MANAGEMENT SUMMARY
Offering loyalty programs to consumers is of essential importance for retailers nowadays. Not only because loyalty programs are a tool to create loyal consumers but also due to the increasing competition in the market place. During the time that this research was conducted the FIFA Football World Cup in South Africa took place. More than 10 retailers on the Dutch retailer market presented some form of loyalty program to their consumers. The challenge for retailers now is to create a perfect fit between the program that they offer and the consumers that they are targeting. That is what this research has tried to do.
Loyalty programs usually consist of saving points or stamps in order to obtain a reward. However, these rewards are not always free for a customer. Many reward programs require the participant to pay a certain amount before being able to obtain the reward.
The question arises, which reward elements are of such importance to the consumers that they will guide his/her intention to participate in a loyalty program. The results of this research are relevant for companies offering loyalty programs for retailers and managers of retailers involved with loyalty programs.
This research proposes certain recommendations for Brand Loyalty and other retailers. Collect as many characteristics and demographics as possible of the consumers who visit the specific retailer. Create a profile of their purchase behavior and match rewards to make a perfect fit in the loyalty program. Consumers will feel special when they realize that the loyalty program offered fits well with their demands and interests.
The analysis has shown that the monetary element of the rewards offered in a loyalty program is still of great importance to consumers. Looking at past research it is therefore recommended to eliminate the additional payment for consumers and offer all rewards at a 100% cash value. Consumers will not mind that they have to spend more time collecting stamps.
Results predicted higher participation intention from consumers than that was concluded after the loyalty programs were finished in respectively Singapore and Germany. Brand knowledge and brand quality perception are important aspects for consumers when deciding whether or not to participate in the loyalty program. It is recommended to use high quality brands and popular brands as rewards in a loyalty program.
PREFACE
This thesis forms the final part of my MSc degree in Business Administration with the specialization Marketing Management. The courses followed throughout the past year gave me many new insights. These insights enabled me to complete this Master’s Thesis. It is likely that many more changes will happen in this field in the near future, which I hope to follow from close by, as I intend to begin a career in this area. First of all, I would like to thank Brand Loyalty International and especially Mr Freek de Vrij for his extensive support in the preparation of this thesis. The first months were quite tough, but as a result of the open and lively exchange of ideas we eventually came to an interesting approach of which the end results you find here before you. Furthermore, I would like to thank the market research staff at BLI, particularly Messrs Matthijs van der Pas and Vick Tielemans who were always available for advice during these five months. Special thanks to Mr Jacob Wiebenga who introduced me to Brand Loyalty and provided me with the opportunity to conduct my research at BLI. The brainstorm sessions we had in person, and through other means eventually created the match between Brand Loyalty and me. I started off with a passion for football cards and marketing, which was later transformed into a study about loyalty programs.
programs and how participation levels can be influenced. The research will be done for Brand Loyalty International (BLI). BLI has been operating in the world of loyalty marketing in the worldwide food retail market since 1995. BLI’s overall objective is to increase the loyalty of customers towards a retailer through attractive loyalty programs.
Previous research by BLI focused on the effect of loyalty programs at various retailers. Through an online questionnaire customers were asked about their perceptions concerning the program. A number of factors that influence loyalty program successes were identified as a result of this research such as awareness, competing retailers, store image, product types and participation. Seeing that consumer participation is instrumental to the success of a program, it was decided that more detailed research needed to be done. Therefore this research focuses solely on participation and what can be done by retailers to influence it.
1.1 Brand Loyalty International B.V.
Since 1995 Brand Loyalty International (BLI) has been operating in the area of loyalty marketing within the world food retail market. BLI is a company with a worldwide presence and through subsidiaries active in many different markets. The company has grown steadily over the past years becoming one of the market leaders in its field. With more than 2000 successfully launched loyalty programs in around 35 different countries BLI’s experience with loyalty marketing has become extensive. BLI’s goal is to increase customer loyalty at a retailer by offering attractive loyalty programs. Traditional loyalty programs are 95% of BLI’s business. The remaining 5% consists of special promotions. Compared to a loyalty program a special promotion gives the customer free products when an x‐amount of money is spent. Special promotions are used to ‘lure’ more customers to the retailer to increase turnover Traditional loyalty programs on the other hand are designed to increase loyalty and to reward loyal customers. Loyalty programs are also aimed at increasing purchase frequency of the customer.
1.2 Research Background
“What can Brand Loyalty learn from its own programs and how can Brand Loyalty use these research insights in the future to become a better consultant and create better programs?”
This first test was performed using three break‐even and profit programs (two in Germany and one in Mexico) in the period between December ‘09 and March ’10. With each of the three programs a pre‐program research was done to establish the expectations for a program and a second research half way through the program to see what the program actually delivered. This first test was very broad and aimed to find indications on key points that affect the loyalty concepts, and the way a specific program is performing. The key points derived were: awareness, participation, brand and product, the retailers, and competitors.
Our research will focus solely on the key point participation.
1.3 Problem statement
Objective
The objective of this research is, with the help of an experimental design, to determine consumer’s participation intention and loyalty behavior. The content of this research assesses and analyzes current loyalty programs and investigates how to create a fit between consumer characteristics and the loyalty program design and reward structure.
