Data analysis

Table 8 provides a summary of the types of data collected, data sources and how data was utilized in the analysis. The text in this section provides an overview of the approaches used for analyzing the data obtained from the interviews with managers and from the documentation

Table 8: Types of data collected and used in the analysis and the construct of case studies.

Data source Type of data Utility of data Purpose

Interviews with

banks’ management Textual data obtained from interview transcripts Provided insight into managerial perspectives on the role of social media in marketing for banks and managers’ own interpretations and understanding of the opportunities and challenges that social media presents to bank marketing and RM. Used to corroborate insights gathered from other sources of information.

Enabled to uncover themes constructing managerial

perspectives on the role of social media in bank marketing and RM. Facilitated

identification of opportunities, challenges, obstacles, barrier and advantages related to the prospects of utilizing social media in marketing and RM.

Documents Textual data in the form of:

- Official reports published by banks online (e.g. annual reports, white papers)

Provided additional information about banks’ marketing practices. Provided evidence of banks’ online Facilitated gathering statistical information about banks’

performance and scope of activities in the retail sector, as well as

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- Press releases - Articles

- Industry reports etc.

marketing activities. Used to corroborate insights from the interviews with bank management information about banks’ marketing campaigns and initiatives. Observations on banks’ online marketing activities

Textual and numerical data in the form of observations about banks’ social media pages and corporate websites Provided additional information about banks’ online marketing activities to complement insights gathered in interviews with managers and documentation analysis. Assisted to uncover changes and developments in banks’ online marketing activities over time. Complemented other types of data utilized for the construct of case studies.

Analysis was conducted firstly on the within-case basis (i.e. analyzing the data pertaining specifically to the individual case), and secondly via cross-case comparison of insights between cases. This logic was also followed by Ellis-Chadwick et al (2002). Within-case analysis provided descriptive insights that helped build an understanding of each bank’s approach to online marketing, RM, and the outlook on the role of social media (Ellis-Chadwick et al, 2002). Cross-case analysis helped identify literal and theoretical replications across cases (Yin, 2003).

Data gathered from interviews with key informants was transcribed from the audio recordings and converted into text for the purposes of analysis. The recordings were transcribed immediately after the interviews in order to allow the researcher to spot areas for additional discussion. Thus, transcription of interviews occurred as the data was collected.

Data from interviews was analyzed by employing thematic analysis of the text from the interview transcripts (Hancock and Algozzine, 2006; Stavros and Westberg, 2006; Yin, 2003). According to Vaismoradi et al (2013), thematic analysis is defined as a qualitative descriptive approach of data analysis, involving the effort to discern the patterns and themes within the data, to analyze how themes are constructed, and to report prominent themes and constructs extracted from body of data. It essentially entails the practice of segmenting the text into smaller units of the content, containing distinct ideas, and then subjecting these segments to descriptive treatment (Vaismoradi et al, 2013, p. 400). Due to meticulous and thorough approach to reporting on the patterns of ideas emerging from the body of data, thematic analysis is valued for its rich, complex and detailed account of the data (Vaismoradi et al, 2013).

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Some of the key characteristics of thematic analysis in qualitative research are provided in Figure 5.

Figure 5: Characteristics of thematic analysis, adopted from Vaismoradi et al (2013, p. 399).

Thematic analysis was based on the following sequential phases of data processing, described by Vaismoradi et al (2013, p. 402):

1) Becoming familiar with the data: transcribing interviews, re-reading

interview transcripts, taking notes and summaries about the ideas for the possible categories and themes;

2) Generating initial codes: assigning codes to the data systematically across

the entire data set, codes emerge from the terminology used by participants in interviews, organizing data by codes;

3) Searching for themes: organizing codes into potential themes, assigning

data to each potential theme;

4) Reviewing themes: cross-checking how data is attributed to themes,

generating thematic map;

5) Defining themes: refining the specifics of each theme to arrive to the

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6) Producing the report: selecting vivid and compelling examples from data

excerpts, drawing comparisons across emergent findings and existing knowledge from the literature, producing the final report on findings. According to Vaismoradi et al (2013), a theme is an abstract entity, which

“captures something important about data in relation to the research question and represents some level of response pattern or meaning within the data set” (p. 402).

Themes were discovered and formulated following the inductive approach, whereby codes and themes emerged from the data and themes were data-driven, rather than trying to fit the data into the pre-established models (Vaismoradi et al, 2013). Patterns and links across themes were identified and outlined, which helped to develop constructs answering the research questions (Hancock and Algozzine, 2006; Yin, 2003). Appendix C provides an example of a summary sheet of categories explored during one of the interviews with the management of Bank A, which demonstrates how themes were identified.

Documentation gathered for the construct of case studies was translated in English (using Google Translate online service) and was analyzed for information that corroborated the insights discovered in the interviews with the managers. Documentation was incorporated as an evidence supporting the insights gained from the interviews, and thus enabled an internal validation through in-case triangulation (Eisenhardt, 1989; Yin, 2003).