1. Casino Customer Demographics
2. Casino Customer Demographics
3. Casino Nsw Demographics

Just like its rivals for consumers’ disposable income, America’s $90-billion-a-year gaming and casino industry is significantly driven by database marketing. But gaming customers are very different in one major respect.

While adult patrons of a hit movie, for example, know they will spend about $8 to $10 on a ticket, perhaps buy soda and popcorn and then head home, some casino customers lose huge sums of money while a few others might actually make a profit, especially those who are skilled at games such as blackjack.

1. In 2011 there were 10558 people living in Casino. 48.2% are male and 51.8% are female.Casino has a population of 937 indigenous people.
2. Those are two of the new 2600 cabinet series arcade-style games Synergy Blue unveiled in hopes of widening the casino demographic. The others are similar to popular mobile games like Toon Blast.
3. In the 2011 census the population of Casino was 10,558 and is comprised of approximately 51.8% females and 48.2% males. The median/average age of the population of Casino is 40 years of age. 89.1% of people living in the suburb of Casino were born in Australia.
4. Forty-five percent of casino players are men, 55 percent are women. Gamblers coming to the casinos during the next decade, however, may be different. Gaming industry leaders have discovered a new trend. They believe casino patrons of the future will have a higher level of college education, and be younger and more carefree.

Can casino owners more accurately identify and predict which of their regular customers will lose the most money? How often will these customers visit? How will they allocate their bets among slots and tables? By targeting those players, can casinos follow up with a more effective direct marketing campaign?

The questions inspired two Wharton faculty members and a colleague at New York University’s Stern School of Business to see if they could develop a mathematical model to identify these most lucrative customers. The three researchers — marketing professors Raghuram Iyengar and Jehoshua Eliashberg, and Sam K. Hui, a marketing professor at Stern — say that the answer is an unqualified yes. Indeed, they wonder why casinos aren’t already using these tools.

The share of American adults that visited a casino in the last year jumped to 44 percent in 2019, up nine percentage points in 2018. This trend looks to continue as almost 124 million American adult —49 percent of the U.S. Adult population— say they will visit a casino to gamble over the next 12 months, up 20 million from 2018.

The issue for casinos “is one of attracting their best customers,” said Iyengar, noting that most casinos and slots parlors already collect some types of extensive marketing data on their customers. “Our list overlaps somewhat with their list, but the lists are not identical.” The casinos are reaching out to their customers, “but they could be doing it better.”

The study by Iyengar, Eliashberg and Hui — entitled “A Model for Gamers’ Revenue in Casinos” — develops a mathematical model which integrates gamers’ frequency of casino visits, their total wagers and the distribution of those bets at table games versus slots machines. The researchers determined if revenue from specific players was derived from “skill” or “luck,” and they were able to identify players who are highly skilled or perhaps revenue-producing high rollers.

Avoiding ‘Unattractive Customers’

Casino Customer Demographics

In addition, the team looked at ways that demographics could provide casino owners with valuable marketing insights. The data suggested, for example, that women devote more of their spending to slot machines than to table games like blackjack, and that men have a higher level of skill at the gaming tables than women. Iyengar and Eliashberg suggested that more useful information could have been gathered if they had been given more specific demographic data. “This information would really help [casinos] target more precisely the most attractive customers, because you certainly don’t want to target the unattractive customers,” Eliashberg said. “You want to spend your money where you get the most bang for your buck.”

While the characteristics they studied are fairly unique to the gaming industry, the authors said there are other business situations in which customers can be identified and targeted based on their specific skills or unusual customer behavior. For instance, they noted that better modeling of customer behavior might help hotel managers to more intelligently market the use of mini-bars or business centers, or allow car-rental firms to target extra-cost products like GPS units or satellite radios.

But it is the sheer size of the casino industry in the United States that makes it such a strong candidate for this kind of individualized predictive modeling, more commonly known as database marketing. Americans spend more money on gaming than on trips to the cinema by a 10-1 ratio, and more money is lost during a typical casino visit than is spent in an average visit to a mall. Of the $90 billion spent on legalized gaming, according to the American Gaming Association, some $59 billion is spent in casinos as opposed to lotteries or pari-mutuel wagering.

Unique aspects of the casino industry suggest that casino operators should be developing different tools for customer relationship management than, for example, mall operators — who analyze how much customers spend on a typical visit to a store and what products they purchased. Through the use of gaming loyalty cards and other tools, casino executives have the ability to more closely track the performance of individual gamers. Access to such player-level behavior, together with mathematical modeling, can help uncover a gambler’s level of skill — an important consideration in determining the individual targets of direct marketing campaigns.

“The use of mathematical models to predict future behavior is very important [because] the most recent profitable gamer is not necessarily going to remain [the] most profitable in the future,” Eliashberg said. “You have to look at the frequency of going to a casino in general and combine it with all sorts of aspects of wagering behavior. Does the customer wager more on slot machines or at the tables? You also have to look at the skill level. You need a model for human beings.”

Iyengar and Eliashberg noted that casinos already perform broad mathematical calculations — based on aggregate behavior — in an effort to predict their overall revenues and profits. The goal of this research, they said, was to come up with a mathematical model that would measure the difference between a typical player’s theoretical and real spending relative to the player’s skill level. The use of a “formal model, which makes clear distinctions among individual gamers,” is a more effective tool than a casino operator’s “judgment based on intuition,” Eliashberg stated.

