Oscar Kylberg & Alfred Carlwe
Customer experience in retail banking
A Swedish study
Business Administration Master’s Thesis
30 ECTS
Term: Spring 2020
Supervisor: Poja Shams
3 Acknowledgement
This thesis has been made possible thanks to Poja Shams, Katrin Lättman and Patrik Gottfridsson, who has guided us through this journey. We would also like to extend our thanks to the two interviewees, who provided us with extensive and important material for this research. Our last thanks go out to those that participated in our survey.
All content of the thesis has been written together and both authors are equally responsible for its’ content.
Karlstad, June 2020
_______________________ _______________________
Oscar Kylberg Alfred Carlwe
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Abstract
Customer experience has become more difficult for companies to control with the expanding number of touch points that the companies must be aware off. One of the major reasons behind the expanding number of touch points has been digitalization. The financial sector is not excluded from this change. With the digitalization continuously improving and new financial technology (fintech) being developed, things might have changed. For example, bank offices and employees have been viewed as important in earlier studies, but has this changed? What is important and affects the customer experience in the Swedish financial sector today?
The purpose of this paper is to gain a deeper understanding of which factors of banking services are considered important by customers today and
whether there has been a shift since earlier studies. Thereby, we seek to establish what impacts the customer experience in financial institutions today. To find the answer to the purpose, a qualitative and quantitative study were conducted.
The results of the full study show that employees are, as earlier studies have shown, still considered important when conducting a bank errand.
However, in what context the employees are important seems to have changed. The results show that the quality that is delivered by the staff is important, while in earlier studies the relational aspect has been more important. Furthermore, the results show that bank offices are no longer considered important for the customer experience. Therefore, a shift can be identified. The study also show that it is important for the customer
experience that the banks offer different channels for the customers to reach the bank. Furthermore, having the option to choose whether to resolve the bank errand on your own or obtain help from the bank is important for the customer experience. These two aspects are connected to the digital
development of the industry. The results of the earlier research, referred to in this study, has not found these two aspects important. Our study therefore shows a significant shift, compared to earlier studies, in what customers consider important in contact with financial institutions.
Key words: Financial institutions; Fintech; Digitalization; Customer experience; Touch points; Customer journey.
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Table of content
1. Introduction ... 7
1.1. Problem background ... 7
1.2. Problem statement ... 9
1.1. Purpose ... 13
1.2. Research question ... 13
1.3. Disposition ... 13
2. Theory... 14
2.1. Previous research ... 14
2.2. Customer experience ... 17
2.2.1. Customer journey ... 18
2.2.2. Touch points ... 18
2.2.3. Fintech... 20
2.3. Conclusion of the theory ... 20
3. Method ... 22
3.1. Method approach ... 22
3.2. Qualitative method... 25
3.2.1. Sampling method - Qualitative research ... 26
3.2.2. Data analysis - Qualitative method ... 27
3.2.3. Validity and Reliability- Qualitative study ... 28
3.3. Quantitative method ... 28
3.3.1. Sampling method – Quantitative research ... 29
3.3.2. Non-responses & missing responses ... 30
3.3.3. Data analysis - Quantitative data ... 30
3.3.4. Validity and Reliability – Quantitative study ... 33
3.4. Method criticism ... 34
3.5. Ethics... 36
4. Results... 38
4.1. Insights from the Qualitative study... 38
4.1.1. Channels ... 38
4.1.2. Digital applications ... 39
4.1.3. Fast and smooth processes ... 39
4.1.4. Expert advisory ... 39
4.1.5. Functions in the App ... 40
4.1.6. Innovative layout ... 41
4.1.7. Third parties ... 41
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4.1.8. Sustainability ... 42
4.1.9. Logistics ... 42
4.1.10. Additional information ... 42
4.2. Results – Quantitative study ... 44
4.2.1. Factor analysis ... 44
4.2.2. Cronbach’s alpha ... 47
4.2.3. Sample descriptive ... 51
4.2.4. Multiple regression analysis ... 53
4.2.5. Summary ... 55
5. Discussion & Analysis ... 57
5.1. The App ... 57
5.2. Contact channels ... 57
5.3. Bank offices ... 58
5.4. Third parties and sustainability ... 58
5.5. Significant factors ... 59
5.5.1. Employees ... 59
5.5.2. Customer interaction ... 60
5.5.3. Speed ... 60
5.5.4. Digitalization and Digital applications ... 61
5.6. Additional thoughts... 61
6. Conclusion of the thesis ... 62
6.1. Conclusion ... 62
6.2. Contribution... 63
6.3. Future research ... 63
References ... 64
Appendix ... 69
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1. Introduction
In this chapter we will give a background, which will describe the customer experience, the customer journey and the touch points involved, together with a presentation on financial technology (fintech). A background on what the banking sector has looked like, and its’ present state after the digitalization and growth of fintech, will also be presented. Furthermore, we will present the results and findings of earlier research, regarding what customers deem as important in contact with the banks. To fill the research gap that exists, we will explore the issue of how the customer experience have changed and how that has affected what customers deem as important in financial institutions. The chapter will conclude with the purpose of this study, its research questions, and the scope of it.
1.1. Problem background
A customer experience is formed when consuming a service or a product (Lemon & Verhoef 2016). This customer experience can be conceptualized by developing a customer journey. The customer journey stretches from the time before the purchase until the actual consumption. Within this customer journey, there are several touch points which help shape and form the customer experience. Examples of touch points can be stories from friends, the layout of a store, the personnel etc. With the rapid advancement in technology many industries have seen shifts, which have resulted in added touch points (Lemon & Verhoef 2016). Due to the added touch points, the customer experience has transformed. For example, people now walk around with a small computer in their pockets, i.e. smartphones. A
technology that was previously only able to make and receive calls. In other words, the touch points of a phone went from two, making and receiving calls, to several thousand touch points. Applications (apps) in phones now enables the users to do everything from playing a game to use it as a car key.
The financial sector, which according to Thakor (2020) barely has had its costs changed for centuries, has over the last couple of years started to change as well. This change is mainly a result of financial technology (Fintech).
Fintech is a term that refers to IT-technology within the financial sector.
What the exact definition of fintech is, is debated. Thakor (2020) defines it as technology that provides new and improved services within the financial
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sector. Das (2019) in his study, which tried to find a common definition amongst several studies, ended up with the following: “Fintech is a new financial industry that applies technology to improve financial activities”
(Das 2019, p.14). This is in line with Thakor’s definition. Often it is about making processes automatic. Shifting from manual tasks done on routine to nonroutine cognitive decision making (Das 2019). According to Lee & Shin (2017), fintech is amongst the topmost important innovations in the industry.
