THE IMPORTANCE OF CUSTOMER EXPERIENCE
IN THE ELECTRONICS RETAIL INDUSTRY
THE IMPORTANCE OF CUSTOMER EXPERIENCE
IN THE ELECTRONICS RETAIL INDUSTRY
University of Groningen
Faculty of Economics and Business Master thesis Business Administration Specialization: Marketing Management & Marketing Research September 2011
1st supervisor: J.E.M. van Nierop 2nd supervisor: Prof. Dr. P.C. Verhoef
Author Lieneke Janzen Oostersingel 32 9711 XD Groningen lieneke_janzen@hotmail.com 06-53891298 Student number: 1651536 Company Store Support
Management Summary
In the current market situation competitive advantages are getting more important. Many researchers state that competitive advantage can be reached by a stronger focus on the customer. Therefore, customer experience is becoming important for companies.
This thesis is conducted on behalf of the company Store Support. The objective of this thesis is to obtain understanding about which factors influence customer experience and to what extent these factors influence customer experience. Furthermore, the goal of this thesis is to find out what the influence of customer experience is on customer satisfaction and on turnover. In addition, the moderating role of income, gender and purpose of shopping on the relation between a factor and customer experience is investigated. The research question is therefore: ‘Which factors, and to what extent, play a role with customer experience and to what extent do customer experience and customer satisfaction influence turnover?’
Literature review revealed that customer experience consists of a direct and indirect part. In this thesis only the direct part of customer experience is investigated, which takes place during the visit of the store. Four factors that influence customer experience are found in the literature, namely price, service, store atmosphere and assortment. Where service consist of four components (reliability, responsiveness, assurance and empathy) and store atmosphere of two (ambient conditions of the store and design).
To be able to answer the research question, data is collected at three electronics stores in Utrecht by asking customers to fill in a questionnaire when they left the store. In total the research has a sample size of 287 respondents. On this sample several descriptive analyses are performed to show differences between the three stores and between the group that had contact with an employee (service) and did not have contact with an employee (no service). For the further analyses the three stores are pooled, because no significant difference was found between the three stores.
When performing a regression analysis on the whole model, with all the factors and their components and the moderating effects included, only responsiveness of the employee (service), design of the store (store atmosphere) and assortment show an effect on customer experience. All other variables do not show an effect on customer experience.
Furthermore, a positive relation between customer satisfaction and customer experience is proved. Unfortunately, no evidence is found for the relation between customer experience and turnover and customer satisfaction and turnover.
The results have several managerial implications for electronics stores. They should focus on the responsiveness of the employee, employees should act quickly and should be willing to help. Furthermore, the layout of the store should be clear and easy. It is important for the store to gain good customer experience in order to achieve positive customer satisfaction.
The managerial implications for Store Support are that at least one question each about the following subject should be included in the questionnaire for mystery shopping: the responsiveness of the employee, the design of the store, and the perceived assortment size. Furthermore, this thesis provides evidence for (new) clients that investing in service is important, because it leads to better customer experience, which on his turn leads to a better customer satisfaction.
Preface
This Master thesis is the conclusion of the Master Business Administration with a specialization in Marketing Management and Marketing Research. This thesis demonstrates the knowledge that I gained during my Bachelor and Master study. I would like to take the opportunity to thank a number of people who have contributed to the conclusion of this Master thesis.
First of all I would like to thank Store Support for the opportunity to conduct this research. Special thanks to my supervisor A. van Hijum who made this possible and introduced the subject to me. His enthusiasm about customer experience was infectious. Furthermore, I would like to thank A. van Hijum and M. van Loenen for their advice, feedback and interest in my thesis during the whole process.
I would like to thank my supervisor dr. J.E.M van Nierop for his insights, feedback and advice regarding my thesis. Furthermore, I would like to thank my second supervisor prof. dr. P.C. Verhoef for his final feedback.
Furthermore, I would thank my parents and brother for their unconditional support and trust during my whole study and especially in these final months. Next, I would like to thank my boyfriend, who supported and encouraged me during the whole process. And finally I want to thank my friends for their love and support during the years that I studied in Groningen.
Table of contents
1. Introduction ... 1
1.1 Introduction of the company ... 1
1.2 Background of the problem ... 2
1.3 Problem statement ... 4
1.4 Relevance ... 5
1.5 Structure of the thesis ... 6
2. Theoretical framework ... 7
2.1 Customer experience ... 7
2.2 Factors that influence customer experience ... 9
2.2.1 Price... 9 2.2.2 Service ... 10 2.2.3 Store atmosphere ... 12 2.2.4 Assortment ... 14 2.3 Customer satisfaction... 15 2.4 Moderators ... 18 2.4.1 Income ... 18 2.4.2 Gender ... 18 2.4.3 Purpose of shopping... 19 2.5 Conceptual framework ... 21 3. Research design ... 23 3.1 Research method ... 23 3.2 Data collection ... 26 3.3 Plan of analysis ... 28 4. Results ... 32 4.1 Descriptive analysis ... 32 4.2 Factor analysis ... 36 4.3 Pooling issues ... 38 4.4 Regression analysis ... 38 4.4.1 Customer experience ... 39 4.4.2 Customer satisfaction ... 42 4.4.3 Turnover ... 42 4.5 Predictive validity ... 43
5. Conclusions and recommendations ... 48
5.1 Conclusions ... 48
5.2 Managerial implications ... 52
5.3 Limitations and suggestions for further research ... 54
References ... 56
Appendix 1: Questionnaire ... 62
1. Introduction
In this chapter, the introduction of this master thesis is given. First, the company Store Support is introduced, as this research is conducted on behalf of this organization. Second, background information on the problem is described. Third, the central problem statement and the deduced research question and sub questions are discussed. Fourth, the scientific and practical relevance of this thesis is explained. Finally, the structure of the rest of this thesis is outlined.
1.1 Introduction of the company
This research is conducted on behalf of the company Store Support, a commercial external party specialized in mystery shopping and customer satisfaction research. Store Support was founded in 2004. The company Store Support investigates to what extent the processes of a company are customer oriented, sales driven and they investigate how customers experience the company. They use the following tools to test this: mystery shopping, mystery calling and mystery e-mailing. In the next paragraph the procedure of mystery shopper is explained. Store Support has clients in eight different sectors of industry, being: retail, telecommunication, government (town), banks, insurance companies, care sector, public utilities and automotive.