Research Question
1. How do loyalty program reward elements and how do their (monetary) value influence consumer’s intention to participate in a loyalty program? 2. How do consumer’s characteristics moderate for this relationship? Use of research results This research will be used as a benchmark for future loyalty programs. In addition it will be used to gain greater insight into consumer’s loyalty program behavior. 1.4 Report set up The next chapter describes the results of the literature study about loyalty programs, loyalty and word of mouth as concepts and reward elements as part of a loyalty program. The third chapter is dedicated to the research design and how data is collected and analyzed. This gives a basic
2 THEORETICAL FRAMEWORK
In this chapter, the definition of loyalty as used in this research will be given. Furthermore, a review of existing literature of loyalty programs, loyalty program design and reward structure will be presented. This should provide the reader with a better understanding of loyalty in general and how loyalty programs are built to enhance loyalty. Within this literature review, the concepts used within the conceptual framework will be defined and discussed. As such, this chapter aims to provide a basis for the conceptual model that follows at the end of this chapter. The world of loyalty programs is quite diverse and quite some academic research has already been done. With this research the aim is to discover how different types of consumers respond to different types of loyalty programs. In the end the goal is to contribute to existing literature as well as help BLI in designing appropriate loyalty programs for their wide array of retail customers.
The present research suggests that understanding the relative fit of individual customers to specific offers and options may often be more important than measuring their "absolute" preferences, which are often fuzzy and unstable. That is, a one‐to‐one marketer may not gain a significant competitive advantage if the offer made fits the preferences and conditions of the particular customer no better than it fits the preferences and conditions of other customers. In contrast, offers that provide idiosyncratic fit, even if that fit relates to a less important dimension, can have a significant impact on customer evaluations and loyalty (Kivetz & Simonson, 2003). Loyalty has become an extensively studied topic in recent years. It is now well recognized that an old customer retained is worth more than a new customer won (Nunes & Dreze, 2006). Therefore it has become important to design loyalty programs in such a way that they create the highest level of consumer participation. This though is not an easy task. But as Nunes & Dreze (2006) state, loyalty programs can be ingenious marketing tools when they are designed and executed well.
2.1 The Loyalty concept
Loyalty is seen as the “holy grail” of marketing and also seen as one of the most valuable assets of a firm. Aaker (1991) even refers to loyalty as the flip side of brand equity. Loyalty finds its origin in relationships between the supplier and the customer. With time suppliers started realizing that transactions with customers should not be limited to a onetime event but efforts had to be made to keep attracting customers to their stores. It is from this thought that many definitions of loyalty appeared in various literature.
In literature the term ‘loyalty’ has been defined in many ways. Although not all literature is consistent in its definition of loyalty Melnyk et al. (2009) state that common elements among many of the loyalty definitions are that there is a relationship of some sort (i.e., ranging from very shallow to very strong) between an actor and another entity and that the actor displays behavioral or psychological allegiance to that entity in the presence of alternative entities. One of the most widely used definitions of loyalty is the one by Oliver (1999) where it is described as: a deeply held
commitment to rebuy or repatronize a preferred product/service consistently in the future, thereby causing repetitive same‐brand or same brand‐set purchasing, despite situational influences and marketing efforts having the potential to cause switching behavior. This definition is the one that was
considered when performing this research.
In previous academic research two constructs of loyalty have emerged, namely attitudinal loyalty and behavioral loyalty. In the literature, commitment is very often used to measure the attitudinal dimension of customer loyalty (De Wulf & Odekerken‐Schröder 2003; Fullerton 2003; Garbarino & Johnson 1999; Morgan & Hunt 1994). Previous studies measuring retail store loyalty (Fitzgibbon & White, 2004) have operationalized the attitudinal component of loyalty as commitment and the behavioral dimension as repeat purchase and positive word‐of‐mouth. Further studies of attitudinal and behavioral loyalty state that ‘attitudinally loyal customers are considered to be more profitable than behaviorally loyal customers’ (Chaudhuri & Holbrook, 2001). This research uses the following definitions of attitudinal and behavioral loyalty:
Attitudinal loyalty is defined as ‘The consumer’s predisposition towards a brand as a function
of psychological processes. This includes attitudinal preference and commitment towards the brand’
Behavioral loyalty exists when a consumer repeatedly purchases a product or service, but does not necessarily have a favorable attitude towards the brand. This may be due to convenience, habit or because the barriers to change are too great (Reinartz & Kumar, 2002).
2.2 Definition of Loyalty Programs
Many firms have installed loyalty programs as a core component of their marketing strategy. This proliferation of loyalty programs reflects a changing market environment that is increasingly characterized by intense competition, more demanding and knowledgeable consumers, and a development toward relationship marketing and customer relationship management in marketing thinking and practice (Liu & Yang, 2009).
Loyalty programs are common among retailers. McKinsey research found that about half of the ten largest U.S. retailers have launched such programs, and the rate is similar among U.K. and Dutch retailers (Leenheer & Bijmolt, 2008). A main goal of loyalty programs is to stimulate customer purchase behavior by providing rewards to customers who sign up for the program (Kivetz & Simonson, 2002). Customers who perceive a good fit between the loyalty program and their personal situation (e.g., because they live close to the store or have a relatively high purchase frequency) have a high propensity to join the program (Kivetz & Simonson, 2003). Loyalty program members have extensive purchase relationships with the firm (Zeithaml, Rust, and Lemon, 2004), and they tend to overlook negative evaluations of that particular firm (Bolton, Kannan, and Bramlett, 2000). Conversely, non‐ members tend to be less loyal (Leenheer et al., 2004). Thus, loyalty programs lead to a natural split of a store's customer base into members and nonmembers. At the same time, loyalty programs do not lead to increased penetration, which shows that they have little effect on recruiting new customers and mainly influence the repeat purchase behavior of existing consumers (Meyer‐Waarden & Benavent, 2007). A loyalty program can accelerate the loyalty life cycle, encouraging a 1st or 2nd year customer to behave like a company's most profitable 10th year customer. These customers become business builders by buying more, paying premium prices, and bringing in new customers by referrals (O'Brien & Jones 1995).