As a result of this advancement in fintech, there has been an explosion of fintech start-ups. These are financial firms that combine software with financial services. Globally, in 2016 alone, $12 billion were invested in fintech and the number has kept increasing (SVD 2017). In 2018 this number increased to $122 billion (Das 2019). The new technology has allowed fintech start-ups, by using niche, unique, personalized services, to challenge the traditional financial firms (Lee & Shin 2017). But fintech has also allowed traditional banks to improve as well. SEB for example invests nearly SEK 100 million annually in fintech firms. Nordea invested about SEK 15 million in the fintech Wrapp during 2016 (DI 2017). The new technology and software have not only changed the internal processes within banks, but also the external processes (Lee & Shin 2017). This has affected the customer experience within the industry. Fintech has brought new innovations, that have opened up new ways of, for example, connecting, paying, communicating and much more (Das 2019). All this has been made possible by introducing fintech solutions in services. These solutions include, amongst others, having your bank on a phone app, paying with your smartwatch through apple pay or through direct transaction over Swish, etc. These services were earlier performed in direct contact with the banks. The innovations mentioned have created a physical distance between the bank and its customers. This by enabling customers to use banking services on their own terms to a greater extent. Over the last ten years, the number of bank offices in Sweden has decreased from 1.400 to only 889 (DN 2018).
Between 2016 and 2017, a total of 90 offices were shut down. Swedbank, one of the five large banks in Sweden, has in nine years shut down 176 offices (Expressen 2016). The reason behind the closing of the bank offices is mainly the increased digitalization. An increasing number of customers have started to use the mobile apps and websites to a larger extent (Omni 2018). The digitalization and growth of fintech has also allowed niched companies, such as Klarna or Izettle, who specializes in a few financial services, to enter the
9 market (IDG 2019). In other words, digitalization and fintech solutions have created additional touch points in the customer’s journey when conducting a bank errand. Thereby it has changed the entire customer experience. Thus, what has been important to the customers before, might not be the same now.
Earlier studies have stated that employees, direct contact, bank offices and their layouts are considered the most important aspects to customers (Fandos Roig et al. 2006; Kyguolienè & Makutènas 2017; Ivanauskienė et al. 2012;
Narteh & Kuada 2014).
1.2. Problem statement
During recent years, the need and desire to create strong customer experience has increased (Lemon & Verhoef 2016). This statement is also supported by a study executed by Accenture (2015). The study showed that executives viewed working with improving customer experience as the most important priority in the short-term for companies. The main reasons that it is important to create a better customer experience is that it leads to an improved bottom line, due to, for example, word of mouth and customer loyalty (Lemon &
Verhoef 2016). According to Lemon & Verhoef (2016), managing and controlling the customer experience and the customer journey has become a difficult task for companies. The digitalization gives the customers more options and because of that, the companies lose control over the customer journey. In financial institutions, this statement can be connected to the changes caused by fintech, as described by Das (2019). Additionally, it can be connected to the distance created between the bank and its customers, as described above. Because of the increased customer options, firms must integrate multiple functions to regain control over the journey (Lemon &
Verhoef 2016). Examples of these functions are involving external partners, information technology, marketing, human resources, service operations and logistics.
Fintech start-ups have been able to grow in numbers. This due to the rapid advancement in technology, together with new EU-laws that were passed in 2013 and 2015 (PSD2). These made it easier for other firms than banks to provide banking services (Pantielieieva et al. 2018). With the rise of fintech and fintech firms, customers have started to use several different financial institutions for different needs (Lee & Shin 2017). This could be a result of the fact that different fintech start-ups specialises in certain services,
making them unique and personalized. This has led to concern within the
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industry. In 2016, 83 percent of the financial institutions saw the fintech start-ups as potential threats to their business (Lee & Shin 2017). For the banking industry, the digitalization has meant shorter turnaround time, lower operational costs and easier interaction with existing and future customers. This advancement may have led to a change in what customers consider important in services provided by financial institutions. Fandos Roig et al. (2006) found that the customer viewed the personal contact with the employees, together with the emotional value, as the most important aspect. This aspect made the largest contribution to the perceived value of purchase. What is meant with emotional value in this context, is what the customer feels internally. With these results, Fandos Roig et al. (2006), suggested that the front-line employees in a bank play a significant role in the process of providing services. Perceived value is “a multidimensional formative construct made up of six dimensions: functional value of the installations of the establishment; functional value of the contact personnel;
functional value of the service (Quality); functional value price; social value; and emotional value” (Fandos Roig et al. 2006, p.7). According to Kyguolienè & Makutènas (2017), the interaction with the employees is important and something as simple as a smile from an employee can lead to customer satisfaction. Fandos Roig et al. (2006) also found that customers viewed aspects such as “It seems tidy and organized” and “The installations favour the confidentiality and the privacy of dealings”, connected to the functional value of the establishment, i.e. the offices, important.
In a study by Ivanauskienė et al. (2012), the emotional value was found to be important to the customers. Factors that contributed to the emotional value were, for example, a positive atmosphere, relaxation and security, and trust in the bank’s personnel. Another study by Pisnik et al. (2016) instead pointed towards price being the most important factor in services provided by retail banking. The relational factors that Fandos Roig et al. (2016) found important, were also found important by Kyguolienè & Makutènas (2017), Ivanauskienė et al. (2012) and Narteh & Kuada (2014). Relational factors consisted of aspects such as the frontline staff being courteous, polite and helpful towards the customer at all times.
We believe that what is considered important today regarding customer experience in services, provided by financial institutions, are not the same things that were considered important in earlier studies. In fact, we believe
11 that the landscape has changed to such extent, that earlier studies has
become partly obsolete. The reason for this being digitalization and the rise of fintech. As mentioned before, digitalization has dramatically changed the landscape of the financial sector. Digitalization has lowered the cost of IT- infrastructure significantly. It has also made it possible to offer services across borders in a way that simply was not possible a few years ago. This, together with the PSD2-regulation, makes establishment of new
fintech’s much easier than previously. Due to digitalization, it is now technically even possible to start a bank by buying an “of the shelf- product”, with all necessary systems already built and ready to use (Banking4Bankers 2020). The landscape has also changed, due to digitalization, by enabling endless possibilities for the traditional banks (McKincey 2018). For example, banks can partner up with other companies and offer a mix of internal and third-party offerings. By doing so, it enables the banks to offer a single one-stop channel, making it much simpler and easier for their customers. Widening the assortment of the offerings that the bank has, gives the customers a larger range of choices and price-levels.