Mystery shopping is a form of participant observation. It is a tool to get more insight in the experiential nature of service (Wilson 2001). Mystery shopping is done by specially trained people, called mystery shoppers. A mystery shopper visits a store as an ordinary customer and checks the service standard on several aspects, which are on forehand concurred with the client company (Morrison et al. 1997). In advance the mystery shopper receives a detailed briefing in which points of attention are stated and in some cases a specific scenario is described to which the mystery shopper has to behave (Wilson 1998). After the visit the mystery shopper fills in a questionnaire in which the received service is discussed.
to increase their service level, increase the number of clients, diminish churn, increase turnover per customer and to increase profit.
1.2 Background of the problem
Mystery shopping exposes the level of service that is delivered in a store. The experience in the store, based on the service but also on the store itself and maybe other variables, forms a customer experience. Therefore, a closer look at customer experience and some examples of companies that look at customer experience are discussed below. Furthermore, customer experience is part of customer satisfaction. As such, also customer satisfaction will be discussed below.
Customer experience
In the current market situation competitive advantages are getting more important. Modern customers have more choice than ever before, like more channels and more products (Meyer and Schwager 2007). However, how does a company develop a competitive advantage? Many researchers state that competitive advantage can be reached by a stronger focus on the customer (e.g. Woodruff 1997, Gentile et al. 2007).
It is important to know how a customer experiences a shopping trip, so the trip can be made as pleasant as possible. For companies this means that they need to create value for their customers in the form of experiences. Creating the superior customer experience has become a necessity to survive in the competitive business environment. But creating customer experience is much more than providing entertainment or being creative (Berry et al. 2002). Companies need to understand the customer’s journey, which starts at the expectations the customer has before the experience take place and ends with the appraisal after the experience. The whole journey is influenced by anything that can be perceived or sensed (Berry et al. 2002).
Another example is the coffee company Starbucks. One of the major elements of the success of Starbucks is the focus on creating a distinctive customer experience (Michelli 2007). At Starbucks customers are willing to pay more for their cup of coffee, and to sit in a trendy environment while listening to their favorite music.
However, companies still do not understand why it is important to look at customer experience. Furthermore, there exist companies that collect and quantify data about customer experience but do not know how to use the collected data. The extent of the problem is highlighted in a research from Bain & Company’s who did a survey among customers of 362 companies. Only eight percent of the customers described their experience with the company as ‘superior’, even though 80 percent of the companies believed that they delivered ‘superior’ experience. Clearly a huge gap between the perception of customer’s experience of the customer and of the company exists (Meyer and Schwager 2007). Customer experience is in the mind of customers and is thus subjective and might be different for each customer (Frow and Payne 2007), which makes the customer experience harder for companies to capture.
Customer satisfaction
Following the definition of Oliver (1997), customer satisfaction is a “consumers’ judgment that a product or service feature, or the product or service itself, provided (or is providing) a pleasurable level of consumption-related fulfillment, including levels of under- or over-fulfillment”. Customer satisfaction is an important determinant of customer retention, which, in turn, has a very strong effect on profitability. Therefore, customer satisfaction plays a prominent role in marketing strategy. (Johnson and Fornell 1991)
(Drake et al. 1998). Therefore, for companies it is of interest to take a closer look at customer satisfaction.
1.3 Problem statement
At the moment Store Support is one of the largest players on the Dutch market in mystery shopping. The mystery shopping sector has several big players that offer similar services. Therefore, it is important for Store Support to have a good business philosophy to outperform their competitors.
As mentioned before, Store Support generates data about the quality of service of companies. Store Support wants to know which factors influence customer experience and especially what the role of service is, because the magnitude of impact of service on customer experience is not known yet.
Moreover, many companies perform customer satisfaction measurements. However, service is directly linked to customer experience and not to customer satisfaction, because customer satisfaction is about all the experiences of the customer with the company and customer experience is only about one experience. As such, measuring the relationship between service and customer experience is interesting for Store Support, because with mystery shopping each mystery shop is based on one experience. In addition, especially the link between customer experience and turnover is of interest, because little is known about this relationship.
The goal of this research is to get insight into how customers perceive customer experience and what the influence of customer experience is on customer satisfaction and turnover. This knowledge might enable Store Support to improve their mystery shopping and when proved, Store Support can convince companies that accomplishing mystery shops does have a positive effect on turnover.
Research question
The problem statement can be translated into the following research question:
Sub questions
The following sub questions will support the answer to the central research question: • What is customer experience?
• What is customer satisfaction?
• Which factors play a role with customer experience?
• What is the link between customer experience and customer satisfaction?
• What effect does customer experience and customer satisfaction have on turnover?
1.4 Relevance
The accomplishment of this research is relevant in two different ways, namely scientifically and practically. First, the scientific relevance is discussed, followed by the practical relevance.
Scientific relevance
In the literature several articles about factors that influence customer experience are published (e.g. Grewal et al. 2009, Puccinelli et al. 2009, Verhoef et al. 2009). However, most of the articles only give an overview of existing literature and suggestions for further research, but do not engage in pursuing these suggestions. In this thesis the factors that influence customer experience are actually tested to find out to what extent they have an effect on customer experience. Furthermore, despite research about the factors that influence customer experience, the relationship between customer experience and turnover is not tested yet. These two subjects are a contribution to the present scientific knowledge.
Practical relevance
At the moment a lot of attention is given to customer satisfaction measurements. However, those are in general not well linked to goals and actions within organizations. Quite often standard questionnaires are used, which are not specific for the organization. This results in scores which do not indicate what has to be done by the company (Van der Wiele et al. 2005). Therefore, another measurement should be used to better capture the focus of customers. By making use of mystery shopping more in-depth knowledge of the customer’s perception is gathered. With mystery shopping it is, however, still necessary to ask the right questions to provide the right image of the company for managers.
experience and in what extent. Questions about the most important factors should be included in the questionnaires for mystery shopping, so companies get a better understanding of the customer’s experience. Therefore, this research contributes to an improved questionnaire for mystery shopping.
In this research no mystery shopping is used, instead a questionnaire is conducted. The results will be used by Store Support to improve the questionnaires for mystery shopping, and maybe even the questionnaires for mystery calling and e-mailing. Furthermore, the results might be used to convince companies to cooperate with Store Support. Dependent on the results, the vision of Store Support might change due to new insights.
1.5 Structure of the thesis
2. Theoretical framework
In this chapter, the term customer experience is discussed in more detail and a clear definition is provided. Second, several factors that influence customer experience are described. Third, customer satisfaction is discussed, the relationship between customer experience and customer satisfaction is discussed and the relationship between customer satisfaction and turnover is described. Fourth, the moderators purpose of shopping, gender and income are explained. Finally, the conceptual framework is displayed.