Before analyzing loyalty programs more extensively it is essential to define the concept accordingly. Leenheer (2006) provided the following definition:
A loyalty program is an integrated system of relational marketing efforts aimed at increasing attitudinal and behavioral loyalty of customers participating in the program.
As Dowling and Uncles (1997) state, operating loyalty programs requires knowledge of long‐ run customer loyalty patterns in order to justify and evaluate investments. Customer loyalty patterns can be seen as the behavior that consumers show when participating in a program. It can also refer to non‐participation or behavior during the participation decision making process. Usually programs are designed so that customers, no matter how loyalty is defined or measured, will shop and regularly return to repurchase at their stores, despite competitive efforts to thwart this practice. According to Levy & Weitz (2004), the retailing concept, an adaptation of the marketing concept, is a management orientation that focuses a retailer on determining the needs of its target market and satisfying these needs more effectively and efficiently than its competitors. Loyalty programs often focus on targeted groups of customers, often a retailer’s “best customers,” whose continued patronage is critical to bottom line performance. Efforts to satisfy these and other frequent shoppers provide a basis for incorporating certain “benefits” that are sought by consumers. Furthermore, loyal customers cost less to serve, partly because they are familiar with the store and its operations and know where the merchandise is located. Present day consumers have become high‐demanding which means that the days of push marketing are over. Loyalty programs do not, nor have they ever, “created” loyalty. What successful loyalty marketers do is, in fact, market loyalty. They market the idea that you are loyal to your customers by exceeding their expectations, delivering differentiated value and driving highly personalized interactions. The customer will choose the level of interaction based on the extra value delivered. In order to gain a better understanding of loyalty programs an overview of types of loyalty programs is given below.
2.2.1 Loyalty program effectiveness
depends not only on the programs themselves but also on other facilitating or inhibiting factors present in the environment (Liu & Yang, 2009). Performance and success of loyalty programs also depends on the goals that have been set out beforehand for the program. Nunes & Dreze (2006) suggest that loyalty programs can serve different goals, such as retaining customers, increasing spending, and gaining customer insights. For a frequency program to be effective in increasing loyalty, it must have a structure that motivates consumers to view purchases as a sequence of related decisions rather than as independent transactions (Lewis, 2004). O’Brien & Jones (1995) suggest that the major factors that customers consider when evaluating programs are the relative value of rewards and the likelihood of achieving a reward.
As Nunes & Dreze (2006) conclude: creating a successful loyalty program starts with defining what should be gained from the effort. That is what retailers often forget to do, which is why this research tries to create the match between consumer’s characteristics, loyalty program design and the reward structure. These constructs will be discussed in the following section.
2.3 Consumer Characteristics
Although proper program design and management are critical, it is consumers’ reactions to a loyalty program that ultimately determine program success. Consumer characteristics can be crudely classified into firm specific attitudinal and behavioral factors versus traits and characteristics that carry across firms (Liu & Yang, 2009). Previous research has examined the moderating effect of consumer’s usage levels. But only few studies have really examined the impact of consumer characteristics on loyalty program effects. This is one of the reasons that certain consumer characteristics have been examined in this research.
It is important to segment consumers on the basis of their characteristics. It is essential to distinguish between heavy and light purchasers. Research has shown that light purchasers, for whom the likelihood of achieving a reward is low, are probably attracted to instant sales promotions offered by competitors, since loyalty cards are less beneficial to them. It can thus be presumed that the choice of retail outlet as well as loyalty are guided by elements other than the loyalty program, in particular the competitive position, proximity, inertia, comfort, choice, product variety, store size, sales promotions and the store's relative isolation from other retail outlets (Meyer‐Waarden & Benavent, 2007). One variable that is used to segment consumers is gender. Academic research has discovered important differences in cognitive processes and behavior between male and female consumers. These differences are reflected in the widespread use of gender as a segmentation variable in marketing practice (Melnyk et al. 2009).
1. Recency: It is the time that has elapsed since the customer made his most recent purchase. If the latest buying time is far from the present, it means that the customer purchasing behavior may have changed.
2. Frequency: It is the total number of purchases that a customer has made within a designated period of time. It measures the degree of interaction between the customer and the firm in a certain time. Higher value indicates a higher degree of interaction between customer and business.
