Using Science to Increase Intent to Return for Male and Female Gaming Customers

Using Science to Increase Intent to Return for Male and Female Gaming Customers

Understand the difference between male and female gaming customers and use this information to create more loyal and profitable guests.

Player development is important in the gaming industry. Increasing a customer’s average daily theoretical (ADT) increases profits. How is this accomplished? How do you get customers to increase their ADTs?

Player development cannot be accomplished unless players return to the gaming establishment. Determining what drives a customer’s intent to return is a complex process. You need to be very knowledgeable about your customer base and important target markets within it. Customer behavior does not occur in a vacuum – it occurs in a social context of values.

Take, for example, the gaming behavior of men versus women. Rachel Volberg, Ph.D., has conducted numerous studies on gambling. Comparing data from two national surveys examining male and female gaming behavior she illustrates why both segments of the customer base are important. Data collected in 1975 indicated that the proportion of women who reported ever having gambled was 61%. This number increased to 83% in a 1998 survey. Likewise, the proportion of men who reported ever having gambled was 75% in the 1975 survey and 88% in the 1998 survey. Both segments of the target population are increasing in number although the percentage of women who gamble is increasing at a higher rate. This is likely due to a greater social acceptance of gambling behavior in women.

Other gender differences in gaming behavior exist. Johnnie Johnson and Alistair Bruce have researched gambling behavior extensively and found that gender differences include: the types of games men and women prefer, the types of venues frequented, and propensity for risk taking. It is logical to deduce that gender differences exist in the factors driving intent to return as well. These differences must be identified in order to successfully meet the expectations of both genders and keep them returning to your establishment.

In order to identify how to increase customer satisfaction of both male and female customers you could rely on data from large industry surveys. One such study conducted by Nerilee Hing and Helen Breen indicated that women were influenced by the attractiveness and perceived safety of gambling venues. This study also indicated women liked establishments in which they perceived they were treated with respect. You could use such data in your marketing to women however; since this information is based on many segments of the industry you cannot be sure that the results reflect the attitudes of your customers.

Does it really make a big difference? It does if the attitudes and values of your customers are not identical to those of the people represented in the industry survey. The likelihood that the industry data reflect the attitudes and values of your unique customer base is low. Human behavior is very diverse. That is why social scientists conduct cross-cultural studies. They are aware that the attitudes and behaviors of people in one part of the country can be very different from those in another part of the country. Also, the attitudes and behaviors of people in one country can be quite different from those in other parts of the world.

To illustrate how this can become a problem, let’s say one casino chain uses the information from the industry survey mentioned above to develop their services and marketing toward women. The chain pays great attention to the attractiveness of their facilities and provides their employees with extra training in how to treat customers. They also take measures to increase safety and to inform customers about these measures in order to enhance customer perceptions of safety. All of these actions are taken at some cost but the assumption is that the actions will pay off in increased repeat business. However, intent to return for the women who visit this chain may actually be driven by the desire for a casino environment that is fun and exciting. Therefore, the behavior of these customers is unlikely to be affected by the measures the casino chain has taken.

So how can you know what drives the behavior of your customers and increases intent to return? A survey of your own customers is the obvious solution but how should you go about it? Should you have the survey written in-house or hire a survey research firm? While writing the survey in-house may seem like the most cost-effective solution, just the opposite may be true. Many companies make the mistake of assuming that it does not require any special background to write survey questions. In reality, in order to get useful information from a survey it is imperative that it be well written. Each question must be carefully designed to be clear, nonbiased, and to elicit the type of information you are looking for. Poorly written questions result in useless data.

If you do have someone in your company with a background in sample survey methods who is well qualified to construct your questionnaire, the next issue is how to collect the data. How are you going to select customers to participate in the survey and how will they be contacted? How will the data be compiled? Do you have the necessary hardware and software to collect and analyze the data? Do you have someone with a statistical background who knows how to perform analyses of the data and interpret the results?

The survey process can be a daunting task and most companies do not have sufficient in-house resources to carry out all the necessary components of a good quality survey. It is no surprise that many Fortune 500 companies out-source their customer surveys.

But how do you go about hiring the right research firm for your survey? Here are seven tips for selecting a survey research firm:

