After studying this section you should be able to do the following:
- Understand how Harrah’s has used IT to move from an also-ran chain of casinos to become the largest gaming company based on revenue.
- Name some of the technology innovations that Harrah’s is using to help it gather more data, and help push service quality and marketing program success.
Harrah’s Entertainment provides an example of exceptional data asset leverage in the service sector, focusing on how this technology enables world-class service through customer relationship management.
Gary Loveman is a sort of management major trifecta. The CEO of Harrah’s Entertainment is a former operations professor who has leveraged information technology to create what may be the most effective marketing organization in the service industry. If you ever needed an incentive to motivate you for cross-disciplinary thinking, Loveman provides it.
Harrah’s has leveraged its data-powered prowess to move from an also-ran chain of casinos to become the largest gaming company by revenue. The firm operates some fifty-three casinos, employing more than eighty-five thousand workers on five continents. Brands include Harrah’s, Caesars Palace, Bally’s, Horseshoe, and Paris Las Vegas. Under Loveman, Harrah’s has aggressively swallowed competitors, the firm’s $9.4 billion buyout of Caesars Entertainment being its largest deal to date.
Data drives the firm. Harrah’s collects customer data on just about everything you might do at their properties—gamble, eat, grab a drink, attend a show, stay in a room. The data’s then used to track your preferences and to size up whether you’re the kind of customer that’s worth pursuing. Prove your worth, and the firm will surround you with top-tier service and develop a targeted marketing campaign to keep wooing you back (Magnini, et. al., 2003).
The ace in the firm’s data collection hole is its Total Rewards loyalty card system. Launched over a decade ago, the system is constantly being enhanced by an IT staff of seven hundred, with an annual budget in excess of $100 million (Swabey, 2007). Total Rewards is an opt-in loyalty program, but customers consider the incentives to be so good that the card is used by some 80 percent of Harrah’s patrons, collecting data on over forty-four million customers (Wagner, 2008; Haugsted, 2007).
Customers signing up for the card provide Harrah’s with demographic information such as gender, age, and address. Visitors then present the card for various transactions. Slide it into a slot machine, show it to the restaurant hostess, present it to the parking valet, share your account number with a telephone reservation specialist—every contact point is an opportunity to collect data. Between three hundred thousand and one million customers come through Harrah’s doors daily, adding to the firm’s data stash and keeping that asset fresh (Hoover, 2007).
Who Are the Most Valuable Customers?
All that data is heavily and relentlessly mined. Customer relationship management should include an assessment to determine which customers are worth having a relationship with. And because Harrah’s has so much detailed historical data, the firm can make fairly accurate projections of customer lifetime value (CLV). CLV represents the present value of the likely future income stream generated by an individual purchaser1. Once you know this, you can get a sense of how much you should spend to keep that customer coming back. You can size them up next to their peer group and if they fall below expectations you can develop strategies to improve their spending.
The firm tracks over ninety demographic segments, and each responds differently to different marketing approaches. Identifying segments and figuring out how to deal with each involves an iterative model of mining the data to identify patterns, creating a hypothesis (customers in group X will respond to a free steak dinner; group Y will want ten dollars in casino chips), then testing that hypothesis against a control group, turning again to analytics to statistically verify the outcome.
The firm runs hundreds of these small, controlled experiments each year. Loveman says that when marketers suggest new initiatives, “I ask, did we test it first? And if I find out that we just whole-hogged, went after something without testing it, I’ll kill ’em. No matter how clever they think it is, we test it” (Nickell, 2002). The former ops professor is known to often quote quality guru W. Edwards Deming, saying, “In God we trust; all others must bring data.”
When Harrah’s began diving into the data, they uncovered patterns that defied the conventional wisdom in the gaming industry. Big money didn’t come from European princes, Hong Kong shipping heirs, or the Ocean’s 11 crowd—it came from locals. The less than 30 percent of customers who spent between one hundred and five hundred dollars per visit accounted for over 80 percent of revenues and nearly 100 percent of profits (Swabey, 2007).
The data also showed that the firm’s most important customers weren’t the families that many Vegas competitors were trying to woo with Disneyland-style theme casinos—it was Grandma! Harrah’s focuses on customers forty-five years and older: twenty-somethings have no money, while thirty-somethings have kids and are too busy. To the premiddle-aged crowd, Loveman says, “God bless you, but we don’t need you” (Haugsted, 2007).
Data-Driven Service: Get Close (but Not Too Close) to Your Customers
The names for reward levels on the Total Rewards card convey increasing customer value—Gold, Diamond, and Platinum. Spend more money at Harrah’s and you’ll enjoy shorter lines, discounts, free items, and more. And if Harrah’s systems determine you’re a high-value customer, expect white-glove treatment. The firm will lavish you with attention, using technology to try to anticipate your every need. Customers notice the extra treatment that top-tier Total Rewards members receive and actively work to improve their status.