2.1 Customer experience
Nowadays creating customer experience seems to be one of the central objectives in retail. Marketing practitioners and scholars have begun to recognize the importance of the customer experience. However, already almost three decades ago Holbrook and Hirschman (1982) paid attention to the aspects that refer to the emotional and rational side of customer behavior, called “experiential consumption”. Experiential consumption has a strong focus on multisensory aspects of customers’ experience of high involving products and services in the customer environment leading to multisensory images and emotional feelings. This approach states that customers are not only influenced by the product, but also by other factors.
In the end of the nineties Pine and Gilmore (1999) adopted the “experiential consumption” approach and introduced the “experience economy”. They present experience as a new economic offering, which emerges as the next step after commodities, goods and services in what they call the ‘progression of economic value’. When customer experience is unique it can create a higher economic value for companies. Since then research about customer experience has slowly increased.
Over the past few years many definitions of customer experience have started to circulate in the literature. The most common are displayed in Table 1. Some definitions are broader and more specific than others. Frow and Payne (2007) stress that customer experience is about the user’s interpretation. As such customer experience is for every customer different and thus subjective, which corresponds with the definition of Meyer and Schwager (2007).
customer experience as the interaction between the customer and the product, service or company.
Meyer and Schwager (2007) state that customer experience is based on any direct or indirect contact with a company. Direct experience is usually initiated by the customer and takes place during purchase, use and service. Indirect experience involves usually unplanned encounters with representatives of a company’s products, service or brand in the form of, for example, word-of-mouth recommendations or criticisms, reviews and advertising (Meyer and Schwager 2007). Also Verhoef et al. (2009) make a distinction between those elements which the retailer can control (service interface, retail atmosphere, assortment, price), and those elements that are outside the retailer’s control (influence of others, purpose of shopping). Furthermore, they indicate that customer experience is about the total experience, including the search, purchase, consumption, and after-sale phase of the experience, and may involve multiple retail channels.
Verhoef et al. (2009) and Gentile et al. (2007) underline that there is a response after the customer experience. Customers react based on the experience they encountered. The other three definitions (Frow and Payne 2007, Grewal et al. 2009 and Meyer and Schwager 2007) do not explicitly mention this.
Table 1: Definitions customer experience
Authors Definition customer experience
Frow and Payne (2007) Customer experience is the user’s interpretation of his or her total interaction with the brand.
Gentile et al. (2007)
The customer experience originates from a set of interactions between a customer and a product, a company, or part of its organization, which provoke a reaction.
Grewal et al. ( 2009) Customer experience includes every point of contact at which the customer interacts with the business, product or service.
Meyer and Schwager (2007) Customer experience is the internal and subjective response customers have to any direct or indirect contact with a company.
Verhoef et al. (2009)
Despite the amount of different definitions Gentile et al. (2007) identified two core characteristics of customer experience. First, they state that customer experience has a temporal dimension which originates from the entire set of contact points between the customer and the company, or the company’s offer. Second, customer experience is strictly personal, and involves and engages a customer at different levels (rational, emotional, sensorial, physical and spiritual).
One remark should be made about all the definitions, namely that none of them give a clear definition of the term experience. Overall can be concluded that several terms are mentioned more often in the definitions of customer experience. These are ‘interaction’, ‘subjective’, and ‘response’. Furthermore, customer experience is about the total interaction and thus not only about the physical interaction with a store, but also about, for example, social and emotional interactions with a store. Therefore, customer experience is holistic in nature. These ingredients combined results in the definition of customer experience that is used in the rest of the thesis:
“Customer experience is holistic in nature and involves the user’s interpretation of his or her interaction with a product, service, company or part of an organization, which provoke a customer response”.
In this thesis the focus is on the direct experience part of customer experience. The reason for this purpose is the feasibility of the research. It is not possible to measure the indirect experience part of customer experience for this thesis due to the type of research. Using this approach, it can be stated that customer experience is determined at one moment or shopping trip and thus visit-specific, because the direct experience takes place during one shopping trip.
2.2 Factors that influence customer experience
The user’s interpretation of interaction with a product, service or company, as mentioned in the definition of customer experience, is determined by factors that influence customer experience. Prior research shows that customer experience is influenced by several factors. For this thesis the factors that influence customer experience are based on research of Grewal et al. (2009), Puccinelli et al. (2009), and Verhoef et al. (2009). The factors are price, service, store atmosphere and assortment. In the following part these factors are explained more extensively.
2.2.1 Price
preferences are determined by consumers’ perceptions of a retailer’s prices and, therefore, are of strategic importance for retailers (Ofir et al. 2008). Setting the right price is a difficult task for retailers. A store or category can be perceived as high priced by one customer but can be perceived as low priced to another, also due to the fact that consumers buy different market baskets (Kopalle et al. 2008). As such, a favorable price for all consumers is desired.
Consumer’s perceptions of the price image of a store are partially established by store names, advertising messages and claims, slogans, presence or absence of reference prices, semantic price cues, various forms of promotions, and price matching guarantees that are offered (Ofir et al. 2008). Furthermore, a consumer’s store price image is determined by the number of relatively low priced products a consumer can recall. The greater the number of low-priced products at a store, the lower the price image is among knowledgeable consumers (Ofir et al. 2008).
Moreover, price can also be a determinant of quality. This is known as the price-quality ratio, which is about the perceived quality compared to the price paid (Matzler et al. 2006). When a retailer prices a product or service too low, consumers have negative associations with it, such as low quality or a poor performance. However, when a product or service is priced too high, consumers might view it as a poor value and will not buy it (Grewal et al. 2009). Thus, consumers make a tradeoff between the quality of the product or service and the price that has to be paid.
When a perceived price image does not correspond with the expectations of the customer, this has influence on the customer experience. Due to the fact that store preference is partly determined by price, it can be stated that if consumers perceive the price as sufficient compared to their expectations this positively influences their experience. Therefore,
H1: Perceived price image compared to the expectation of the customer is positively
related to customer experience.
2.2.2 Service
responsiveness, assurance and empathy) to measure the customer perceptions of service quality in service and retailing organizations, called SERVQUAL. This measurement focuses on the perceived quality, which is the consumer’s judgment about an entity’s overall superiority or excellence (Zeithaml 1987).
SERVQUAL has been a standard in service marketing and a basis for other measurements, like the SERVPERF scale. SERVPERF does not focus on the gap between expected and perceived quality as SERVQUAL does, but focuses on the performance of the service (Cronin and Taylor 1992). In the literature a lot of attention is paid to both scales. Different authors have compared the two scales in different business sectors and with different variables. Despite many researchers support the superiority of the SERVPERF scale, in practice the SERVQUAL scale is still more used. Therefore, in this thesis the SERVQUAL scale is used as basis.
