Journal of Interactive Advertising, Volume 5, Number 1, Fall 2004
The University of Mississippi
Increased competition in the gaming industry has resulted in the need for casinos to identify consumer segments that will be most receptive to their communications. In the past, casinos have traditionally used behavioral variables (i.e., frequency of visits, amount of money wagered, etc.) to segment and target customers. However, recent work in segmentation advocates the value of also segmenting customers based on attitudinal variables (i.e., commitment, affect, etc.). The purpose of this study was to explore attitudinal measures of relationship strength to segment casino patrons. Based on a qualitative research design, we used indicators of relationship strength to identify four potential and unique segments. Strategic implications for both online and brick-and-mortar casino marketers are proposed for each segment.
In recent years, the American public has accepted gaming as an option for fun and entertainment while the industry continues to grow across the United States (Rutherford 2004). Casinos now attract a wide variety of customers who are familiar with slot machines, video poker, and table games and who are more comfortable with gaming than ever before (Boone 2003a). Though once Las Vegas, and later Atlantic City, were kings of the gaming industry, now 28 states host casinos on Native American reservations. Gaming on tribal property is a $9.6 billion industry that continues to grow nationwide (Useem 2000). Online gaming has also grown in popularity in recent years, taking in an estimated $1.6 billion a month (Smith 2004b), and annual online gaming revenues are expected to grow to $14.5 billion by 2006 (Pappas 1998).
As a result of the increasing number of gaming options available to customers, competition has intensified in the industry (Smith 2004a). Casinos have increasingly turned to using marketing tools and incentives in order to lure customers away from competitors and into their establishments (Busby 2000). Specifically, it has become important for marketers in the industry to find ways of identifying distinct customer groups through segmentation strategies and then direct appropriate marketing communications to the most profitable segments (Rundle-Thiele and Bennett 2001). Effective marketing communications are particularly important for online casinos, some of which are willing to pay up to $20 per person clicking on online ads, compared to the average web site’s rate of 24 cents per click (O’Brien 2002).
Gaming, whether online or in casinos, is a highly interactive experience. Online casinos offer games such as blackjack, slot machines, and roulette wheels, which are available from the comfort of a customer’s home. Website software allows consumers to bet and play as games are programmed to win or lose a percentage of the time, and winnings are then mailed to consumers (Pappas 1998). In addition to the interaction between people and machines such as video poker and slot machines, many casinos have employed interactive loyalty programs that track customer behavior through the use of loyalty cards. A customer carries a card through the casino, and at each game inserts the card. A computer tracks how much he or she bets, how long he or she plays, what he or she plays, etc. The customer can then approach a casino host to obtain proportionate rewards for his/her patronage, such as free meals, free rooms, or gift-shop merchandise. Online gaming, too, has databases that track visitor activity through the website in order to identify those customers who are most profitable. Duncan (2002) observes that successful communication with customers requires a service provider to understand the nature and strength of the relationship a customer has with the establishment. The authors suggest that interactivity is required in order to truly understand which consumers will be the most profitable ones to enter into relationships with.
Rundle-Thiele and Bennett (2001) recommend using both behavioral (i.e. purchase frequency) and attitudinal (i.e. commitment) measures to identify those customer segments with strong bonds to an organization, as well as those that have the potential to become loyal customers. Though many casinos currently use behavioral measures to describe their customer segments in terms of how often they play, what games they play, etc. (Boone 2003b; Mullaney 2003), it may also be valuable to determine what attitudinal measures distinguish current or future profitable customers from others.
The use of attitudinal measures as a potential segmentation technique offers several benefits to casino marketers. First, attitudes are stable and enduring, which may provide marketers with more reliability in predicting profitable customer segments than behavioral measures (Nairn and Berthon 2003). Second, attitudinal measures might also identify loyal customers who are not identified by traditional behavioral measures of loyalty (e.g. recency/frequency/monetary value models) alone.
Thus, of particular interest to this study is identifying and segmenting casino customers based on attitudinal measures of relationship strength. Relationship strength is a method of segmentation that focuses on identifying attitudinal differences between customers with the goal of finding those customers with strong attitudinal commitments and feelings toward the organization, even if they are not necessarily profitable customers in behavioral terms (Schijns and Schroder 1996). The purpose of this study is to explore and determine relevant segments of casino patrons based on relationship strength. Specifically, the authors wish to address the following research questions:
RQ1: Can we identify casino patrons based on relationship strength?
RQ2: If so, what are the implications for marketers in the gaming industry?
The authors first review the literature on behavioral and attitudinal segmentation strategies and why they are valuable for casinos. Second, the research design and data collection procedures from focus groups conducted at a casino resort in the Southeast are discussed. Third, findings from the analysis of the focus group transcripts are presented. Finally, specific implications and strategies for each of the four segments are discussed for casino marketers.
In his pioneering piece on segmentation, Smith (1956) acknowledged that heterogeneity, not homogeneity, exists in markets and, as such, perfect competition is inadequate for describing the business environment. Instead, imperfect competition is a better characterization of companies. Smith (1956) described segmentation using demand curves. He stated that a segmented market exists when customers are on several demand schedules, rather than just one. Other authors have suggested similar definitions for segmentation (Dickson and Ginter 1987).
Following Smith’s (1956) piece, a series of segmentation studies ensued. Many of these studies were conducted to identify variables that were suitable for segmenting consumers. For example, variables studied in the segmentation literature include benefits sought from products (Haley 1968), psychographics (Wells 1975), demographics (McCarty and Shrum 1993), geography (Kahle 1986), “person-situation segmentation” (Dickson 1982), and family life cycle segmentation (Schaninger and Danko 1993; Wagner and Hanna 1983). While all of these segmentation methods can be helpful in describing and locating customers, few methods focus on the relationship a customer has with a product or service. More recently, with the focus in the field shifting to relationship marketing (Berry 1995), measures of relationship strength have been proposed as a valuable way of segmenting customers (Schijns and Schroder 1996).
