Understand the difference between winning and losing gaming customers and use this information to create more loyal and profitable guests.
Common sense tells us that winners and losers perceive their gaming experience differently. Everyone likes to win. Therefore winning, in and of itself, is reinforcing. No one starts a game saying, “I hope I lose!” Repeat customers are important to the profitability of any business. In the gaming industry, repeat business is imperative for player development. Since winning is reinforcing but losing is not, the gaming industry faces a unique challenge – how to keep both winners and losers returning.
To learn how to keep both winners and losers returning, we can examine motives for gambling. There has been much scientific research conducted on the factors motivating people to gamble. This research has been conducted by scientists in various disciplines including economics, psychology, psychiatry, and sociology. Ronald Smith and Frederick Preston, both faculty at the University of Nevada, Las Vegas, conducted a study on motives for gambling behavior. In this scientific study, published in Sociological Perspectives, they examine eleven typologies of motives proposed by scientists in numerous disciplines. In their study, gamblers most often reported “play, leisure, and recreation” as their motives for gambling. Smith and Preston also found the related motive of “relieving boredom and generating excitement” to be important.
June Cotte, a scientist at the University of Connecticut, has also conducted research on gambling motives. Specifically, she set out to answer the question, “Why do gamblers spend their leisure time and money on gambling?” Her study indicates that gambling motives are diverse and complex and include risk-seeking, thrill-seeking, or just looking for something new to do on a Friday night.
In addition to having knowledge about motives for gambling, it is also helpful to know how the experiences of winners compare to those of losers if we want to increase intent to return in both types of customers. While common sense can tell us that the experiences of winners and losers differ, science can tell us how they differ. The research studies mentioned above found that motives for gambling include excitement and thrill-seeking, experiences that bring about physiological changes in the body. When a person experiences excitement, the intense emotional state increases arousal in the nervous system. This is evidenced by, among other things, an increase in heart rate. Kenny Coventry and Jennie Hudson, psychologists at the University of Plymouth, conducted a study comparing heart-rate increases during gambling in winners and losers. Although they found significant increases in heart-rate while a person was gambling – compared to measurements taken before the person began gambling – in losers these increases were slight compared to the increases found when participants won during play. In addition, Coventry and Hudson found that winning/losing was the only variable among a range of variables that was a significant predictor of heart-rate increase during play. These results are even more interesting given that people who won played, on average, fewer trials than people who lost. Thus, they concluded that winning during gambling is essential in order to maintain increased heart-rate levels during play.
Psychologist Edelgard Wulfert at the University of Albany, State University of New York, led a laboratory experiment to determine whether the chance to win money influenced excitement as measured by heart-rate. In this study, winning and losing were experimentally manipulated. Participants watched a videotaped horse race with an exciting neck-to-neck finish. While all participants predicted the winning horse, half made a wager on the race with the chance to increase their bet seven-fold, the other half of the participants made no wager. The participants who had a chance to win money showed greater heart-rate elevations and reported more subjective excitement while watching the race compared to those participants who did not wager. Of the participants who wagered, the winners had higher heart-rates after the end of the race than those who lost. Wulfert’s findings indicate that the expectancy of winning money is an important contributing factor to the excitement associated with gambling.
So from the scientific studies conducted on motives for gambling and winner/loser differences we learn that (1) many gamblers are looking for excitement; (2) excitement is evidenced by higher heart-rates; (3) the expectancy of winning money contributes to excitement when gambling; and (4) winning increases heart-rates much more than losing. While informative, these facts do not answer the question of what will motivate customers to return to your gaming establishment. You could try to provide a gaming environment that is very exciting but how do you know what, specifically, besides winning, will cause a customer to perceive your establishment as exciting? Also, how do you meet the greater challenge of getting losing customers to perceive their experience as exciting?
Let the customers tell you how.
If only it were that simple, right? It is. Psychologists say that people have attitudes about everything and knowledge of customers’ attitudes can help us predict their behavior. If you want to know your customers’ attitudes about their gaming experience at your establishment, ask them and they will tell you. However, while customers have knowledge of their attitudes, their knowledge of the predictors of their own behavior is limited. Why?
