Customers’ expectations and loyalty to their loyalty programs

How customers are reacting according to their socio-demographic factors.

Author: Loriane Genre-Grandpierre Tutor: Mosad Zineldin Examiner: Anders Pehrsson Date: 2015-05-29 Subject: Thesis, Advanced level Level: Master thesis Course code: 5FE00E

ABSTRACT

Title: Expectations of customers to their loyalty programs: how customers react

according to their socio-demographic factors. Keywords: Loyalty programs, Perceived benefits, Demographic factors, Customer loyalty,

Satisfaction

Background: Nowadays with the very competitive business environment, it is essential for

companies to gain loyal customers. Loyalty programs are one of the tools at the

disposition of companies to attract and retain their customers. The relationship

between customer loyalty and some socio-demographics factors have been a

subject of researches but the specific relationship between socio-demographics

factors and customer loyalty programs has not been studied yet. This study is

going to try to fulfil this gap.

Purpose: To study the influence of socio-demographic factors on customers’

expectations of their loyalty programs and on their loyalty. Research questions:

1. Which socio-demographic factors are influencing customers’ expectations of their loyalty programs?

2. Which socio-demographic factors are influencing program loyalty and company loyalty?

Methodology: Quantitative research. Conclusion: It is possible to say that all socio-demographic factors studied have an

influence on at least one of the expectations of customers concerning their

loyalty programs and on their loyalty too. Those factors are then really

important for a company to look at when they start a loyalty program or when

they try to improve it.

Table of contents

1  INTRODUCTION  ...........................................................................................................................................  1  1.1  BACKGROUND  ...........................................................................................................................................  1  1.2  PROBLEM  FORMULATION  .....................................................................................................................  2  1.3  RESEARCH  GAP  AND  PURPOSE  ............................................................................................................  3  1.4  REPORT  STRUCTURE  ..............................................................................................................................  4  

2  THEORETICAL  FRAMEWORK  ..................................................................................................................  5  2.1  CUSTOMER  LOYALTY  PROGRAMS  ......................................................................................................  5  2.2  PERCEIVED  BENEFITS  ............................................................................................................................  6  2.2.1  UTILITARIAN  BENEFITS  .......................................................................................................................................  6  2.2.2  HEDONIST  BENEFITS  .............................................................................................................................................  6  2.2.3  SYMBOLIC  BENEFITS  ..............................................................................................................................................  7  2.3  CUSTOMER  LOYALTY  ..............................................................................................................................  8  2.3.1  CUSTOMER  LOYALTY  AND  SATISFACTION  ..................................................................................................  8  2.3.2  LOYALTY  TO  THE  PROGRAM  ...............................................................................................................................  9  2.3.3  LOYALTY  TO  THE  COMPANY  ...............................................................................................................................  9  2.4  SOCIO-­‐DEMOGRAPHIC  FACTORS  .....................................................................................................  10  2.4.1  GENDER  .....................................................................................................................................................................  10  2.4.2  AGE  ..............................................................................................................................................................................  10  2.4.3  EDUCATION  .............................................................................................................................................................  11  2.4.4  INCOMES  ...................................................................................................................................................................  11  2.4.5  MARITAL  AND  PROFESSIONAL  STATUS  .....................................................................................................  11  2.5  CONCEPTUAL  FRAMEWORK  ..............................................................................................................  12  

3  METHODOLOGY  ........................................................................................................................................  14  3.1  RESEARCH  APPROACH  ........................................................................................................................  14  3.1.1  INDUCTIVE  VS.  DEDUCTIVE  RESEARCH  .....................................................................................................  14  3.1.2  QUALITATIVE  VS.  QUANTITATIVE  RESEARCH  ........................................................................................  15  3.2  RESEARCH  DESIGN  ...............................................................................................................................  16  3.3  DATA  SOURCES  ......................................................................................................................................  17  3.4  RESEARCH  STRATEGY  .........................................................................................................................  17  3.5  DATA  COLLECTION  METHOD  ............................................................................................................  19  3.6  OPERATIONALIZATION  ......................................................................................................................  19  3.6.1  OPERATIONALIZATION  TABLE  ......................................................................................................................  20  3.7  SAMPLING  ................................................................................................................................................  21  3.8  SAMPLING  FRAME  .................................................................................................................................  22  3.9  QESTIONNAIRE  DESIGN  ......................................................................................................................  22  3.10  DATA  ANALYSIS  METHOD  ...............................................................................................................  23  3.10.1  PEARSON’S  CORRELATION  ............................................................................................................................  23  3.10.2  ANOVA  ANALYSIS  ...............................................................................................................................................  24  3.11  QUALITY  CRITERIA  ............................................................................................................................  24  3.11.1  RELIABILITY  .........................................................................................................................................................  24  3.11.2  VALIDITY  ................................................................................................................................................................  25  3.12  SUMMARY  .............................................................................................................................................  26  

4  EMPIRICAL  FINDINGS  .............................................................................................................................  27  4.1  PEARSON’S  CORRELATION  ................................................................................................................  27  4.2  PRESENTATION  OF  THE  RESULTS  H1  .............................................................................................  28  4.2.1  GENDER  .....................................................................................................................................................................  28  4.2.2  AGE  ..............................................................................................................................................................................  28  

4.2.3  EDUCATION  .............................................................................................................................................................  29  4.2.4  MARITAL  STATUS  .................................................................................................................................................  30  4.2.5  PROFESSIONAL  STATUS  .....................................................................................................................................  31  4.2.6  INCOMES  ...................................................................................................................................................................  31  4.3  CUSTOMER  LOYALTY  ...........................................................................................................................  32  4.3.1  GENDER  .....................................................................................................................................................................  32  4.3.2  AGE  ..............................................................................................................................................................................  33  4.3.3  EDUCATION  .............................................................................................................................................................  33  4.3.4  MARITAL  STATUS  .................................................................................................................................................  34  4.3.5  PROFESSIONAL  STATUS  .....................................................................................................................................  35  4.3.6  INCOMES  ...................................................................................................................................................................  36  

5  ANALYSIS  ....................................................................................................................................................  36  5.1  CUSTOMERS’  EXPECTATIONS  ABOUT  LOYALTY  PROGRAMS  .................................................  36  5.1.1  GENDER  .....................................................................................................................................................................  37  5.1.2  AGE  ..............................................................................................................................................................................  37  5.1.3  EDUCATION  .............................................................................................................................................................  38  5.1.4  MARITAL  STATUS  .................................................................................................................................................  38  5.1.5  PROFESSIONAL  STATUS  .....................................................................................................................................  38  5.1.6  INCOMES  ...................................................................................................................................................................  39  5.1.7  SUMMARY  .................................................................................................................................................................  39  5.2  CUSTOMER  LOYALTY  ...........................................................................................................................  40  5.2.1  GENDER  .....................................................................................................................................................................  40  5.2.2  AGE  ..............................................................................................................................................................................  40  5.2.3  EDUCATION  .............................................................................................................................................................  40  5.2.4  MARITAL  STATUS  .................................................................................................................................................  41  5.2.5  PROFESSIONAL  STATUS  .....................................................................................................................................  41  5.2.6  INCOMES  ...................................................................................................................................................................  41  5.2.7  SUMMARY  .................................................................................................................................................................  42  

6  CONCLUSION  ..............................................................................................................................................  43  

7  DISCUSSION  ................................................................................................................................................  43  7.1  LIMITATION  ............................................................................................................................................  43  7.2  MANAGERIAL  IMPLICATIONS  ...........................................................................................................  44  7.3  FUTURE  RESEARCH  ..............................................................................................................................  44  

REFERENCES  ..................................................................................................................................................  46  

APPENDIX  .......................................................................................................................................................  54  APPENDIX  A  –  QUESTIONNAIRE  .......................................................................................................................  54  APPENDIX  B  -­‐  PRESENTATION  OF  THE  DEMOGRAPHIC  FACTORS  (SPSS)  .....................................................  58  APPENDIX  C  –  SATISFACTION  (AUTHOR’S  ELABORATION)  ............................................................................  59  APPENDIX  D  –  CUSTOMERS’  EXPECTATION  ACCORDING  TO  THEIR  LOYALTY  PROGRAMS  (AUTHOR’S  ELABORATION)  ..................................................................................................................................................  60  APPENDIX  E  –  CUSTOMER  LOYALTY  ACCORDING  TO  THEIR  LOYALTY  PROGRAMS  (AUTHOR’S  ELABORATION)  ..................................................................................................................................................  60  

 

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1 INTRODUCTION

1.1 BACKGROUND

Nowadays, a very competitive business environment is occurring (Bose and Rao, 2011). It can be

difficult for a customer to appreciate the distinction between different companies’ products or

services (Ibid.). In this context, it is challenging for companies to gain loyal customers, as it is

nearly always possible for them to choose an alternative for the same product (Ibid.). According to

McIlroy and Barnett (2000, p. 348) loyalty can be described as “customer’s commitment to do

business with a particular organization, purchasing their goods and services repeatedly, and

recommending the services and products to friends and associates”. Loyal customers are « better »

customers for companies as they tend to spend more regularly and more money than the other

customers (Selin et al.,1988). Moreover, if customers are satisfied and loyal to a brand they could

also generate new customers though a positive word of mouth (O ́Brien and Jones, 1995). The

financial cost for a company is also a motive, as « it has been estimated that attracting a new

customer is three to five times more costly than retaining an existing customer” (Jang and Mattila,

2005, p. 402).

Loyalty programs are significant tool of firms’ Customer Relationship Management (also CRM)

strategies to retain customers (Liu, 2007). Their aim is to attract new customers, retain existing ones

by rewarding their purchases with the aim of increasing their spending and their loyalty to the brand

or to the company (Ibid). Demoulin and Zidda (2009) are showing that firms are using loyalty

programs for three reasons: retain their customers, make them more loyal and gather as many

information as possible on their customers’ shopping attitude. Dowling and Uncles (1997) are

listing more reasons to explain why firms are creating and using loyalty programs: to protect sales,

margins and profit; strengthen loyalty and increase the value for the existing customer; stimulate

existing customer’s cross-product sale; use them as a tool for differentiate themselves compared to

competitors; make the entry of a new brand more difficult; and to finish make the introduction of a

comparable loyalty program more difficult. Loyalty programs have extended during the last decades

and are really popular especially in the retail industry (Berman, 2006). Around 90% of consumers

in UK, United States and Canada are involved at least in one loyalty program (Ibid). Because of the

omnipresence of customer loyalty programs, several researches have been done to measure the

effectiveness of them or the benefits for companies (Bolton et al., 2000). Those programs had

become more and more complex because of CRM systems and they now give access to customers’

private information like purchase tracking or preferences (Injazz and Popovich, 2003).

 

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The expansion of loyalty programs has led to changes in the loyalty of customers: according to Yi

and Jeon (2003) there are now two different kind of loyalty: program loyalty and brand loyalty.