3. Monetary: It is each customer's average purchase amount.
RFM is usually used to measure customer loyalty and contribution. Customers with higher loyalty and contribution to a certain product mean higher probability that they will continue buying that product again. Thus, RFM is used to analyze the continuous purchasing power of the customer (Weng et al. 2006). Therefore it can be hypothesized that:
H2a: Consumers who visit the specific store more often are more likely to participate in the loyalty program
H2b: Consumers who spend a higher percentage of their shopping budget at the specific store are more likely to participate in the loyalty program
2.4 Program Design
builds on three of the above mentioned value elements namely aspirational value, cash value and relevance. In this research the definition of relevance is slightly revised and is seen as the necessity of the reward for the consumer. 2.4.1 Relevance The question that is asked here is: do the consumers really need the product? Many of the rewards and loyalty programs in the marketplace today reveal a limited understanding of customer needs and desires. From a customer's perspective, they lack relevance. Relevance as referred to by O’Brien & Jones (1995) aims to show the goal of the loyalty program for consumers. What is it that will ensure that consumers join the loyalty program? Does the product/reward that can be earned have relevance for them? In many loyalty programs companies or retailers tend to match any random product to their loyalty program. This could be one that they still have in stock and need to get rid of or one that can be acquired quite cheaply. In most cases the wishes of the consumers are ignored. Therefore it is of great interest to determine beforehand if the products/rewards that are being offered really create a needed benefit for consumers. Therefore it can be hypothesized that: H3: With a higher level of perceived relevance it is more likely for consumers to participate in the loyalty program 2.4.2 Aspirational value
when effort requirement is high, whereas a less aspirational necessity reward is preferred when effort requirement is low.
Consumers often persist in their efforts to achieve goals that are accompanied by discrete, extrinsic rewards (Nunes & Dreze, 2006). This shows that consumers will be more highly motivated to participate in a program if they are influenced by hedonic benefits. These elements stand in line with the questions about luxury and functionality of the rewards. Therefore it can be hypothesized that:
H4: The aspirational value of the brand that is offered in the loyalty program is of positive influence to program participation by consumers
2.4.3 Cash value
O’Brien & Jones (1995) state the following simple rule: think of the value of a reward (what the customer would have to pay in cash to acquire it) as a percentage rebate on what the customer spent to earn that reward. That is what drives consumers in their thoughts of whether it is beneficial for them to participate in the loyalty program. Most thoughts in literature about loyalty programs come to the conclusion that the cash value of the reward, which can also be seen as the intrinsic value of the reward, that can be obtained is one of the most important factors driving consumers’ willingness to participate. De Wulf et al. (2003) found that participation costs drive the participation decision for about 46%. This can be considered quite a high number since program benefits were only rated at 23%. If there is a negative discrepancy between participation costs and benefits, which in essence determines the cash value of the reward, then consumers will not participate. Not only monetary costs are important, non‐monetary costs also can play a role in the value perception.
H5: Rewards with a higher cash value will positively influence participation level in the loyalty program.
2.4.4 Reward divisibility
Customers prefer highly divisible programs because they provide many exchange opportunities and thus reduce award waste. A critical concern is arriving at the right price per reward point (Nunes & Dreze, 2006). Customers see a low‐divisibility program as having such a high threshold for rewards that it deters them from ever embarking on the quest (Nunes & Dreze, 2006).
Research by Nunes & Dreze (2006) has shown, for example, that in a grocery store setting (high usage, low differentiation), a $50 reward for every $500 spent engenders greater customer loyalty than either a $10 reward for every $100 spent or a $100 reward for every $1,000 spent (too much and too little divisibility, respectively). This information was used a basis for some of the questions that were asked in the questionnaire.
To be attractive, a program must lead to redemption; that’s when the benefits really become the most salient to the consumer. The key for managers is to make the redemption as inexpensive as possible to the company. Nunes & Dreze (2006) have found that if companies allow program members to redeem their points in combination with hard currency, it lowers the psychological cost to consumers. In other words, it can increase the perceived benefit to the consumer without undue cost to the company. Furthermore, companies stand to gain incremental sales when they’re flexible in how they allow customers to combine currencies. The answers to the questionnaire used should be able to demonstrate if this is the case for this research as well.
The question that arises is if the variation in reward divisibility really has an effect on consumer’s participation intention. Do consumers care how much they have to spend before they qualify for redemption of a reward? This research proposes that consumers do not base their decision on how much they have to spend at the store. Nonetheless, this research does believe that consumer income can be of influence on the participation decision. Therefore it can be hypothesized that:
H6: Reward divisibility has no direct effect on participation level.
H6a: The height of the weekly grocery budget is of moderating influence on the relation between reward divisibility and participation
2.4.5 Participation and Word of Mouth
The design of a loyalty program has one important goal: participation. The aim of participation comprises the attractiveness to make customers enroll in the program. If customers do not participate in the program, the program obviously has no effect. The design of a loyalty program is very important for the decision of a customer whether to participate in the program or not (Leenheer et al. 2007).
difficult to differentiate between the various programs. Lastly, when consumers are in the process of deciding whether to participate in a program they compare the possible current benefits with past experience in loyalty programs; if that experience was unsatisfactory it will have a strong influence on the present decision. If a consumer has had a negative experience in the past it has proven to be very difficult for retailers to regain these consumers trust.
In the marketing context, Word of Mouth (WOM) communications are defined as “informal communications directed at other consumers about the ownership, usage, or characteristics of particular goods and services and/or their sellers” (Westbrook, 1987). Arndt (1967) defined word of mouth as “oral, person‐to‐person communication between a perceived non‐commercial communicator and a receiver concerning a brand, a product, or a service offered for sale. The likelihood of customers spreading WOM will depend on their satisfaction level for at least two reasons. First, the extent to which the product or service performance exceeds the customer’s expectations might motivate him or her to tell others about his or her positive experience. In the context of service recovery, for instance, the salience and recency of the experience might explain why satisfaction with the recovery prompts customers to tell family and friends about their positive experience (Maxham & Netemeyer 2002b). Second, to the extent that the customer’s expectations are not fulfilled, possibly creating a customer regret experience, this customer will engage in WOM behavior as a form of “venting” his or her negative emotions, such as anger and frustration, reducing anxiety, warning others, and/or seeking retaliation (Sweeney et al. 2005).
