies must avoid stereotypes such as using a sumo wrestler to seem more Japanese or a kung fu fighter to sell to Chinese. “These are all very cultural segments that don’t apply to everybody. Similar to how we cannot assume that all Americans are cowboys,” he says. Targeting too narrowly could backfire, as Ocner’s surname shows. Stirista’s software took him for “Hispanic (typically Mexican or Brazilian).” In fact, his family is from Argentina and Jewish.
“Any communication that comes across as very stereotypical is not going to get a good reaction from the intended audience,” says Bagnall. Here again, big data can establish the boundaries by testing the results of the marketing. “What has really increased exponentially is our ability to measure whether an ethnic campaign is working or not,” he says. Because of sophisticated use of personal data, such campaigns often do prove effective.
Yet many marketers are cautious about going too far. In a presentation at the 2012 DMA conference, Acxiom’s Suther urged marketers to show restraint even if they could make ever more clever uses of personal data. He told a room full of peers that they would be tempted to go to the dark side and use sensitive data about people.26 “Please do not do it,” he said. “Ask yourself: am I doing something for the customer, or am I doing something to the customer?”
Acxiom regularly solicits Caesars for business, boasting that over the past few years it has sold information to four of the five largest gaming companies, to good effect.27 A former executive for Wynn Resorts says the company made extensive use of Acxiom data and estimated that at the peak, before 2008, its marketing with that data contributed at least 15 percent of the hotel’s occupancy—a number Wynn’s spokesman disputes.28 Acxiom also sells a “casino gambling propensity score” for millions of people. That score combines interest expressed in surveys as well as data on past activities.29
For a long time Gary Loveman and the top Caesars brass were skeptical about the utility of outside data, whether specifying a person’s background or estimated propensity to gamble. “We don’t need to know the income level in Adam’s ZIP code or whether he bought a lawn mower last week or whether his wife had a baby,” Loveman said in one of our early meetings. “We don’t play in any of that stuff. We’re taking a look at whether we are missing something by not doing much of that, but historically we haven’t.”
But everything started to change when the clouds darkened over perpetually sunny Las Vegas in 2008.
8
Recession
The Economic Crisis Hits
Gary Loveman had made Caesars so attractive by 2006 that two private equity firms, Apollo Global Management and TPG Capital, swooped in to take Harrah’s private. Financial markets were soaring, so they paid a staggering $30.7 billion. The firms financed the deal, which was completed in January 2008, by taking out a huge amount of loans. The debt saddled the casino company with big interest payments it would be obligated to pay long into the future. Everything would be fine if business kept growing.
It turned out to be an especially inauspicious time to buy a massive casino company. Vegas was heading into dark days. After continuously building ever more grandiose structures, the industry faced unprecedented debts and liabilities.1 A glut of new rival casinos under construction as the crisis hit worsened matters. Interest payments on past debt claimed an ever greater percentage of revenue.
Loveman started making cuts and other pre-emptive moves to stabilize the business. The numbers were daunting. In Nevada, casinos lost $15 billion in the four years after 2008 before federal income taxes.2 In 2008, Harrah’s lost $5.2 billion. Those guests who continued to come noticed the cutbacks. In a 2009 company survey, customers said they had the impression that the recession had hurt Harrah’s more than it had hit their own pocketbooks. They did not want to come as often, not so much because of their tighter belts but because of the difficulties experienced by the casino chain. “We had cut labor, they didn’t think the property was clean, we had cut marketing offers, maybe some of their favorite employees weren’t there,” said David Norton, the executive who had worked for years to attract steadily spending regulars who had not traditionally been considered VIPs. With the recession putting his back against the wall, Loveman had to squeeze even more value out of his most valuable asset: the personal data in the Total Rewards program.
Massive Total Rewards sign on the side of Bally’s Las Vegas. Source: Author photo.
The New Personal Data Guru
Loveman wanted to hand over the mantle of Total Rewards to someone with fresh ideas and energy, someone who might be able to help the company emerge from the slump. He spent more than a year searching for the right person. In June 2010, after others had conducted preliminary interviews, Loveman invited Joshua Kanter, then a thirty-six-year-old consultant at McKinsey & Company, to lunch at an Italian restaurant across the street from the Harvard Club in New York City. Kanter, with a round face giving him a choirboy look, projected an image about as different from the rough-hewn casino underlings of yesteryear as possible. He wore half-frame eyeglasses and a Harvard class ring on his right hand. He had come a long way since his University Painters days.