A common acceptance in both marketing literature and practice is that it is less expensive for a business to retain an existing customer than it is to recruit a new one (Berry 1983; Hennig-Thurau, Gwinner, and Gremler 2002; Sheth, and Parvatiyar 1995). Relationship marketing attempts to capitalize on this philosophy by insuring that both the business and customer benefit from the extended affiliation with each other (Berry 1995; Peterson 1995). From a firm’s perspective, establishing relationships with loyal customers has many advantages. Reichheld and Sasser (1990) illustrated that profits can increase 100% by retaining (i.e. preventing defection to another organization) just 5% of customers. Furthermore, when customers have a variety of organizations to choose from, as they do now in the gaming industry, sustaining a competitive advantage requires establishing and building long-lasting relationships with loyal customers (Barlow 2000; Raider 1999).
Though forming relationships with customers offers many benefits to a firm, not every customer should be the target of relationship building tactics. Some customers simply will not be profitable for a company in the long run (Reinartz and Kumar 2003). Duncan (2002) observes that differences in relationship strength, or intensity, vary across product categories and customers, and thus the levels of relationship intensity of customers should be assessed in order to effectively communicate with target markets. For example, some customers might have or desire strong relationships with a company, whereas others do not desire a relationship at all and may actively avoid relationship building efforts by an organization (Noble and Phillips forthcoming). Therefore, it is important for firms to assess their target markets and discover which measures provide the greatest success in identifying customers with strong relationships, or those that have the potential to build strong relationships. Duncan (2002) suggests that “companies that understand the importance of creating long-term relationships with consumers will base their segmentation strategies on both consumers’ perceptions of their relationships with a company and their behavior within that relationship” (p. 256). In other words, it is important to evaluate both behavioral and attitudinal facets of relationship strength. Table 1 displays the relationship between attitudinal and relational measures of relationship strength.
Table 1: The Attitudinal and Behavioral Measures Matrix
Source: Adapted from Duncan (2002).
Behavioral Measures: Many measures of identifying profitable customer segments focus on the quality of a customer to the organization, such as their recency of visits/purchases, frequency of visits/purchases, and monetary value spent during these purchases (called recency/frequency/monetary value models). Schijns and Schroder (1996) call these measures “behavioral audits of relationship development” because they measure customers’ behavior in terms of frequency of visits and money spent at the organization. Traditionally, in the marketing literature, loyalty has been measured using behavioral indicators of patronage (Baldinger and Rubinson 1996). Both brick-and-mortar casinos and online casinos commonly use behavioral variables such as what games customers play, how often they play, how much they spend, and what other services they use to determine which customers are most profitable to the establishment (Boone 2003b; Brindley 1999; Mullaney 2003). Such information is also used to construct identities of customers, i.e. whether or not a player is a high roller, a “careful better”, or a risk taker who is eager to try new games and services (Brindley 1999).
However, behavioral indicators alone may not provide sufficient proof of relationship strength. Repurchase behavior should not be the sole reason for marketers to attempt to develop a relationship with a customer (Kumar, Bohling, and Ladda 2003). Furthermore, loyalty cannot be judged by measures of behavior alone, but rather should be considered in terms of both behavior and attitudes towards the product or service. Many authors warn that looking only at the behavioral indicators of a relationship may cause marketers to misunderstand which customers are truly loyal and attractive targets for relationship building efforts (Baldinger and Rubinson 1996; Day 1969; Rundle-Thiele and Bennett 2001). Strong consumers in behavioral terms are not necessarily the best consumers, because behavioral measures cannot capture the attitude of the consumer toward his or her relationship with the organization; a consumer has a strong relationship with an establishment only when he or she perceives it to be so (Schijns and Schroder 1996). Behavioral measures may neglect underlying attitudes which contribute to the desire to build relationships with organizations (Tax, Brown, and Chandrashekaran 1998).
Attitudinal Measures: Schijns and Schroder (1996) introduced a second way to identify potential long term customers through what they call a “relationship audit.” This method involves an emphasis on understanding customer attitudes toward an organization or product so that those customers who are not necessarily behaviorally profitable, but still add value or have the potential to add value to the organization, are not overlooked. The assessment of attitudinal measures of relationship strength can contribute greatly to identifying customer segments with strong relationships to an organization because such measures provide a more accurate reflection of loyalty, or the propensity to be loyal, than behavioral measures alone (Baldinger and Rubinson 1996; Rundle-Thiele and Bennett 2001; Schijns and Schroder 1996). Schijns and Schroder (1996) find that relationships have both a behavioral and a psychological dimension, and that the psychological dimension has been measured by variables such as satisfaction, attractiveness, perceived switching costs, trust, involvement, and long-term expectations.
Attitudinal measures are thought to be important in assessing relationship strength because these indicators allow marketers to separate those customers that frequent an establishment due to their true affinity for it from those that purchase out of habit or fear of incurring switching costs (Liljander and Strandvik 1995). For example, an individual may frequently reuse a product or service and yet have little loyalty toward the brand or organization. Though the customer’s behavioral bonds may be strong, his or her lack of attitudinal bonds indicates that his or her relationship strength with a brand or organization is weak. Duncan (2002) would say this customer is reflecting inertia loyalty and is prone to switching behavior (see Table 1, cell 2).
Another benefit of targeting customers with attitudinal measures is that even if a customer does not currently generate a lot of profits, but has a strong relationship with the organization (in terms of attitudinal measures), he or she is likely to generate positive word-of-mouth which is likely to be very valuable to an organization (Schijns and Schroder 1996). Additionally, these customers are likely to remain committed to the organization over time and might eventually become profitable in terms of behavioral indicators. Duncan (2002) characterizes those customers who are weak by behavioral indicators but high in attitudinal bonds as having latent loyalty (see Table 1, cell 3). Thus, there may be value in pursuing this customer segment.
Schijns and Schroder (1996) indicate that the strongest customer relationships are exemplified by both high behavioral and high attitudinal bonds, a scenario Duncan (2002) terms premium loyalty (see Table 1, cell 4). These customers are the most valuable to the firm. Conversely, customers with both weak behavioral and attitudinal bonds to an organization are unlikely to be profitable to an organization, and are termed no loyalty customers (Duncan 2002) (see Table 1, cell 1). Targeting communications to these customers is often seen as unprofitable.