Digitalization has also allowed for banks to extend value across the
customer journey. Some years ago, banks could be viewed as a means to an end for customers. The banks at that time usually only tended to certain parts of the customers’ different needs. For example, when buying a house, the customer would only deal with the bank to get a mortgage. Now,
digitalization has changed this. An example of this is the Commonwealth Bank in Australia, which has created an app that allows their customers to get statistics, such as price, sales history etc. and even connect the customer to a real estate agent. All this by simply taking a photo of a property with the phone (McKincey 2018).
The 2010s was predicted to become the decade when digital banking had its’ real breakthrough (Oracle 2016). And as we have witnessed, this
prediction has come true. The digitalization of the banking sector has come a long way in Sweden. The number of Swedish fintech’s is now more than 70 (Swedish Fintech Association 2017). Statistics places Sweden at 6th place of 28 countries in Europe regarding the use of online banking (Statista 2020). A big step in the digitalization was Mobile BankID, that was
launched in Sweden in 2010 (BankID 2020). It has become an important part in further extending the possibilities of broadening the scope of
possible services to the customer. This innovation allows people to identify
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themselves through their smartphones, which is the first step and a pre- requisite in many service processes. In 2014, only 50 percent of the population over the age of 16 used Mobile BankID (Svenskarna och Internet 2020). By 2019 this had increased to 94 percent and the service is now broadly used outside the banking sector as well. In 2009, Swedbank was the first bank in the Nordics to launch a mobile app (Swedbank 2014).
Although there were only a few users of the app initially, the Mobile BankID later allowed for a much easier way to log in. Thereafter, the number of users exponentially increased. Now all major banks in Sweden have their own mobile apps (SEB 2020; Nordea 2020; Handelsbanken 2020
; Danske Bank 2020). Additionally, the Mobile BankID allowed for the development of Swish, which was released only two years after the Mobile BankID (Swish 2020). Swish has had a large impact on the market. It allows the Swedish population to make quick, simple, and safe day-to-day payments and transactions. The number of Swish users rapidly increased between 2014 and 2019, during which it increased from 44 percent of the Swedish population to 88 percent (Svenskarna och Internet 2020). The usage of internet and mobile banking has become a commodity over the last ten years and have thus had a tremendous impact on the customer
experience and behaviour in the financial industry.
As a result of aforementioned factors, the physical distance between the banks and the customers has grown. Now the customers can reach the bank anywhere, at any time. This raises the question; Are the employees and bank offices, that earlier studies have shown as important, still relevant?
The studies that have been mentioned were also made in countries with less developed technology. Furthermore, they were made in a time when the digitalization was not as developed. With all the above said and stated, it is important to understand how the changes of the landscape has affected the customers and their experience. If banks are unaware of what attracts customers, they will lose them to the fintech competitors (Oracle 2016), which in turn may lead to a loss of income. Eventually, it may also lead to the loss of their current key advantage of being the sector with the most information about their customers (Oracle 2016). With this paper, we want to investigate if, with the digitalization over the last years, there has been a change from what earlier research has stated. Thereby, it can be concluded whether the customer needs and expectations have changed. We would like to gain a deeper understanding of what factors in this new digital market are
13 relevant and important to the customers. To understand this, we will use customer experience as a measurement.
1.1. Purpose
The purpose of this paper is to examine which factors of banking services are considered important by customers today and whether there has been a shift since earlier studies. Thereby, we seek to establish what impacts the customer experience in financial institutions today.
1.2. Research question
Has there, with the digitalization and rise of fintech firms, been a change in what customers view as important in services provided by financial institutions?
What is viewed as important for the customer experience in services provided by financial institutions today?
1.3. Disposition
Six chapters, excluding references and appendix, make up this thesis. The first chapter is an introduction, which contains the problem background and a discussion of the problem, the purpose of the study and research
questions. Following the introduction, the relevant theories will be presented. In the third chapter, the method approach is discussed and the methods that were used are presented. In the chapter Results, the results and data from the qualitative and quantitative study are presented. In the fifth chapter, the results are discussed and analysed. Finally, a conclusion
containing the most important findings and suggestions for future research, is presented.
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2. Theory
This chapter will present the theoretical framework, on which the thesis is built upon. Firstly, previous research about customers in retail banking is presented. Secondly, the theories customer experience and customer journey are presented. This is followed up by touch points and purchase-stages, which are concepts connected to the two theories. After that, fintech is presented and lastly the theory is concluded in a summary.
2.1. Previous research
Fandos Roig et al. (2006) made a study about perceived value by adapting the GLOVAL scale to the banking sector. The GLOVAL scale is a measurement that considers both the functional and affective aspects. These two aspects constitute the overall perceived value. Functional aspects are, for example, the personnel, the quality of the service and the price. An emotional dimension and a social dimension make up the affective dimension. The results of the study conclude that emotional value, together with the employees, are deemed as the most important factors. This implies that employees have an extremely important role, especially in direct contact with the customers. Therefore, the study suggest that the focus should be on recruiting and training the contact personnel. Secondly, the service quality could also be considered important. In another study, by Ivanauskienė et al.
(2012), perceived customer value in the banking sector was measured. The approach to perceived customer value was that the concept considers social, emotional and functional dimensions. The findings in the study suggests that emotional value and contact personnel competences were the two most significant factors. In this study, emotional value consisted of factors such as comfort, good psychological climate, positive emotions, experience, reliability, satisfaction etc. The service quality was also significant, but not to the same extent.
Furthermore, Pisnik et al. (2016) investigated perceived value and instead found that price was the most important aspect. Price was considered even more important than the service quality. The factor price consisted of both monetary and non-monetary price. Non-monetary price, in this instance, was time spent on acquiring information about the banking services and how quickly the service could be provided. Monetary prices consisted of the bank
15 providing favourable interest rates for loans and commissions. Interest rates of loans was considered the most important factor for the perceived value.