Similarly, others researchers such as Evanschitzky et al. (2011) differentiate loyalty to the program

itself and the loyalty to the company. The first kind of loyalty can be defined as “a high relative

attitude leaning toward the loyalty program” (Yi and Jeon, 2003, p. 232). On the other hand,

Sirdeshmukh, Singh, and Sabol (2002) are giving the following definition for company loyalty:

“intention to perform a diverse set of behaviours that signal a motivation to maintain a relationship

with the focal firm”. The relationship between customer loyalty and some socio-demographics

factors have been a subject of researches. Women tend to regard highly a long-term relationship

with a brand and as consequences are expected as more loyal compared to men (Patterson, 2007).

Ndubisi (2007) has explored the question of the difference between ages towards customer loyalty

and has found that there is one. Complementarily, Patterson (2007) is arguing that loyalty is more

common upon senior person than young people. Some researchers have found that both genders are

joining loyalty programs but the distinction between them is when it comes to loyalty and their

shopping behaviours (Kuruvilla, Joshi and Shah, 2009). Nevertheless, the specific relationship

between socio-demographics factors and customer loyalty programs has not been studied yet. For

this study, gender, age, education, professional status, marital status and incomes are going to be

studied in the specific area of customer loyalty programs.

1.2 PROBLEM FORMULATION

The efficiency of loyalty programs is still questionable and some researches are even showing that

nowadays, with the multiplying of those programs, the link between them and customer loyalty is

not automatic (Uncles and Dowling, 2003).

Prior researches have explored the factors of success for loyalty programs. Jang and Mattila (2005)

have focused their research on the preferences of customers upon the types rewards; on the other

hand Keh and Lee (2006) have explored the question of customers’ preferences about the timing of

rewards. The type of rewards is about what kind of rewards the customer is going to receive (e.g.

Monetary vs non-monetary rewards); whereas the timing refers to when the customers prefer to

receive the reward (Jang and Mattila, 2005; Keh and Lee, 2006).

Other researchers have shown that monetary rewards were the main interest in joining a loyalty

program (e.g. Berry, 1995; Peterson, 1995). Minouni-Chaabane and Volle (2010) have later

developed a scale to measure the impact of perceived benefits of loyalty programs upon customer

loyalty. Their research was made to fill the gap on customers’ point of view on loyalty programs

(Ibid). It shows that there is five types of perceived benefits which all are important: monetary

 

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savings, exploration, entertainment, recognition, and social benefits (Ibid.). Several other researches

have followed to enhance or apply this scale to different sector or cultures (Kim and al, 2013; Bose

and Rao, 2011; Wel and al., 2011). This scale is going to be used in this study to understand the

expectations of customers about their loyalty programs, the benefits they received from them and

the loyalty that implies from it.

1.3 RESEARCH GAP AND PURPOSE

Customer loyalty and customer loyalty programs have been a large source of interests for

researchers. As seen before, some researches about the impact of gender and age on customer

loyalty have been done already (Ndubisi, 2006; Kuruvilla, Joshi and Shah, 2009; Patterson, 2007).

In his study Ndubisi (2006) is arguing that for futures researches on the subject of customer loyalty

it would be good to consider more demographic factors other than gender. McGoldrick and Andre

(1997) also have the same opinion on the fact that it is important to look at demographic factors

when studying customer loyalty. Moreover, the focus of those studies was on customer loyalty and

there are only few researches about the impact of demographic factors in the specific subject of

customer loyalty programs. It is important to differ people according to socio-demographic factors

when looking at their membership to a loyalty program. In fact, it will not mean the same according

to those differences and the expectation they have on it could differ according to the situation they

are in (O’Malley, 1998).

This research is going to try to intend to fulfil this gap. The following demographic factors are

going to be used to evaluate their influence on customers’ expectations and perceptions of loyalty

programs’ benefits: gender, age, education, level of income, marital and professional situation. Thus

the purpose of the thesis is to investigate how socio-demographic factors can influence the

perception of loyalty programs as well as their loyalty. To reach this purpose, the thesis answers the

following question: How socio-demographic factors are influencing customer loyalty programs?

The research question is separated into this two following sub-questions:

1. Which socio-demographic factors are influencing customers’ expectations of their loyalty programs?

2. Which socio-demographic factors are influencing customers’ loyalty?

The objective of the study is to present an empirical knowledge on how customers value their

loyalty programs according to their identity and background and consequently display if the loyalty

programs are in accordance with those results.

 

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1.4 REPORT STRUCTURE

This paper is composed with seven chapters. The first chapter is an introduction where the

background and the problem formulation of the study are presented. It also includes the research

gap, which have been pointed out thought previous researches and thus is the purpose of this study.

The second chapter is the literature review and the theoretical framework. It includes theory and

concepts about customer loyalty programs, their benefits, customer loyalty and socio-demographic

factors. Moreover, the research model is displayed in this chapter. Chapter 3 is the methodology

information about the research. The author has chosen to conduct a deductive approach with

primary data. It has been chosen to conduct a descriptive and quantitative research with

questionnaire as data collection method. The operationalization table is presented with the different

measures used. In the chapter 4, the results of the surveys are displayed. To facilitate the

understanding of the findings, data is presented thanks to recap charts that are based on the results

from SPSS. Correlation and ANOVA analysis have been chosen to analyse the data statistically.

The chapter 5 is analysing those results. The aim of this chapter is to discuss the influence of socio-

demographic factors on the perceived benefits of loyalty program and on customer loyalty. The

chapter 6 is presenting the conclusion of this research. The chapter 7 is the last one and present a

discussion of the conclusion of the study with a presentation of its limitation, the managerial

implication of this conclusion and some recommendation for future research.

 

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2 THEORETICAL FRAMEWORK In this chapter the concepts used in this study are going to be presented. First there is an

introductory part about loyalty programs, followed by a review of their perceived benefits and to

finish, customer loyalty is going to be broached.

2.1 CUSTOMER LOYALTY PROGRAMS

The definition of loyalty programs has interested different researchers. Liu (2007) is defining

loyalty programs as a program that recompenses customers with free rewards when they are buying

repeatedly with a firm. This definition puts emphasis on the importance of purchase’s repetition, as

the program will not be advantageous for the customer for only one purchase but from several

(Ibid.). One of the tools that enhance customer loyalty programs is the targeted communication and

the customization the program according to the customer (Lacey and Sneath, 2006). As

consequences, customers’ loyalty programs are different from the firm’s promotional campaign

because of their long-term objectives (Sharp and Sharp, 1997).

Specific areas of customer loyalty programs have been observed (Bose and Rao, 2011). One of the

main areas that have been research about is the impact of customer loyalty programs on customers,

on customers or marketers’ point of view (Ibid.). Dowling and Uncles (1997) are showing that the

value of the company’s products or services is improved by effective loyalty programs and are

provoking a good retention of customers. Several others researchers have proved the effectiveness

with loyalty programs on the fact that customers are going to buy again with this specific firm. For

example, Knox and Denison (2000) studied loyalty programs in the specific industry of e-grocery

store in UK and their effect on customers’ loyalty and retention. The study shows that loyalty

programs are increasing the annual amount of purchase by customers (Ibid.). Loyalty programs tend

to have a higher impact on moderate and light buyers because they are increasing their purchase

frequency, whereas studies have shown that it is not the case for heavy buyers who tend to just

collect their rewards without increasing their purchase frequencies (Liu, 2007; O’Brien and Jones,

1995). Moreover, loyalty programs also have an impact on customers’ perception of prices and

competition (Bose and Rao, 2011). A large number of researchers have explored the impact of

loyalty programs on customers’ price sensitivity, and most of them have concluded that a loyal

customer have a lower sensitivity to prices (e.g., Guadagni and Little 2008; Srinivasan and al.,

2002), especially when it is associated with easy and quick earned rewards (Nako, 1997). Loyalty

programs also have impacts on customers’ perception of competitors’ prices; as they are going to

purchase repeatedly from a specific firm, they will loose track of competitors’ prices (Reichheld,

 

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1996). Nevertheless, Liu and Yang (2009) are showing with their study of airline industry that

successful loyalty programs, in a very competitive market, tend to be those from high market share

firms. In fact, they are going to be the only one to be able to increase their sales thanks to loyalty

programs because of their strong customer base and products (Bose and Rao, 2011).

2.2 PERCEIVED BENEFITS

Academics have research about the link between the benefits of a loyalty program and customer

loyalty to those programs. Indeed, Leenheer and al. (2007) found that customers are more likely to

join a loyalty program if they see that they will receive economical or non-economical benefits

from it. Moreover, if they perceive that this specific program is more interesting for them than those

from competitors, they will be more inclined to participate to this program (Wirtz and al. 2007).

Perceived benefits of a loyalty program can be divided into three categories: utilitarian benefits

(monetary savings), hedonic benefits (exploration and entertainment) and symbolic benefits

(recognition and social benefits) (Minouni-Chaabane and Volle, 2010).

2.2.1 UTILITARIAN BENEFITS

Utilitarian benefits can be defined as the functional, instrumental and practical benefits of a loyalty

program (Chitturi and al., 2007). Utilitarian benefits report to basic desire like safety needs and

generally refer to a product’s tangible attributes (Minouni-Chaabane and Volle, 2010). Customers

arbitrate characteristics of a loyalty program by its success to accomplish what it was supposed to,

meaning if the utilitarian value have been reach (Ibid.). Utilitarian benefits is basically monetary

savings (Ibid.)

2.2.1.1 MONETARY SAVINGS

Monetary savings seem to be the most important motivation for consumers to join a loyalty

program (Peterson, 1995). To start a relationship, customers need to perceive that the firm is going

to offer them more value with a lower price (Parvatiyar and Sheth, 1995). Monetary saving can be

cash-back offer or coupon that customers can accumulate by buying regularly with the same firm

(Minouni-Chaabane and Volle, 2010).

2.2.2 HEDONIST BENEFITS

Hedonic benefits refer to the experiential and enjoyment-related benefits of the loyal program

(Chitturi and al., 2007). They can be experienced throughout shopping, the use of a media and they

 

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have a positive impact on customer loyalty (Arnold and Reynolds, 2003, Babin and Attaway, 2000,

Babin et al., 1994, Jones et al., 2006 and McQuail et al., 1972). They can be divided into two

dimensions: exploration and entertainment (Minouni-Chaabane and Volle, 2010).

2.2.2.1 EXPLORATION

Exploratory behaviours are the fact for consumers to desire to experience new or innovative

products or services, to challenge their curiosity by changing their purchase habits, seeking new

information about products or promotional offers and so forth (Arnold and Reynolds,

2003 and Baumgartner and Steenkamp, 1996). Consumer magazines or direct mail can be tools for

customer’s exploration (Minouni-Chaabane and Volle, 2010).

2.2.2.2 ENTERTAINMENT

Loyalty programs can allow customers to collect and redeeming points, which is entertaining for

them (Johnson, 1999). Entertainment can also be because of the possibility of enjoying experiences

or activities that would not have been possible if they did not had join the program (Minouni-

Chaabane and Volle, 2010). In fact, most of loyalty programs are offering attractive and enjoyable

incentives to provide joy and make customer see loyalty program as an end in itself (Ibid.).