Surshchander et al. (2002) argue that four of the five dimensions of the SERVQUAL scale correspond to the human element in service delivery, namely reliability, responsiveness, assurance and empathy. All four are based on the correctness of the front-line employee. Baker et al. (2002) indicate that employees that behave friendly create a more active, arousing store environment, as opposed to unpleasant and unfriendly employees. Furthermore, only one dimension of the SERVQUAL scale corresponds to the tangibles, to which belong design, atmospherics and decor elements.
In the offline retail industry personnel plays a big role in the service component, the personnel plays a key role in understanding and anticipating customer needs. Therefore, in the next part the focus is only on the human element. The four components of the human element are discussed more extensively.
Reliability of the employee
Reliability refers to the ability to perform the promised service dependably and accurately (Parasuraman et al. 1988). Hence, it is important that the employee gives reliable and accurate information to the customer and that the promises the employee makes are being fulfilled. In order to influence the customer the use of promises and the exchange of information are tools which the employee can use (McFarland et al. 2006). Therefore,
Responsiveness of the employee
Responsiveness involves the willingness to help customers and provide prompt service (Parasuraman et al. 1988). Hence, it is important that the employee is motivated and responds quickly to inquiries and complaints of the customer. Furthermore, the delivery of service on demand is a factor of responsiveness (Schneider and Bowen 1995). Therefore,
H2b: Perceived responsiveness of the employee is positively related to customer
experience.
Assurance of the employee
Assurance is to a large extent about the relationship between the customer and the employee. Sufficient knowledge is a necessity to identify the customer needs, while selling skills are an important determinant of an employee’s performance (Churchill et al. 1985). A clean and neat look of the employee is part of the courtesy determinant, just like friendliness and respect (Churchill et al. 1985). Finally, assurance is about making credible recommendations and the aptitude of employees. So, assurance captures the competences (knowledge and skills), courtesy (respect, friendliness, politeness, and consideration), and credibility (believability, trustworthiness and honesty) of employees and their ability to inspire trust and confidence (Parasuraman et al. 1988). Therefore,
H2c: Perceived assurance of the employee is positively related to customer experience.
Empathy of the employee
Empathy means caring, and individualized attention that the company provides to its customers (Parasuraman et al. 1988). Hence, it is important that customers have a short waiting time and perceive full attention of the employee. Inspirational and ingratiation appeals are tools which employees can use in order to create a sense of empathy and influence the customer in this way (McFarland et al. 2006). Therefore,
H2d: Perceived empathy of the employee is positively related to customer experience.
2.2.3 Store atmosphere
(Puccinelli et al. 2009). In this thesis the focus is on the interior atmosphere. The social factor of interior atmosphere consists of people in the environment, such as personnel and the other customers. This factor is already discussed in more detail in chapter 2.2.2 about service. In the next part the two other components of interior atmosphere, ambient and design, are discussed.
Ambient conditions of the store
Bitner (1992) defines ambient conditions as a factor that influences the perceptions and responses of consumer on the environment. Ambient conditions affect the five senses of consumers: smell, touch, sight, odor, and taste. Ambient conditions include the background characteristics of the environment such as the temperature (humidity, circulation, and ventilation), lightning, noise (level, and pitch), music, and scent. As such, ambient factors are background conditions that exist below the level of immediate awareness (D’Astous 2000). This means that customers and employees will not experience these factors consciously. Thus ambient conditions can be noticed or unnoticed, and when noticed pleasant or irritating. Even if the cues are not noticed, they still may influence the perception, attitude and behavior of consumers (Baker and Grewal 1992).
Merchandise value and store patronage intentions are influenced by ambient cues (Baker et al 2002). For example, Areni and Kim (1993) conducted an experiment about the music played in a wine store. They found that when classical music is played in a wine store, more expensive wine is sold, compared to playing top 40 music in the same wine store (Areni and Kim 1993). Furthermore, lighting that is too bright can increase the perceived waiting time (Baker and Cameron 1996). Moreover, from an experiment about scented conditions of Spangenberg et al. (1996) can be concluded that consumers who shopped in a scented condition perceived that they spent less time in the store than consumer in a no-scented condition. Those examples demonstrate that ambient conditions have influence on the interaction between customer and company and thus on customer experience.
It can be concluded that environmental stimuli can influence the emotional state of a consumer, which affects the consumer’s behavior, positive or negative, and thus his/her experience (Puccinelli et al. 2009). Therefore,
H3a: Perceived annoying ambient conditions of the store is negatively related to customer
Design of the store
Store layout, the functionality of a store and the signing inside a store are part of the design component, the other element of the interior atmosphere. According to Lovelock and Wirtz (2007), design factors are stimuli that exist at the forefront of the consumer’s awareness.
For many shoppers, the shopping goal is convenience, which includes getting in and out of the store effortless and the ease of finding the merchandise they seek. The layout of a store, the floor plan, contributes to efficient movement through a store, which plays a role in the experience of a customer. Signing inside the store can support the layout. Poorly designed stores may cause customers to incur psychic costs, which may reduce shopping pleasure (Baker et al. 2002). Moreover, Baker et al. (2002) indicate that the influence of design cues on the perception of a customer is stronger than the influence of music and employee cues. They also discovered that design has a positive effect on service quality, merchandise quality and monetary price, and a negative effect on cost perception. Thus, design cues do influence the experience of customers in stores. Therefore,
H3b: Perceived pleasant design is positively related to customer experience.
2.2.4 Assortment
Determining the product assortment which is offered by the retailer is a basic strategic decision all retailers have to make. One of the challenges of retailers is to get the right merchandise in the right quantities to the right stores at the right time to satisfy customers’ needs. Supplying the right number of choices of a product or service, balanced by the right variety of choices adds value to the experience of a customer (Knutson and Beck 2003).
It is difficult to predict what consumers want because they desire flexibility. This is because purchase and consumption of a product are not at the same moment, consumers often buy now and consume later. Therefore, the consumer must predict his or her future utilities. But consumers rarely know what they really want when they buy (Kahn and Lehrman 1991). Furthermore, the consumers’ preferences are instable. An optimal assortment of a retailer offers the first choice preference of each consumer in the target market. However, in many circumstances no first choice preference exists, because the first choice preference varies between particular situations (Mantrala et al. 2009).