Narteh & Kuada (2014) used customer satisfaction as a measurement when studying retail banking services. In this study, core, relational and tangible dimensions constituted customer satisfaction. The core refers to the core service, which includes all components of a service. The tangibles dimension refers to the sense of quality that the tangible cues of the banks provide. The relational dimension, on the other hand, refers to the added values that customers receive from the relational exchanges. In the relational dimension, the front-line employees are key. This by being friendly and by helping customers, providing their skills and competence and being efficient in their service recovery. The findings of Narteh & Kuada (2014) showed that the relational factors were the most significant ones, but the other two dimensions, core and tangibles, also played a significant role. Factors such as the competence and accuracy when delivering the service, the physical appearance of the staff and visually appealing facilities, were found important.
By identifying 14 factors, that contributed the most to customer satisfaction, Al-Eisa & Alhemoud (2009) measured customer satisfaction in retail banking. Their results showed that the courtesy and helpfulness of the employees, the speed in which the service was delivered, and self-banking services contributed the most to the customer satisfaction.
Karatepe et al. (2005) measured service quality in banks using service environment, interaction quality, empathy and reliability as dimensions of measurement. In the findings of the study, interaction quality was considered the most important dimension. This dimension included factors such as the knowledge of the employees, that the employees were polite, experienced, understanding towards the customers and had good manners.
Another article, by Miguel-Dávila et al. (2010), studied the service quality in banks and its effect on satisfaction and loyalty. To measure the service quality and satisfaction, four aspects were used; Operative, Physical, New Technologies and Human. In their findings, the operative aspect was identified as the main contributor to service quality and satisfaction. The convenience of the opening-hours, range of products and services in keeping with latest innovations, offer of high profitability rates and short period of
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waiting for service delivery, are examples of factors which constituted the operative aspect.
The measurement customer experience was used by Kyguolienè &
Makutènas (2017) in the banking sector, with the focus on generation Y (Gen-y). Here, customer experience was measured using seven touch points and several related statements to those touch points. The touchpoints were;
atmosphere, technology, communication, process, customer-employee interaction, customer-customer interaction and product interaction. The use of customer experience as a measurement was motivated by the possibility to take a closer look at the factors that affect the customers. This because customer experience view customers as active participants. Other measurements, such as the SERVQUAL model, treats the customer as a passive observant. In the study, the atmosphere in the banks was found as having a positive effect on the customer experience. Speed and the communication with the bank’s staff were also identified as influencing the customer experience. Another observation was that technology and technological innovations were important for Gen-Y.
Garg et al. (2014) developed a way to measure customer experience, specifically for the banking sector. The reasons for this was, as Kyguolienè
& Makutènas (2017) also stated, that customer experience is a way to observe the customer's perspective from a point where the customer is seen as active in the service process (Garg et al. 2014). This compared to service quality and the SERVQUAL model, where the customer is treated as a passive observant. Garg et al. (2014) criticize SERVQUAL for not capturing all the touch points, that the customer has with the organization, and therefore is seen as an insufficient method. Secondly, Garg et al. (2014) views the other measurements as insufficient since these have been developed to be used in other industries. Thirdly, measurements that have been used before has taken either the offline or online settings into account, separately. The measurement that Garg et al. (2014) developed consisted of 14 factors, which in turn consisted of 51 items, that were used to measure the customer experience. The result of the study was that the factor Convenience was the most important contributor to the customer experience. This factor contained items such as the location of bank offices, the distance to an ATM, and the opening-hours of the offices. Ten other factors were also significant. These were employees, speed, servicescape, core service, presence of other
17 customers, value addition, online functional elements, online aesthetics and service process. The factors marketing-mix, customization and online hedonic elements, on the other hand, were not significant for the customer experience. This also implied, with servicescape and convenience being highly significant, that bank offices were still important. At the same time, the online aspects were also indicated as important, since online functional elements and online aesthetics were significant.
2.2. Customer experience
The interest in customer experience has grown over the past decade (Becker
& Jaakkola 2020), leading to business leaders viewing customer experience as a central part for firms to gain competitive advantages. Being a new concept has also led to theoretical confusion and no common understanding of what customer experience actually is (Becker & Jaakkola 2020). There is an ongoing discussion about how to actually define customer experience (Lemon & Verhoef 2016). One way to view customer experience is that it reflects the offerings that firms manage and stage (Pine & Gilmore 1998).
Another way is to define it as the responses that customers have to firm- related contact (Homburg et al. 2015; Lemon & Verhoef 2016; Meyer &
Schwager 2007). In other words, the customer experience is formed by customers when they consume something (Lemon & Verhoef 2016).
Becker & Jakkola (2020) developed a framework for customer experience, based on literature about customer experience. Becker & Jakkola (2020) tried to integrate and draw connections among entities. The framework consists of four premises, which can be observed in the table below.
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Table 1. Premises of customer experience
In another study by Garg et al. (2014), several different definitions of customer experience created by different scholars and researchers in a 30- year timespan, were gathered. From these different definitions, three common denominators could be extracted. One of the denominators is that it is an emotional connection between the organization and the customer.
The second denominator is that the experience is internal to the customer.
Finally, the customer experience depends on the moments of contact. Garg et al. (2014) later conceptualized the customer experience in order to move away from the mentioned definition, which can be seen as an elusive and non-figurative notion. This was done by focusing on what factors
contributes to the customer experience.
2.2.1. Customer journey
Customer journey is a way to conceptualize customer experience by taking multiple touch points that occur during the customers purchase cycle into account (Lemon & Verhoef 2016). The total customer experience can also be conceptualized as a dynamic process. This process consists of the pre- purchase stage, the purchase stage, and lastly the post-purchase stage.
2.2.2. Touch points
During the above mentioned process and all the mentioned stages, customer experience touch points exists (Lemon & Verhoef 2016). By applying the concept customer journey, it is possibly to obtain the customer’s viewpoint
19 of the service process (Følstad & Kvale 2018). Lemon & Verhoef (2016) identified four different types of categories under which the touch points fall. These categories are: brand-owned, partner-owned, customer-owned, and social/independent touch points. The customer journey can be mapped by companies in order to gain important knowledge and information about what affects the customer experience. As follows, the categories are
described.
Brand owned
The firm can design its own touch points and they are called brand owned touch points (Lemon & Verhoef 2016). These touch points are controlled and managed by the firm. Examples of brand owned touchpoints are
websites and advertising, product attributes, packaging and other elements, which are controlled by the firm.
Partner owned
The next category of touch points is the partner owned ones. These are interactions that, during the experience, are managed, designed or
controlled together with one or more partner/partners (Lemon & Verhoef 2016). A partner can be a distribution partner or a marketing agency. The brand owned and partner owned touch points partly walks hand in hand.
These touch points are only possible to control to some extent, since there are other actors, beyond the company, that are involved.