‘Share of Wallet’

Casino Customer Demographics

The data that researchers examined came from a major U.S. casino operator with gambling facilities in a number of U.S. locations. It provided the authors with detailed information — gathered through the use of loyalty cards — on more than 1,500 customers who made a total of about 9,000 casino visits from December 2004 through April 2007. The gaming company also offered age and gender information for about 400 of those customers.

To determine the skill of the players, the authors ran through a series of complex calculations based upon factors, including the particular games the individual played, the expected take by the casino versus the actual take, and whether a gambler’s winning or losing on one visit affected behavior on the next. While the researchers noted that more work must be done to learn how a gambler’s skill improves at a game, such as blackjack, over time, they believe their model can be a powerful starting point. For example, the authors predict that this new and more detailed type of data can be combined with customer survey results to obtain much better information on so-called “share of wallet” — that is, how much of the money that a gambler budgets for the casino is actually lost on a visit.

Beyond that, they also urge additional research on casino promotional activities — such as complimentary hotel stays or cash-back awards — in order to develop a better sense of how marketing efforts affect high and low revenue gamblers differently. In addition, they note that the customized data could help operators as they weigh how to better design their casino floor space to increase revenues, such as the use of environmental cues to encourage gambling or altering the ratio of table games to slot machines.

“The behavior may change from one facility to another, but we believe this information is helpful in designing your facility in line with customer behavior,” Eliashberg said. In future research, the authors note, they would like to examine more demographic data such as relationship status, home address, profession and education level to gain even more insights into gambling habits.

According to Iyengar, the research has implications in other industries. “A sales force manager could better understand how a person makes a sale,” Iyengar said. “It might make a difference if they could figure out whether it’s the product that’s selling or whether it’s the skill level of the sales person.”

Going to a casino means more than just putting cash into a slot machine or playing some table games. The modern casino has high quality restaurants, fun nightclubs, and even concerts for people to enjoy. This gives the casino demographics an interesting twist that other industries don’t usually have.

The demographic profile of a casino visitor is very similar to the profile of the average American in the US population.

It is a misconception to say that the poorest households typically visit casinos the most. Although this may be true in from a localized standpoint at some casinos, the average household income of a casino visitor is above $35k, but below $100k per year.

Here Is The Typical Casino Visitor

• 78% of casino visitors who go to gamble are generally optimistic about their personal financial situation.
• 57% of gambling casino visitors have saved more money this year when compared to the year before. Only 44% of non-gambling casino visitors can say the same thing.
• 1 in 5 casino gamblers say that they are approached for their opinion about how people should invest their money.
• 37% of all casino visitors say that they speak to friends or relatives when they have questions about financial matters.
• 3 out of 4 gamblers who have not yet retired have plans in place to set aside enough money to meet their retirement goals. 2 out of 5 non-gamblers don’t have any retirement plans in place.
• Men are slightly more likely to find themselves visiting a casino when compared to women.
• If gamblers do find themselves with an income of less than $35k, then they are more likely to have a gambling addiction when compared to other income groups.

Is the sub-20% of people who are living in poverty in the US going to outspend those not in poverty at a casino? Very doubtful. Someone with $100k in income can spend 3x more gambling and still be reasonably secure financially. The problem is that when people who are poor gamble, they are gambling a larger percentage of their income on a game instead of things they may need. This is why the perception exists that gambling hurts the poor the most. Yet despite this, non-gambling revenues exceed gambling revenues in Las Vegas.

How Connected Are Casino Visitors?

• 51% of gamblers who visit a casino say that they stay in-touch with people through email on a regular basis.
• Gamblers [78%] are more likely than non-gamblers [72%] to be homeowners.
• More than 50 million people visit a casino in the average year. Each person makes an average of 7 trips per year, with many using electronic games as their primary source of entertainment.
• People in the 36-50 age demographic are more likely to play slot machine games than any other age demographic. They’re also the most likely to be married and enjoy playing bingo-style games.
• Younger gamblers prefer to play traditional or electronic versions of blackjack.
• People who go to a casino to play craps are the most likely to also gamble online.

Just because electronics and the internet make gambling easier than ever to accomplish, this doesn’t mean that people are actually taking advantage of these mediums. Although casinos are seeing a rise in younger players embracing slot-style machines with electronic versions of roulette, craps, and blackjack available, there is still a preference for table games – especially for players who enjoy poker. Casino visitors are connected, but they don’t necessarily use those connections to actually gamble.

The Values of Casino Visitors

• 58% of gamblers say that they view their work as a career. 51% of non-gamblers say that they view their work as just a job.
• Half of all casino visitors who gamble say that they view owning their own business as their ideal work situation.
• 44% of gamblers say that their definition of personal success includes being a good spouse and/or parent.
• Gamblers are less likely to place an emphasis on what God thinks of them when compared to non-gamblers in every demographic.
• Although both gamblers and non-gamblers [4% each] volunteer at equal rates, it is the gamblers who are more likely to donate money to social issues [33%] than non-gamblers [20%].

Values are something that is subjective to the individual. When it comes to the average casino visitor, the notion of not judging a book by its cover seems very applicable. Gamblers especially are full of surprises when it comes to the values that they hold. It isn’t the poor that are in desperate need for a meal, a bath, and fresh clothes that you’ll find at your average casino. The casino demographics show that someone just like you is who you’re going to find.

Casino Nsw Demographics