The paragraphs above discuss both participation and Word of Mouth behavior as two distinct concepts. The concept loyalty has also been mentioned. It has often been stated in literature that loyalty leads to positive Word of Mouth behavior. This research sees a positive participation experience as leading to loyalty which is when consumers will engage in positive Word of Mouth. The elements aspirational value, relevance, cash value and reward divisibility and their values are seen as influencers of consumer’s participation in the loyalty program. Therefore this research not only draws conclusions on participation intention by consumers but also measures their experience with the loyalty program after participating. The result of that measurement, being positive shows loyalty and being negative shows a lack of loyalty. When consumers are then loyal to the program they will also communicate this positively to their friends and/or family.
First of all the influence of the independent variables on the dependent variables are analyzed. Secondly the influence of the dependent variables on each other are analyzed. This leads to the following hypotheses:
H6: Word of mouth is positively influence by a positive participation experience in the loyalty program.
H6a: Consumers are more likely to indulge in (a) positive word of mouth and (b) repeat purchase behavior when the aspirational value of the reward is high and when they can receive the award for free
H6b: Consumers are more likely to indulge in (a) positive word of mouth and (b) repeat purchase behavior when they participate in the loyalty program
In order to test the hypotheses stated above the variables that will be used, dependent and independent, have to be quantified. The mentioned hypotheses are displayed graphically in Figure 1 on the next page. An overview of the mentioned variables with a short description is displayed in Table A.
TABLE A – Overview of the relevant variables
Independent variables Measurement Description Literature
Relevance Yes / No
Identifies relevance of reward. Do consumers need the reward?
O’Brien & Jones (1995) Aspirational Value High / low Identifies quality of brand and consumers perception.
O’Brien & Jones (1995)
Cash Value a. 50%
b. 75% c. 100%
Measures the discount amount that consumers receive on the reward compared to the retail value.
O’Brien & Jones (1995)
Reward Divisibility
a. 20 euro reward for every 100 euro spent b. 50 euro reward for every 250 euro spent c. 100 euro reward for every 500 euro spent
Describes the monetary value of the reward compared to the money that has to be spent to be able to redeem the reward.
Nunes & Dreze (2006) Moderating variables Description Consumer Characteristics a. Purchase behavior b. Household size c. Income d. Age / Gender
Describes consumers purchase behavior, income, household size and further demographics
Dependent variables Description
Participation Likert scale (1‐7) Indicates consumer’s intention to actively collect in the program. Preference for the LP over competitors, preference for specific LP and intention to participate.
Word of mouth Likert scale (1‐7) Measures consumer’s intention to communicate strengths of program to others. Willingness to recommend LP to friends and/or family.
2.5 Conceptual Model
Four covering constructs; relevance, aspirational value, cash value and reward divisibility are believed to have an influence on participation. Consumer characteristics are seen as a potential moderator in this relationship. These constructs are described in detail in following the model:
3 RESEARCH DESIGN & METHODOLOGY
This chapter will deal with how the hypotheses are tested. First, the method of research will be explained. Second, the way how the research was executed will be explained. Finally, the plan of analysis will be discussed and elaborated on the statistical tests that were used. 3.1 Method
3.1.1 Pre Study
One of the independent variables used was aspirational value. The two options in this case were high and low quality. To give respondents an idea of the quality that was being referred to, car brands were used. In both countries the perception of the quality of the brands was tested amongst BLI managers. The brand used for high quality was BMW and the brand used for low quality was Daihatsu. The respective managers were confronted with a simple questionnaire to draw conclusions about their perception of the brands. In the ranking scale 1 is seen as high and 7 as low. Table 2 below shows the results.
TABLE 2 – Results brand perception questionnaires Singapore and Germany
Mean Score (1 – 7) N
Germany Singapore Germany Singapore
Brand Performance ‐ BMW ‐ Daihatsu 2 5 2 4 4 4 4 4 Brand Quality ‐ BMW ‐ Daihatsu 2 5,2 1,8 5,8 4 4 4 4 Word of Mouth intention ‐ BMW ‐ Daihatsu 2,6 7 2,4 7 4 4 4 4
The results of the questionnaire provide evidence that the perception of the quality of the brands as determined by the researcher was similar to the perceptions of respective managers in Singapore and Germany. In terms of performance and quality the brand BMW scores very high. Daihatsu scores poorly on quality and performance. Seeing that the aim was to analyze quality of the brand, BMW is categorized as high and Daihatsu as low.
3.1.2 Questionnaire Set up
It was decided to separate the analysis of both countries for comparative purposes. For ease of description the method of analysis for both countries is combined. The analysis of part C of the survey in which the respondents are confronted with questions about the actual program running in the loyalty store is also done separately for each country.