Although the gaming industry most often uses behavioral measures to segment customers, Youn, Lee and Doyle (2003) used motivational and attitudinal measures to differentiate between on-line gaming customers and non-gaming internet users with some success. The authors found that online gamers were more impulsive than non-gaming internet users and that internet users might be more receptive to controversial advertisements than non-internet users. Behavioral and attitudinal measures have also been used together to measure consumer loyalty to products such as soft drinks (Bonfield 1974), television programs (Donthu 1994) and medical prescriptions (Harrell and Bennett 1974). Rundle-Thiele, Dawes, and Sharp (1998) used behavioral and attitudinal measures to gauge loyalty in a telecommunications setting. Schijns and Schroder (1996) used both behavioral and attitudinal data to identify distinct segments of consumers in regards to their relationship strength with a beer producer.
Using attitudinal and behavioral indicators provides a level of predictive ability that may not be achieved by behavioral measures alone (Baldinger and Rubinson 1996). Baldinger and Rubinson (1996) found that the stronger an individual’s attitude toward a given brand, the more likely customers were to either become loyal to that brand or to remain loyal to the brand. In addition, those with strong positive attitudes toward brands were almost three times as likely to remain with that brand for a year as opposed to those that were gauged as loyal by behavioral measures alone.
Rundle-Thiele and Bennett (2001) also support the use of both behavioral and attitudinal measures of loyalty, but argue that if only one or the other is to be used, then the characteristics of the market and the industry should be taken into consideration. For service-intensive industries, such as the gaming industry, the authors suggest that attitudinal measures are better predictors of loyalty due to the importance of attitudinal variables such as affect and satisfaction in repeat patronage of service providers.
As this review illustrates, casinos that are using only behavioral measures to gauge the current and future profitability of their customers may be making the mistake of establishing relationships with habitual users prone to switch (i.e those with inertia loyalty), or overlooking those customers who are developing close attitudinal ties with the casino but are not yet recognized as profitable (i.e. those with latent loyalty). The authors acknowledge that behavioral measures are likely to remain the most essential data a company collects, since no matter how much a person desires to form a relationship with a company, there will be no bearing on profitability unless there is eventually some increase in actual money spent at the organization. However, attitudinal variables will be valuable in providing an accurate assessment of promising targets for relationship building. To our knowledge, no one has yet looked at what attitudinal variables may be salient in measuring relationship strength in casino patrons. For our purposes, the most relevant attitudinal data to collect involves the customer’s intention or desire to form a relationship with a casino. Thus, we attempt to identify attitudinal measures that are appropriate in the use of relationship strength segmentation schemes for casinos.
Sample and Industry
Due to the exploratory nature of this study, four focus groups were conducted at a medium-sized casino in the Southeast. Individuals were solicited by casino hosts and asked to participate in a 40-minute discussion regarding their patronage at the casino. For their participation, customers were given a ticket for a free buffet. Groups 1 and 2 consisted of individuals who had visited the casino three times or less in a three-month period. These individuals were solicited to represent customers with weaker behavioral bonds (as measured by frequency of visits to the casino). Groups 3 and 4 consisted of customers who had visited the casino 16 times or more in the last year and had been dubbed “must call list” customers by the casino. Based on their frequency of visits, these customers were classified as having stronger behavioral bonds than the previous two focus groups.
The focus groups ranged from 6 to 13 individuals. The average age of respondents was 50 years old. The age, gender, and self-reported frequency of visits for each participant in all groups are listed in Table 2.
Table 2: Demographic Characteristics of Focus Group Members
Individuals with weak behavioral bonds*
Group 1 and 2:
*Visited less than three times in the last three months.
Individuals with strong behavioral bonds*
Group 3 and 4:
Data Collection Procedures
The focus group procedure consisted of three structured questions. First, the focus group participants were asked to elaborate on their current behavior and relationship (if any) with the casino. Second, they were asked to describe their relationship with the casino, and third, participants were asked to indicate whether their behavior in using the services provided by the casino had changed at all since their first visit. Focus group responses were audio-taped and later transcribed.
Focus group transcripts were independently analyzed by two researchers, one of whom had participated in the data collection. The analysis of the transcripts involved an iterative reading strategy in which each researcher developed a holistic understanding of each transcript while also noting similarities across the transcripts. During each iteration, the researcher noted emerging themes related to behavioral and attitudinal measures of relationship development. The transcripts were reanalyzed to develop these themes further and to determine if aggregation was appropriate (see Strauss and Corbin 1990). Once each researcher had independently developed a framework of meaningful themes, the two researchers worked together to resolve minor differences in findings. The resulting themes are described in the next section.
Four attitudinal themes emerged from the transcripts. Each theme is described below with illustrating quotes. Following each quote is an indicator of the strength of the respondent’s behavioral bond with the casino (measured by frequency of visits). Including a measure of behavior was useful in attempting to assess which attitudinal variables are most relevant at which stage of the relationship building process.