2.2.3 SYMBOLIC BENEFITS

Symbolic benefits are linked to personal expression, self-esteem and social approval and are

provided by extrinsic advantages of a specific product or services (Keller, 1993). Loyalty programs

are offering those symbolic benefits by differentiate customers in members and non-members by

having some special treatments for the first category, which can be considered as a sign of respect

or distinctiveness (Gordon et al., 1998).

2.2.3.1 RECOGNITION

Csikszentmmihalyi (2000) is pointing out that member of loyalty programs are consequently

experiencing recognition benefits. Recognition can be defined as the customer’s feeling about their

retailer treating them better than non-members (Beatty et al., 1996 and Gwinner et al., 1998). It can

be perceived by special status, feeling distinguished and special treatments (Minouni-Chaabane and

Volle, 2010)

 

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2.2.3.2 SOCIAL BENEFITS

Social benefits can be defined as the feeling of being part of an exclusive group that share common

values about the brand (Muniz and O'Guinn, 2001). Customers see themselves as privileged

customers and identify themselves with this specific group (Ibid.)

2.3 CUSTOMER LOYALTY

2.3.1 CUSTOMER LOYALTY AND SATISFACTION

The concept of loyalty in marketing has been research a lot by academics. Past studies have shown

that customer satisfaction tend to lead to customer loyalty (Bose and Rao, 2011). A customer is

going to stay loyal if he or she perceives that the company gives him or her better product or

services than competitors (Ibid.). In a business perceptive, loyalty is defined as the commitment of a

customer to have a business relationship with a specific organisation, by buying their products or

services repeatedly and having the desire of recommending the products or services to friends and

associates (McIlroy and Barnett, 2000). Shoemaker and Lewis (1999) are defining loyalty as “. . .

loyalty occurs when the customer feels so strongly that you can best meet his or her relevant needs

that your competition is virtually excluded from the consideration set and the customer buys almost

exclusively from you”. Oliver (1999) contradicts those definitions of loyalty, as he considers that

past definitions are unsuccessful to give a unitary definition of it and fail to integrate the attitudinal

perspective of it. Attitudinal loyalty involves cognitive, affective and conative aspects (Oliver,

1997) and more recently the author has added a fourth phase, which is action (Oliver, 1999). The

first stage is the cognitive one and is constructed thanks to prior knowledge or experience about a

specific company (Olivier, 1997). The second stage is the affective phase, which is the fact of

liking or have feelings for a brand. After this one comes the conative loyalty when the customer has

the intention to keep purchasing a product with this specific firm. The final stage is the action

loyalty, which is the transformation of intention of buying into the readiness to act. (Oliver, 1999)

Retaining existing customers is crucial in retail markets because of the intense competition that is

occurring (Sirohi et al., 1998) and it has become a strategy in itself to conserve a competitive

advantage over competitors (Grönroos, 2009). Moreover, Reichheld (2001) has pointed out that a

loyal customer is costing less to a company than creating a new one.

Marketing literature is considering that satisfaction is a necessary antecedent to customer loyalty

(Sivadas and Baker-Prewitt, 2000; Abdullah and al., 2012). Consumer satisfaction had a lot of

definition throughout academic literature. Satisfaction can be defined as an evaluative judgement

that is occurring after doing the choice of buying a specific product or service (Day, 1984).

 

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Generally the evaluation of satisfaction is happening by comparing the expectation of customers

before buying the item and the performances of the item perceived after the purchase (Bearden and

Teel, 1983; Oliver, 1980; Westbrook, 1980). Satisfaction is as consequence a result of the

evaluation of the perceived performance of the item, it could be confirmed or not (Danaher and

Haddrell, 1996).

The most accepted view is that satisfaction has a positive impact on loyalty (Sivadas and Baker-

Prewitt, 2000; Abdullah and al., 2012). Nevertheless, it is important to see that there is more than

just this relation between the two concepts as even satisfied customers could be unfaithful to a

brand. Reichheld’s (1996) research has concluded that 65% to 85% of the disloyal customers were

actually satisfied or very satisfied. In the same way, Chandrashekaran and al. (2007) are studying

the results obtained by the U.S. Office of Consumer Affairs (Technical Assistance Research

Program, 1986) and pointed out that only 54% of household who have faced services problems

were satisfied by the resolution of those problems but they would not remain. Moreover, another

study has shown that only 25% of the variance in repeated purchase is explained by satisfaction

(Henard and Szymanski, 2001).

2.3.2 LOYALTY TO THE PROGRAM

Companies are creating loyalty programs in the aim of influencing the way and the frequency of

customers’ buying, what they think about the company, their relationship with it and to create more

loyalty among those customers (Henderson et al., 2011). Loyalty programs are providing financial

benefits (Bolton, Lemon, and Verhoef, 2004) such as discounts, promotional offers and coupons

(Mimouni-Chaabane and Volle, 2010). They also give the opportunity for customers to discover

new products and try some (Ibid.). Moreover, loyalty programs tend to create a sense of community

and personal recognition (Gwinner, Gremler, and Bitner, 1998). They create a feeling of belonging

and are making customer feel important (McMillan and Chavis, 1986). The financial features, the

fact of discovering new products and the felling of belonging increase the customer loyalty to the

program because they perceived a utility of the program (Meyer-Waarden, 2007).

2.3.3 LOYALTY TO THE COMPANY

When customers are joining a loyalty program they become a member of a more or less exclusive

group where they can share same values and can identify themselves with this group (Muniz and

O'Guinn, 2001). Customers who are loyal to a program tend to develop strongest relationship with

the company in question (Ahearne et al., 2005 and Bhattacharya et al., 1995). Moreover, one benefit

of loyalty to program is that customers have more access to information about the company and

 

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they are going to interact more with it (Bolton et al., 2000) and then customers tend to be less

receptive to negative and external information about this company and as a consequence are going

to be more loyal to the company (Ibid.)

2.4 SOCIO-DEMOGRAPHIC FACTORS

The moderating effect of socio-demographic factors on customer loyalty and satisfaction has been

research by academics. The different factors are going to be presented below. Nevertheless, the

effect of them on the expectations and perceived benefits from loyalty programs have not been a

subject of research, which is going to be the aim of this study.

2.4.1 GENDER

It has been shown that there is an important difference in how females and males are shopping

(Kuruvilla et al., 2009; Helgesen and Nesset, 2010). Previous studies seem to indicate that females

tend to be more loyal than males but it not true in every situation because it depends on what they

are buying (Melnyk et al., 2009). According to Patterson (2007), females value more long-term

relationship where there are personal contacts. Melnyk et al (2009) agreed on that, saying that

females are more interested in the personal relationship rather than on the company as an entity.

Schwartz and Rubel (2005) ran a study in 70 different countries and found that men and women’s

behaviours are driven by really different values and motives. They pointed out that men are seeking

more than women for social status, prestige, dominance and achievement. In the other hand, women

are valuing more the individual and personal relationships (Baumeister and Sommer, 1997). As

consequences, women are less interested in the elite grade of a loyalty program and the social status

that is conveyed by those kind of status. On the contrary, it more important to be recognized as

individuals and that companies understand they have a name, a birthday and preferences (Melnyk et

al., 2009). It is also less important for them that the personalization of the program is visible to

everyone because they are less concerned about showing off to the others compared to men. (Ibid.)

2.4.2 AGE

According to different authors, age has a moderating effect on customer satisfaction and loyalty

(Baumann, Burton, and Elliott 2005; Homburg and Giering 2001). Those authors found that older

customers are more loyal to a specific brand in the industry of automobile and banking (Ibid.).

However, those results can be tempered by the large-scale study from the American Association of

Retired Persons, which have found that older consumers have the same proportion to switch from a

 

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brand to another compare to young people (Moos 2004). Moreover, older consumers have more

free time and so more time to spend on shopping and as consequences are more able to shop at

numerous stores (East et al. 1995; East et al. 2000). The middle-age group has been found to be the

group the more loyal. Wright and Sparks (1999) has shown that the 35-44 age group are the most

loyal which has been supported by McGoldrick and Andre (1997) who are demonstrating that loyal

shopper have more chance to be from the middle-age group.

2.4.3 EDUCATION

Research on the subject tends to show that a higher level of education leads to lower level of loyalty

among customers (Chance and French 1972; Mittal and Kamakura 2001; Murphy 1978). In fact,

people with higher level of education tend to gather more information and usage before making a

decision and as a consequence are more aware of the possible alternatives (Capon and Burke 1980).

Moreover, it has been shown that people with higher level of education tend to gain higher income

(Farley, 1964) and, as it is going to be exposed below, higher income levels tend to be less loyal

customers.

2.4.4 INCOMES

A lot of research have demonstrated that income have a negative impact on customer loyalty (Crask

and Reynolds, 1978; Korgaonkar, Lund, and Price, 1985; Zeithaml 1985). The reason is that

consumers with higher income have fewer shopping restriction and so are considered to be less

loyal to a specific brand compare to those with lower income (Sharir 1974; Zeithaml 1985).

Nevertheless, those findings are not unanimous. In the sector of online services Keaveney and

Parthasarathy (2001) found that consumers that were switching of brand have a lower average

income levels than the one that are loyal.

2.4.5 MARITAL AND PROFESSIONAL STATUS

The relationship between marital status, professional status and loyalty does not appear a lot in the

extant literature. In fact, some researchers have explored the impact of marital and professional

status on customer loyalty but it was always on a secondary level, in a specific industry or specific

cultural context. As consequences, it is hard to draw some tendencies. This study is going to try to

fill that gap.

 

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2.5 CONCEPTUAL FRAMEWORK

The research model, presented in the figure 1, is going to give a full view of the study. Socio-

demographic factors are divided into gender, age, education, marital, professional status and

incomes. Perceived benefits are divided into monetary saving, exploration, entertainment,

recognition and social. The link going from the demographic factors to perceived benefits, and

loyalty are illustrating the potential influence of them. The rest of the model is presented to

understand what implies loyalty and is going to be used to go further and give some managerial

implications for this study but only the part in the square is going to be studied here.

 

  13  

 

Socio-demographic

factors

Gender Age

Education Professional

situation Marital status

Income

Figure 1. Research model (Author’s elaboration) H1: Socio-demographic factors have an influence on customers’ expectation of a loyalty program H2: Socio-demographic factors have an influence on customers’ loyalty

Customers’ expectation on benefits in a program

Monetary savings

Exploration Recognition

Social

Customers’ perceived benefits in a program

Monetary savings

Exploration Recognition

Social

Customer loyalty

Loyalty to the program Loyalty to the company

Satisfaction

H1  

H2  

 

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3 METHODOLOGY This chapter includes an explanation of how the study was conducted in order to solve the research

problem.

3.1 RESEARCH APPROACH

Research approach is how the research problem is going to be solved in this particular thesis. A

research that is qualified to be high quality needs to include two main concepts: relevance and

rigour (Bryman and Bell, 2011). Relevance is composed of different points that need to be reached:

the research need to have managerial and theoretical interesting results, it needs to be achievable in

a certain time and be understandable (Ibid.). The research also needs to be rigorous, meaning that

other researchers could be able to accomplish the study again (Ibid.). Burns (2003) also emphasis

the importance of reliability, valid data, reasonable time and low costs which can be reached thanks

to the right choice of research approach. There are different ways of conducting a study; it is

possible to conduct an inductive or deductive research and choose between a quantitative or

qualitative one (Bryman and Bell, 2011).