3.2 Execution
The population for this research is grocery store shoppers in Singapore and Germany. Out of these consumers a random sample of 2004 was drawn; 1003 shoppers in Singapore and 1001 shoppers in Germany. Table 1 below shows an overview of the demographic characteristics, including gender, age and household size. TABLE 1 – Demographic characteristics of the sample in Germany and in Singapore Demographic variable N Percentage
Germany Singapore Germany Singapore
Gender Male 493 488 49.25 48.65 Female 508 515 50.75 51.35 Age 18‐24yrs 117 94 11.69 9.37 25‐34yrs 267 421 26.67 41.97 35‐44yrs 255 322 25.47 32.10 45‐54yrs 232 133 23.18 13.26 55‐64 yrs 108 30 10.79 2.99 >65yrs 22 3 2.20 0.30 Household size 1 231 35 23.08 3.49 2 370 131 36.96 13.06 3 199 214 19.88 21.34 4 147 305 14.69 30.41 5+> 54 318 5.39 31.70 3.3 Plan of Analysis
two of the scenarios. At the end of each scenario the respondent would have to answer 4 questions concerning the hypothetical loyalty program that has been described in the loyalty program. The first question was concerning the preference for the loyalty program proposed over other loyalty programs running at competing stores. The second question measured the specific preference of the consumer for the loyalty program mentioned. The third question measured word of mouth intention and the fourth question asked consumers about their willingness to participate in the loyalty program. Each question was measured by use of a likert scale (1 – 7) in which a score of 1 was ‘quite a lot’ and 7 was ‘not at all’.
Questions 1, 2 and 4 were combined to create the dependent variable Participation. A reliability analysis was conducted and the results (Cronbach’s Alpha of 0,937 and 0,966 for Germany and Singapore respectively) of this analysis showed that combining these three questions was allowed. The new variable Participation showed the mean score of the three questions combined. Most of the analysis below used the new variable and this can be seen in the results.
In order to conduct a regression analysis the dependent variables participation and WOM were tested for normality of distribution. If the distribution was not normal then a logarithmic transformation was used to possibly achieve the normal distribution. Furthermore, ANOVA was used to test the influence of the independent variables on participation and WOM. T‐tests were used to compare the scenarios. In order to test the hypotheses correlations were performed before conducting a regression analysis. This was done to establish the strength of the relationship between the independent and dependent variables beforehand. Conclusions about the strength of the relationship led to the decision to perform a regression analysis with control variables to improve quality of the outcome.
4 RESULTS
The results of the survey are displayed below in Table 3. The outcomes of the ANOVA are displayed in Table 4 on the next page. First, the participation scores will be discussed. Second, the effect of the reward value elements on participation and Word of Mouth will be discussed. Finally, the link between the hypothetical programs and the real programs will be discussed.
The analysis was done separately for Germany and Singapore and therefore the results are also demonstrated separately. The next section shows the results of all the analyses that were performed. Following each table is an explanation of the values shown.
4.1 Survey results
This section, by use of tables, graphs and figures, shows the results of the SPSS analysis that was done to draw accurate conclusions and to come to an answer for the research question. The first part deals with the participation intention by consumers respective of the different reward value elements. The second part deals with the hypotheses that were formulated for this research.
meaning that the consumers do not yet own the product in their household. The most popular cash value is 75% with a participation rating of 32,3%. Lastly, it is clear that consumers have a strong preference for a reward divisibility of €50 – €250.
Table 3b above, containing the results of the survey conducted in Singapore, shows stronger scores than the survey in Germany. It is clear that the aspirational value of the reward is very important. (49,1% versus 33,2%) Furthermore, as in the German survey, consumers prefer collecting for rewards that they do not own (36,7% versus 32,7%). The consumers have a strong preference for S $30 – S $150 reward divisibility (30,4% versus 25%) and a slight preference for a 75% cash value (28,6% versus 25%).
BEST COMBINATION
Further surprising information concluded from the table shown above is the scores that were given when the aspirational value of the reward is low. For the most part the respondents in Germany are more likely to participate in a program than the respondents in Singapore when the apsirational value is low. (3,82 versus 4,99) In Germany consumers have the strongest preference (3,04) for a loyalty program with a €50 ‐ €250 reward divisibility, high aspirational value, high relevance and with a cash value ‘for free’. The results for Singapore are similar. Both are at high aspirational value and high relevance but the difference between a reward divisibility of S$30 – S$150 or S$60 – S$300 and a cash value of 75% or ‘for free’ is very low. (3,35 versus 3,32)
As with the two pie charts above the ones below show the two combinations’s of reward elements that lead to the highest participation in Singapore. Figure 2a – Singapore – Value elements (High / Already / 60 – 300 / 75%) Figure 2b – Singapore – Value elements (High / Do not / 30 – 150 / 50%) Interesting to note concerning the pie charts in Singapore, in comparison to the charts in Germany, is the lower importance of the value element relevance. In the charts above participation scores (69% versus 63%) show that there is not a great difference between low or high relevance in Singapore. Another factor that is of interest is the cash value results. In Germany consumers were specifically interested in the ‘for free’ option which would lead them to participation whilst the Singapore consumers have no specific preference for the ‘for free’ option. Consumers in Singapore are considering a 50% or 75% cash value option.