Customer owned
These touch points are often occurring in the early process of purchase (Lemon & Verhoef 2016). The touch points contain the customer actions that firms or partners are unable to control, for instance the customers’ own needs and desires before actually buying something. Preferences in the purchase process, such as payment method or ordering method, for example through internet or a store, is also owned by the customer. The most
difficult aspect to influence is the preferences in the prepurchase stage, since the customers themselves evaluates what is best for them.
Social/external touch points
Across the customer journey, the firm’s customers are also affected by other external touch points (Lemon & Verhoef 2016). This can for example
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be independent information sources, environment around the shop/counter, peer influences and other customers. An experience at a restaurant or a cinema might be destroyed or distorted by external factors such as other customers. These external factors can also be a strength, for example if a customer speaks well about a company or leaves a positive review in social media or at a review site. With these distinctions between different contact points within a customer journey, a company can try to influence as many stages as possible in order to have as much control over the customer journey as possible. Some touch points though, mostly the external, are more difficult to control. In this digital world, where much of the banking are done digital and from a distance, it is possible to argue that the external variables, such as other customers, waiting time and facilities, has
decreased its impact but that word of mouth through social media has increased.
2.2.3. Fintech
Fintech is technology used in the financial sector in order to automate processes (Thakor 2020). The financial industry is made up of different areas (Das 2019). Within banks this could be trading, fraud detection and risk management. Areas more exposed to customers are lending and mobile banking. All these areas have been affected by the development of
technology, as they have become more automated, based on machine learning, big data, cloud computing and algorithms (Das 2019). The
technological development has led to fewer middle hands, regardless of the business (Gupta & Tham 2019). Fewer middle hands and processes saves money and makes it easier to contact new customers (Das 2019). The potential of unbundling services is also one major driver of the growth of fintech in the financial sector. Instead of using one financial institution, customers can pick and choose services from different fintech companies depending on the need. For instance, PayPal for payments and the
traditional bank for mortgage (Lee & Chin 2017).
2.3. Conclusion of the theory
A common theme in previous research, done in the area at hand, is that employees are significantly important for the customers when conducting bank errands (Fandos Roig et al. 2006; Ivanauskienė et al. 2012; Narteh &
Kuada 2014; Al-Eisa & Alhemoud 2009; Karatepe et al. 2005; Kyguolienè
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& Makutènas 2017). The aspect of the employees being courteous and polite is, in the mentioned studies, brought up as a main contributor to the factor employees. The relational and emotional aspects with the employees are therefore deemed as important, while the professional aspect (delivering quality service) of employees could regarded as second. Other important factors that were common in the previous research, were those connected to the facilities (Fandos Roig et al. 2006; Narteh & Kuada 2014; Miguel- Dávila et al. 2010; Kyguolienè & Makutènas 2017; Garg et al. 2014).
Examples of such factors are; visually appealing facilities, the atmosphere, the opening-hours, the location and the layout of the offices. The results from Pisnik et al (2016) stood out as the only study that found price as the most important contributor.
Kyguolienè & Makutènas (2017) and Garg et al. (2014) began to find indicators that technology, and aspects surrounding it, was considered important for the customers. These studies are fairly recent and as Lemon &
Verhoef (2016) states, with the rapid advancement in technology a lot of industries have seen shifts. This as a consequence of added touch points, which has led to the customer experience in industries being transformed.
Measuring customer experience, compared to using SERVQUAL or perceived value, can be motivated by the fact that customer experience allows the researcher to capture more aspects of the customer journey (Kyguolienè & Makutènas 2017; Garg et al. 2014). This since customer experience, unlike the other measurements, observe the customer as an active participant. The touch points in a customer journey can be captured by mapping the journey and the different purchase stages (Lemon &
Verhoef 2016). Finding out which touch points exists in a journey is crucial for companies. Because, in order to provide a satisfying customer
experience, the companies need to know what they have to control and manage. By mapping the customer journey in the Swedish banking sector, insights on what touch points exists can be gained. When knowing what touch points that exists in the journey, it can also be tested and found out what is important for the customers. After knowing what is important for the customer experience in today’s situation, the results can be analysed in order to find out if there has been a change. The change being due to, as Kyguolienè & Makutènas (2017), (Das 2019), Garg et al. (2014) & Lemon
& Verhoef (2016) indicates, the technological and digital development.
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3. Method
In the following chapter a motivation behind the choice of methods will be presented. Following this, the qualitative and quantitative methods that are used, along with the reliability and validity, will be presented. The chapter will round up with a presentation of the study’s ethics and method criticism.
3.1. Method approach
The study was conducted by using two different forms of studies, a
qualitative study and a quantitative study. This is called mixed methods and refers to research that integrates both qualitative and quantitative methods in one single project. This can be done in several different ways. The approach that was used in this study has been a mixture of an Exploratory Sequential Design and an Embedded Design. The procedure in an
exploratory sequential design is to use the qualitative study as a preparation for the quantitative study (Bryman & Bell 2015). An embedded design refers to when one of, either the quantitative or qualitative study, is used to enhance and elaborate the other study. The study that was carried out could be considered an exploratory sequential design. This, since two semi
structed interviews were conducted in order to find key touch points in a customer journey.
Mapping the customer journey is a tool which can be used in order to understand customer motivations and behaviour (Crotsier & Handford, 2012). Customer journey mapping does this by plotting out the various steps that a customer takes when making a purchase (Mucz & Gareau- Brennan 2019). These steps are divided into prepurchase, purchase and postpurchase. The prepurchase stage is the phase before the customer has gone through with the transaction (Lemon & Verhoef 2016). This phase encompasses all the aspects of the customer’s interaction, i.e experiences, with the brand and the environment from the time when the customer recognizes his/her needs, until this need is satisfied through a transaction.
The next phase is the purchase stage, which encompasses all the interaction that the customer experience with the brand and the environment during the event of the transaction (Lemon & Verhoef 2016). Choice, ordering and payment are behaviours that is linked to this phase. Postpurchase is the last phase in the customer’s journey. This phase encompasses all the customer interactions with the environment and the brand after the transaction
23 (Lemon & Verhoef 2016). Consumption, usage, service requests, and
postpurchase engagement is examples of behaviours that are linked to this phase. At the postpurchase phase, the product is central and becomes a critical touch point.
