Abstract
This chapter discusses the usefulness of netnography as a research method in the digital banking context. Netnography has become a relative attractive data collection and data analysis method in some social science research areas but is still relatively unknown in financial research. Compared with other research methods, netnography seems to have some advantages in the digital banking world, such as real-time customer feedback. Moreover, virtual observations can be used not only by researchers but also by bank representatives to, for example, find out how bank customers can contribute to value co-creation.
TopIntroduction
In the rapidly changing business-to-customer (B2C) environment, companies must consider customer experience and behaviour (Heinonen & Medberg, 2018; Yang et al., 2015). In particular, rapid digitalisation has driven companies in various industries to follow their customers and develop more advanced digital alternatives. At the same time, social media platforms have become among the most important sources of up-to-date information for companies eager to improve their products and services (Sharma et al., 2018). This has, in turn, pushed companies to find better strategies and methods to take advantage of their users’ experiences and predict future customer behaviour.
Although changed customer behaviour has hit traditional retail stores the hardest, ongoing developments in the financial service industry are similar. Changed bank customer behaviour has decreased the number of bank branches (Fabris, 2019), and financial service companies, banks included, have started to reach their customers online by their websites and social media pages (Shankar et al., 2020). This phenomenon was accelerated by the Covid-19 pandemic, which has forced all groups of customers to contact their banks digitally (Rosenbaum & Russell-Bennett, 2020). The use of social media analysis (SMA) can encourage banks to develop their products and services, and help bank representatives manage various issues related to the ongoing digitalisation. Dimitrova and Öhman (2021) highlighted various barriers to digital banking development, including concerns related to privacy (i.e. undesired monitoring of financial behaviour), security (e.g. hacking and fishing attacks), access (i.e. limited bank services due to system breakdowns), and impersonalisation (i.e. lack of face-to-face services). Such barriers could have a significant long-term impact and even lead to resistance groups of bank customers organising themselves in support of, among other things, keeping cash as a payment method (Arvidsson et al., 2017).
Collecting data about their customers gives all kinds of companies feedback regarding their market position, product and service management, and what can be improved. Many companies rely on traditional data collecting methods such as surveys, interviews, and focus groups even in digital contexts (Medberg & Heinonen, 2014). However, the decreasing response rates in surveys (Baltar & Brunet, 2012), the lack of naturalism in interviews and focus groups (Kozinets, 2002), and difficulties recruiting respondents/interviewees have made traditional research methods less useful. Scholars and private companies have found SMA suitable as a substitute for traditional data collection methods in digital environments in which real-time customer experience can be observed and analysed (Laurell et al., 2020). Using various forms of SMA allows companies to stand out in a highly competitive environment and create value with the involvement of their customers (Shaikh & Karjaluoto, 2016). Amit and Zott (2001) emphasised that value co-creation (i.e. value creation involving customers) allows companies to tailor their products and services in a way that appeals to their customers. Even financial companies can co-create value by adjusting their business models in the rapidly changing digital environment. However, Mainardes et al. (2017) and Mostafa (2020) argued that more research is needed regarding value co-creation in the banking industry.
An increasingly popular research method is netnography, i.e. a data collection and analysis method based on observations made over the Internet. The method can, for example, be used in marketing research and when investigating customer experience or behaviour in various industries. Despite increased use in some social science research areas, the method has not received the same recognition in banking research and practice (Clemente-Ricolfe & Royo, 2020). The purpose of this chapter is, therefore, to discuss the usefulness of netnography as a research method related to customer experience in the digital banking context.
Key Terms in this Chapter
Digital Banking: Banking services through the Internet, offering a range of potential advantages such as greater accessibility and convenience.
Bank Customer Online Communities: Online groups or communities of bank customers, often on social media platforms, sharing their financial experience.
Netnography: An advanced digital qualitative research method suitable for academic and business applications in studying online communities.
User Experience: The interaction that end users have with a company’s product or service.
Impersonalisation: The lack of personal contact and communication in a specific context.
Value Co-Creation: Involving customers in business value creation by analysing their opinions and user experience.
Virtual Observations: Active (participant) or passive ( non-participant) observations made online (in virtual reality).