3.1.1 INDUCTIVE VS. DEDUCTIVE RESEARCH

The deductive approach occurs when an author is gathering information about existing theories and

researches to make own hypothesis. Those hypotheses are going to be accepted or rejected thanks to

the empirical data that the authors will gather and its comparison to existing theories (Bryman and

Bell, 2011). Beiske (2007) is saying that deductive research approach is the fact of investigating an

existing theory or phenomenon and experiment if that theory is still valid in others situations or

conditions. According to Robson (2011), deductive studies have five sequential stages of progress

to follow. The first stage occurs when the authors are deducting hypothesis from theory. The second

stage is about the operationalization of the hypotheses that need to be breaking down into

measurable items. The hypotheses need to be tested in the third stage and then they are rejected or

accepted in accordance with the results of the study. In the last stage, the theory is modified or not

according to the results. (Ibid.)

On the other hand, inductive research is working on the other way around. An inductive research’s

aim is to generate new theory as a result of observations (Brewerton and Millward, 2001). In the

inductive approach, the research is not based on theory and no hypotheses are formulated at the

 

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beginning of it but it is based on learning from experience, resemblances or premises (Lancaster,

2005; Lodico and al, 2010).

According to Bryman and Bell (2011), the deductive approach is more logical than the inductive

one. Moreover, most of the time deductive researches are connected to quantitative data collection

whereas inductive researches are connected to qualitative data collection (Ibid.)

This research is going to be conducted as a deductive approach because the author started to gain

information on the specific subjects of customer loyalty, customer loyalty programs and socio-

demographic factors in the existing theory; which are concepts that have been already research a

lot. The information collected constitutes the literature review of this study. Two hypothesises have

been formulated and will be accepted or rejected at the end of the research. The result of this study

is going to fulfil the existing gap of the specific relationship between customer loyalty program and

the influence of socio-demographic factors on it.

3.1.2 QUALITATIVE VS. QUANTITATIVE RESEARCH

It is common that qualitative and quantitative researches are seen as contrasts to each other

(Bryman and Bell, 2011). Qualitative research is preferred when authors want to go deeper into

gathering information about a specific subject (Clayton, 2010). It is usually used when there is not a

lot of existing knowledge about the specific area or when the problem is complicated and authors

want to totally understand it (Bryman and Bell, 2011). Nevertheless, there are drawbacks to those

studies: conclusions made thanks to qualitative studies can not be generalized as they are based on

beliefs and attitudes, it is hard to replicate those studies and there is a chance that respondents do

not answer what they really think but rather what the author wants to hear and so distort the

conclusions (Ibid.).

Quantitative researches are mostly studies that answer questions such as “how often” or “how

much” (Amaratunga and al., 2002; Hartman, 2004). The results from quantitative data collection are

numbers that are going to be presented in graphs or in a mathematical way (Clayton, 2010;

Hartman, 2004; Bryman and Bell, 2011). It is why quantitative researches are more structured and

controlled than qualitative one because of its numeric questions (Hartman, 2004). Results of those

studies are measurable and presentable (Ibid.) and that is why it is easier for other researchers to

replicate the study (Bryman and Bell, 2011). According to Hartman (2004), quantitative studies

have three phases: planning, collection and analysis.

The area of customer loyalty and customer loyalty programs has existing theories and studies about

it. Nevertheless, the author has found a gap in this existing knowledge about the impact of

 

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demographic factors on the relationship between customer loyalty programs and customer loyalty.

As consequences, this study is going to have a quantitative approach because the author needs to

collect data from a large number of customers from different background to have quantifiable

numbers and then be able to base the study on those numbers that are not available yet.

3.2 RESEARCH DESIGN

The research design is vital for the study as it is the plan researchers decide to use to resolve the

problematic of their studies (Bryman and Bell, 2011; Saunders and al. 2009). The first step is to

formulate the problem and there are three paths to choose from: the exploratory, the descriptive and

the explanatory (Bryman and Bell, 2011).

An exploratory study is when authors are searching for new understanding of a specific area to clarify

the problem they have raised (Saunders and al., 2009). This kind of research occurs when there are few

existing studies on the subject (Krishnaswami and Satyaprasad, 2010) or when a problem has

happened and authors want to research the reasons why (Churchill and Iacobucci, 2005).

A descriptive study is about presenting the proper profile of persons, event or specific situations

(Robson, 2011). Moreover, it helps answering the questions to who, what, when where and why

someone act in a certain way. (Churchill and Iacobucci, 2005). A descriptive research needs to be

based on previous researches and be analytic (Grønmo and Winqvist, 2006). Most of the time,

surveys are used in descriptive research (Burns, 2003).

The last kind of path is the exploratory research, which is when authors are focused on a unique

problem or situation and the aim is to demonstrate a causal relationship between variables (Saunders,

Lewis and Thornhill, 2009).

The purpose of this study is to describe in which way the demographic factors are influencing, or not,

the expectations of customers on their loyalty programs and their loyalty. Moreover, the purpose of the

study is to see if it possible to se if there is some resemblance among category of customers. As

consequence, this study is going to have a descriptive research design. To measure impact it is possible

to use frequencies in order to see how many time a particular thing occurs (Churchill and Iacobucci,

2005) and that is what the author is going to perform in this study to see if there is an influence of

demographic factors on customer loyalty programs and on customer loyalty. Concepts of customer

loyalty and customer loyalty programs are already well researched and are going to be the

foundation for this research.

 

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3.3 DATA SOURCES

There are two types of data sources that can be gathered for a research. The differentiation between

them is based on who is collecting the data.

Primary data are collected by the researchers themselves in the aim of responding to a specific

question. This kind of data is time consuming and expensive. Secondary data are collected by

someone else for a purpose but the researcher is going to use them for another purpose or as a

starting point of his/her study. Secondary data are classified into internal and external sources.

Internal sources are when the data are gathered inside a company for example whereas external

sources are collected from outside sources such as Internet or statistics. It is easier and less

expensive to collect secondary data but as they are not collected for the own purpose of the

researcher, it might not fit completely the study or been obsolete. (Bryman and Bell, 2011)

Secondary data such as information about customer loyalty and customer loyalty programs have

been collected as a starting point to this study. Nevertheless, the main source of data is primary

data, gathered by the author, to solve this research problem.

3.4 RESEARCH STRATEGY

No research strategy is better than the other (Bryman and Bell, 2011), but it is important to make

the good choice about the strategy used as it is the essence of the research and will answer the

problematic of the research (Saunders, Lewis and Thornhill, 2009).

According to Yin (2009), there are five types of strategies that can be seen in the table 1:

Experiment, Survey, Archival analysis, History and Case study. The choice between the different

strategies is made according to what the authors are looking for (Ibid.). The second column of the

table 1 shows the question possible that could be researched. The third column is about whether or

not the strategy request control over behavioural events and to finish the last column presents the

strategy focus on contemporary events (Ibid.).

 

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Table 1. Research strategy adopted from Yin (2009) p. 8

Archival analysis and history are often used to gather secondary data (Saunders, Lewis and

Thornhill, 2009). As consequence, they were not interesting for this study as this one involves

primary data. Most of the time experiment is linked to qualitative researches and its aim is to

explore the link and the potential change between different variables (Bryman and Bell, 2011). This

research’s aim is to examine the loyalty programs at the moment present and then not to do a

comparison over different situations, as consequence this possibility was excluded.

The two choices left are case study and survey. Yin (2014) is explaining that a case study is preferred

when: (1) the main research question is focusing on how and why, (2) the author has few or no control

over behavioural events and (3) the focus of the study is contemporary. Case studies are often focusing

on just two or three cases for comparatives purposes and it is hard to generalize those studies to an

entire sector for example (Bryman and Bell, 2011). Because of the purpose of this study, which is to

examine the whole sector of retail industry and their loyalty programs and not just to gather some

information about few companies, the case study research has also been excluded.

Surveys are used when the objective is to present the data with numbers and statistics (Bryman and Bell,

2011). Moreover, it does not require control over behavioural events and focus on contemporary events

(Yin, 2009). This description match well the intention for this study

 

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3.5 DATA COLLECTION METHOD

There are five most common methods for collecting data: surveys, in-depth interviews,

observations, focus groups and contents analysis (Yin, 2014; Bryman and Bell, 2011).

Questionnaires have been the method chosen for quantitative research. Questionnaires are used to

present a population’s attitude and opinion on something thanks to quantitative description of a

sample (Creswell, 2009). It is easier to answer closed questions than open one, as consequences

Bryman and Bell (2011) are recommending to use those first kinds of questions in the

questionnaires as most of the people do not want to answer a question by themselves. Moreover, the

authors are giving more advices on how to run the questionnaire. The design of it need to be easy to

read and to follow and questions need to be totally clear and understandable. A short explanation of

the concepts can be displayed to make it easier for the reader (Ibid.). They also lay emphasis on the

importance of the layout of the questionnaire: the more professional the questionnaire looks, the

more people are going to be disposed to answer the questions. Another way of encouraging people

to respond is to add some rewards or any kind of incitement (Ibid.). Questionnaires allow having

reliable and valid data from a sample of the population within a moderate period of time and with

low costs (Burns, 2003). This is why questionnaire has been chosen for this study and because it

enables to gather a large number of data due to an easy diffusion. The questionnaire in English,

shown in the appendix A, was sent by email, through social medias or has been given by hand to

respondents.

3.6 OPERATIONALIZATION

Operationalization is the process of transforming theory into reality, meaning that the theory

concepts are going to be transformed into measurable concepts (Saunders, Lewis and Thornhill,

2009; Bryman and Bell, 2011). Operationalization is required to be sure that the data collection is done

in a rigorous way (Ibid.) and so ensure the credibility in the outcome of the research (Hartman, 2004).

Hartman (2004) thinks that operationalization should focus on: validity, reliability, usability and

clarity. There are several steps that need to be followed to conduct the operationalization. First, get

the theoretical insights of the concept used in the study (Holme and Krohn, 1997; Hartman, 2004;

Bryman and Bell, 2011) secondly create a conceptual definition of them with the help of previous

research (Hartman, 2004; Bryman and Bell, 2011). The third step is to do an operational definition

(Ibid.), then do an inventory of the potential variables (Holme and Krohn, 1997; Bryman and Bell,

2011), a pre-test is going to be done then and only the accurate variables are going to persist and the

final test is to create the instrument for the collection of data (Bryman and Bell, 2011).

 

  20  

Concepts used for this study in the literature review are going to be inserted in the

operationalization table (Table 2, pp.20). Those concepts have been transformed into measures,

which have been explored before by authors in the field of customer loyalty programs and customer

loyalty (Liu, 2007; Minouni-Chaabane and Volle, 2010; Day, 1984; McIlroy and Barnett, 2000)

3.6.1 OPERATIONALIZATION TABLE

Table 2. Operationalization table (Author’s elaboration) Theoretical concepts

Concept definition Operational definition Questions

Customer loyalty programs

“Loyalty program is defined as a program that allows consumers to accumulate free rewards when they make repeated purchases with a firm.” (Liu, 2007)

A measure that indicates if customers are members of a loyalty program and how often they are using it

Are you a member of a customer loyalty program? How often do you use your loyalty program? What kind of customer loyalty program are you in?