Feelings of Friendship and Affiliation. In describing their relationship with the casino, patrons indicated feelings of friendship and a sense of connection with the staff and personnel. Rather than viewing the staff simply as employees, patrons indicated that their relationship was warm and personal, and in some cases casino workers were described as being just like friends. Ties of friendship with the employees seemed to indicate a participant’s willingness to acknowledge his or her relationship with the casino. The following quotes illustrate these feelings toward the casino and staff:
“The personnel here keep me coming back. I’ve established a friendship with a lot of the personnel here.” (Strong behavioral bond)
“We have a close connection to a lot of the people here that we’ve gotten to know really well.” (Strong behavioral bond)
“The staff and everybody are very friendly. We are on a first name basis.” (Weak behavioral bond)
Feelings of Appreciation. Feelings of appreciation arose when respondents felt that the casino treated them as valued customers. The casino’s staff and personnel welcomed these customers to the establishment and made each individual feel special. In most cases, the respondents seemed to feel that the staff had gone above and beyond the call of duty in making them feel valuable. Patrons seemed to appreciate the respect that the casino staff showed them. The following quotes illustrate this theme:
“Well, I feel like they [the employees] appreciate me being here. They wouldn’t have a job if it wasn’t for me. And they show that.” (Strong behavioral bond)
“As I said before, people are –they welcome you. Some other places it’s just like going to Wal-mart. There’s two or three greeters, but the rest of them could care less if you’re there.” (Strong behavioral bond)
Feelings of Loyalty and Obligation. Some customers felt a sense of obligation to patronize the casino since the personnel treated them so well during their stay. These feelings of obligation were not results of guilt inflicted by the casino’s staff. Rather, they were motivated by a sense of loyalty to the casino for the time and effort spent making the customer’s stay special. Additionally, these feelings seemed to indicate the desire to reciprocate the kindness and dedication shown by the casino, and as such may reflect a true relationship in which both parties are committed to each other. The following quotes are from individuals who expressed such themes:
“If this casino is going to pay for my room and my food and things, I don’t think you should be running off somewhere else.” (Strong behavioral bond)
“I feel like they spend the time and effort to treat me special, so in return, I patronize their location.” (Weak behavioral bond)
Being Part of the Family. Often patrons felt such a strong bond to the staff and personnel that they seemed to become like family members and, as such, the casino became a home-away-from-home refuge. These feelings perhaps grew out of initial feelings of friendship and affiliation, strengthening until the patron felt as comfortable among the casino personnel as he or she felt in her own home. Patrons looked for specific employees upon their return visits and reported feeling joy to see them time and time again. The following quotes illustrate this familial bond:
“I feel like I’m home. I really do. I mean I come in, and everybody knows me. I enjoy it and I know all the people, and I’m just – well, I feel better than when I’m at home really.” (Strong behavioral bond))
“You recognize the employees here. And that goes back to the family feeling. The longer and happier you keep the employees, the happier we feel. And if there is a problem, you feel comfortable discussing it.” (Strong behavioral bond)
Consistent with previous segmentation studies that identified behavioral measures of segmentation, we identified six behavioral themes that can be used to segment casino patrons. These behavioral themes emerged when patrons were asked to indicate whether their behavior in using services provided by the casino had changed since their initial visit. This question was included in an attempt to explore how behavioral measures of relationship strength change over time (as the relationship progresses), and also whether these indicators can be used as segmentation variables. These quotes emerged from those focus groups that had strong behavioral bonds with the casino, because to note changes in their behavior, participants necessarily must have been frequenting the establishment for a while. Each theme is described below with supporting quotes.
Monetary Value. The most frequently mentioned behavioral theme was the increase in the amount of money patrons wagered while gambling. Most customers indicated that they started off placing smaller wagers on table games and playing 5 or 25-cent slots. However, they slowly increased their wagers over time. The following quotes illustrate these changes in the amount they wagered:
“I make larger wagers and play for shorter periods of time.”
“I started out with nickel video poker, and then I went to quarters. I practiced and learned and read and all that. Then I got lucky and won some money and tried dollar slots. I’ve been playing dollars ever since.”
Length of Time Playing Games. Customers who had been coming to the casino for an extended period of time indicated that the length of time they gambled had increased. Specifically, these customers felt that they stayed on the casino floor for longer periods of time than they did when they started patronizing the casino. The following quotes illustrate this theme:
“I was a small time gambler. Then over the years you know, I started to change the amount I wager and I play for longer amounts of time.”
“I’ve been graduating up in my playing amounts and I also play longer hours now.”
Type of game. As customers increasingly patronized the casino, their playing behavior seemed to increase in variety. Some customers moved to playing slots (if they originally played only table games) and others began trying table games (if they started originally with slots). Perhaps this variety-seeking behavior exhibits an initial level of exploration by the casino patrons after they begin to gain a sense of familiarity with their surroundings and the establishment. The following quotes illustrate these changes in type of game played:
“I used to play a lot more blackjack. Now I play half blackjack and half slots.”
“Maybe we didn’t play as much blackjack at first, but now we play a little bit more blackjack.”
“I’ve increased I guess more aggressive play. I’ve changed from tables, especially extremely low odd tables to the higher odds video poker. I’ve become more educated in the odds of each game and play games that have better odds.”
Trying new services. Customers who frequently visited the casino indicated that they were more likely to try out different services offered by the resort. Some customers mentioned trying out the restaurants instead of eating at the buffet and others mentioned staying overnight in the hotel when they did not stay the night in the past. The following quotes were offered by participants and illustrate this exploration of services:
“You just sort of come in, you start feeling the place out. Then you graduate up and try something a little different [referring to trying out the services at this casino].”
“I used the limo service. The limo service is great. I also use the opportunity to call and get a room at the last minute. I like that, too.”
Word of Mouth. Recommending the casino to friends and bringing guests with them to experience the casino themselves were frequently mentioned by focus group patrons. Customers who felt a strong sense of loyalty to the casino were often the ones who talked about referring their friends to the casino. Those customers with very positive attitudes about their relationship with the casino were most likely to report word-of-mouth referrals. These patrons enjoyed their stay at the casino so much that they wanted other people to have the same experience. As such, the following quotes illustrate word of mouth referrals:
“We’ve brought probably, oh, I guess 50 different families down here. Right now, we’ve got—we live in a town of 10,000, and we’ve got about 14 couples here right now from our town. And every one of them is because of us.”
“I brought 30 at once. Would you believe, I just called and asked Charlie (a host)—I said, I need enough rooms for 30 people that I’m bringing with me. I said I’m not asking you to give me rooms for them. But I’m asking you to help me on a discount. He said—how about 5 rooms? What other casino will do that that?”
Frequency of Visits. Customers mentioned that over time, they patronize the casino more often. As time went by and participants enjoyed their visit to the casino, they reported wanting to come to the casino more often. The following quote illustrates this change in behavior:
“Well, I come a bit more often than I did.”
This study attempted to answer two research questions. Our first question (RQ1) was to determine if casino patrons could be segmented by relationship strength, and if so, our second question (RQ2) asked what implications might be relevant to casino marketers in targeting these segments. Based on our results, it appears that relationship strength can indeed be used to segment customers in the casino market. Our results show that by looking at both attitudinal and behavioral measures, a different picture of patrons from that provided by behavioral measures alone emerges. According to Duncan (2002), segments that are identified based on both customers’ attitude towards the relationship and their behaviors in the relationship are called “relationship loyalty segments.” What follows is an interpretation, discussion, and suggested strategies for these types of segments for brick-and-mortar casinos. Additionally, implications and future research directions for online casino marketers are also provided.