In isolation these different steps might not seem that important, but put together and in the context, they can provide powerful insights (Crosier &
Handford 2012). By using this technique, emotional responses that
customers have to services, products and goods, can be revealed. Customer journey mapping also helps to identify where improvements can be made (Mucz & Gareau-Brennan 2019). This since it helps reveal glitches that may exist in the service process (Crosier & Handford 2012).
Figure 1. Understanding customer experience throughout customer journey (Lemon &
Verhoef 2016, s. 77).
The touch points were then later used in the quantitative study. The
qualitative study was also used to elaborate the results from the quantitative study, which also made it an embedded design.
The touch points found in the qualitative study were transferred to an inquiry that was sent out to in order to help answer the purpose of this study. The purpose of this paper was to gain a deeper understanding of
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which factors of banking services are considered important by customers today and whether there has been a shift since earlier studies. Thereby, we sought to establish what impacts the customer experience in financial institutions today.
The motivation behind this was that earlier studies had shown that factors such as personal contact and the layout of the bank offices had a large impact on the customers’ perceived experiences. This might have changed with the digitalization and growth of fintech. In order to find out what customers consider important today, we used a measurement of customer experience developed by Garg et al. (2014). There were several reasons to why we used this measurement of customer experience, opposed to using measurements such as SERVQUAL or perceived value. According to Garg et al. (2014) and Kyguolienè & Makutènas (2017), customer experience allows the researcher to take a closer look at the factors that constitutes the customer experience. This, since the customer is regarded as an active participant, while other measurements only treat the customers as passive observants. The second reason for using the measurement by Garg et al.
(2014), was that this measurement was developed specifically for retail banking. Lastly, this measurement included both online and offline elements, while others usually measure either online or offline. The
measurement was, according to Garg et al. (2014), adapted to a developing country. Therefore, they suggested that, when using it in a developed country, it should be adjusted thereafter. By conducting the qualitative study, this could be achieved.
The measurement of customer experience by Garg et al. (2014) consists of, as described above, 14 factors and 51 items connected to those factors. The factors are; convenience, servicescape, employees, online functional
elements, presence of other customers, online aesthetics, customization, value addition, speed, core service, marketing-mix, service process, online hedonic elements and customer interaction. These 14 factors were taken from a previous study by Garg et al. (2012). To validate these factors and items, Garg et al. (2014) went through several steps. Through an extensive literature review, 234 items connected to the factors were identified. In order to narrow down these items several steps of validation were
performed. Firstly, a panel of six experts, consisting of professors and bank managers, were asked to review and rate the 234 items. After the review, 84
25 items were left. Secondly, a panel of four external experts reviewed the 84 remaining items, which resulted in 71 items. These 71 items were finally reviewed by 44 management graduates, resulting in 61 items. When the reviewing from different expert sources was finished, the items were test- piloted with a survey which included 203 responders. The outcome from the survey resulted in 51 remaining items. The factors, together with the items, were then validated through a final survey, which consisted of 384 responders.
3.2. Qualitative method
As mentioned, this study was done by conducting both a qualitative and a quantitative study. One of the reasons behind the qualitative study was to extract touch points from a customer journey from someone who possessed extensive knowledge in the area. The answers that were provided in the interviews enabled us to extract touch points that could be used as a
framework for the quantitative study. These touch points were added to and extended the measurement system for customer experience made by Garg et al. (2014). To adapt it into our situation, which were the Swedish banking industry today, we regarded this necessary. The other reason for the interviews was to help elaborate on and explain the results from the quantitative study.
Since a face-to-face interaction is the best way of understanding the mind of another person, two interviews were conducted. Bryman and Bell (2015) argues that a qualitative study can contain trivial details and unwanted information, which can take time to review. This is something that had to be taken into consideration during the interviews, in order to prevent irrelevant questions. On the other hand, it is also stated by Bryman and Bell (2015) that these collected details are important to get a deeper understanding of the context.
When performing interviews, it is possible to choose between an unstructured interview and an semi structured interview. Qualitative
researchers prefer less structured interviews. This means that there are a set of questions to be answered, but the questions can differ depending on the answers from different respondents (Denscombe 2018). They can be more or less detailed and more or less participation from the interviewer can be needed through follow up questions. This flexibility is a characteristic of
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semi-structured interviews (Bryman & Bell 2015), which suits our purpose of deep understanding. Problems with semi-structured interviews are that the respondent can receive questions that are based on presuppositions from the researcher. But since there was a clear purpose of the interviews, the interview guide was used as a base to talk about the correct subject and to let the respondent answer as open as possible. The use of an interview guide is also recommended by Bryman & Bell (2015). According to David &
Sutton (2017), it is important to record interviews in order to transcribe and code them, which provides deeper insights. Since the interviews were the base for the rest of the research, the recording, transcribing and coding were an important part of the process. This made it possible to listen to the
answers several times and to examine the important parts that led to the extracting of touch points.
3.2.1. Sampling method - Qualitative research
Lemon & Verhoef (2016) has elaborated on the critical need to understand customer experience and the customer journey. The questions in the
interviews were formulated to be rather open questions about how
customers would proceed when conducting a bank errand. Since this was done to get a deeper understanding of the customer journey and what customer usually do, two semi structed interviews was preferred.
The respondents for the two interviews were chosen through purposive sampling (Bryman & Bell 2015). Purposive sampling, according to Bryman
& Bell 2015), is when the researcher chooses the respondents based on the research questions. The objectives were to find relevant touch points to be used in the quantitative study, but also to gather information that could be used when analysing the results of the quantitative study. Therefore, two employees of a big Swedish bank were contacted. These two employees have a long experience within banking and are today working with customer relations. Therefore, they can be viewed as experts. The reason why this particular bank was chosen, was due to convenience, since we had contacts in this bank. The two employees were first contacted via mail, where details about the purpose and intentions of the study were explained.
Both agreed to an interview via phone and to the fact that the interviews were to be recorded with a Dictaphone. Each interview lasted between 30 to 40 minutes. The reason why the interviews were conducted via phone, instead of it face-to-face, was because of the current COVID-19-situation.
27 During the interviews, the interviewees answered the questions and
provided detailed answers. The process of analysing the calls was facilitated by the fact that they were recorded.
3.2.2. Data analysis - Qualitative method
When conducting a qualitative data analysis, Bryman & Bell (2015)
mentions two strategies – grounded theory and analytic induction. Analytic induction mainly revolves around a studies hypothesis. Since this study does not have a hypothesis, grounded theory is better suited. When analysing qualitative data, grounded theory is the most used framework.