Expectation - Perceived benefits – Monetary saving

« Monetary savings develop from cash-back offers and coupons that participants accumulate while regularly buying the same brand or shopping with the same retailer.” (Minouni-Chaabane and Volle, 2010)

A measure that indicates the degree of importance of monetary saving in the perceived benefits from loyalty programs

I shop at a lower financial cost I spend less I save money

Expectation - Perceived benefits – Exploration

« Trying new or innovative products, satisfying curiosity about events and promotional offers, or seeking information to keep up with new trends represent examples of exploratory behaviours” (Minouni-Chaabane and Volle, 2010)

A measure that indicates the degree of importance of exploration in the perceived benefits from loyalty programs

I discover new products I discover products I wouldn't have discovered otherwise I try new products

Expectation - Perceived benefits – Entertainment

« Programs also enable customers to enjoy unique experiences that they would not have undertaken otherwise, because many organizations offer pleasure-providing incentives, such as

A measure that indicates the degree of importance of entertainment in the perceived benefits from loyalty programs

Collecting points is entertaining Redeeming points is enjoyable When I redeem my points, I feel good at myself

 

  21  

getting to drive a Jaguar for a day or attending an opera.” (Minouni-Chaabane and Volle, 2010)

Expectation - Perceived benefits – Recognition

« Consumers consequently may experience recognition benefits; they may feel like the firm and frontline personnel treat them better than they would treat non-members of the program” (Minouni-Chaabane and Volle, 2010)

A measure that indicates the degree of importance of recognition in the perceived benefits from loyalty programs

They take better care of me I'm treated better than other customers I'm treated with more respect I feel I am more distinguished than other customers

Expectation - Perceived benefits – Social

«The program enhance perceptions of social benefits, such that members consider themselves part of an exclusive group of privileged customers, identify with that group, and share values associated with the brand” (Minouni-Chaabane and Volle, 2010)

A measure that indicates the degree of importance of social in the perceived benefits from loyalty programs

I belong to a community of people who share the same values I feel close to the brand I feel I share the same values as the brand

Loyalty to the program

« A company devises loyalty programs to influence customers' perceptions of status, buying habits, and relationship with the company and thus encourage greater customer loyalty » (Kang and al., 2015).

A measure that show to what extent customers are loyal to their loyalty programs

I like this loyalty program more than other programs. I have a strong preference for this loyalty program. I would recommend this loyalty program to others.

Loyalty to the company

“Perceptions of membership encourage customer-company identification formation. Customers who are loyal to a program tend to develop more embedded relationships with the sponsoring company.” (Kang and al., 2015).

A measure that show to what extent customers are loyal to their company

I say positive things about this company to my friends. I would recommend this company from someone seeking my advice. I encourage friends and family to shop at this company.

3.7 SAMPLING

It is often not realizable to examine a whole population because of time and money; that is why

samples are useful to fix that issue and is used to represent the population (Holme and Solvang,

 

  22  

1997). To define a sampling there are three steps to follow. The first one is to determine the

population that need to be studied, the second one is to define the sampling frame and the last one is

to choose the sample size (Bryman and Bell, 2011). The sample size means to determine how much

people have to answer the questionnaire to reach reliability for the answers (Churchill and

Iacobucci, 2005).

3.8 SAMPLING FRAME

A sampling frame is the entire list of the members of a population that have been selected for the

study (Bryman and Bell, 2011). According to Burns (2003), there are two kinds of sampling: the

sample survey and the census survey. The first kind is used when not the whole population but only

a part is used for the study. The second one is when the entire population is used. (Ibid.)

This study is going to be a sample survey. Empirical data was collected from members of loyalty

programs. Data was collected from customers in different ages, genders, from different marital

status, education and incomes in order to examine the potential differences in the benefits they

expect from loyalty programs and the influence of them on their loyalty to the program and the

company. The author decided to not specify any particular sector for this study to be able to have a

bigger sampling and to be able to have reliable samples in each socio-demographic category of

customers (see Appendix B, p57). Moreover, the focus was into the influence of demographic

factors rather than on the kind of loyalty program. The population is customers of BtoC shops and

the sampling frame is customers who are members of loyalty programs. The sample size is chosen

considering previous researches which had around 150-300 answers when examining loyalty

programs, perceived benefits and customer loyalty programs (Bose and Rao, 2011; Kim and al,

2013; Follin and Fransson, 2013). This study has gathered 344 answers in which 271 are valid; as

consequences the sample size have been respected.

3.9 QESTIONNAIRE DESIGN

The design of the questionnaire is really important for the success of the study. The look of the

survey and its organization, if they are well done, are likely to have a positive impact on the

response rate, as said previously (Bryman and Bell, 2011). It is hard to choose the good questions

for a questionnaire and that is why it is more convenient to use questions or items from already

existing questionnaires or researches. As consequences, items and questions that are relevant for the

purpose of the study should be selected (Burns, 2003).

 

  23  

To be able to create a good questionnaire there are things to remember. First, it is important to not

finishing the questionnaire with important questions. Secondly, it is good to numerate the questions

to be more easily followed by the reader (Bryman and Bell, 2011; Burns, 2003). The questionnaire

also needs to be the clearer possible and be lightened (Burns, 2003). For the formulation of the

question, it is important to remember to always keep the question as simple as possible (Ibid.)

Moreover, authors need to decide what kind of question they are going to use. Closed questions,

open-ended questions or scales questions are the choices authors can have to construct their

questionnaires. Closed questions have fixed answer with two or more options, for example yes or

no. The advantage of them is that it is easy to code them for statistical analysis but their weakness is

the superficiality of the answer. Open-ended questions are questions where interviewees are invited

to answer the question with their own words and so give more information than the closed

questions. Open-ended questions are not possible to predict and it is difficult to code them. Scales

questions are forcing respondents to reply to pick one of the alternatives possible on a fixed-scale.

The most important thing to considerate when creating a scale question is to have alternatives that

express the interviewees’ opinion; answers need to be balanced between a mid-point, for example

neutral, and then the rest of the alternatives, strongly disagree/disagree/agree/strongly agree for

example. (Burns, 2003)

This survey is composed of twelve questions; which are closed questions and scales questions. The

questionnaire is starting with a qualification question about their membership to a loyalty program.

This question is asked to only focus on the people who are part of the sample of this study which

are members of loyalty programs. The author used an online and a paper version of the

questionnaire to be able to reach different group of ages and to send the questionnaire to other

countries.

3.10 DATA ANALYSIS METHOD

3.10.1 PEARSON’S CORRELATION

According to Pallant (2001), the correlation analysis is applied to verify if a linear relationship

between two variables is strong or not. Correlation and causality are different because correlation is

not aimed to show if there is one factor that is causing the other. The results can have a positive or

negative correlation; the results are ranging from -1 to 1. If the result is close to 1 then it is possible

to say that the correlation is strong. If the result is 0 then it means that there is no correlation

between the variables. For the analysis, it is possible to use the guidelines providing by Cohen

(1988)

 

  24  

Figure 2. Correlation guidelines. (Cohen, 1988)

3.10.2 ANOVA ANALYSIS

Anova analysis is a linear model is comparing the mean of different factors. This tool is only

applicable for numeric data (Howell, 2002). The ANOVA-model is used to determine if there is a

significant difference between the means of three or more groups. Those groups needs to be

independent from each other, it means that the participants of the first group are not part of any

other groups (Ibid). When an Anova test is run it is possible to see that there is no significant

different or that at least two groups are. However, it is impossible to know which group is different

from the other. A post hoc test is necessary to be able to know which group is different. (Ibid)

The author decided to run an ANOVA analysis rather than a regression analysis because the

purpose of the study is not to see if a variable have an impact on the other (regression) but to point

out the differences between the independent groups inside a demographic group.

3.11 QUALITY CRITERIA

3.11.1 RELIABILITY

Reliability is the fact of testing if the concepts and the results are reliable and if it is possible to

replicate the study in another context and still have the same results (Bryman and Bell, 2007).

This study is based on previous research with questions and items that have been tested several

times before (Minouni-Chaabane and Volle, 2010; Kang and al., 2015). As consequences, the sources

used for this study are reliable. The questions from the questionnaire and items have been

controlled by the author. It is possible to run a test to measure the reliability of the data that has

been gathered, the Cronbach’s alpha test. The maximum is 1 and if the result of it is between 0.7

and 0.95 then it would be acceptable to say that the results are reliable (Tavakol and Dennick,

2011). If the result is lower than 0.7 can be due to a too low amount of questions or variables that

are too heterogeneous (Ibid.).

 

  25  

Figure 3. Reliability Statistics (Source: SPSS)

Reliability Statistics

Cronbach's Alpha N of Items

,927 47

As seen in Figure 3, Cronbach‟s alpha for this study was 0.927 which shows a high reliability.

Moreover, this study has a total of 271 valid answers (over 344 answers in total) with a good

distributing over the different demographic group (see Appendix B, p57), which enhance the

validity of this study.

3.11.2 VALIDITY

Validity is when the conclusions of the study are making sense compared to the aim intended at the

beginning of the research. (Bryman and Bell, 2007).

It is possible to raise the content validity by asking someone who have some expertise and

knowledge about the subject which is researching about. The aim is to review the questionnaire

before gathering the data. This is why the questionnaire has been reviewed by an expert in

quantitative research at Linnaeus University. Moreover, the questionnaire has been reviewed during

a focus group to be able to improve the quality of the questionnaire.

Authors have to deduce the information they are using in their studies from actual concept research

by other authors in able to be valid (Bryman and Bell, 2011). Those information need to be relevant

for the subject researched. One way to be able to raise the validity is to operationalize the concepts

(Gray, 2009) In this study, the concepts have been operationalized in the table 2.

External validity is occurring when the study and the results can be generalized and it is possible to

do the research again in another context or tested on another group of the population (Ritchie &

Lewis, 2003; Phillipson, 2013). The operationalization table (p. 21) and the Appendix A (p. 54)

have been displayed to help future researchers to research again this speficic topic in another

context.

 

  26  

3.12 SUMMARY

Table 3. Summary table (Author’s elaboration)

Research approach

Deductive Quantitative

Research design

Descriptive

Data sources

Primary

Research strategy

Survey

Data collection method

Questionnaire

Data analysis method

Correlation

Anova

Quality criteria

Validity Reliability

 

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4 EMPIRICAL FINDINGS

4.1 PEARSON’S CORRELATION

Table 4. Pearson’s correlation

Variables Gender Age Education Marital status Professional status Incomes

Expectation Monetary Savings - 0.15* 0.03 0.03 0.06 0.10 0.05 Expectation Exploration - 0.11 0.26** - 0.20** 0.12* - 0.13* 0.17** Expectation Entertainment - 0.06 0.27** 0.03 - 0.02 - 0.17** 0.28** Expectation Recognition 0.05 0.31** - 0.07 0.02 - 0.29** 0.32** Expectation Social 0.12 0.13* - 0.13* 0.18** - 0.13* 0.08 Loyalty to the program - 0.14* 0.19** - 0.06 0.17** - 0.09 0.03 Loyalty to the company - 0.11 0.06 - 0.07 0.24** - 0.09 - 0.08

*. Correlation is significant at the 0.05 level (2-tailed).