To understand and interpret the attitudinal themes expressed by the casino patrons, as well as how these themes relate to the various behavioral themes, we examined literature in social psychology on relationship development. According to Perlman and Fehr (1987), relationships tend to develop in three stages: 1) acquaintance or friendship; 2) continuation; and 3) commitment. The acquaintance or friendship stage is characterized by weak interpersonal ties, appreciation, and mutual enjoyment of the relationship. This feeling was exemplified by a patron in our study by observing, “the staff and everybody are very friendly.” When partners perceive the early interaction as mutually beneficial, the continuation stage develops and is characterized by commitment or obligation and familiarity. Finally, the commitment stage of the relationship develops due to the perception that each partner will act in a manner consistent with the other’s expectations (Perlman and Fehr 1987). For example, a patron in our study exemplified this final stage by observing, “if there is a problem, you feel comfortable discussing it, because I know it is going to be resolved.” Other respondents acknowledged this commitment through feelings of reciprocity. Since casino employees had treated them so well, patrons felt that in order to uphold their role in the relationship, they should show loyalty to the casino.
In the current study, patrons whose relationship with the casino was still at the friendship/acquaintance stage were considered as attitudinally weak in their relationship strength with the casino. Those whose relationship with the casino had progressed from the initial friendship stage to the continuation stage (i.e. feelings of loyalty/obligation and feeling like part of the family) were considered as having stronger attitudes towards the relationship. When appropriately nurtured by the casino, feelings of friendship and appreciation can eventually develop into feelings of loyalty, obligation, and family that represent the commitment stage of the relationship and thus strong attitudinal measures of relationship strength.
The relevance of using both attitudinal and behavioral measures in this study is that both of these measures may be used to detect customers who are likely to be overlooked due to their stage in relationship development. For example, individuals who visited the casino infrequently (i.e., have weak bonds to the casino in terms of “behavioral” measures) mentioned several attitudinal indicators of relationship development. Here, a patron with a weak behavioral measure said, “we’ve been treated very well by the staff. Everybody treats us very good.” This indicates that although this customer might not frequent the casino often at this point in time, and might not be identified as profitable by behavioral indicators, he or she may have a favorable attitude towards a relationship with the casino. This type of individual is likely to be overlooked by the casino if only behavioral indicators are used to segment customers. Yet, as these attitudinal bonds are nurtured and strengthened, this type of customer is likely to remain a loyal patron. Additionally, as these attitudinal bonds strengthen, this customer may very well be likely to recommend the establishment to his or her co-workers, friends, and family.
To further examine and discuss the implications of our findings, we developed a matrix that segments customers based on attitudinal and behavioral measures. As displayed in Table 3, examining relationship strength in such a manner may provide marketers with richer information on which segments are attractive targets and what strategies or tactics may be most effective in reaching them. Instead of developing a marketing communication plan based only on behavioral indicators, the communication message and tactics may be dramatically improved by developing different programs for different loyalty segments (Bulger 1999; Gordon 2003). This means that strategies appropriate for customers with weak relationships should differ from those with strong relationships. Table 3 summarizes our results with corresponding suggestions for both online and offline marketers in the gaming industry.
Table 3: The Attitudinal and Behavioral Measures Matrix
Implications for Bricks-and-Mortar Casino Marketers
The first cell in the matrix, dubbed No Loyalty, contains patrons with a weak attitude towards the relationship and a low behavioral measure of relationship strength. Patrons in this segment are still at the initial stages of the relationship development process and also do not visit the casino frequently. They expressed feelings of friendship and appreciation, and had visited the casino three times or less in the last three months. As a suggested strategy, customers in this segment should be monitored because there is still the probability that they may become loyal customers (Schijns and Schroder 1996). However, Duncan (2002) suggests that since minimum returns are expected from such customers, this segment should rarely be targeted. Here, retail or web atmospherics and solid customer service from a well trained staff can be used as stimuli to increase their frequency of patronage and perhaps decrease the likelihood of switching behavior.
Additionally, these individuals may be variety seekers – they may enjoy trying out different casino environments. Thus, this segment may be enticed by novel short-term franchise building tactics such as sales promotions. For example, casinos might hold a drawing for a big ticket item or a chance to win tickets to a casino sponsored event (i.e., concerts, sporting events). Another objective for the no loyalty segment is to maintain an awareness-building advertising campaign that seeks to keep the name of the casino in this segment’s consideration set when seeking out gambling as an entertainment venue.
Cell number 2, Inertia Loyalty, is comprised of customer groups with weak attitudinal measures but high behavioral measures of relationship strength. Although these patrons have a weak relationship with the casino (expressed only feelings of friendship and appreciation), they had visited 16 times or more in the last year and, as exemplified by the quote in this quadrant, may bet larger sums of money each time they come back. Patrons in this segment feel little attachment to the casino, yet they continue to visit out of habit. For this segment, a suggested strategy is to develop marketing communications tools that will entice the customers to bond more with the organization and make their frequent visits effortless and more valuable. Thus, this segment must perceive that they are rewarded for their frequent patronage. Here, a rewards program via frequent player cards can be helpful to casino marketers. In fact, most casinos provide percentage rebates based on wagers in the form of cash-back points, which can be redeemed for future comps (Rutherford 2004). Long-term strategies or franchise-building activities like frequency or loyalty programs can be used to attempt to change the attitudes of patrons in this segment from feelings of friendship and appreciation to feelings of family and loyalty. For example, loyalty points can be earned by spending money on the casino floor and these accrued points can be redeemed for consumption of other parts of the casino like restaurants, show discounts, and hotel accommodations, to encourage more variety and wider consumption of all services offered. Additionally, by knowing the customer’s preferences in the Inertia Loyalty segment and by fostering ease of using casino services, the casino may be able to create switching costs that make this customer less likely to defect.