Kanter was born in Phoenixville, Pennsylvania, a town outside Philadelphia where part of the cult 1958 sci-fi movie The Blob had been filmed. Growing up, he had devoured math classes; he scored 790 on his math SAT scores, a tad shy of perfect. He had gone to college at Wesleyan, Loveman’s alma mater, dropped out to tend to his painting business, and then resumed his undergraduate studies at Harvard. He had graduated the same year Loveman left the business school across the Charles River to join Harrah’s.
Kanter had first visited a casino as a college student when he went to Foxwoods Resort Casino in Connecticut with his girlfriend and roommate in the middle of the night. When he arrived, he took $100
out of the ATM and decided he would leave with either a second Benjamin in his pocket or nothing at all. Within minutes he had lost $75 at the roulette wheel. He lasted another hour or so at the blackjack table before losing his last dollar. After college he became a consultant in New York. He distinguished himself by working from seven in the morning to eleven at night and by wearing his long black hair far past his shoulders, all while navigating the button-down world of financial services.
About forty-five minutes into their lunch, Loveman paused, tilted his head a bit, and looked straight at Kanter: “I want you to take this job.” The CEO then told him why he should discontinue his twelve-year career as a consultant and join the casino business.
Loveman viewed Kanter as “a very sophisticated, quantitatively literate marketing guy.” He saw the consultant as his third hire of the same ilk, a data F-14 pilot following in the footsteps of Rich Mirman and David Norton, both of whom had served as chief marketing officers. By then Mirman had left the company to become a private consultant in Las Vegas, and Norton was soon to go.3
Later that day a Harrah’s recruiter called Kanter with a job offer and details of a generous package.
The night Kanter accepted the job, he recorded his thoughts in his leather-bound diary. He would not move to Las Vegas, he reminded himself. New York was home to his girlfriend, friends, and a rich array of cultural offerings. He commuted to Las Vegas for a while, staying in company hotels. As a consultant he was used to extensive travel; he took three to five flights a week. Yet the long commute to Las Vegas started to take a toll. Eventually he decided he wanted to live and work in the same place. He gave in and moved to the US casino capital. Breaking into social life in Las Vegas took some time, but the city was much cheaper than New York. He bought the McMansion of his dreams, a 4,200-square-foot house with a pool overlooking a golf course in a gated community. He parked a spiffy Audi A5 sports car in the oversized garage.
Kanter moved to Las Vegas as the company was consolidating its management in an effort to cut costs and make operations more efficient. Instead of duplicating marketing, accounting, and other functions in each region, statistics-loving executives in Vegas oversaw marketing initiatives from Mississippi to Indiana, from the New Jersey shore to San Diego.
The move marked a big change. For much of US casino history, local managers and their pit bosses had great autonomy over their operations. The dealer had a say in what happened at his table, the floor supervisor was responsible for his group of tables, and the manager oversaw his casino. James McElroy remembers well how things used to be. He has worked in Vegas casinos for forty years, climbing his way up from dealer to assistant casino manager at Caesars Palace. He nostalgically recalls the days when the dealer or supervisor had the power to dole out comps, including to friends or even to himself, to enjoy a steak dinner. “A lot of people were receiving comps that didn’t deserve them,” he says.
Joshua Kanter at Caesars Palace, Las Vegas. Source: Author photo.
Today McElroy spends his days in the elegant Caesars Palace high-limit room, where players might wager $50,000 on a single hand of blackjack, and where those putting up $500,000 are escorted into a private gambling salon. But he cannot arbitrarily treat people to free meals. He must follow the same data formula that applies across the company.
The centralization of management gave executives like Joshua Kanter wide authority to set policy for all Caesars properties. But that did not make their jobs any easier. The real problem was that it was getting harder to lure gamblers into casinos. The massive cost-cutting that followed the recession made marketing more difficult. The total number of employees fell dramatically, from 87,000 reported in March 2008 to 69,000 two years later.4
Kanter remained optimistic, believing that even in slower economic times, when plunging staff rolls made the casinos a bit less friendly, Caesars’ trove of personal data remained invaluable for targeting offers and encouraging client loyalty. Yet he thought the company could make better use of the data. In addition, he thought it prudent to expand the amount of information Caesars gathered—not only about gambling but about client spending and behavior more widely.
A lot had changed since the company had formalized its “no outside data” policy on clients in the mid-2000s. Many of the best insights were out in the open in social media, including Facebook.
9
The Puzzle of Your Identity
Six Degrees to Harry Lewis
During Gary Loveman’s time at Harvard Business School, a respected computer science professor became dean of Harvard College on the other side of the Charles River. Harry Lewis was even more of a numbers nerd than Loveman, having earned a PhD in applied mathematics. A top expert on data, he has taught thousands of students about computer science. Like Loveman, he was very interested in what human insights can be gained from people’s data. Because he had worked so long in computer science—starting long before the personal computer era—he was concerned about how much could be revealed about people by aggregating their data. Lewis did not know Loveman, but had heard of him.