In addition, consumers react differently to different assortment sizes. Too much choice can be confusing and frustrating for consumers (Huffman and Kahn 1998). Therefore, retailers have to make a tradeoff between a wide enough assortment, so consumers will not shop elsewhere, but not so wide that consumers are overwhelmed (Grewal et al. 2009). When an assortment is too large, delisting items can have positive effects. Delisting items can improve the overall assortment satisfaction, and increase the perceived and actual search efficiency without lowering perceived assortment variety. Due to less search time, primarily new buyers can be attracted (Sloot et al. 2006). It can be concluded that it is important that consumers are satisfied with the perceived assortment variety and size. Therefore,
H4: Perceived assortment size is positively related to customer experience.
2.3 Customer satisfaction
Just like for customer experience, there are also multiple definitions available for customer satisfaction. Customer satisfaction can be defined from two different perspectives: transaction-specific and cumulative aspects (Johnson et al. 2002). The transaction-transaction-specific aspect is about the value customers obtain after finishing one specific transaction. The cumulative aspect is the overall measurement of all the purchases and consuming experiences of a consumer related to an organization’s past, present, and future performance (Johnson et al. 2002). Since the definition of customer experience is holistic in nature, about an interaction with a company and is subjective, the cumulative aspect of customer satisfaction fits the best for this thesis.
et al. 1987, Zeithaml and Bitner 2000). Expectations are determined by personal needs, past experience, word-of-mouth and external communication (Yuan 2008). Only Spreng et al. (1996) take another approach and describe customer satisfaction as satisfying the needs and desires of the consumer.
Table 2: Definitions customer satisfaction
Authors Definition customer satisfaction
Anderson et al. (2004) The overall evaluation of the purchase and experience of a consumer.
Cadotte et al. (1987) An affective state that is the emotional reaction to a product or service experience.
Cronin and Taylor (1992) The level of what a consumer would expect. Spreng et al. (1996) Satisfying the needs and desires of the consumer.
Zeithaml and Bitner (2000) A conceptualized measurement, describing to what level consumers needs and expectations are being met.
The main difference between customer experience and customer satisfaction is that customer experience is determined by the experience of one moment or shopping trip and is thus visit specific. However, customer satisfaction is determined by the total satisfaction and can thus consist of more experiences or shopping trips.
Moreover, customer satisfaction is essentially the culmination of a series of customer experiences, or in other words the net result of the good minus the bad experiences (Meyer and Schwager 2007). Customer satisfaction is the summation of previous and present experiences and encounters of consumers with the product or service (Frow and Payne 2007). Consumers are satisfied if the experience meets or exceeds the expectations and are dissatisfied if the experience does not meet the expectations (Yuan and Wu 2008). It can therefore be concluded that customer experience and customer satisfaction have a positive relation. Therefore,
H5: Customer experience is positively related to customer satisfaction.
warranty costs, customer complaints, price elasticity, and customer defection (Fornell et al. 2006). Negative customer satisfaction leads to the opposite.
Several studies have done research about the relation between customer satisfaction and customer retention. This is of importance for companies, because the cost of retaining existing customers is less than the cost of acquiring new customers (Reinartz and Kumar 2002). Customer retention or repurchasing of customers is in the literature often mentioned as loyalty (Caruana 2002). In research a positive link is found between loyalty and profitability (Reinartz and Kumar 2002). So, research explored a link between customer satisfaction and loyalty, and other research a link between loyalty and profitability. Other studies did research about both links in one study, which is that customer satisfaction influences customer loyalty, which in turn affects profitability (Heskett et al. 1994, Storbacka et al. 1994).
However, in the literature there are only a number of papers about the direct link between customer satisfaction and financial performances. Yeung and Ennew (2000) found that customer satisfaction has a positive and significant effect on financial performances such as operating income, net income, sales and retained profit. Furthermore, Rust and Zahorik (1993) have empirically demonstrated the relationship between customer satisfaction and profitability for a health care organization. Moreover, Anderson et al. (1994) demonstrated the nature and strength of the link between customer satisfaction and economic returns in Sweden.
In this thesis the financial performance turnover is measured. The relationship between customer satisfaction and turnover is taken into account, because the variable is good measurable within the limitations of time and data. Therefore,
H6: Customer satisfaction is positively related to turnover.
A positive relation between customer experience and turnover is expected based on the expected positive link between customer experience and customer satisfaction and on the definition of customer experience, which states that customer experience provokes a customer reaction (e.g. buying). Therefore,
2.4 Moderators
Different customers find different aspects of the retail experience important, like the relational aspects or the quality of the core offering (Babakus and Yavas 2007). There can be thought of differences between customers in demographics, like age and gender, or differences in the purpose of shopping. The moderators taken into account in this thesis are among others based on research of Verhoef et al. (2009). The moderating effect of income, gender and purpose of shopping on the relationship between a factor and customer experience are taken into account in this thesis.
2.4.1 Income
The moderator income only has influence on the relationship between price and customer experience, which is discussed below.
Price
Households with lower incomes exhibit greater price sensitivity than households with higher incomes. Furthermore, the price search decreases with the amount of income (Wakefield and Inman 2003). Among others, Urbany et al. (1996) found that household incomes are inversely related to price search. However, Mulhern et al (1998) found the opposite, a negative relationship between income and price elasticity during a research about liquor. An explanation given for this finding is that probably higher income consumers are better able to take advantage of price deals via stockpiling. Another explanation is that it had to do with the product (liquor). But in general it can be stated that customers with a high income will less care about the price and therefore, the perceived price compared to the expectations of the customer will have a small effect. Therefore,
H8: The relation between the perceived price compared to the expectations of the
customer and customer experience is stronger for consumers with a low income than for consumers with a high income.
2.4.2 Gender
Service
Men and women both shop in different ways. Women tend to value and use information provided by others during decision making, whereas men prefer independence and achievement (Meyers-Levy 1988). Furthermore, women find interacting with a store employee who provides informational and personal cues more important than men (Noble et al. 2006). Therefore:
H9a: The relation between perceived service and customer experience is stronger for
females than for males.
Store atmosphere
D’Astous (2000) has done research about irritating aspects of the shopping environment, like crowding, a bad smell in the store, waiting lines, indifference of sales personnel, and an unclean store. He found that women seem usually more irritated than men in an environment with irritating aspects. Furthermore, he discovered that age has a significant impact on the extent of irritation. However, both depend on which specific irritating factor is considered.Therefore,
H9b: The relation between perceived store atmosphere and customer experience is
stronger for females than for males.