Cell number 3, Latent Loyalty, contains customers with strong connections to the casino, but weak behavioral measures of relationship strength. As the quote in this quadrant illustrates, such individuals have a strong relationship (as measured by their sense of attachment to the establishment – expressed feelings of loyalty and family) with the casino, but they had visited the casino only three times or less in the last three months. As such, customers in this segment may not contribute much to the profitability of the casino at the moment. However, an appropriate strategy is to encourage such patrons with promotions that make the most of their strong attitudinal bonds. Here, the goal is to capitalize on this segment by using them as advocates of the casino. Since they have a strong perception of the relationship, Latent Loyalists can be very valuable at spreading positive word-of-mouth about their casino experience or the establishment to co-workers, friends, and family. Thus, this segment needs to have the casino in its top-of-mind awareness. This can be accomplished by using reminder advertising in media that this segment watches, reads, or listens to on a regular basis. Additionally, incentive programs, sometimes called viral marketing programs that capitalize on this segments’ positive word-of-mouth can be implemented. For example, "bring a friend and dine for free" or “recommend this website to a friend and dine for free” direct mail sales promotions would encourage this segment to visit the casino or website more often and bring in potential new customers. Internet promotions that give this segment rewards (i.e., "e-mail 5 friends and receive complimentary buffet tickets") for spreading the word about the casino can also be beneficial. Also, short term strategies or non-franchise building activities like coupons can be used to change behaviors. Some casinos run short-term promotions like ‘high roller bonuses of the month,’ where patrons are rewarded for gambling frequently.
Customers in cell number 4, the Premium Loyalists, are the most attractive to the casino because they are the most loyal and potentially the most profitable in terms of attitudinal and behavioral measures of relationship strength. Patrons in this segment expressed feelings of loyalty and obligation and feelings of family themes and also had visited the casino 16 times or more in the last year. According to Schijns and Schroder (1996), customers in this segment both contribute to higher returns for the company and determine customer loyalty. Duncan (2002) suggests that a strategy for this segment is to create a sense of belonging to a special club, either in actuality or in spirit. Some of these individuals may organize a club on their own much like the Harley Owners Group (Schouten and McAlexander 1995). Others may just feel like they are part of a club in spirit because of their preferential treatment. For the Premium Loyalist segment, casinos must offer unique services that are not available to other patrons in order to have a successful relationship. Special privileges such as comped meals and hotel stays, limo service, and premium seating at shows are just a few suggestions. Casino marketers must make sure that these privileges are perceived by this segment as unique due to their loyalty. Thus, another strategy for this attractive segment that can aid in preventing switching behavior is to periodically survey these customers about their satisfaction with the services provided and to express appreciation to patrons for being valued customers.
A general strategy that can be used to increase customer loyalty in all four segments is for the human resource management of casinos to hire employees with high interpersonal and communication skills. Such employees will be better suited for interacting with patrons and making them feel welcome. More importantly, casino hosts should be trained to improve their communication skills, to recognize the need to form long-term relationships with customers, and to identify those patrons interested in forming such long-term relationships (Johnson 2002). For instance, The Luxor casino in Las Vegas sends its employees to a one-month customer relations training program designed to promote better overall service. Similarly, MGM Grand sends its new employees to an in-house training facility called the "University of OZ," where they are given training in customer service and other general skills (Jobmonkey.com 2004).
By segmenting casino patrons based not only on behavioral but also attitudinal measures, casino marketers can further customize their communication and promotion strategies. Here, segments that may have been overlooked can now be recognized as valuable targets for developing a relationship with the casino.
Implications for Online Casino Marketers
Although our study focused on brick-and-mortar casinos, we believe that conclusions drawn from the study can be extended to the online environment. Segmenting online casino patrons based on both behavioral and attitudinal measures of relationship strength is more efficient than segmenting on the basis of behavioral measures alone. Similar to the brick-and-mortar environment, online casinos may overlook gamers who have weak behavioral measures (i.e., patrons who do not visit the website often), although such gamers may have favorable attitudes towards the website. With appropriate strategies, such patrons who might otherwise be overlooked can be converted into profitable lifetime customers. Below are some suggestions for marketers in the online gaming industry for targeting segments as displayed in Table 3.
In reference to cell 1 in Table 3, an appropriate strategy is for online casinos to increase patronage by using personalized greetings. The interactive nature of the internet and databases can be used to generate personalized greetings to imitate the friendly nature of well trained staff in the brick-and-mortar casinos. Further, awareness advertising via banner links and pop-up ads may help this segment keep the website in their consideration set when choosing an online gambling site.
Patrons in cell number 2 feel little attachment to the online casino although they visit it out of habit. Such patrons can be enticed to bond more with the online casino by ensuring fast payouts and awarding loyalty/bonus points in a timely manner, as well as safe-guarding personal information. For online casinos, the availability of customer databases implies that the customer’s preference can be easily collected and used to create switching costs to reduce the likelihood of this customer defecting.
Cell 3 contains patrons who have strong attitudes towards online casinos but do not visit the website often. To increase the loyalty of patrons in this segment, some online casinos have referral programs where players receive points from net bets once their referrals start playing. Other casinos increase frequency of patronage in this segment by offering a 100% match bonus up to $500.
Similar to patrons in the brick-and-mortar casino, online patrons in Cell 4 are the most profitable. According to Duncan (2002), an appropriate strategy for this segment is to create a sense of belonging to a special club. Here, online casinos can encourage continued loyalty by allowing social interaction among loyal players (Choi and Kim 2004). Online casinos can organize online clubs and chat-rooms that allow members to communicate with each other.
Collecting Attitudinal and Behavioral Data from Casino Patrons
Our findings indicate that both attitudinal and behavioral methods of segmentation can be beneficial for casino marketers. Fortunately, many casinos have already initiated loyalty programs which allow tracking of consumer activity in exchange for rewards. Customers are accustomed to receiving requests for information from the casino and the casino has already integrated technology to manage customer data, albeit largely behavioral data at present. Online casinos, which have readily available consumer databases, have an extraordinary opportunity to collect both behavioral and attitudinal data on customers that can then be used for relationship building strategies such as personalization and customization for selected target groups (Brindley 1999). Attitudinal data could be collected via phone or email surveys in exchange for comps or free playing points, simultaneously when consumers fill out forms for loyalty cards, or can be purchased through other marketing research firms that have this information.
Both open-ended and closed-ended questions can be used to collect the necessary attitudinal information. For instance, closed-ended questions can be used by asking patrons to select words from a list describing their feelings towards the relationship they have with the casino. Similarly, open-ended questions can be used to collect attitudinal information by asking patrons to describe their feelings towards the relationship they have with the casino. The attitudinal information collected can then be integrated into existing databases for tracking consumer behavior. Attitudinal and behavioral data can be integrated by using database management programs such as Structured Query Language (SQL) to manipulate the data. A programmer can write syntax to segment patrons in certain segments by specifying which behavioral and attitudinal measures to select. The program will then pull up only those consumers, for example, with weak behavioral but high attitudinal responses.