**. Correlation is significant at the 0.01 level (2-tailed).

It is possible to see that there are some statistically significant correlations between some variable

of the table. Expectation on exploration is the variables that have the more of statistically significant

correlations. The correlations are significant for age, education, marital status, professional status

and incomes.

For monetary savings, gender has a small negative correlation (-0.15). For exploration, age, marital

status and incomes have positive small positive correlations (0.26; 0.12; 0.17) and education and

professional status have negative small correlations (-0.20; 0.13). For entertainment, age and

incomes have small positive correlations (0.27; 0.28) and professional status have a small negative

correlation (-0.17). For recognition, age and incomes have medium positive correlations (0.31;

0.32) and professional status have a small negative correlation (-0.29). For social, age and marital

status have small positive correlations (0.13; 0.18) and education and professional status have small

negative correlations (-0.13 for both). For loyalty to the program, age and marital status have small

positive correlations (0.19; 0.17) and gender has a small positive correlation. For loyalty to the

company, marital status has a positive small positive correlation (0.24).

Those findings are going to be used afterwards to strengthen or not the results of ANOVA.

 

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4.2 PRESENTATION OF THE RESULTS H1

H0: Socio-demographic factors do not have an impact on customers’ expectation of a loyalty program H1: Socio-demographic factors have an impact on customers’ expectation of a loyalty program 4.2.1 GENDER

Table 5. ANOVA H1 – Gender

Gender Respondents (n=271) Min Max

Anova F

Sig

Mean S.D. 1. Monetary savings 4.16 1.090 1 5 5.996 .015 2. Exploration 2.93 1.313 1 5 3.326 .069 3. Entertainment 3.10 1.38 1 5 .947 .331 4. Recognition 3.08 1.34 1 5 .727 .395 5. Social 2.52 1.32 1 5 3.809 .052

Table 6. LSD Post-hoc H1 - Gender

Gender Mean Female (n=150)

Mean Male (n=121)

Anova F

Monetary savings 4.31 3.98 5.996* Exploration 3.06 2.77 3.326 Entertainment 3.17 3.01 .947 Recognition 3.02 3.16 .727 Social 2.38 2.69 3.809

There was a statistically significant difference between groups as determined by one-way ANOVA

only for monetary saving = (F(1,269) = 5.996, p = .015). A LSD post-hoc test could not been run

because there is only two categories of gender.

4.2.2 AGE

Table 7. ANOVA H1 – Age

Age Respondents (n=271) Min Max

Anova F

Sig

Mean S.D. 1. Monetary savings 4.16 1.090 1 5 2.651 .034 2. Exploration 2.93 1.313 1 5 7.628 .000 3. Entertainment 3.10 1.38 1 5 9.832 .000 4. Recognition 3.08 1.34 1 5 15.531 .000 5. Social 2.52 1.32 1 5 9.937 .000

 

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Table 8. LSD Post-hoc H1 - Age

Age 24 and under (n=65)

25 - 34 (n=45)

35 - 44 (n=71)

45 - 54 (n=48)

55 and older (n=42)

Anova F

LSD tests

Monetary savings 4.08 4.24 4.01 4.58 3.98 2.651* 1,3,5<4

Exploration 2.34 2.67 3.37 2.94 3.38 7.628** 1,3,4<5

Entertainment 2.35 2.96 3.65 3.04 3.55 9.832* 1,2,4<3,5

Recognition 2.45 2.46 3.76 2.98 3.69 15.531* 1,2<3

Social 2.08 2.20 3.28 2.27 2.55 9.937* 3>1,2,4,5 *. The mean difference is significant at the 0.05 level. **. The mean difference is significant at the 0.01 level.

For all the different expectations there was a statistically significant difference between groups as

determined by one-way ANOVA: Monetary savings = (F(4,266) = 2.651, p = .034); Exploration =

(F(4,266) = 7.628, p = .000); Entertainment = (F(4,266) = 9.832, p = .000); Recognition =

(F(4,266) = 15.531, p = .000) and Social = (F(4,266) = 9.937, p = .000). A LSD post-hoc test

revealed some age group were significally higher or lower than others, in the table in bold.

4.2.3 EDUCATION

Table 9. ANOVA H1 – Education

Education Respondents (n=271) Min Max

Anova F

Sig

Mean S.D. 1. Monetary savings 4.16 1.090 1 5 3.505 .016 2. Exploration 2.93 1.313 1 5 3.896 .009 3. Entertainment 3.10 1.388 1 5 1.748 .158 4. Recognition 3.08 1.347 1 5 1.192 .313 5. Social 2.52 1.324 1 5 1.590 .192 Table 10. LSD Post-hoc H1 - Education

Education Grammar school (n=7)

High school or equivalent (n=31)

Trade/technical school (n=26)

Postgraduated degree (n=207)

Anova F

LSD tests

Monetary savings 4.57 4.16 3.54 4.23 3.505* 1,2,4>3 Exploration 3.86 3.35 3.31 2.79 3.896** 1,2>4 Entertainment 3.71 2.97 2.62 3.16 1.748

Recognition 3.50 3.11 3.48 3.01 1.192 Social 3.14 2.84 2.69 2.43 1.590

 

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*. The mean difference is significant at the 0.05 level. **. The mean difference is significant at the 0.01 level.

For monetary savings and exploration there was a statistically significant difference between groups

as determined by one-way ANOVA: Money savings = (F(3,267) = 3.505, p = .016) and Exploration

= (F(3,267) = 3.896, p = .009). A LSD post-hoc test revealed some education group were

significally lower than others, in the table in bold.

4.2.4 MARITAL STATUS

Table 11. ANOVA H1 – Marital status

Marital status Respondents (n=271) Min Max

Anova F

Sig

Mean S.D. 1. Monetary savings 4.16 1.090 1 5 4.791 .003 2. Exploration 2.93 1.313 1 5 7.207 .000 3. Entertainment 3.10 1.388 1 5 3.093 .028 4. Recognition 3.08 1.347 1 5 8.781 .000 5. Social 2.52 1.324 1 5 6.296 .000 Table 12. LSD Post-hoc H1 – Marital status

Marital status Married (n=108)

Single (n=97)

Divorced/widowed/Separated (n=31)

Domestic partner (n=35)

Anova F

LSD tests

Monetary savings 4.24 3.99 3.84 4.69 4.791** 4>1,2,3 Exploration 3.02 2.52 3.16 3.60 7.207** 2<1,3,4 Entertainment 3.31 2.76 3.32 3.20 3.093* 2<1,3 Recognition 3.32 2.55 3.60 3.33 8.781** 2<1,3,4 Social 2.43 2.24 3.23 2.97 6.296** 1,2<4,3

*. The mean difference is significant at the 0.05 level. **. The mean difference is significant at the 0.01 level.

For all the different expectations there was a statistically significant difference between groups as

determined by one-way ANOVA: Monetary savings = (F(3,267) = 4.791, p = .003); Exploration =

(F(3,267) = 7.207, p = .000); Entertainment = (F(3,267) = 3.093, p = .028); Recognition =

(F(3,267) = 8.781, p = .000) and Social = (F(3,267) = 6.296, p = .000). A LSD post-hoc test

revealed some age group were significally higher or lower than others, in the table in bold.

 

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4.2.5 PROFESSIONAL STATUS

Table 13. ANOVA H1 – Professional status

Professional status Respondents (n=271) Min Max

Anova F

Sig

Mean S.D. 1. Monetary savings 4.16 1.090 1 5 2.013 .077 2. Exploration 2.93 1.313 1 5 6.023 .000 3. Entertainment 3.10 1.388 1 5 2.845 .016 4. Recognition 3.08 1.347 1 5 6.293 .000 5. Social 2.52 1.324 1 5 2.700 .021 Table 14. LSD Post-hoc H1 – Professional status

Professional status

Employed full-time (n=137)

Employed part-time (n=32)

Unemployed (n=13)

Retired (n=10)

Student (n=70)

Other (n=9)

Anova F

LSD tests

Monetary savings 4.02 4.50 3.92 4.50 4.20 4.78 2.013 2,6>1 Exploration 3.01 3.16 3.31 4.30 2.36 3.33 6.023** 5<1,2,3,4,6 Entertainment 3.32 2.94 3.38 3.40 2.61 3.33 2.845* 5<1 Recognition 3.46 2.88 3.00 3.35 2.43 2.89 6.293** 5<1,4 Social 2.57 2.84 3.00 3.20 2.16 2.00 2.700* 5<1,2,3,4

*. The mean difference is significant at the 0.05 level. **. The mean difference is significant at the 0.01 level. For all the different expectations, except for monetary savings there was a statistically significant

difference between groups as determined by one-way ANOVA: Exploration = (F(5,265) =

6.023, p = .000); Entertainment = (F(5,265) = 2.845, p = .016); Recognition = (F(5,265) =

6.293, p = .000) and Social = (F(5,265) = 2.700, p = .021). A LSD post-hoc test revealed some age

group were significally higher or lower than others, in the table in bold.

4.2.6 INCOMES

Table 15. ANOVA H1 – Incomes

Incomes Respondents (n=271) Min Max

Anova F

Sig

Mean S.D. 1. Monetary savings 4.16 1.090 1 5 .507 .603 2. Exploration 2.93 1.313 1 5 6.639 .002 3. Entertainment 3.10 1.388 1 5 11.404 .000 4. Recognition 3.08 1.347 1 5 20.975 .000 5. Social 2.52 1.324 1 5 4.109 .017

 

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Table 16. LSD Post-hoc H1 – Incomes

Incomes >1500€ (n=91)

1500 - 2499 € (n=61)

>2500€ (n=118)

Anova F

LSD tests

Monetary savings 4.12 4.08 4.24 .507 Exploration 2.54 3.25 3.06 6.639** 1<2,3

Entertainment 2.62 3.02 3.50 11.404** 3>1,2 Recognition 2.38 3.48 3.41 20.975** 1<2,3 Social 2.26 2.89 2.53 4.109* 1<2

*. The mean difference is significant at the 0.05 level. **. The mean difference is significant at the 0.01 level. For all the different expectations, except for monetary savings there was a statistically significant

difference between groups as determined by one-way ANOVA: Exploration = (F(5,265) =

6.023, p = .000); Entertainment = (F(5,265) = 2.845, p = .016); Recognition = (F(5,265) =

6.293, p = .000) and Social = (F(5,265) = 2.700, p = .021). A LSD post-hoc test revealed some age

group were significally higher or lower than others, in the table in bold.

