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BACKPAGE            andrew pearson




From dice to predictive analytics

G
          ambling—the wagering of something valuable on            hood of his or her response to an offer based upon spending
          an event of an uncertain outcome with the prima-         history. For example, if a customer has a history of dining
          ry intent of winning additional money or material        at the casino’s finer restaurants, he or she may not respond
goods—has been with us since ancient times. Greek mythol-          to—or even be offended by—an offer for a buffet.
ogy tells the story of Poseidon, Zeus and Hades dividing the         One key thing that must be factored into these models is
world between themselves in a dice game; Poseidon won the          to look beyond the redemption rate, but into the additional
sea, Zeus the heavens and Hades the underworld. The land, I        revenue generated from these offers. If the patron received
presume, was left to the rest of us.                               an offer, redeemed it and hit the tables to gamble extensively,
  This intriguing beginning has rise to the opulent gambling       he or she is obviously being valued over other customers that
temples of today: Las Vegas’s Bellagio, Palazzo and Wynn,          take the free food and don’t gamble. Models that include fac-
Atlantic City’s Taj Mahal, Tropicana and Caesars, and Ma-          tors of overall spending can help casinos to target their most
cau’s Venetian, Grand Lisboa, and, ironically we come full         profitable customers, instead of gambling their promotional
circle, to the clumsily named casino ‘Greek Mythology’ in          offers—and valuable hotel rooms—on customers that gener-
Taipa.                                                             ate less revenue.
  Just like executives in every other industry, today’s casino
executives are faced with an inherent question—how do I            Campaign optimization
differentiate myself from my competitors when the tools I            Models such as these aren’t unique to the gaming indus-
have are basically the same industry-wide? The answer lies in      try. The financial services, telecommunications, retail, insur-
business intelligence, customer intelligence, data modeling        ance and healthcare industries can all benefit from using such
                                                                   data modeling and analytics techniques. Through matching
                                                                   marketing offers with the customer profile, a company can
                                                                   project the anticipated redemptions and potential revenue to
     ROI trumps all and nothing
                                                                   be generated from a campaign. This gives the marketing de-
     else matters
                                                                   partment enormous leverage, as they can review an antici-
                                                                   pated campaign and make adjustments to achieve the desired
and predictive analytics. Companies now have to be smarter         results, before it even started.
than their competitors in understanding and attracting their         Casinos all have a daunting weekly task: to fill thousands of
customers. Although marketing is best when it’s subtle and         hotel rooms and hundreds of gaming tables. But the lessons
taps into a customer’s desires and needs, the goal of market-      learned here are not unique to the gaming industry. Customer
ing is anything but subtle. Its sole objective is to generate      relationship management is important to almost every indus-
revenue. ROI trumps all and nothing else matters.                  try and the lessons learned in the gaming industry should be
   There is an old adage in marketing circles that says it’s far   heeded by all.                                              3
more cost effective to keep a customer than to acquire a new       Note that the views expressed by BackPage contributors do
one. Technologies like business intelligence, customer intel-      not necessarily reflect the views of Computerworld Hong
ligence, data modeling and predictive analytics help to retain     Kong or its editorial staff.
customers, as they are not just about analyzing data. They are
about creating a predictable relationship with the customer.
These tools help predict future customers’ behaviors by ana-                          Andrew Pearson is a consultant at
                                                                                      Qualex Consulting Service. His expert
lyzing their basic demographics and the psychological traits
                                                                                      includes business analytics in the
of their desires and needs, thereby bringing them offers that                         gaming industry and mobile marketing.
are more enticing and irresistible.                                                   Contact him at andrew@qlx.com.
   In the casino industry today, analytics are used to identify
the optimum offer for specific customer by projecting likeli-

42 Computerworld Hong Kong October 2011                                                                            www.cw.com.hk

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From dice to predictive analytics

  • 1. BACKPAGE andrew pearson From dice to predictive analytics G ambling—the wagering of something valuable on hood of his or her response to an offer based upon spending an event of an uncertain outcome with the prima- history. For example, if a customer has a history of dining ry intent of winning additional money or material at the casino’s finer restaurants, he or she may not respond goods—has been with us since ancient times. Greek mythol- to—or even be offended by—an offer for a buffet. ogy tells the story of Poseidon, Zeus and Hades dividing the One key thing that must be factored into these models is world between themselves in a dice game; Poseidon won the to look beyond the redemption rate, but into the additional sea, Zeus the heavens and Hades the underworld. The land, I revenue generated from these offers. If the patron received presume, was left to the rest of us. an offer, redeemed it and hit the tables to gamble extensively, This intriguing beginning has rise to the opulent gambling he or she is obviously being valued over other customers that temples of today: Las Vegas’s Bellagio, Palazzo and Wynn, take the free food and don’t gamble. Models that include fac- Atlantic City’s Taj Mahal, Tropicana and Caesars, and Ma- tors of overall spending can help casinos to target their most cau’s Venetian, Grand Lisboa, and, ironically we come full profitable customers, instead of gambling their promotional circle, to the clumsily named casino ‘Greek Mythology’ in offers—and valuable hotel rooms—on customers that gener- Taipa. ate less revenue. Just like executives in every other industry, today’s casino executives are faced with an inherent question—how do I Campaign optimization differentiate myself from my competitors when the tools I Models such as these aren’t unique to the gaming indus- have are basically the same industry-wide? The answer lies in try. The financial services, telecommunications, retail, insur- business intelligence, customer intelligence, data modeling ance and healthcare industries can all benefit from using such data modeling and analytics techniques. Through matching marketing offers with the customer profile, a company can project the anticipated redemptions and potential revenue to ROI trumps all and nothing be generated from a campaign. This gives the marketing de- else matters partment enormous leverage, as they can review an antici- pated campaign and make adjustments to achieve the desired and predictive analytics. Companies now have to be smarter results, before it even started. than their competitors in understanding and attracting their Casinos all have a daunting weekly task: to fill thousands of customers. Although marketing is best when it’s subtle and hotel rooms and hundreds of gaming tables. But the lessons taps into a customer’s desires and needs, the goal of market- learned here are not unique to the gaming industry. Customer ing is anything but subtle. Its sole objective is to generate relationship management is important to almost every indus- revenue. ROI trumps all and nothing else matters. try and the lessons learned in the gaming industry should be There is an old adage in marketing circles that says it’s far heeded by all. 3 more cost effective to keep a customer than to acquire a new Note that the views expressed by BackPage contributors do one. Technologies like business intelligence, customer intel- not necessarily reflect the views of Computerworld Hong ligence, data modeling and predictive analytics help to retain Kong or its editorial staff. customers, as they are not just about analyzing data. They are about creating a predictable relationship with the customer. These tools help predict future customers’ behaviors by ana- Andrew Pearson is a consultant at Qualex Consulting Service. His expert lyzing their basic demographics and the psychological traits includes business analytics in the of their desires and needs, thereby bringing them offers that gaming industry and mobile marketing. are more enticing and irresistible. Contact him at andrew@qlx.com. In the casino industry today, analytics are used to identify the optimum offer for specific customer by projecting likeli- 42 Computerworld Hong Kong October 2011 www.cw.com.hk