Ethical Considerations for Casino Marketers
It is important to note that the use of the above strategies to enhance customer loyalty raises certain ethical issues. Since the aim of these strategies is to create premium loyalists (customers who have strong behavioral and strong attitudinal measures of relationship strength), casino operators should be aware of strategies that create too much loyalty. The prospect of winning rewards, coupled with the use of databases to create targeted promotions and personalized communications, stimulates gamblers and may cause addictive behavior (Brindley 1999). In the online environment, the potential for addiction to gambling is enhanced by unlimited access to the casinos (Brindley 1999). Addiction to gambling leads to serious financial losses and gambling providers have a duty to operate in a socially responsible manner (Hing and Mackellar 2004). Responsible gambling can be encouraged by educating and surveying patrons periodically to find out whether players understand responsible practices and the addictive nature of gambling. Casinos can also monitor players’ gambling behaviors and gamblers suspected of addictive behaviors should be identified by employees trained to recognize them and offered counseling (Hing and Mackellar 2004). Online casinos, too, should monitor database information to watch for and prevent excessive patronage.
Due to the exploratory nature of this study, there are some limitations. First, due to the limited number of patrons in the focus groups, caution should be taken in interpreting the results, as these customers might not be representative of all casino patrons. Additionally, the majority of focus group respondents had traveled to the casino from the Southeast region of the country. Perhaps different attitudinal themes may emerge from different areas of the country. Future research should replicate this study with a more representative sample to assess the generalizability of the attitudinal themes identified. Although we believe that the conclusions drawn from this study can be applied to online casinos, it would be beneficial for future research to replicate this study in the online environment to assess whether these attitudinal themes can indeed be identified. The methodology used in this study was for exploratory purposes and intended only to assess the feasibility of using both attitudinal and behavioral measures simultaneously to identify potentially profitable casino patrons. To yield more conclusive evidence of the ability of these measures to correctly identify the level of relationship strength in customer segments, a longitudinal study might be employed which studies in-depth how attitudinal and behavioral measures evolve over the course of the relationship. Such a study might identify additional attitudinal measures at intermediate points in the relationship building process.
Additionally, the current study focused on more extreme stages of relationship building. The authors looked primarily at initial stages of relationship formation and those customers who already had formed strong bonds with the casino. We acknowledge that, by focusing on the extremes of the high/low dichotomy of both behavioral and attitudinal strength, we lose information about the segment that is moderate in both behavioral and attitudinal measures of relationship strength. To provide insight about this segment, future research needs to look at segments along the behavioral-attitudinal strength continuum. As a strategy for moderate segments, contests and sweepstakes can be used to stimulate behavior and effective service provision may produce more favorable attitudes in the hopes of moving this segment along the continuum towards stronger relationship segments.
The findings of this study provide initial support for identifying online and offline casino patrons by both attitudinal measures and behavioral measures. By utilizing both of these segmentation strategies, casinos may be better able to identify and classify customers by relationship strength than those using behavioral measures alone. Attitudinal measures are likely to identify potentially loyal and profitable customers above and beyond behavioral measures because attitudinal measures have the potential to flag customers who might be profitable in the future. Although further work in this area is needed, the current study offers insights about the benefits of segmenting casino patrons based on relationship strength, as well as proposing several avenues for further investigation.
Baldinger, Allan L. and Joel Rubinson (1996), “Brand Loyalty: The Link Between Attitude and Behavior,” Journal of Advertising Research, 36 (6), 22-34.
Barlow, Richard G. (2000), “Frequency Marketing—What’s Next?” Direct Marketing, 62 (9), 2-4.
Berry, Leonard L. (1983), “Relationship Marketing,” in Emerging Perspectives on Services Marketing, Leonard L. Berry, Lynn G. Shostak, and Gregory D. Upah, eds., Chicago, IL: American Marketing Association, 25-28.
——— (1995), “Relationship Marketing of Services-growing Interest, Emerging Perspectives,” Journal of the Academy of Marketing Science, 23 (4), 236-245.
Boone, Timothy (2003a), “Casino Executive Tells Gaming Crowd: Public Attitudes Toward Gambling Changing,” The Sun Herald, (May 8).
——— (2003b), “Technology Helps Casinos Grow,” The Sun Herald, (May 8).
Bonfield, E.H. (1974), “Attitude, Social Influence, Personal Norm, and Intention Interactions as Related to Brand Purchase Behavior,” Journal of Marketing Research, 29 (May), 201-215.
Brindley, Clare (1999), “The Marketing of Gambling on the Internet,” Internet Research, 9 (4), 281-286.
Bulger, David W. (1999), “The Evolution of Relationship Marketing: Reaching an Audience of One,” Direct Marketing, 61 (12), 54-57.
Busby, Charles (2000), “Competition among Biloxi, Miss., Casinos Causes Rise in Use of Advertising,” The Sun Herald, (March 24).
Choi, Dongseong and Jinwoo Kim (2004), “Why People Continue to Play Online Games: In Search of Critical Design Factors to Increase Customer Loyalty to Online Contents,” CyberPsychology & Behavior, 7 (1), 11-24.
Day, George S. (1969), “A Two-Dimensional Concept of Brand Loyalty,” Journal of Advertising Research 9 (3), 29-35.
Dickson, Peter R. (1982), “Person-Situation: Segmentation’s Missing Link,” Journal of Marketing, 46 (Fall), 56-64.
——— and James L. Ginter (1987), “Market Segmentation, Product,
Differentiation, and Marketing Strategy,” Journal of Marketing, 51 (2), 1-10.
Donthu, Naveen (1994), “Double Jeopardy in Television Program Choice,” Journal of the Academy of Marketing Science, 22 (2), 180-185.
Duncan, Tom (2002), IMC: Using Advertising and Promotion to Build Brands, Boston, MA: Irwin-McGraw Hill, Inc.
Gordon, Ian (2003), “Measuring Customer Relationships: What Gets Measured Really Does Get Managed,” IVEY Business Journal, (July/August), 1-6.
Haley, Russell I. (1968), “Benefit Segmentation, A Decision-Oriented Research Tool,” Journal of Marketing, 32 (July), 30-35.