The problem is partially due to the difference between explicit and implicit attitudes. Explicit attitudes are conscious attitudes that we can easily verbalize. For example, if you ask me what my favorite flower is, I will immediately tell you the answer – a rose. I can answer the question immediately because my attitude about flowers is explicit. However, implicit attitudes are unconscious and difficult or impossible to verbalize. These are attitudes we may not even be aware that we have, but they influence our behavior nonetheless. Since some of our attitudes are implicit, this poses a challenge when trying to use attitudes to predict customers’ behaviors.
There is a second challenge to using attitudes to predict customers’ behaviors – attitudes are poor predictors unless they are specific. Let’s say, for example, that I want to predict whether people in a sample will attend some type of religious service this week. I could measure their attitudes by asking a simple “yes” or “no” question – “Are you religious?” If the person answers in the affirmative we could predict that he or she will attend some type of religious service this week. Unfortunately, our predictions will not be very accurate because the attitude we have measured is too general. What does it really mean to be religious? People attach many different meanings to this term. Instead, we need to measure a specific attitude. To accomplish this we could ask, “Do you believe it is important to attend religious services on a regular basis?” We can predict with a much greater degree of accuracy that people who answer this question in the affirmative will attend some type of religious service this week. Of course, we still will not be able to predict with 100% accuracy since some of the individuals in the sample may be ill or have to work on the day or days they would normally attend. Still, the accuracy will be significantly higher than it was with the general question.
To predict behavior you need to know about a person’s specific explicit attitudes, and their implicit attitudes. How do you discover this information? If learning about customer attitudes is as simple as asking them, but some attitudes are implicit, how do you get all the information you need to predict behavior and keep your customers coming back?
The answer is two-fold. First, question quality is one key. A question must be well-written in order to discover specific explicit attitudes. The second key is the analysis – it takes a highly specialized type of statistical analysis to discover implicit attitudes and predictors of behavior.
As for the first key, how do you know if a survey item/question is well-written? Here are seven characteristics of well-written questions:
- 1. They are simple sentences that ask only one question at a time.
- Too often people write survey questions that are actually two questions in one. For example, “The casino has a good mix of table game types and limits.” If customers respond to this question by saying “moderately agree,” you do not know if they are agreeing that the casino has a good mix of table game types or if they are agreeing that the casino has a good mix of table game limits. Perhaps they strongly agree that the casino has a good mix of table game types, but only slightly agree that the casino has a good mix of table game limits thus they choose the “moderately agree” option. The only way to know how your customers feel about each issue is to divide these into two separate questions.
- 2. Well-written questions are concise and efficient.
- To avoid confusion the questions should not be too long or ambiguous.
- 3. Good survey items avoid using the words “always” and “never.”
- It is rare for something to always be true or to never be true. Using these words in a survey question will reduce the usefulness of your data.
- 4. Well-written survey items avoid providing negative information.
- Items are informative as well as inquisitive. For example, “The gaming rewards card program is difficult to understand” tells the customer that the program is difficult to understand. The item should read, “The gaming rewards card program is easy to understand.”
- 5. Good quality survey items are actionable.
- “I am satisfied with the wait time for casino cashiers” is an actionable item. If customers disagree with this statement, you know exactly what you need to do to correct the problem – add more cashiers at peak times.
- 6. Survey item response scales should be balanced (unbiased to the positive or the negative).
- If customers are given a scale that includes only: disagree, slightly agree, moderately agree, and strongly agree, the scale is not balanced; rather, it has a positive bias. While a positively biased scale may make your statistics look good, it will not provide you with the valid and informative data you need to take profit-increasing actions.
- 7. The item response scale should have no neutral point.