2.4.3 Purpose of shopping
Several studies have done research about the purpose of shopping, or the shopping motivations, of consumers. Researchers approach the purpose of shopping differently; some take a broader approach or are just more detailed than others. Wagner and Rudolph (2010) proposed three hierarchical levels including purpose-specific (recreation and task-fulfillment), activity-specific (efficiency shopping, sensory stimulation, inspiration, gratification, gift shopping, socialization, and bargain hunting), and demand-specific (service convenience, store atmosphere, assortment innovation, assortment uniqueness, personnel friendliness, and price) shopping motivations. Furthermore, Lombart and Labbé-Pinlon (2007) distinguish five different behaviors of consumers at retail outlets, namely utilitarian shopping, hedonic shopping, window-shopping, information gathering and browsing. Moreover, Moe (2003) created a framework for the online shopping motivations. She distinguished four shopping strategies, namely directed buying, search and deliberation, hedonic browsing and knowledge building.
Buying
When a shopper intends to make a purchase and a store visit results in an immediate purchase, the consumer has a buying strategy. The consumer needs to collect very little information and the search process is nearing an end. The objective of the store visit is making the purchase (Moe 2003).
Searching
The search strategy is like the buying strategy also goal-directed. On forehand a planned purchase is in mind. However, the difference with the buying strategy is the moment of the purchase. The objective of the visit with the search strategy is to obtain relevant information to make the best choice in the future. The consumer is still unsure which specific product in the category to buy (Moe 2003). With the search strategy it is possible that the visit ends with a purchase.
Browsing
Browsing can be defined as ‘the examination of a store’s merchandise for recreational or informational purposes without a current intent to buy’ (Bloch and Richins 1983). As such, browsing can be seen as a form of leisure activity. In contrast with buying and searching, with browsing no purchase is planned. The visit is stimulus-driven and only now and then results in impulse buying (Moe 2003).
Consumers can not always be clearly categorized according to a strategy. The different strategies tend to be ‘linked together’ in the consumers’ life (Lombart and Labbé-Pinlon 2007). For example, consumers can visit a store with several reasons. Such as buying a gift and browsing the leisure department of the same store without the intention of making a purchase.
atmosphere and customer experience, and assortment and customer experience. Above mentioned leads to the following hypotheses,
H10a: Buying strategy moderates the effect of price on customer experience.
H10b: Search strategy moderates the effect of service on customer experience.
H10c: Browsing strategy moderates the effect of store atmosphere on customer
experience.
H10d: Browsing strategy moderates the effect of assortment on customer experience.
2.5 Conceptual framework
Based on the literature and the hypotheses of the previous section, a conceptual framework can be designed (see Figure 1). The user’s interpretation of the interaction with the product service or company is influenced by price, service, store atmosphere and assortment. The holistic part of the definition of customer experience is captured in these four factors as well, because customer experience is not only about the physical interaction.
The aim of the thesis is to investigate the extent of influence of the four factors on customer experience. Furthermore, it is stated that customer experience has a relation with customer satisfaction. Following the definition, customer experience provokes a reaction, which is captured in the term turnover, and results in the conceptual framework in a relation between customer experience and turnover. Moreover, the relation between customer experience and customer satisfaction, and customer satisfaction and turnover is investigated.
---- moderating effect
Figure 1: Conceptual framework
H6 H7 H5 H4 H2a b c d H3a b H1 Customer Experience Customer Satisfaction Turnover Service
Purpose of shopping (moderator)
3. Research design
In this chapter the research design is outlined, the research method is discussed and the questionnaire design is described. Furthermore, the method of data collection is explained and the plan of analysis is discussed.
3.1 Research method
First, the method that is used to generate the data for this research is discussed. Second, the questionnaire design is described.
Method
Several research methodologies are available to perform a reliable research (Malhotra 2007). In this thesis exploratory and descriptive research are used. Exploratory research is used in chapter 2 by reviewing the existing literature on issues related to the problem. The outcome of the exploratory research is used as input for the descriptive research. The goal of descriptive research is to determine the view of the consumers.
For this research personal interviewing is chosen as research method. A common way to perform personal interviewing is to conduct interception personal interviews. In interception personal interviews respondents are intercepted while they are shopping. Personal interviews are efficient when respondents need to have an experience and see, touch, feel or consume the product or service before they give a well founded meaning. This is the case in this research, because it is about customer experience. To gain data for this thesis a quantitative questionnaire is conducted, which is statistically analyzed.
A disadvantage of a personal survey is the potential for interviewer bias. An interviewer can bias the results by the manner in which he or she select the respondents, asks the research questions, and records the answers (Malhotra 2007). By using mostly Likert scale questions the disadvantages will be reduced.
Questionnaire design
respondents feel comfortable, followed by more specific questions. The questionnaire is composed of a mixture of questions, mostly based on previous research, but consists also of some self-formulated questions by the researcher. Because the questions in the questionnaire which are based on previous research have already been tested, their validity is reliable.
The questionnaire starts with a short introduction of the researcher and where the survey is for and is about. Then the questionnaire continues with three general questions about the gender, age and income of the respondent. Age is not directly asked, but the year of birth is asked, because people are probably more willing to give this. Furthermore, income is asked on an ordinal scale with seven categories. The scaling is acquired from an annual scale of Synovate Interview-NSS (2007) and converted to monthly income. Monthly income is chosen because this is more on top of the mind of respondents than annual income.
The general part continues with a question about the purpose of shopping based on the differentiation of Moe (2003). Constant sum scaling is chosen for this question to get more insight in the answer of the respondent. As mentioned in chapter 2.4.3 consumers can visit a store for several reasons. Using constant sum scaling clarifies how many purposes of shopping a respondent has and the importance of the different purposes. The general part ends with a question about the spending of the respondent during the shopping trip.
The second part consists of questions and statements where respondents have to indicate to what extent they agree or disagree with a question or statement. It is specifically mentioned that while answering the questions or statements the visit of a moment ago has to be taken in mind.
In addition, there are questions and statements about the four factors that influence customer experience: store atmosphere, service, price and assortment. Three questions are asked about each factor or the components of the factor. The reason for asking three questions is that the internal consistency reliability of the variables can be tested with a Cronbach’s alpha test.
The store atmosphere statements consist of three statements about ambient conditions, developed by Baker et al. (2002), and three statements about the design of the store, developed by Chang and Horng (2010). All six questions are asked on a 7-point Likert scale from “totally disagree” to “totally agree”.
After the store atmosphere questions the respondent is asked whether he/she had contact with an employee. There is explicitly mentioned that contact with a cashier does not count as an employee. This is because the questions about service are specifically formulated for employees in the store, and can not always be answered when only contact with a cashier took place. If the respondent had contact with an employee in the store, the respondent continues with the questionnaire. If not, the respondent skips the statements about service and continues with the statements about assortment. The variable service consists of four components, which all consist of three statements, thus 12 statements in total. The statements are measured on a 7-point Likert scale from “totally disagree” to “totally agree”. The statements are based on research of Parasuraman et al. (1988) and Furrer et al. (2002). The statements of the four components are mixed, so respondents do not automatically link them to each other and answer them the same.