Figure 4a – Germany – Interaction effect (High aspirational value)
Figure 4b – Germany – Interaction effect (Low aspirational value)
4.2 Testing the hypotheses
This section shows the SPSS results that were obtained after performing various analyses. The SPSS analyses were used to draw accurate conclusions about the hypotheses that were formulated. Although analyses were performed separately for Singapore and Germany, the tables show the results of each country next to each other. As in the earlier analyses the hypotheses were tested with the dependent variables participation and word of mouth that were both scaled with 1 being ‘very likely’ and 7 ‘unlikely’. The table below gives an overview of the hypotheses that were tested. Table 5 – Overview of the hypotheses Hypotheses H1: Females are more likely to participate in a loyalty program than males H1a: Females are more likely to indulge in positive word of mouth behavior than males
H2a: Consumers who visit the specific store more often are more likely to participate in the loyalty
program H2b: Consumers who spend a higher percentage of their shopping budget at the specific store are more likely to participate in the loyalty program H3: With a higher level of perceived relevance it is more likely for consumers to participate in the loyalty program H4: The aspirational value of the brand that is offered in the loyalty program is of positive influence to program participation by consumers H5: Rewards with a higher cash value will positively influence participation level in the loyalty program. H6: Reward divisibility has no direct effect on participation level. H6a: The height of the weekly grocery budget is of moderating influence on the relation between reward divisibility and participation H7: Word of mouth is positively influenced by a positive participation experience in the loyalty program. H7a: Consumers are more likely to indulge in (a) positive word of mouth and (b) repeat purchase
behavior when the aspirational value of the reward is high and when they can receive the award for free
H7b: Consumers are more likely to indulge in (a) positive word of mouth and (b) repeat purchase
behavior when they participate in the loyalty program
Table 6 – Results of T Test
N Mean Score P ‐ value F ‐ value
Singapore Germany Singapore Germany Singapore Germany Singapore Germany
Participation ‐ Male ‐ Female 488 515 495 506 3.55 3.86 4.25 4.30 0.866 0.118 0.028 2.443 Word of Mouth ‐ Male ‐ Female 488 515 495 506 3.59 3.88 4.28 4.27 0.919 0.326 0.01 0.964
Table 7 – Results of ANOVA tests
N Participation (1‐7) F – value P ‐ value
Singapore Germany Singapore Germany Singapore Germany Singapore Germany
Purchase Frequency ‐ Every day of the week ‐ 2‐3 times per week ‐ Once a week ‐ Once every 2 weeks ‐ Once a month 41 362 490 91 14 8 82 382 358 171 2,54 3,57 3,79 4,26 4,24 3,25 3,79 3,97 4,46 4,87 18.078 22.597 0.00 0.00 Total 1003 1001 % of budget spent at store ‐ 0‐20% ‐ 20‐40% ‐ 40‐60% ‐ 60‐80% ‐ 80‐100% 190 378 259 129 42 335 370 209 72 15 4,00 3,77 3,62 3,33 3,56 4,65 4,17 3,95 4,12 4,09 7.248 12.504 0.00 0.00 Total 1003 1001 Cash Value ‐ 50% ‐ 75% ‐ For free 331 336 336 333 334 334 3.77 3.73 3.64 4.30 4.22 4.31 1.032 0.556 0.356 0.574 Total 1003 1001 Note: significant relations (p<0.05) are highlighted in bold
Table 8a – Germany ‐ Correlations participation word of mouth aspirational value relevance reward divisibility1 reward divisibility2 participation 1 word of mouth .927** 1 aspirational value ‐.057* ‐.064** 1 relevance 0.013 0.004 0.009 1 reward divisibility1 0.028 0.026 ‐0.012 ‐0.036 1 reward divisibility2 0.028 0.026 ‐0.012 ‐0.036 1.000** 1 cash value 0.002 0.001 0.002 0.01 ‐0.035 ‐0.035 ** Correlation is significant at the 0.01 level (2‐tailed). * Correlation is significant at the 0.05 level (2‐tailed). Table 8b – Singapore ‐ Correlations participation word of mouth aspirational value relevance reward divisibility1 reward divisibility2 participation 1 word of mouth .927** 1 aspirational value ‐.150** ‐.159** 1 relevance 0.029 0.023 0.009 1 reward divisibility1 .060** 0.038 0.001 ‐0.011 1 reward divisibility2 .060** 0.038 0.001 ‐0.011 1.000** 1 cash value ‐0.031 ‐0.034 ‐0.006 ‐0.009 0.001 0.001 ** Correlation is significant at the 0.01 level (2‐tailed). * Correlation is significant at the 0.05 level (2‐tailed).
that the height of the weekly grocery budget is of moderating influence on the relation between reward divisibility and participation. This interaction effect was not significant (p>0.1) which tells us that H6a can be rejected.
Finally the influence of the dependent variables on each other is discussed. Hypothesis 7 states that word of mouth is positively influenced by a positive participation experience in the loyalty program. The hypothesis can be accepted in Singapore (F=12227.8, r²=0.86, p<0.1) and also in Germany (F=12160.7, r ²=0.86, p<0.1). Details can be seen in table 10 below. Table 10 – Influence of dependent variables on each other B t P ΔR2 F Germany Independent variable 0.859 12160.728 Participation 0.988 110.276 0.000 Singapore Independent variable 0.860 12277.849 Participation 0,972 110.805 0.000 Hypothesis 7a which states that consumers are more likely to indulge in (a) positive word of mouth and (b) repeat purchase behavior when the aspirational value of the reward is high and when they can receive the award for free is tested and accepted in Germany (4.15 versus 4.39, F=1.867, p<0.1) and in Singapore (3.46 versus 4.02, F=0.55, p<0.1). Table 11a – Results of T‐tests Aspirational Value
N Participation (1‐7) F – value P ‐ value
Singapore Germany Singapore Germany Singapore Germany Singapore Germany
Table 11b – Results of ANOVA tests
Hypothesis 7b states that consumers are more likely to indulge in (a) positive word of mouth and (b) repeat purchase behavior when they participate in the loyalty program. The results of the ANOVA tests to see if this hypothesis could be accepted are as follows: In Germany this is accepted (3.01 versus 3.77, F=11.231, p<0.01). In Singapore this is also accepted (2.25 versus 2.74, F=38.813, p<0.01).