- If you give customers a response choice such as “neither agree nor disagree,” twenty percent of the time they will choose this option. As stated previously, people have attitudes about everything. However, psychological research has shown that most people do not want to think any harder than they have to. Thus, when given the option not to think about an item people will sometimes take it rather than exert the mental effort needed to answer the question. Neutral responses do not provide you with useful information. The bottom line – they waste your money.
As for the second key, what type of statistical analyses can uncover implicit attitudes and predictors of behavior? To accomplish this you must use inferential (predictive) statistics. Inferential statistics are used to infer, deduce, conclude, or predict behavior in a population. First, correlations of all items must be performed to identify relationships. This analysis provides preliminary indicators of key factors or “drivers” of behavior. Next, stepwise, linear regression analyses need to be conducted. The final step involves performing a psychological path analysis. This identifies the item or items that have the greatest effect on the largest number of other items. Once you have this information, you will know what issues you need to address in order to increase your customers’ intent to return to your gaming establishment.
Now you know the characteristics of good survey questions and you know the type of statistical analyses you need to perform in order to predict your customers’ behavior. There is one final issue: “How do you know what questions to ask?” Obviously question content is just as important as question quality. For years, organizational psychologists have relied on one-on-one interviews with customers to find out what the key issues are in order to develop surveys that will measure all of the relevant issues. Unfortunately, this is time-consuming and expensive.
However, there is now a way to avoid this time and expense and still have a scientifically sound research instrument that will help you predict your customers’ behaviors. Since organizational psychologists have conducted explorative customer interviews for years, they have now collected enough data to identify the key issues that are common across customers in every industry! With this information they have been able to develop standardized customer surveys that uncover customers’ attitudes about every one of these issues. In addition, organizational psychologists have also compiled benchmarking data on each of these issues. That means that these questions have been tested on millions of customers and the “normal” responses have been identified. When your customers answer these same questions, you can learn how their responses compare to the responses of other customers across industries or just within your own industry. This information is vital because it is the only way to derive real meaning from your own data. For example, how do you determine if a man who is 5′ 9″ tall is considered by other people to be short, average, or tall? You cannot answer that question unless you know the man’s country of residence. If he is living in the U.S., he will be considered average since the average height of American males is 5 feet 9 inches. However, if the man is living in Vietnam, he will be considered tall since the average height of males in Vietnam is 5 feet 4 inches. Knowing how your customers’ attitudes compare with those of other businesses provides you with the information you need to determine if your score on an item is good or poor.
The National Business Research Institute, Inc. (NBRI) used a standardized customer survey to uncover differences in winning and losing customers for a major hotel and casino chain. This scientific study revealed that winners at this chain want a casino that is fun and exciting and has a good mix of game limits. While these factors increase satisfaction, long wait times for services decrease satisfaction. Additionally, winning customers’ perceptions of security drive intent to return for this casino chain – winning customers are more likely to return to establishments where they feel safe.
Like winning customers, losing customers at this chain want a casino that is fun and exciting. However, the similarities begin and end with this factor. Customer satisfaction for losing customers of this casino chain is also driven by the customer’s perceived value of the gaming rewards card program and the friendliness and helpfulness of the casino restaurant staff. NBRI was able to reveal that intent to return for customers who lose at this chain is also driven by several other factors. Losing customers for this chain are first and foremost more likely to return to a casino where they feel lucky. This factor uncovers an important challenge that the Gaming Industry must address in order to keep losing customers coming back. Secondary drivers of intent to return for losing customers at this chain include the wait time for cashiers – longer wait times decrease a customer’s likelihood of returning – and the quality of the food in the casino’s restaurants. Armed with this information, this casino chain has been able to implement changes to increase repeat business and profitability.
It is important to keep in mind that the drivers of customer behavior are unique to each establishment and change over time. This is why surveying customers regularly is so vital to the profitability of any business. If your company has the desire to understand your customer’s behavior, you should seriously consider hiring a survey research consulting firm to conduct and analyze your customer survey. Organizational psychologists at NBRI have developed a standardized customer survey that contains Best Practice items. NBRI is also the only survey research firm that has customer survey benchmarking data.