The three statements and questions about assortment are based on research of Kahn and Wansink (2004) and are measured on a 7-point Likert scale.
Furthermore, perceived price is measured on a 7-point Likert scale. The statements and question are based on research of Blery et al. (2009) and Nejad et al. (2009). Both measured price on a 5-point Likert scale, but to put consistency in the questionnaire the statements and questions about price are asked on a 7-point Likert scale.
In Table 3 an overview is displayed of the variables, the components the variable consists, the author(s) the questionnaire is based on and the scale the questions are asked on.
Table 3: Overview of research the questionnaire is based on
Variable Components Author(s) Scale
Purpose of shopping
• Buying • Searching • Browsing
Moe (2003) Constant sum scale
Turnover Euro
Customer experience Fornell et al. (1996) and
researcher 7-point Likert scale
Store atmosphere • Ambient conditions • Design
Baker et al. (2002)
Chang and Horng (2010) 7-point Likert scale
Service
• Responsiveness • Reliability • Assurance • Empathy
Furrer et al. (2000) and
Parasuraman et al. (1988) 7-point Likert scale
Assortment Kahn and Wansink (2004) 7-point Likert scale
Price Blery et al. (2009) and
Nejad et al. (2009) 7-point Likert scale Customer satisfaction Fornell et al. (1996) 10-point Likert scale
3.2 Data collection
Before the questionnaire is conducted an industry is chosen where the questionnaire will be conducted. After this decision two pre-tests are performed, followed by the main test.
Industry
store. To approach as many customers as possible and thus create a big database, many customers should visit the store. Above mentioned taken into account, resulted in the industry used in this research, namely electronics stores.
All customers that exit the store are asked to participate in the questionnaire. The respondents that did experience service are of most interest, because with these answers the impact of the factors on customer experience can be measured. The reason for asking all customers is to have a control group that did not experience service.
Pre-tests
Before the questionnaire is conducted, the questionnaire is pre-tested to improve the questionnaire (Malhotra 2007). A group of five respondents is asked to fill in the questionnaire to find possible flaws, vaguenesses and unexpected errors.
The pre-test is followed by a second pre-test. In this second pre-test the questionnaire is tested in a similar environment as where the main test will be tested, at an electronics store. The second pre-test took place at Thursday 9 June 2011 at the exit of the Media Markt in Groningen. In total 40 respondents were asked to cooperate of which only three respondents actually filled in the questionnaire. The reason behind this second pre-test is to find out how willing consumers are to cooperate, to discover how consumers react on the questionnaire and to find residual flaws and vaguenesses in the questionnaire.
The conducted pre-test was useful and made clear that especially the first impression of the person that conducts the questionnaire needed to be improved. It seemed that many consumers thought that the questioner belonged to a charitable organization and wanted the consumer to become member, which resulted in many ‘No’s’, even before the reason of asking the consumer was told. This problem is solved by wearing a polo shirt with the logo of the Rijksuniversiteit Groningen clearly displayed on the shirt (to show that it is not a charity), and a text indicating that the questioner stands at the store for a research. The shirt also promotes that an iPod can be won by participating in the questionnaire. Above mentioned is all used to attract attention of shopping customers.
Main test
For the main test stores had to be chosen that are part of the electronics retail industries. Furthermore, stores are chosen with a large surface, because stores with a big surface are likely to have more travel during the day. Moreover, the questionnaire is conducted at three different electronics stores in the same city. Three different store chains are chosen to dismiss extreme or exceptional cases and one city is chosen to have no bias in the type of respondents.
Above mentioned leaded to execution of the questionnaire in Utrecht at the exit of the Media Markt, Saturn and BCC. The data collected is cross sectional, due to the fact that the collection of data occurred at a specific time. It would have been interesting to have longitudinal data, but due to time constraints and lack of data this was not possible.
On forehand the goal is to administer at least 100 questionnaires at each store, with an as high as possible response rate of customers that had contact with an employee. The questionnaire was conducted on 25 June 2011 from 11.00 to 17.00 hour at the Media Markt, on 1 July from 11.00 to 18.00 hours at Saturn, and on 2 July from 11.00 to 17.00 hours at BCC. Every day there were two questioners who asked shopping people at the exit of the stores, the researcher herself and a well informed friend of the researcher. In total, after three days, 289 respondents filled in the questionnaire. Of those 289 questionnaires two questionnaires were incomplete, which resulted in a total sample size of 287 respondents.
3.3 Plan of analysis
To test the hypotheses the program SPSS 17 and Latent Gold 4.5 is used. Several statistic tests are conducted in order to test if the hypotheses are rejected or accepted. The different statistical tests that are used are discussed below.
Outliers
Another method to detect outliers for a regression analysis, which is used before the regression analysis is actually performed, is the Mahalanobis distance (D²) criterion. The Mahalanobis D² measure has statistical properties that allow for significance testing. The D² measure divided by the number of variables involved (D²/df) is approximately distributed as a t-value. Observations having a D²/df value exceeding four in a large sample (n>80) can be designated as possible outlier (Hair et al. 2009).
Factor analysis
Factor analysis is a well known method to define the underlying structure among variables in the analysis (Hair et al. 2009). Factor analysis will be performed to test if the questions asked in the questionnaire can be grouped into a lower number of variables.
To test if a factor analysis is appropriate, two different appropriateness tests are used. The Kaiser-Meyer-Olkin (KMO) measure looks at whether the partial correlation among the variables is small. The analysis is appropriate when the range of the KMO measure is between 0.5 and 0.9 (Malhotra 2007). Another test of appropriateness is the Bartlett’s test of sphericity. The Bartlett´s test provides the statistical significance that the correlation matrix has significant correlations among at least some of the variables (Hair et al. 2009). In other words, the Bartlett´s test shows if the variables are correlated or not.
To evaluate the acceptable consistency, goodness-of-fit statistics are used, like Cronbach’s alpha. The Cronbach’s alpha is determined to assure the internal consistency reliability of the variables. The generally agreed lower limit for Cronbach’s alpha is 0.7 (Malhotra 2007).
Pooling
Before the rest of the analyses are performed, the option of pooling or aggregating the data is investigated. Pooling offers several advantages in comparison with aggregation. First, the number of observations available for parameters estimation is greater. Second, pooling avoids biases which occur when data is summed or averaged. Finally, pooling does not require an assumption of parameter homogeneity (Leeflang et al. 2000). However, with pooling the different cross-sectional units can not be distinguished.
intercepts (Leeflang et al. 2000). If the null hypothesis of homogeneity is not rejected, pooling the observations is statistically justified.