One day in January 2004, not long after he stepped down after eight years as dean, Lewis received an email from an ambitious student. Bitter winter winds whipped off the Charles River that morning. Lewis had looked forward to starting a sabbatical, the magical bonus of academic life when tenured professors enjoy a semester away from their normal teaching duties.
The student had grown interested in how public information could link different people and reveal interesting characteristics about them. He had set up a website showing connections between people at the university and had mined the school newspaper, The Harvard Crimson, for the information. “Professor, I’ve been interested in graph theory and its applications to social networks for a while now, so I did some research . . . that has to do with linking people through articles they appear in from the Crimson,” the student wrote. “I thought people would find this interesting, so I’ve set up a preliminary site that allows people to find the connection (through people and articles) from any person to the most frequently mentioned person in the time frame I looked at. This person is you.
“I wanted to ask your permission to put this site up though, since it has your name in its title.”
The student called the proposed site “Six Degrees to Harry Lewis.” The titled referenced a famous study by Stanley Milgram, who found that a random person could link to a stranger through people they knew using about six intermediaries.1 Lewis reacted cautiously to the student, whom he knew from his course “Introduction to the Theory of Computation.”
“Can I see it before I say yes? It’s all public information, but there is somehow a point at which aggregation of public information feels like an invasion of privacy,” Lewis wrote. “I am on sabbatical leave as of today, so you are catching me at a moment where I was about to relish some anonymity:)”
The student replied that he had already set up the site. He emailed the link. Professor Lewis replied with a few suggestions on how to improve it and gave his assent to going public: “Sure, what the hell. Seems harmless.”2
Soon after, Professor Lewis, who had also taught Microsoft founder Bill Gates “Introduction to Combinatorial Mathematics” in the 1970s, said goodbye to another one of his brilliant students who decided to drop out of Harvard. A month later, the student, Mark Zuckerberg, built on that early experiment and created Facebook. In retrospect, Lewis’s initial caution about aggregating public information has proven visionary. One can indeed learn a lot from many innocent facts about someone.
Ten years later, much as Zuckerberg briefly mined the Harvard Crimson to find trends, everyone from casino security officers to marketers and academic researchers regularly hunts for patterns in Facebook and other social networks. Often people find that sites like Facebook give away clues about us that we did not intend to reveal.
Consider, for example, the clues embedded in a person’s “likes.” In June 2007, David Stillwell had just f
inished college in Britain and had time to kill before starting graduate school in psychology. Facebook had about thirty million users at the time (it passed the one billion point in 2012). The social network had just started allowing outside developers to write applications that operated inside the site. Such apps could tap into profiles if users granted permission. Stillwell created myPersonality, an online test that allowed people to take a personality test that measures five main traits: openness to experience, conscientiousness, extraversion, agreeableness, and emotional stability.3 Since then, nearly eight million people have taken the personality test, typically teenagers and twenty-somethings. Americans, Brits, and Canadians are the most active participants. Around 40 percent of those who took the test allowed Stillwell and other researchers to see their Facebook profiles.
In 2013, Stillwell and two other researchers published an analysis of what they could learn from the Facebook “likes” of 58,466 Americans.4 In contrast to some of the more intimate Facebook preferences, likes are among the most innocuous and easily visible items. By default they are public. Just by looking at the likes—and not just obvious preferences such as liking a conservative political site or gay-oriented page—researchers could consistently infer intimate details such as sexual orientation, religion, political views, smoking, alcohol or drug use, and other characteristics. “If we can collect a few bits of data of a person, there is so much that we can predict,” says study coauthor Thore Graepel, a Microsoft researcher. It may sound like a cliché, but the survey supported the idea that liking the musical Wicked or the singer Britney Spears was a good predictor of male homosexuality, much as the preference for rap group Wu-Tang Clan or basketball player Shaquille O’Neal suggested heterosexuality.
The study’s third coauthor, Michal Kosinski, who works with Stillwell at the Psychometrics Centre at the University of Cambridge, is especially sensitive to government abuse of personal information because he grew up in Communist Poland. In fact, he considers himself a product of the martial law that sought to repress the independent Solidarity trade union movement, which eventually undermined the Soviet-backed government. In 1981, when the Polish Communists imposed martial law, many couples opted to spend more time at home rather than go out on the town. Michal was born the following year. He says it might be unnerving for Europeans or Americans to be outed because of how they use the Internet. But it was far more dangerous for people in some other countries. “The same technology used in other countries is not unnerving, just directly dangerous,” he says. “There are many worse things that could happen.”5