Grounded theory starts with theoretical sampling, which then leads to coding of the material (Bryman & Bell 2015). Coding is about breaking down the data into component parts and identifying important parts which are given different names (Fejes & Thornberg 2015). After the coding is done, the next step is theoretical saturation. Theoretical saturation is a process, relating to the two first phases – the coding of data and the
collection of data. The coding of the data part is about having reached to a point where it is useless to continue reviewing your data. The collection of data is about reaching the point where no new data can further illuminate the concept that has been developed. The last step in the grounded theory is constant comparison, which is the process in which a close connection between conceptualizing and data is maintained (Bryman & Bell 2015). The reason for this is that the correspondence between categories and concepts should not be lost. The outcome of grounded theory are concepts,
categories, properties, hypotheses and theory. Concepts are extracted through open coding and refers to labels, which are given to discrete phenomena. Concepts, which has been detailed and regarded as representing real-world phenomena, then make up categories.
One of the objectives with the qualitative study was to extract touch points seen in the customer journey, in order to conduct the quantitative study. The other objective was to use the information gathered from the interviews to elaborate and explain the results from the quantitative study. Therefore a, partly, grounded theory was best suited. This, since it allowed the extraction of concepts and categories which later were transferred to the survey. It was the categories and concepts that were of interest for us to gather. Since a hypothesis or theory were not the objective of the study, we stopped the process of grounded theory after the extraction of the categories. Since the
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quantitative study, and its’ survey, were built on the qualitative study, a thorough analysis in order to extract the touch points was needed.
3.2.3. Validity and Reliability- Qualitative study
The preciseness and accuracy of the data is what is discussed when talking about validity regarding qualitative research (Denscombe 2018), but
validity regarding qualitative research is difficult. It is nearly impossible to state that the data is “the correct data”. Some measurements to try
validating qualitative data, in the sense that the data is “the correct data” is, to some extent, possible though. One way is to use the respondents to validate the data (Denscombe 2018). This was done through the pilot study being sent out to the interviewees and our mentor.
Reliability addresses the question if the survey or interview will provide the same answers when conducted again at a different time (David & Sutton 2017). Internal reliability is one way to strengthen the reliability of a
qualitative study according to Bryman (2016). What is meant by this is that within the research team, more than one person agrees with what has been heard and seen. When coding the interviews together and formulating the questions/items, both of us came to the same conclusions. Thus,
strengthening the reliability.
3.3. Quantitative method
Before the survey was sent out, a pilot study was conducted. A pilot study can be a strength, since it enables getting feedback about the phrasing in the questions (Denscombe 2018). This is done to avoid misunderstandings when conducting the real survey. The questions in the survey were based on the study by Garg et al. (2014). These were then supplemented with the gathered touch points from the interviews in the qualitative study. Some of the questions from the study by Garg et al. (2014), that we viewed as less relevant, were removed. This since we, with our added questions, wanted to keep the survey relatively short in order to increase the respondent rate. The questions were translated from English to Swedish in order to avoid that anything got wrongly interpreted. This is a proven method used by
Ivanauskienė et al. (2012), who translated their questions from English to Lithuanian in order to meet the requirements of content validity. The aim with conducting the survey was to gain insights about how customers value different aspects of services provided by financial institutions. This by
29 observing what factors contributed to the customer experience the most.
Then the results were compared to the results from earlier studies.
Our survey consisted of 49 questions, which could be answered on a scale from one to seven, a so-called Likert scale. This scale is recommended by Denscombe (2018) as the most frequent used and most suitable for
quantitative studies. An answer close to one meant that this is not
important, while an answer close to seven meant that this is very important.
The sample method that was used in the quantitative study was a non- probability sample, which was a mixture of a convenience- and snowball sampling. Convenience sampling is when the researcher chooses
respondents out of convenience because of the accessibility of the respondents (Bryman 2016). Snowball sampling, on the other hand, is contacting a group of people and through them find contact with others.
Snowball sampling, according to Denscombe (2018), is also used mostly in small scale research. This was the case of this thesis. The survey was carried out online using Survey&Report, which was shared via links on Facebook and LinkedIn. This made it a convenience sample in the way that it was an easy way for us to gather the information. At the same time, it could have been seen as a type of snowball sample. This because of some people sharing the links forward. Reasons for using online surveys to collect data, as Bryman and Bell (2015) states, is that it is efficient.
Efficient regarding both the financial and the time aspect. Online surveys also make it possible to quickly reach a large number of people. Time and resources are something of concern when conducting a probability sample (Bryman 2016). The lack of both these things lead us to not perform a probability sampling. A probability sample, though, would have allowed us, according to Bryman (2016), to make conclusion about the general
population.
3.3.1. Sampling method – Quantitative research Our survey consisted of 49 questions. It was shared on social media sites, such as Facebook and LinkedIn, in order to have a large reach and a representative sample. Another reason was that we lacked time and
resources. Only the answers from people over the age of 18 were collected.
The age limit was motivated by the fact that people above the age of 18 are legally allowed to conduct banking errands in their own regime. A total
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number of 273 answers were collected. In order to analyse the results from the survey, the answers from Survey&Report were transferred to Statistical Package for the Social Science (SPSS).
3.3.2. Non-responses & missing responses
When conducting the survey, 332 people answered. Out of these 332 people, 273 respondents sent in their answers. This resulted in a response rate of 82,2 percent. Out of these 273 responses, 51 answers had missing data and were therefore removed, leaving us with 222 respondents.
3.3.3. Data analysis - Quantitative data
After we collected all the data provided by the respondents, the data was transferred from Survey&Report into Excel. In Excel, the data was cleaned up, as described in the section “Non-responses & missing responses”, and transferred to SPSS statistics. This in order to conduct the analyses. Before the analyses though, some variables had to be coded into dummy variables (David & Sutton 2017). Through coding, qualitative variables becomes binary variables, thus creating so called dummy variables. A dummy variable is coded into 0, which implies the event does not occur, and 1, which implies that the event does occur. After the coding was completed, a factor analysis and a Cronbach’s alpha reliability test was performed. This was done in order to improve our independent variables. When the
variables had been improved, a descriptive analysis was conducted in order to get and present an overview of the data. After presenting the data, a multiple regression analysis was conducted. Finally, all the different analysis were summarized.
Factor analysis
With factor analysis it is possible to check if the items, in our case the questions in the survey, fits together in order to explain a variable (Sundell 2011). By, for example, testing our items that forms our independent variable Convenience, its’ variance is explained. When conducting the analysis, the first value that is observed is the “Eigenvalue”. The higher the eigenvalue, the higher the degree of variation in the variable is explained.