4.3 CUSTOMER LOYALTY

H0: Socio-demographic factors do not have an impact on customer loyalty

H2: Socio-demographic factors have an impact on customer loyalty

4.3.1 GENDER

Table 17. ANOVA H2 – Gender

Gender Respondents (n=271) Min Max

Anova F

Sig

Mean S.D.

1. Loyalty to the program 3.55 .838 1 5 5.545 .019 2. Loyalty to the company 3.49 .057 1 5 3.243 .073

Table 18. LSD Post-hoc H2 – Gender

Gender Mean Female (n=150)

Mean Male (n=121)

Anova F

1. Loyalty to the program 3.66 3.42 5.545* 2. Loyalty to the company 3.58 3.37 3.243

 

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*. The mean difference is significant at the 0.05 level. **. The mean difference is significant at the 0.01 level.

There was a statistically significant difference between groups as determined by one-way ANOVA

only for Loyalty to the program = (F(1,269) = 5.545, p = .019). A LSD post-hoc test could not been

run because there is only two categories of gender.

4.3.2 AGE

Table 19. ANOVA H2 – Age

Age Respondents (n=271) Min Max

Anova F

Sig

Mean S.D.

1. Loyalty to the program 3.55 .838 1 5 2.824 .025 2. Loyalty to the company 3.49 .057 1 5 1.073 .370

Table 20. LSD Post-hoc H2 – Age

Age 24 and under (n=65)

25 - 34 (n=45)

35 - 44 (n=71)

45 - 54 (n=48)

55 and older (n=42)

Anova F

LSD tests

1. Loyalty to the program 3.29 3.59 3.54 3.67 3.79 2.824* 1<4,5 2. Loyalty to the company 3.36 3.59 3.51 3.36 3.67 1.073

*. The mean difference is significant at the 0.05 level. **. The mean difference is significant at the 0.01 level.

There was a statistically significant difference between groups as determined by one-way ANOVA

only for Loyalty to the program = (F(4,266) = 2.824, p = .025). A LSD post-hoc test revealed the

age group of 24 and under, in the table in bold, was significally lower than the group of 45 – 54

(3.67 ± .889) and 55 and older (3.79 ± .993).

4.3.3 EDUCATION

Table 21. ANOVA H2 – Education

Education Respondents (n=271) Min Max

Anova F

Sig

Mean S.D.

1. Loyalty to the program 3.55 .838 1 5 2.505 .060

 

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2. Loyalty to the company 3.49 .057 1 5 3.684 .013

Table 22. LSD Post-hoc H2 – Education

Education Grammar school (n=7)

High school or equivalent (n=31)

Trade/technical school (n=26)

Postgraduated degree (n=207)

Anova F

LSD tests

1. Loyalty to the program 4.29 3.58 3.32 3.55 2.505 1>2,3,4 2. Loyalty to the company 4.29 3.62 3.08 3.49 3.684* 3<1,2<4

*. The mean difference is significant at the 0.05 level. **. The mean difference is significant at the 0.01 level.

There was not a statistically significant difference between groups as determined by one-way

ANOVA for Loyalty to the program (F(3,267) = 2.505, p = .060) except for the category of

Grammar school.

There was a statistically significant difference between groups as determined by one-way ANOVA

for Loyalty to the company (F(3,267) = 2.505, p = .060). Loyalty to the program = (F(3,267) =

3.684, p = .013). A LSD post-hoc test revealed the group of Grammar school was significally

higher than the group of Trade/Technical school (3.08 ± 1.060) and Postgraduated degree (3.49 ±

.935).

Moreover, the group of Trade/Technical school was significally lower than Grammar School (4.29

± .678), High School (3.62 ± .744) and Postgraduated degree (3.49 ± .935).

4.3.4 MARITAL STATUS

Table 23. ANOVA H2 – Marital status

Marital status Respondents (n=271) Min Max

Anova F

Sig

Mean S.D.

1. Loyalty to the program 3.55 .838 1 5 3.743 .012 2. Loyalty to the company 3.49 .057 1 5 5.670 .001

 

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Table 24. LSD Post-hoc H2 – Marital status

Marital status Married (n=108)

Single (n=97)

Divorced/widowed/ Separated (n=31)

Domestic partner (n=35)

Anova F

LSD tests

1. Loyalty to the program 3.48 3.44 3.71 3.93 3.743* 4>1,2 2. Loyalty to the company 3.32 3.43 3.63 4.03 5.670** 4>1,2

*. The mean difference is significant at the 0.05 level. **. The mean difference is significant at the 0.01 level. There was a statistically significant difference between groups as determined by one-way ANOVA

for Loyalty to the program and Loyalty to the company.

Loyalty to the program = (F(3,267) = 3.743, p = .012) and Loyalty to the company = (F(3,267) =

5.670, p = .001). A LSD post-hoc test revealed the group of Domestic partner (3.93 ± .828/ 4.03 ±

.887) was significally higher than the group of married for both kind of loyalty (3.48 ± .866/ 3.32 ±

.973) and Single (3.44 ± .8.16/ 3.43 ± .882).

4.3.5 PROFESSIONAL STATUS

Table 25. ANOVA H2 – Professional status

Professional status Respondents (n=271) Min Max

Anova F

Sig

Mean S.D.

1. Loyalty to the program 3.55 .838 1 5 2.316 .044 2. Loyalty to the company 3.49 .057 1 5 3.141 .009

Table 26. LSD Post-hoc H2 – Professional status

Professional status

Employed full-time (n=137)

Employed part-time (n=32)

Unemployed (n=13)

Retired (n=10)

Student (n=70)

Other (n=9)

Anova F

LSD tests

1. Loyalty to the program 3.64 3.39 3.33 4.17 3.40 3.52 2.316* 4>1,2,3 2. Loyalty to the company 3.63 3.13 3.10 4.07 3.39 3.30

3.141** 4>1>2,3

*. The mean difference is significant at the 0.05 level. **. The mean difference is significant at the 0.01 level.

 

  36  

There was a statistically significant difference between groups as determined by one-way ANOVA

for Loyalty to the program and Loyalty to the company.

Loyalty to the program = (F(5,265) = 2.316, p = .044) and Loyalty to the company = (F(5,265) =

3.141, p = .009). A LSD post-hoc test revealed the professional group of Retired (4.17 ± .689/ 4.07

± .872) was significally higher for both kind of loyalty than the group of Employed full time (3.64

± .928/ 3.63 ± .961), employed of part-time (3.39 ± .640/ 3.13 ± 1.015) and Unemployed (3.33 ±

.680/ 3.10 ± .762)

4.3.6 INCOMES

Table 27. ANOVA H2 – Incomes status

Incomes Respondents (n=271) Min Max

Anova F

Sig

Mean S.D.

1. Loyalty to the program 3.55 .838 1 5 .602 .549 2. Loyalty to the company 3.49 .057 1 5 .962 .384 Table 28. LSD Post-hoc H2 – Incomes

Incomes >1500€ (n=91)

1500 - 2499 € (n=61)

>2500€ (n=118)

Anova F

LSD tests

1. Loyalty to the program 3.49 3.64 3.56 .602

2. Loyalty to the company 3.57 3.54 3.40 .962

There were not statistically significant differences between groups as determined by one-way

ANOVA for Loyalty to the program and Loyalty to the company concerning Incomes.

5 ANALYSIS

5.1 CUSTOMERS’ EXPECTATIONS ABOUT LOYALTY PROGRAMS

As seen in the theoretical framework, there were not a lot of theory or studies about the influence on

socio-demographic factors on the expectations of customers concerning their loyalty programs.

 

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The only factor that has been studied is the difference among gender about recognition and social

aspect of loyalty programs (Schwartz and Rubel, 2005).

5.1.1 GENDER

Schwartz and Rubel (2005) have pointed out that men are seeking more than women for social

status, prestige, dominance and achievement. In fact, women are less interested in the elite grade of

a loyalty program and the social status that is conveyed by those kinds of status.

It is possible to support the statement made by Schwartz and Rubel (2005) with the results of this

study. In fact, it is possible to see that men attach more importance to the recognition and social

benefits than women (3.16 vs. 3.02 and 2.69 vs. 2.38). Recognition is the second benefits the most

important for men after monetary savings, which show its importance for them. However, it is

possible to qualify the results for social benefits: in fact, they are the last benefit in term of

importance. As consequences, men value more social benefits than women but those benefits are

secondary.

Moreover, this study is showing that there is a significally difference between women and men for

the monetary savings’ expectation. Women are valuing more this benefits than men, on average

monetary savings has an importance of 4.31 over 5 compare to 3.98 for men. Women have an

average higher on the expectations of Exploration (3.06 vs. 2.77) and Entertainment (3.17 vs. 3.01).

5.1.2 AGE

Age is significant for all the expectations of customers. One of the most significant differences can

be seen for the age group of 24 and under and the following age group, from 25 to 34. In fact, those

age groups are reacting similarly to the different benefit they can expect from their customer loyalty

programs. They have the lower rates in every category of expectation, except monetary savings,

which are important for them. As consequence, they are not expecting to have any benefits from a

loyalty program except having some discounts or some specials prices.

The age group from 35 to 44 are more sensitive to recognition and social benefits than other age

groups, respectively 3.76 and 3.28 over 5. Nevertheless, comparatively those benefits are not the

one they put first in term of expectations from a loyalty program; which is monetary savings (4.01

over 5).

Monetary savings is a really important expectation no matter which age the respondents are but this

expectation has the highest rate for the age group of 45 – 54 years old.

 

  38  

The last group has a high interest in exploration, they expect from a loyalty program to discover and

try new products they would not have used otherwise.

5.1.3 EDUCATION

Education is not significant for several expectations: entertainment, recognition and social.

Monetary savings has a high rate in every category of education groups (between 3.54 and 4.57

over 5). The group who is expecting the more from monetary savings benefits is the group, which

has the lower level of education, Grammar School. The highest level of education, postgraduated

level, is not the category that has the lowest expectation in monetary savings; in fact they come just

after the last category with a rate of 4.23. The lowest rate is for those from trade and technical

school.

For the expectations of exploration, the rate is inversely proportional to the level of education. The

higher the level of education is, the lower the exploration expectations are. The respondent with a

postgraduated diploma have an expectation of exploration of 2.79 over 5, those from trade and

technical school have a rate of 3.31, those from high school have a rate of 3.35 and those from

grammar school have a 3.86 rate.

5.1.4 MARITAL STATUS

Marital status is significant for all the expectation from customers concerning their loyalty

programs.

Single people have the lowest rate in every category of expectations except monetary savings. In

fact, they tend to think that exploration (2.52), entertainment (2.76), recognition (2.55) and social

(2.24) are not important.

The highest rate for monetary savings and exploration is made by the domestic partners category

(3.60) and the highest rate for entertainment, recognition and social are made by the category of

divorced, separated and widowed (respectively 3.32, 3.60 and 3.23).

5.1.5 PROFESSIONAL STATUS

Professional status is, as marital status, significant for all of the expectations from customers.