Regression analysis
To estimate the relation between the four factors (independent variables) and customer experience (dependent variable), multiple regression analysis is used. Simple regression is applied when the relationship between customer experience (independent variable) and customer satisfaction (dependent variable) is estimated. Also simple regression is applied to measure the relationship between turnover (dependent variable) and customer satisfaction (independent variables) and the relationship between turnover (dependent variable) and customer experience (independent variables). By using multiple regression analysis, it is simultaneously tested whether the slope significantly differs from zero and whether the slope is in the same direction as formulated in the hypothesis based on literature.
When validating the results of a regression analysis, several tests are performed. A major problem with regression models is multicollinearity. Multicollinearity takes place when an independent variable tends to be highly correlated with other independent variables, which results in unreliable parameter estimates (Leeflang et al. 2000). A common method to look for multicollinearity is the variance inflation factor (VIF), which can be computed when performing a regression analysis. A VIF greater than 10 signals that collinearity is a problem (Leeflang et al. 2000). After solving the multicollinearity problem, regression analysis is performed.
Predictive validity
Predictive validity tests demonstrate how well a model is able to predict future observations. Well known methods are the Average Prediction Error (APE) which is used to judge whether the forecast errors are zero on average, the Average Squared Predictor Error (ASPE), which tests for a lack of bias and variance, the Root Average Squared Prediction Error (RASPE), which weight large prediction errors more heavily than small errors and the Mean Absolute Percentage Error (MAPE), which is dimensionless and useful if a comparison of forecast accuracy across different settings is wanted (Leeflang et al. 2002). All previously mentioned predictive validity test are performed on a holdout sample (10% of the dataset).
Latent class regression analysis
experience and the independent variables are the factors and their components. The moderators are not included in the model, because with latent class regression heterogeneity is already taken in to account. No latent class regression analyses are performed for the other regression analyses, because these regression analyses consist about only one independent variable. This makes latent class regression analysis not useful.
Advantages of latent class regression analysis over multiple regression analysis are that latent class regression analysis can be used to develop separate regressions to target each segment, diagnostic statistics are available to determine the value of R², and covariates can be included in the model to improve classification of each case into the most likely segment. A drawback of latent class regression is that there is no guarantee that the solution is the maximum likelihood solution (Magidson and Vermunt 2011).
When performing latent class regression the right number of classes has to be determined. Specifying too few classes ignores class differences, specifying too many classes may cause the model to be unstable (Vermunt and Magidson 2005). Several complementary approaches are available to assess the fit of latent class regression models and determine the most appropriate number of classes, namely the Log Likelihood (LL), Bayesian information criteria (BIC), Akaike’s information criteria (AIC, AIC3) and the approximate weight of evidence (AWE). The lower the value, the better the model. Andrew and Currim (2003) researched which information criteria have the highest segment retention rate. They indicate that the AIC3 is most useful. However, always all criteria have to be taken into account when making the decision.
4. Results
This chapter starts with an overview of some descriptive analysis about the three stores and about contact or no contact with an employee. Second, several statistical tests are performed with the final goal of testing the hypotheses. First of all a factor analysis is performed, followed by the decision to pool or not to pool the data. Next several regression analyses are performed and the predictive validity is checked.
4.1 Descriptive analysis
Before analyses are performed on the data, possible outliers need to be detected. The method used is the univariate method, which checks the standard scores of every variable. If the standard score is four or beyond, the respondent is a possible outlier. In this dataset the standard scores are all below four and therefore no outliers are detected. The other outlier test (Mahalanobis distance) will be executed when regression analysis is performed.
In this part the three stores are discussed in more detail. A closer look is given at the gender, age, income and money spend at the store (turnover) for each store. Furthermore, a distinction is made between customer that did have contact with an employee (service) and customer that did not have contact with an employee (no service).
In Table 4 an overview is given of the gender, age, income, turnover and number of customers that did or did not have contact with an employee, for all three stores separately and the average is displayed. The demographics are discussed all separately.
Store
Table 4: Overview of the demographic data
Total Media
Markt Saturn BCC Service
No service Contact employee Service 58.9% 58.1% 58.2% 63.4% No service 41.1% 41.9% 41.8% 36.6% Gender Male 58.9% 53.4% 68.4% 56.1% 58.6% 59.3% Female 41.1% 46.6% 31.6% 43.6% 41.4% 40.7% Age ≤25 15.6% 24.3% 6.2% 7.3% 13.7% 18.6% 26-35 22.6% 23.6% 22.7% 19.5% 20.2% 26.3% 36-45 23.3% 16.9% 32.0% 26.8% 28.0% 16.9% 46-55 23.3% 22.3% 26.8% 19.5% 22.0% 25.4% 56-65 11.5% 10.8% 9.3% 19.5% 13.1% 9.3% ≥66 3.8% 2.0% 3.1% 7.3% 3.0% 3.4% Income Below modal 9.1% 14.2% 2.0% 7.3% 9.5% 8.5% Modal 21.6% 25.0% 15.3% 24.4% 18.9% 25.4%
Between 1 and 2 times modal 28.2% 20.9% 38.8% 29.3% 32.5% 22.0%
2 times modal 13.6% 14.9% 15.3% 4.9% 10.7% 17.8%
Between 2 and 3 times modal 10.1% 9.5% 11.2% 9.8% 10.7% 9.3%
3 times modal or more 8.4% 6.8% 8.2% 14.6% 9.5% 6.8%
Don't know/no report 9.1% 8.8% 9.2% 9.8% 8.3% 10.2%
Turnover €0 29.3% 22.3% 28.6% 56.1% 26.0% 33.9% €1 - €50 31.7% 36.5% 33.7% 9.8% 20.7% 47.5% €51 - €100 11.8% 16.2% 9.2% 2.4% 11.2% 12.7% €101 - €250 13.6% 11.5% 17.3% 12.2% 20.7% 3.4% €251 - €500 6.6% 7.4% 5.1% 7.3% 11.2% 0.0% ≥€501 7.0% 6.1% 6.1% 12.2% 10.2% 2.5% Service
Of the respondents who completed the questionnaire, 58.9 percent did have contact with an employee. This is the case for all three stores, with an exception of the BCC, of which the percentage of customers that experienced service is slightly higher (63%). To test if there is a significant difference between the stores, an ANOVA test is performed. It can be concluded that there is no significant difference between the stores and the amount of service experienced (p=0.818).
Gender