1. Consider only well established firms.
Look for a company that has been around for at least 20 years. If the firm has survived this long it stands to reason they are doing something right. It is also safe to assume that they will see your project through to the end and still be around when you are ready to survey again.
2. Choose a firm dedicated solely to survey research.
These firms tend to have more extensive expertise and resources than consulting firms that try to do it all.
3. Look for a firm with well credentialed consultants.
Survey construction methods and the statistics necessary to predict behavior are things typically only taught at the graduate level. Make sure that the firm has consultants with advanced degrees (master’s degrees may be okay but doctoral degrees are even better) in order to be sure that they have the necessary knowledge to design and conduct a scientifically sound study. Otherwise you will be wasting your money.
4. Select a firm that offers every type of methodology.
The company you choose should offer paper surveys, web-based online surveys, and telephone surveys because you may need more than one method to get a representative sample of your customers. A representative sample is one that adequately reflects the key characteristics of your customer population. Such a sample is necessary to make accurate predictions about customers’ future behaviors.
5. The firm should have normative questions available for your use.
Normative questions are survey items that have already been tested on large numbers of people (preferably millions) and are considered normal questions to ask in a customer survey.
6. Pick a firm that provides benchmarking data.
Benchmarking involves comparing your data to data from other companies who have used the same survey items. This is a crucial feature because it is impossible to derive meaning from a survey item based only on the mean (average) score of your sample alone. A score only has meaning if you can compare it to the characteristics of a larger sample. For example, if you knew someone had an IQ (intelligence quotient) score of 130 but you did not know what the average IQ score was or how much people normally deviate from it, the score of 130 has no meaning. It is only when you learn that the average score is 100 and that most people are within 15 points above or below it that you realize 130 is a very good score.
7. Use a firm that will provide predictive as well as descriptive analyses of your data.
Unfortunately, the majority of firms will only use descriptive statistics to analyze your data. Descriptive statistics provide you with summaries about your data. While this information is valuable, it cannot help you determine how your customers may behave in the future. Only if your data is analyzed using predictive statistics can you predict the future behavior of your customers.

This final tip is one of the most important when it comes to solving the problem of increasing your customers’ intent to return. It requires an intricate combination of asking critical questions and performing highly advanced statistical analyses. This is an impossible task unless you have the right tools to accomplish it.

Fortunately, a groundbreaking technique is now available that can provide you with the information you need in order to take the actions necessary to increase intent to return. This statistical tool is known as the Root Cause Analysis.

The Root Cause Analysis goes beyond giving you just a snapshot of your customers’ behavior. Maximizing the benefits of your research requires identifying the customer issues that have the greatest impact on your gaming establishment and addressing them as quickly as possible. Frequently, it is not the lower scoring items on the survey that are the Root Causes; instead it is an item that would have been completely overlooked without this analysis. The Root Cause Analysis is able to identify the fewest number of issues that have the greatest amount of influence over the greatest number of other issues. When you address these Root Causes with appropriate action, performance in the items significantly driven by the Root Causes will increase as well.

A Root Cause Analysis is conducted by performing correlations, regressions, and path analyses on every survey item with every other survey item. The correlations identify the baseline relationships between variables, indicating which variables are related to each other. While correlations can identify which variables are related to each other, they cannot identify cause and effect. In other words, correlations cannot identify which item is the driver and which item is being driven. Some research firms do not go beyond identifying correlations however, when conducting a Root Cause Analysis, correlations are just the beginning.

The second part of a Root Cause Analysis involves conducting what is called a stepwise, linear regression analysis. This analysis serves to measure how much influence each survey item has on each other survey item. While it is impossible to account for every variable affecting an item with 100% accuracy, the Root Cause Analysis identifies drivers with an error level of less than 1%.

A Psychological Path Analysis is the final step of a Root Cause Analysis. This step requires the expertise of an Organizational Psychologist, a psychologist with doctoral level training on business processes and their interdependencies. The Organizational Psychologist analyzes the results of the correlation and regression analyses and then identifies all of the drivers and the survey items they drive. This provides you with the most important items to address. Without this information you could waste months of manpower trying to prioritize issues and evaluate the manpower and budget requirements of interventions to address the various issues and in the end, you may achieve no significant gains for your organization. However, with a Root Cause Analysis this step, and all the time and money involved, is eliminated. When you get your survey results you can immediately begin to plan your interventions and quickly implement them.

To illustrate how the Root Cause Analysis can identify differences in the drivers of intent to return for male and female customers, let’s look at an example of how this analysis was applied by the National Business Research Institute, Inc. (NBRI) to help a major hotel and casino chain. Remember the large industry survey mentioned earlier and how it identified several drivers of customer satisfaction for women including the attractiveness and perceived safety of the gambling venues and being treated with respect? Just as human behavior is very diverse, Root Causes of customer satisfaction and intent to return are unique for each gaming establishment. NBRI was able to identify several Root Causes driving customer satisfaction and intent to return for female customers of this hotel and casino chain. The Root Causes included the program benefits of the chain’s rewards card, having a good mix of slot machine types, and the friendliness and helpfulness of the casino staff. Notice that these drivers are completely different from those identified in the large industry survey.

The Root Causes driving customer satisfaction and intent to return for men in the NBRI survey also differed from the drivers for women. Drivers for men included a fun casino with a lot of action and excitement, appealing restaurants, the safety of the casino property, and a good mix of slot denominations. Now that this company has precise knowledge of the Root Causes for both its male and female customers, appropriate interventions can be implemented to increase intent to return.

Increasing intent to return has a direct, positive impact on the bottom line. In another customer survey conducted for a large hotel and casino chain, NBRI’s survey results indicated that customer dissatisfaction (and a low intent to return) was caused by poor customer service. A lot of factors are involved in customer service and many variables affect a customer’s perception of service. So where do you start? What kind of intervention do you implement? Without the Root Cause Analysis these questions would go unanswered. NBRI used this tool to identify wait time for service as the Root Cause. The bottom line – one minute of wait time = $1 million in revenue. The hotel/casino added addition personnel at peak times to decrease wait times and increase customer satisfaction and intent to return. This one action had a dramatic impact on profits.