An eigenvalue above 1 is acceptable. If the eigenvalue is OK, the factor loading on each item are checked. The higher the factor loading of an item, the more of the variable is explained by the item. A factor loading >0,3 or
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<-0,3 is considered acceptable (Sundell 2011). The factor analysis was conducted on all items in the survey, grouped together according to what our theory stated. The results will be presented in tables later on.
Figure 2: Example of factor analysis
Cronbach’s alpha
The Cronbach’s alpha is used to test the internal reliability in quantitative data. This because indicators do not always measure the same thing. In the case of this study, we had to be sure that all the items in the factors
measured the same thing. When testing this on the items, a score, known as
“alpha coefficient”, will be set from 0 to 1. 1 indicates perfect internal reliability, whereas 0 indicates no internal reliability. The acceptable level of this coefficient is debated. 0,7 is said to be good enough (Sundell 2012), but 0,8 is also said to be the minimum level of acceptance (Bryman 2016).
To start the test and investigate whether one or more variables should be removed, the measurement “Cronbach’s alpha if item deleted” is used. This shows how the “alpha coefficient” would change, improve or impair, if any item were deleted. If this measurement gives a higher number than the initial “alpha coefficient”, the total alpha coefficient will improve if this item is deleted (Sundell 2012). This method can therefore be used to find out if any item should be removed, due to that the item not being connected to the other items.
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Descriptive analysis
As mentioned before, after the factor analysis and the Cronbach’s alpha reliability test, a descriptive analysis was performed. Exploring individual variables and identifying if there are trends in the data are made possible by a descriptive analysis (David and Sutton 2017). This allows the researcher to get to know and understand the data. Frequencies, central tendency, and distribution measurements are presented in tables in the descriptive
analysis.
Regression analysis
When investigating the relationship between several independent variables and the dependent variable, a multiple regression analysis can be conducted (Edling & Hedström 2003). The multiple regression analysis contains two or more independent variables, compared to a regression analysis which only controls for one independent variable.
The Beta coefficient in a multiple regression analysis shows for each respective independent variable how much one step change in the
independent variable effects the dependent variable (Sundell 2009). In order for the Beta coefficient to actually show if the independent variable has an effect on the dependent variable, the independent variable must be
significant.
The level of significance used in this study is what most studies uses, 0,05 (5%) (Sundell 2009). A model summary is presented when the multiple regression analysis is performed. Here, the level of significance of the model can be observed. If the level of significance of the model is ≤ 0,05, we can with 95 percent confidence state that the variation in the dependent variable can be explained by the independent variables. Furthermore, the level of significance of each independent variable is presented in the
ANOVA-table. As discussed above, this tells us if the independent variable influences the dependent variable (with 95% confidence).
Pearson’s r, also called the coefficient of correlation, shows the strength of the relationship between the independent variables and the dependent variable (Bryman 2016). R can have a value between -1 to 1. The closer the coefficient is to either -1 or 1, the stronger the relationship is. When r takes
33 a value that is negative, there is a negative relationship. If r has a positive value, there is a positive relationship.
R Square, also called the coefficient of determination, shows how much variation in the dependent variable that is explained by the independent variables. R Square takes on a value between 0 and 1 (Sundell 2009). The higher the R Square value, closer to 1, the better does the independent variables explain variance in the dependent variable. What level of R square that is considered “low” is not clear, since it differs depending on what data is being examined (Edling & Hedström 2003). Only including variables that leads to a higher R Square value is not always the best approach. Variables that influence the model to have a lower R Square value might be important to include due to the theoretical framework.
When performing a multiple regression analysis, the VIF-value is also important to observe. The VIF-value shows if there are any
multicollinearity present in the independent variables (Sundell 2010). What is meant by multicollinearity is if there are two or more independent
variables in the model that correlates with each other and explains the same variation in the dependent variable. If the VIF-value is >10 for the
independent variable with the largest value of the Beta coefficient, there might be an issue with multicollinearity (Mendenhall & Sincich 2016).
3.3.4. Validity and Reliability – Quantitative study According to Denscombe (2018), validity can be divided into external and internal factors. These factors are about the accuracy, precision, and relevance of the data. In other words, if the data reflects the reality (David
& Sutton 2017). The external validity shows to which extent the data can be generalised (Denscombe 2018). Internal validity is about the researcher asking if the “right” questions are asked and if the “right” things has been observed (Denscombe 2018). One internal factor is face validity, which is when the researcher defends his/her work by referring to common sense and that it seems reasonable and obvious. Asking other people, for example someone with expertise in the field or experience revolving the subject, is another way to establish face validity (Bryman 2016). Another internal factor, that can be applied, is by referring to earlier research and continue expanding already existing theories (Denscombe 2018). Our survey was built upon an earlier study by Garg et al. (2014), where the questions went
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through several test pilots and views from experts. Therefore, it is strengthened in its validity. The questions that was added, after our qualitative study where two long-time experienced employees in the industry were interviewed, were partly built on face validity. This further validated our data.
Validity is also about getting the “right” answers, not only asking the
“right” questions (Denscombe 2018). What is seen as “right” in this instance, is that there has not been any errors or mishaps during the gathering of data. A preventative way to avoid this issue is to have a pilot study. A pilot study was performed in our study through sending out the survey to five people beforehand, including the two employees that were interviewed.
Lastly, when talking about internal factors, the careful administration and handling of the data, in order to prevent errors, is important (Denscombe 2018). A typical instance, where these errors can occur, is when the data is transferred manually. This was prevented in our study, since the data was transferred from the survey tool to Excel and finally too SPSS, where it was examined thoroughly.
3.4. Method criticism
The report used a mixed method, consisting of both a qualitative and a quantitative study, to answer the purpose of the study. Criticism of the use of mixed method exists. Bryman & Bell (2015) mentions different criticism towards qualitative studies, where one of the critiques are that qualitative research is too subjective. What is meant by this, is that the findings in qualitative researches often are influenced by the researcher and relies on the researcher being unsystematic about what is important and significant.
In the results of the qualitative study we extracted touch points, but which touch points that were seen as important might have been influenced by what we viewed as important. Therefore, there could have been a risk that we overlooked some touch points. The choice of bank to interview can be a source of bias, but it was a relevant choice in this case since answers from an expert was needed. The answers from the interviewees are subjective and if we had collected answers from another bank, the result might have differed. Since the interviews were the basis for the rest of the survey, the