The most interesting category of profession is the students, which have the lowest rate in almost

every kind of expectation. In fact, they do not consider exploration (2.36), entertainment (2.61),

recognition (2.43) and social (2.16) important in the benefits they are expecting from their loyalty

 

  39  

programs. Retired people have the highest rate on several expectations. They attach importance

especially to exploration (4.30) and also entertainment (3.40) and social (3.20).

5.1.6 INCOMES

Incomes are significant for every expectation except monetary savings. The category of people who

are earning less than 1500€ by months are the category that have the lowest rate for every

significant expectations. They do not think that exploration, entertainment, recognition and social

are important in term of benefits they can expect from a customer loyalty program.

On the other hand, the group of people who are earning between 1500 and 2499€ have the highest

rate for exploration (3.25), recognition (3.48) and social (2.89).

5.1.7 SUMMARY

It is possible to conclude that demographic factors are significant when it comes to the different

expectations of customers.

Table 29. Summary of significant correlation H1 (Author’s elaboration)

Gender Age Education Marital status Professional status Incomes

Monetary savings X Exploration X X X X X Entertainment X X X Recognition X X X Social X X X X

Table 30. Summary of significant differences H1 (Author’s elaboration)

Gender Age Education Marital status Professional status Incomes Monetary savings X X X X Exploration X X X X X Entertainment X X X X Recognition X X X X Social X X X X

Age and marital status are significant for every category of expectations. However, gender cannot

be strengthened by the correlation analysis for age and marital status for monetary savings and it is

the same for entertainment and recognition with marital status.

 

  40  

Professional and incomes are significant for every category except monetary savings. It is possible

to strengthen this statement, except for incomes and social, by looking at the correlation table.

Education and Gender are the demographic factors, which have less significance over customers’

expectations. Education is significant for monetary savings and exploration. Nevertheless, the

correlation analysis is showing a different view, by showing that there is a correlation between

education and exploration and social. Gender is only significant for monetary savings, which is

strengened by the correlation analysis.

5.2 CUSTOMER LOYALTY

5.2.1 GENDER

According to previous studies, it has been shown that females tend to be more loyal than male

(Kuruvilla et al., 2009; Helgesen and Nesset, 2010), even if it is not true in every situation as it

depends also on what they are buying (Melnyk et al., 2009). In this study, it is possible to see that

females are more loyal to their loyalty program (3.66 over 5 vs. 3.42 for men) and to the company

(3.58 over 5 vs. 3.37) than men.

5.2.2 AGE

According to previous research it has been demonstrated that age has a moderating effect on loyalty

(Baumann, Burton, and Elliott 2005; Homburg and Giering 2001). Authors do not have the same

opinion about older consumers: some authors are saying that they are more loyal when it comes to

automobile and banking (Ibid.) and some others show that old consumers tend to not be loyal

because they have more free time (East et al. 1995; East et al. 2000). This study is demonstrating

that older consumers are here the most loyal group to the loyalty program (3.79) and to the

company (3.67).

Wright and Sparks (1999) and McGoldrick and Andre (1997) have shown that the 35-44 age group

are the most loyal. This study is not confirming this statement. In fact, the results are showing that

the age group of 35-44 years old is the second less loyal group after the group of 24 years old

concerning loyalty to programs and to company.

5.2.3 EDUCATION

Previous researches tend to show that a higher level of education leads to a lower level of loyalty

(Chance and French 1972; Mittal and Kamakura 2001; Murphy 1978) because they tend to gather

 

  41  

more information before making a decision (Capon and Burke 1980). This study is showing the

opposite of the previous statement. In fact, the lowest category of education, grammar school, is the

one that is the most loyal for both kind of loyalty (4.29 over 5 for both of them). The next most

loyal category is High School (3.58 and 3.62) and then comes the Postgraduated degree’s category

with a rate of 3.55 and 3.49. Those rate are still high on the scale of 1 to 5 so those three category

tend to be loyal to their loyalty programs and companies.

5.2.4 MARITAL STATUS

Marital status is significant for the two kinds of loyalty. Domestic partner’s category has the highest

rate of loyalty for the program and for the company, with rates of 3.93 over 5 for the loyalty to the

program and 4.03 for the loyalty to the company.

Married people are the less loyal concerning their loyalty to the company (3.32) and single people

are showing the lowest rate of loyalty for their programs (3.44). However, those results are still high

if compared to the scale.

5.2.5 PROFESSIONAL STATUS

Professional status is also significant for the two kinds of loyalty. Retired people are showing a

significant difference compared to the other categories. They have the highest rate of loyalty for

their programs and for their company. This is not validating the statement that older consumers,

here retired people, are less loyal (East et al. 1995; East et al. 2000). Unemployed people are

showing the less loyalty to their programs and to the companies (3.33 over 5 and 3.10).

5.2.6 INCOMES

A lot of researches have demonstrated that income have a negative impact on customer loyalty

(Crask and Reynolds 1978; Korgaonkar, Lund, and Price 1985; Zeithaml 1985). Customers who are

earning more have fewer shopping restriction and so tend to switch of brand easier (Sharir 1974;

Zeithaml 1985). However, this statement is not unanimous (Keaveney and Parthasarathy, 2001)

This study is showing that there is no statistically significant difference between the different

incomes category when it comes to loyalty. The different means by themselves are showing a

contrasted point of view. In fact, concerning the loyalty to the program, the highest income category

is not the most unloyal; they have a rate of 3.56; which is showing a tendency of being loyal.

 

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Concerning the loyalty to the company, they are the less loyal compared to the others categories.

However, this statement can be qualified as they still have a rate of 3.40; which is showing a

tendency of being loyal rather than the opposite.

5.2.7 SUMMARY

It is possible to conclude that demographic factors, at the exception of incomes, are significant

when it comes to the loyalty to their customer loyalty programs or to their companies.

Table 31. Summary of significant correlations H2 (Author’s elaboration)

Gender Age Education Marital status

Professional status Incomes

Loyalty to the program X X X Loyalty to the company X

Table 32. Summary of significant differences H2 (Author’s elaboration)

Gender Age Education Marital status Professional status Incomes Loyalty to the program X X X X Loyalty to the company X X X

Gender, age and education are significant all for only one kind of loyalty: gender and age for the

loyalty of the program and education is significant for the loyalty to the company. The correlation

analysis is only strengthening that gender and age for the loyalty to the program. There is no

correlation between loyalty to the company and education.

Marital and professional statuses are both significant for the two kind of loyalty. The analysis of

correlation is strengthening the relation between marital status and the two kind of loyalty but it

does not show any correlation for professional status.

 

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6 CONCLUSION

The aim of this study was to determine if socio-demographic factors are influencing the

expectations and loyalty of customers and in which way. Gender, age, education, marital status,

professional status and income have been tested to see if there were some significant differences

between each category concerning customers’ expectation and loyalty to their loyalty programs and

companies.

As a conclusion it is possible to say that all those socio-demographic factors have an influence on at

least one of the expectations of customers concerning their loyalty programs.

Age and marital status are the factors that are influencing every expectation of customers and

professional status and incomes for every expectation except money savings. As consequences,

those factors are really important for a company to look at when they start a loyalty program or

when they try to improve it. In fact, for those factors, customers are not expecting the same and it is

important to be aware of those differences to increase customers’ satisfaction.

Concerning customers’ loyalty not all of the factors have an influence. Incomes are different from

the others because it did not influence customers’ loyalty to the program and to the company. The

others factors are important to take into consideration, as they influence at least of one the loyalty.

7 DISCUSSION

7.1 LIMITATION

Two limitations are time and the number of respondents. Concerning the number of responses, it

could be said that 271 answers is too low to make general conclusions. This number could have

been better if time was not a limitation for this research.

The sample size of this study was really broad to be able to gather a large number of respondents on

every demographic category, this could be seen as a limitation because the sample size could have

been narrowed to increase the reliability and validity of the results.

 

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7.2 MANAGERIAL IMPLICATIONS

The results of this study are showing the importance of the personalization of the loyalty programs.

All the customers are not reacting or expecting the same concerning their loyalty programs and are

more or less loyal according to their socio-demographic factors. The advantage of loyalty programs

is that it is possible to obtain those information when the customer is joining. They can then create

some promotional campaigns that are focusing on different expectations in accordance with the

inclination of each category. An efficient Customer Relationship Management is necessary to be

able to use all the information gathered by the use of a loyalty program.

Moreover, in the Appendix C (p. 58) the author has shown the difference between the expectations

of the customers compared to what they really have. This is interesting to take an interest in those

differences because it helps managers to know where to work on firstly. Here, is it possible to see

that in general customers are satisfied, they have what they were expecting or even more. However,

there is one expectation where customers are not satisfied, 61% of the respondent have shown that

they their expectation for shopping at a lower cost is higher than what they really have. To reduce

this dissatisfaction it could be interesting for managers to increase the number of campaigns with a

focus of promoting discounts or reductions thanks to their loyalty programs.

7.3 FUTURE RESEARCH

The cultural context has not been approach in this study. It is possible that culture has an impact on

the expectations of customers. Future researches could focus on the cultural impact on the

expectations of customers and see for example the differences between developed countries and

developing countries.

In addition, rewards have also not been the subject of this thesis even if it is one of the expectations

of customers. For the future research, it would be good to analyse the influence of the socio-

demographic factors on the expectation of type of rewards and the frequency of them and if it

impacts their loyalty.

Moreover, this thesis was not focusing on one kind of loyalty program but rather on loyalty

programs in general. In fact, in Appendix D and E (p. 59), the author has displayed the results of

customers’ expectations and loyalty according to which sector they have a loyalty program in. As

conclusion, it is possible to say that for certain kind of loyalty programs, the expectations are not

the same and it is the same for loyalty. As consequence, results could be different for impact of

demographic factors if the focus was just on one kind of loyalty programs. Future researches should

 

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focus in a particular sector to examine the influence of socio-demographic factors for those

particular loyalty programs and also on customer loyalty. Those researches could increase the

knowledge of managers in those specific areas and could let them take better initiatives and actions.

 

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Appendix Appendix A – Questionnaire

 

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Appendix B - Presentation of the demographic factors (SPSS)

Frequency Pourcentage Gender Male 170 49,4 Female 174 50,6 Total 344 100 Age 24 and under 101 29,4 25-34 71 20,6 35-44 77 22,4 45-54 50 14,5 55 and over 45 13,1 Total 344 100 Education Grammar school 12 3,5 High school or equivalent 49 14,2 Trade/Technical school 32 9,3 Post graduated degree 251 73 Total 344 100 Marital status Married 120 34,9 Single 147 42,7 Divorced/widowed/Separated 33 9,6 Domestic partner 44 12,8 Total 344 100 Professional status Employed full-time 158 45,9 Employed part-time 34 9,9 Unemployed 22 6,4 Retired 14 4,1 Student 101 29,4 Other 15 4,4 Total 344 100 Incomes <1500€ 132 38,4 1500 - 2499 € 78 22,7 >2500€ 134 39 Total 344 100

 

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Appendix C – Satisfaction (Author’s elaboration)

 

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Appendix D – Customers’ expectation according to their loyalty programs (Author’s elaboration)

Appendix E – Customer loyalty according to their loyalty programs (Author’s elaboration)