To illustrate this, Loveman points to the obituary of an Ashville, North Carolina, woman who frequented a casino Harrah’s operates on a nearby Cherokee reservation. “Her obituary was published in the Asheville paper and indicated that at the time of her death, she had several grandchildren, she sang in the Baptist choir and she was a holder of the Harrah’s Diamond Total Rewards card.” Quipped Loveman, “When your loyalty card is listed in someone’s obituary, I would maintain you have traction” (Loveman, 2005).
The degree of customer service pushed through the system is astonishing. Upon check in, a Harrah’s customer who enjoys fine dining may find his or her table is reserved, along with tickets for a show afterward. Others may get suggestions or special offers throughout their stay, pushed via text message to their mobile device (Wagner, 2008). The firm even tracks gamblers to see if they’re suffering unusual losses, and Harrah’s will dispatch service people to intervene with a feel-good offer: “Having a bad day? Here’s a free buffet coupon” (Davenport & Harris, 2007).
The firm’s CRM effort monitors any customer behavior changes. If a customer who usually spends a few hundred a month hasn’t shown up in a while, the firm’s systems trigger follow-up contact methods such as sending a letter with a promotion offer, or having a rep make a phone call inviting them back (Loveman, 2005).
Customers come back to Harrah’s because they feel that those casinos treat them better than the competition. And Harrah’s laser-like focus on service quality and customer satisfaction are embedded into its information systems and operational procedures. Employees are measured on metrics that include speed and friendliness and are compensated based on guest satisfaction ratings. Hourly workers are notoriously difficult to motivate: they tend to be high-turnover, low-wage earners. But at Harrah’s, incentive bonuses depend on an entire location’s ratings. That encourages strong performers to share tips to bring the new guy up to speed. The process effectively changed the corporate culture at Harrah’s from an every-property-for-itself mentality to a collaborative, customer-focused enterprise (Magnini & Honeycutt, 2003).
While Harrah’s is committed to learning how to make your customer experience better, the firm is also keenly sensitive to respecting consumer data. The firm has never sold or given away any of its bits to third parties. And the firm admits that some of its efforts to track customers have misfired, requiring special attention to find the sometimes subtitle line between helpful and “too helpful.” For example, the firm’s CIO has mentioned that customers found it “creepy and Big Brother-ish” when employees tried to greet them by name and talk with them about their past business history at Harrah’s, so the firm backed off (Wagner, 2008).
Harrah’s is constantly tinkering with new innovations that help it gather more data and help push service quality and marketing program success. When the introduction of gaming in Pennsylvania threatened to divert lucrative New York City gamblers from Harrah’s Atlantic City properties, the firm launched an interactive billboard in New York’s Times Square, allowing passers-by to operate a virtual slot machine using text messages from their cell phones. Players dialing into the video billboard not only control the display, they receive text message offers promoting Harrah’s sites in Atlantic City2.
At Harrah’s, tech experiments abound. RFID-enabled poker chips and under-table RFID readers allow pit bosses to track and rate game play far better than they could before. The firm is experimenting with using RFID-embedded bracelets for poolside purchases and Total Rewards tracking for when customers aren’t carrying their wallets. The firm has also incorporated drink ordering into gaming machines—why make customers get up to quench their thirst? A break in gambling is a halt in revenue.
The firm was also one of the first to sign on to use Microsoft’s Surface technology—a sort of touch-screen and sensor-equipped tabletop. Customers at these tables can play bowling and group pinball games and even pay for drinks using cards that the tables will automatically identify. Tech even helps Harrah’s fight card counters and crooks, with facial recognition software scanning casino patrons to spot the bad guys (Lohr, 2007).
A walk around Vegas during Harrah’s ascendency would find rivals with bigger, fancier casinos. Says Loveman, “We had to compete with the kind of place that God would build if he had the money.…The only thing we had was data” (Swabey, 2007).
That data advantage creates intelligence for a high-quality and highly personal customer experience. Data gives the firm a service differentiation edge. The loyalty program also represents a switching cost. And these assets combined to be leveraged across a firm that has gained so much scale that it’s now the largest player in its industry, gaining the ability to cross-sell customers on a variety of properties—Vegas vacations, riverboat gambling, locally focused reservation properties, and more.
Harrah’s chief marketing officer, David Norton, points out that when Total Rewards started, Harrah’s was earning about thirty-six cents on every dollar customers spent gaming—the rest went to competitors. A climb to forty cents would be considered monstrous. By 2005 that number had climbed to forty-five cents, making Harrah’s the biggest monster in the industry (Lundquist, 2005). Some of the firm’s technology investments have paid back tenfold in just two years—bringing in hundreds of millions of dollars (Swabey, 2007).
The firm’s technology has been pretty tough for others to match, too. Harrah’s holds several patents covering key business methods and technologies used in its systems. After being acquired by Harrah’s, employees of Caesars lamented that they had, for years, unsuccessfully attempted to replicate Harrah’s systems without violating the firm’s intellectual property (Hoover, 2007).