Harrell, Gilbert D. and Peter D. Bennett (1974), “An Evaluation of Expectancy Value Model of Attitude Measurement for Physician Prescribing Behavior,” Journal of Marketing Research, 11 (August), 269-278.
Hennig-Thurau, Thorsten, Kevin P. Gwinner, and Dwayne D. Gremler (2002), “Understanding Relationship Marketing Outcomes,” Journal of Service Research, 4 (3), 230-247.
Hing, Nerille and Jo Mackellar (2004), “Challenges in Responsible Provision of Gambling: Questions of Efficacy, Effectiveness and Efficiency,” UNLV Gaming Research Journal, 8 (1), 43-58.
Jobmonkey.com (2004), “Developing Your Qualifications for a Casino Industry Job,” <http://www.jobmonkey.com/casino/html/hiring_for_casinos.html>
Johnson, Lesley (2002), “Using the Critical Incident Technique to Assess Gaming Customer Satisfaction,” Gaming Research & Review Journal, 6 (2), 1-12.
Kahle, Lynn R. (1986), “The Nine Nations of North America and the Value Basis of Geographic Segmentation,” Journal of Marketing, 50 (April), 37-47.
Kumar, V., Timothy R. Bohling, and Rajendra N. Ladda (2003), “Antecedents and Consequences of Relationship Intention: Implications for Transaction and Relationship Marketing,” Industrial Marketing Management, 32, 667-676.
Liljander, Veronica and Tore Strandvik (1995), “The Nature of Customer Relationships in Services,” Advances in Services Marketing and Management, 4, 141-167.
McCarty, John A. and L. J. Shrum (1993), “The Role of Personal Values and Demographics in Predicting Television Viewing Behavior: Implications for Theory and Application,” Journal of Advertising, 22 (4), 77-96.
Mullaney, Timothy J. (2003), “Harrah’s,” Business Week, (November 24), 94.
Nairn, Agnes and Pierre Berthon (2003), “Creating the Customer: The Influence of Advertising on Consumer Market Segments—Evidence and Ethics,” Journal of Business Ethics, 42, 83-99.
Noble, Stephanie M. and Joanna Phillips (forthcoming), “Relationship Hindrance: Why Would Consumers Not Want a Relationship with a Service Provider?” Journal of Retailing.
O’Brien, Chris (2002), “Web Sites Turn Against Online Gambling,” San Jose Mercury News, (July 13).
Pappas, Charlies (1998), “Gambling the Net Gain,” Yahoo! Internet Life, 4 (3), 54.
Perlman, Daniel and Steve Fehr (1987), “The Development of Intimate Relationships” in Intimate Relationships: Development, Dynamics and Deterioration, Daniel Perlman and Steve Duck, eds., Newbury Park, CA: Sage Publications, 13-42.
Peterson, Robert A. (1995), “Relationship Marketing and the Consumer,” Journal of the Academy of Marketing Science, 23 (4), 278-281.
Raider, Ann M. (1999), “Programs Make Results Out of Research,” Marketing News, 33 (13), 14-15.
Reichheld, F.F. and W.E. Sasser (1990), “Zero Defections: Quality Comes to Services,” Harvard Business Review, 68 (September-October), 105-111.
Reinartz, Werner and V. Kumar (2003), “The Impact of Customer Relationship Characteristics on Profitable Lifetime Duration,” Journal of Marketing, 67 (January), 77-99.
Rundle-Thiele, Sharyn and Rebekah Bennett (2001), “A Brand for All Seasons? A Discussion of Brand Loyalty Approaches and Their Applicability for Different Markets,” Journal of Product and Brand Management, 10 (1), 25-37.
Rundle-Thiele, Sharyn, J. Dawes, and B. Sharp (1998), “An Empirical Investigation of the Relationship between Three Types of Loyalty,” ANZMAC Conference Proceedings, Dunedin, New Zealand.
Rutherford, James (2004), “The Emperor’s New Cards,” The Casino Journal, (January), <http://www.casinojournal.com/Jan2004/solutions1.htm> (accessed on 2/12/2004).
Schaninger, Charles M. and William D. Danko (1993), “A Conceptual and Empirical Comparison of Alternative Household Life Cycle Models,” Journal of Consumer Research, 19 (March), 580-594.
Schijns, Jos M.C. and Gaby J. Schroder (1996), “Segment Selection by Relationship Strength,” Journal of Direct Marketing, 10, 3 (Summer), 69-79.
Schouten, John W. and James H. McAlexander (1995), “Subcultures of Consumption: An Ethnography of the New Bikers,” Journal of Consumer Research, 22, 43-61.
Sheth, Jagdish N. and Atul Parvatiyar (1995), “Relationship Marketing in Consumer Markets: Antecedents and Consequences,” Journal of the Academy of Marketing Science, 23 (4), 255-271.
Smith, Rod (2004a), “Las Vegas Casinos’ Productivity Is Up; Expert Warns of Possible Bad Impact,” Las Vegas Review Journal, (January 15).
——— (2004b), “Las Vegas Review—Journal Gaming Column,” Las Vegas Review
Journal, (March 28).
Smith, Wendell R. (1956), “Product Differentiation and Market Segmentation as Alternative Marketing Strategies,” Journal of Marketing, 21 (July), 3-8.
Strauss, Anselm and Juliet Corbin (1990), Basics of Qualitative Research, Newbury Park, CA: Sage.
Tax, Stephen S., Stephen W. Brown, and Murali Chandrashekaran (1998), “Customer Evaluations of Service Complaint Experiences: Implications for Relationship Marketing,” Journal of Marketing, 62 (April), 60-76.
Useem, Jerry (2000), “The Big Gamble,” Fortune, 142 (7), 222-226.
Wagner, Janet and Sherman Hanna (1983), “The Effectiveness of Family Life Cycle Variables in Consumer Expenditures Research,” Journal of Consumer Research, 10 (December), 281-291.
Wells, William D. (1975), “Psychographics: A Critical Review,” Journal of Marketing Research, 12 (May), 196-213.
Youn, Seounmi, Mira Lee, and Kenneth O. Doyle (2003), “Lifestyles of Online Gamers: A Psychographic Approach,” Journal of Interactive Advertising, 3 (2).
Copyright © 2004 Journal of Interactive Advertising