4.3 Comparison with actual participation scores
The survey the respondents were confronted with also included questions concerning the actual loyalty program that was running at the store at the time that the respondents were interviewed. The questions tested awareness of the program and method of participation.
Table 12 – Familiarity with the loyalty program
N Percentage
Singapore Germany Singapore Germany
Yes 771 720 76,9% 72% No 232 280 23,1% 28% The table above shows that familiarity with the programs is very high in both Singapore and Germany. Furthermore, it was of interest to analyze how consumers participate in the loyalty program and also if they would recommend the proposed loyalty program to friends and/or family. Word of mouth was measured on a scale of 1 – 7 where 1 is ‘quite a lot’ and 7 is ‘not at all’. Table 13 below shows that participation in the program in Germany is high (469 versus 252) and that positive word
Cash Value N Participation (1‐7) F – value P ‐ value
Singapore Germany Singapore Germany Singapore Germany Singapore Germany
but positive word of mouth is low (337 versus 434). This means that consumers are probably not satisfied with the loyalty program that is running in Singapore. If they were satisfied then the chance that they would spread positive WOM would be bigger. Nonetheless, other unknown factors could have also contributed to these results.
Table 13 – Participation and positive WOM intention
N Percentage
Singapore Germany Singapore Germany
Participation Yes No 555 216 469 252 72% 28% 65% 35% Word of Mouth Yes No 337 434 491 230 43,7% 56,3% 68,1% 31,9% Lastly the consumers were also asked about their perception of the quality of the brand and their knowledge of the brand that was offered as a reward. In Singapore knowledge of the brand Diadora was high with 79% of the respondents stating knowledge of the brand. 49,7% of consumers also stated that they believed the quality of the brand to be high. In Germany knowledge of the brand was very high with 89,3% stating ‘yes’. Respondents in Germany were also very positive about the quality with almost 80% of the respondents being very satisfied with the quality of the brand.
Figure 4a ‐ Quality perception in Germany Figure 4b ‐ Quality perception in Singapore
4.4 Overview of hypotheses
Table 14 below provides an overview of the hypotheses chosen for this research and states if they were or were not accepted. Further remarks will be made in the conclusion and recommendations section.
TABLE 14 – Overview of hypotheses
Hypotheses Correlation Regression (incl. control variables)
H1: Females are more likely to participate in a loyalty
program than males
Reject Reject
H1a: Females are more likely to indulge in positive
word of mouth behavior than males
H2a: Consumers who visit the specific store more
often are more likely to participate in the loyalty program Reject Accept N/A Accept
H2b: Consumers who spend a higher percentage of
their shopping budget at the specific store are more likely to participate in the loyalty program
Accept Accept
H3: With a higher level of perceived relevance it is
likelier for consumers to participate in the loyalty program
Reject Reject
H4: The aspirational value of the brand that is offered
in the loyalty program is of positive influence to program participation by consumers
Reject Accept
H5: Rewards with a higher cash value will positively
influence participation level in the loyalty program.
Reject Accept
H6: Reward divisibility has no direct effect on
participation level.
H6a: The height of the weekly grocery budget is of
moderating influence on the relation between reward divisibility and participation Accept Accept Accept Accept
H7: Word of mouth is positively influenced by a
positive participation experience in the loyalty program
Accept N/A
H7a: Consumers are more likely to indulge in (a)
positive word of mouth and (b) repeat purchase behavior when the aspirational value of the reward is high and when they can receive the award for free
Accept N/A
H7b: Consumers are more likely to indulge in (a)
positive word of mouth and (b) repeat purchase behavior when they participate in the loyalty program
Accept N/A
5 CONCLUSIONS & RECOMMENDATIONS
Ferguson (2008) correctly summarized the value of this research with the following quote: “If
we have indeed entered an era of loyalty program saturation, then carefully crafted program differences based on highly segmented or individualized needs may be the only salvation. One size will no longer fit all. Some marketers are farther ahead down this path of differentiation than others.”
The above stated quote should serve as a guideline for marketers. Our main conclusion is also stated in the quote: marketers have to find the fit with their consumers in order to achieve the highest levels of loyalty program participation.
The aim of this research was to find out what reward elements are the strongest influencers of consumer’s intention to participate in a loyalty program. An interesting new addition within this research was the analysis of the relationship between participation in a loyalty program and the past purchase behavior of consumers together with their Word of Mouth intentions. The conclusion concerning this relationship is that frequency of store visits and WOM behavior are definitely related to participation in the program. It is also apparent that participation in a loyalty program leads to positive WOM behavior. This addition was apparent because research conducted beforehand often focused mainly on the relationship between participation and loyalty. Nonetheless, there are similarities because the researcher believed that WOM behavior is a sign of loyalty by consumers. We can conclude that the monetary element, as referred to in the problem statement, is still one of the most important factors for consumers in their decision to participate in a program. This was the strongest relationship as can be concluded from this research. Nonetheless, it was also apparent that the aspirational value that a consumer links with the rewards to be won in the loyalty program also plays an important role.
The hypotheses presented in this research were largely based on previous experience by the researchers on a probable effect between independent variables. The scenarios created and the experimental design used made it possible to analyze consumer preferences.