Harrah’s efforts to gather data, extract information, and turn this into real profits is unparalleled, but it’s not a cure-all. Broader events can often derail even the best strategy. Gaming is a discretionary spending item, and when the economy tanks, gambling is one of the first things consumers will cut. Harrah’s has not been immune to the world financial crisis and experienced a loss in 2008.
Also note that if you look up Harrah’s stock symbol you won’t find it. The firm was taken private in January 2008, when buyout firms Apollo Management and TPG Capital paid $30.7 billion for all of the firm’s shares. At that time Loveman signed a five-year deal to remain on as CEO, and he’s spoken positively about the benefits of being private—primarily that with the distraction of quarterly earnings off the table, he’s been able to focus on the long-term viability and health of the business (Knightly, 2009).
But the firm also holds $24 billion in debt from expansion projects and the buyout, all at a time when economic conditions have not been favorable to leveraged firms (Lattman, 2009). A brilliantly successful firm that developed best-in-class customer relationship management in now in a position many consider risky due to debt assumed as part of an overly optimistic buyout occurring at precisely the time when the economy went into a terrible funk. Harrah’s awesome risk-reducing, profit-pushing analytics failed to offer any insight on the wisdom (or risk) in the debt and private equity deals.
- Harrah’s Entertainment provides an example of exceptional data asset leverage in the service sector, focusing on how this technology enables world-class service through customer relationship management.
- Harrah’s uses its Total Rewards loyalty card system to collect customer data on just about everything you might do at their properties—gamble, eat, drink, see a show, stay in a room, and so on.
- Individual customers signing up for the Total Rewards loyalty card provide Harrah’s with demographic information such as gender, age, and address, which is combined with transactional data as the card is used.
- Data mining also provides information about ninety-plus customer demographic segments, each of which responds differently to different marketing approaches.
- If Harrah’s systems determine you’re a high-value customer, you can expect a higher level of perks and service.
- Harrah’s CRM effort monitors any customer behavior changes.
- Harrah’s uses its information systems and operating procedures to measure employees based on metrics that include speed and friendliness, and compensates them based on guest satisfaction ratings.
Questions and Exercises
- What types of customer data does Harrah’s gather?
- How is the data that Harrah’s collects used?
- Describe Harrah’s most valuable customers? Approximately what percentage of profits does this broad group deliver to the firm?
- List the services a Rewards Card cardholder might expect.
- What happens when a good, regular customer stops showing up?
- Describe how Harrah’s treats customer data.
- List some of the technology innovations that Harrah’s is using to help it gather more data, and help push service quality and marketing program success.
- How does Harrah’s Total Rewards loyalty card system represent a switching cost?
- What is customer lifetime value? Do you think this is an easier metric to calculate at Harrah’s or Wal-Mart? Why?
- How did intellectual property protection benefit Harrah’s?
- Discuss the challenges Harrah’s may have to confront in the near future.
- Describe the role that testing plays in initiatives? What advantage does testing provide the firm? What’s the CEO’s attitude to testing? Do you agree with this level of commitment? Why or why not?
1“Which Customers Are Worth Keeping and Which Ones Aren’t? Managerial Uses of CLV,” Knowledge@Wharton, July 30, 2003, http://knowledge.wharton.upenn.edu/article.cfm?articleid=820.
2“Future Tense: The Global CMO,” Economist Intelligence Unit, September 2008.
Davenport T. and J. Harris, Competing on Analytics: The New Science of Winning (Boston: Harvard Business School Press, 2007).
Haugsted, L., “Better Take Care of Big Spenders; Harrah’s Chief Offers Advice to Cablers,” Multichannel News, July 30, 2007.
Hoover, N., “Chief of the Year: Harrah’s CIO Tim Stanley,” Information Week Research and Reports, 2007.
Knightly, A., “Harrah’s Boss Speaks,” Las Vegas Review-Journal, June 14, 2009.
Lattman, P., “A Buyout-Shop Breather,” Wall Street Journal, May 30, 2009.
Lohr, S., “Reaping Results: Data-Mining Goes Mainstream,” New York Times, May 20, 2007.
Loveman, G., Speech and Comments, Chief Executive Club of Boston College, January 2005; emphasis added.
Lundquist, E., “Harrah’s Bets Big on IT,” eWeek, July 20, 2005.
Magnini, V., E. Honeycutt, and S. Hodge, “Data Mining for Hotel Firms: Use and Limitations,” Cornell Hotel and Restaurant Administration Quarterly, April 2003, http://www.entrepreneur.com/tradejournals/article/101938457.html.
Nickell, J., “Welcome to Harrah’s,” Business 2.0, April 2002.
Swabey, P., “Nothing Left to Chance,” Information Age, January 18, 2007.
Wagner, M., “Harrah’s Places Its Bet On IT,” InformationWeek, September 16, 2008.
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