Analysing Qualitative Data

Research Methods for Business

Analysing qualitative data

In qualitative research, the analysis process begins as soon as any data has been generated, so that the initial findings can be fed back into the design process. This iteration of data collection and project design is crucial for the validity and reliability of qualitative research. It is through this procedure that the project remains data driven, to maintain its coherence and authenticity with the results that are ‘grounded in the data’.

However, analysing qualitative data is not a clear-cut procedure. It is a very time consuming process, handling many thousands of individual details that require meticulous attention to detail. There are important prerequisites to start the process:

  • an intimate knowledge of the data itself;
  • a comprehensive understanding of the culture within which the problem occurs;
  • a record of the problems and issues that were addressed in the data collection process;
  • a thorough knowledge and understanding of the relevant theoretical frameworks;
  • the choice of method selected must be appropriate to these contextualising factors, and most importantly, to the type of questions for which findings are sought.

There are a number of guidelines that underpin all qualitative analysis. These relate to the analytical process that seeks to examine the data from first principles, so that the findings emerge independently of any other material. This process, known as induction, means that the results are unique to this specific substantive data. The researcher’s role, therefore, is to engage with the data to inductively tease out the key issues and themes.

How, then, can this be achieved? Initially the researcher must immerse her/himself in the data by reading it through thoroughly many times. The main problem for qualitative data analysis is that in the study of social life, the data is often concerned with the ‘everyday activities’ that the researcher and the participants take for granted. A reading through of the transcripts can often lead to the response ‘so what’! How, then, can the researcher, whilst being necessarily sensitive to the culture of the data produced, at the same time, stand outside to see the themes, issues, ideas, actions, and so on? The solution can be found via an active interrogation of the data that elucidates the significance of seemingly everyday talk or behaviour.

One way this can be done is by asking questions such as what? where? when? how? or why? Further insights can be derived by the transposition of each response or action to a different context so that the comparison highlights the important issues of this particular example: what if this was different in type, kind, time, place, event, gender, age, and so on? This transposition often throws up the importance of what is occurring, and leads the researcher to deeper levels of understanding about the significance of the data. For example, the different nature of the social interaction of self service dining out to that of waiter service raises a raft of other interesting issues about the role of service; meanings in food consumption encounters; and so on. As answers to these questions are generated, they provide both a set of new questions with which to interrogate the data, and a range of issues and themes that can be grouped together in types, and labelled into analytical categories.

There are other sets of useful approaches that help the researcher to pursue an in depth analysis inductively. For example, what are the regular patterns, events, taken for granted beliefs at work here; and, what are the extraordinary or special incidents, procedures, beliefs, etc; what strategies are adopted by respondents to get things done; what sorts of relationships/structures exist: formal, informal, power, cliques, responsibilities; what might be the role of the different settings in which this phenomenon take place; how do different respondents choose to define similar situations, social interactions, beliefs, etc; or what sorts of processes are involved in this data: sequences; changes; transformations?

The quality of the analysis can be further enhanced by the constant comparison method that seeks to confirm each emergent concept with supporting data from within the same respondent/event, as well as the others in the sample. During this process, it is equally essential to identify where there is non-supporting data. In the case of non-supporting data, questions such as who, where, what and why are again useful ways of teasing out significance of what is happening and why this contradiction should occur.

The process is therefore to read and annotate, to define the units of data and to organise groups of issues into categories. However, this is not the end of the analysis process. The search for in-depth understanding, a ‘thick description’ of the research phenomenon, requires the researcher to transform the data into higher level of understanding, to generate tentative explanations. The researcher, therefore, seeks to make more sense of the nature of the categories identified and the links and relationships that occur between them, to produce an explanation or theory of what is really going on. The process of transforming the initial analysis into a deeper understanding of the complexities of the research problem can be greatly assisted by the application of conceptual models from the contextualising theoretical frameworks that have been identified in the literature review.

The conceptual models derived from these theories are usually of two kinds: those that are related to the philosophical and methodological bases of qualitative research; and those that are related to the substantive and formal theories of the topic area. Within qualitative research methodologies, certain analytical models have been developed which assist the researcher’s pursuit for understanding of the deeper realities in the research problem, and also take account of the underlying premise that because reality is socially constructed, many possible realities can exist. These approaches allow the researcher to access certain dimensions or facets of the realities constructed by the research subjects: for example, social interactionism, member categorisation, discourse analysis, and semiotic analysis. These conceptual approaches offer the researcher additional insights about the data and the respondents’ world, to foster a richer and more authentic holistic understanding:

  • Social interaction-ism superimposes a framework over the findings to tease out the number, type and characteristics of different types of social interaction that are occurring; for example, in an hotel or restaurant they would be staff/staff, staff /manager, staff/ guest, guest/guest and so on.
  • Member categorisation analyses the data in terms of how respondents associate themselves and other actors into different categories, and what these categories are: for example, the manager of food and beverage may associate himself with the food and beverage group, and/or the restaurant team and so on, but the staff might associate him with the ‘management’.
  • Discourse analysis is a term that can be used in various ways. For our purposes, in qualitative research methods, it normally refers to a concern with how things are said or done rather than just with what is said or done. These details are often simple nuances, sometimes non verbal communication, but they do change the meaning of the exchange/event to some degree. For example, the nature of the social interaction between service staff and customers in the University canteen is different for young students than it is for staff or mature students, even though the result, purchasing a meal, is the same.
  • Semiotic analysis offers a more comprehensive approach to understanding how the true meanings of communication take place. Allied to discourse analysis, it offers the researcher specific ways to interrogate the data beyond the obvious words, to interpret a dominant meaning from the overarching ideological chains of meaning.

In the same way, theoretical frameworks associated with the substantive problem and its formal theoretical context, also help the researcher to recontextualise the data into higher level explanations. These theories will differ according to the research topic. For example in research of television food programmes, it was found that applying conceptual models derived from media studies theory allowed the researcher to identify and develop substantive theory in regard to television food programmes: the chef as intimate, celebrity personality; the ideological role of the non food segments, etc.

We can conclude, therefore, that although analysing qualitative research data is time consuming and painstakingly demanding, it is also a fascinating and rewarding part of the research process. The quality of this analysis, and the validity and reliability of the findings, are determined at this stage by the thoroughness of the operation, and by the choice and justification of the appropriate analytical approaches. As with all aspects of qualitative research, these choices and justifications must be made clear to the reader and demonstrate the relationship of them to the coherence of the project in ways that can be independently followed in an audit trail. In particular, any non-supporting data must be explicitly identified.

The results of research of this type are not designed to make generalised conclusions. Instead, the results should indicate a range of tentative explanations or theories that conceptualise what is happening in this situation. It should identify the relationship of these concepts to the substantive situation and to the broader theoretical propositions wherever possible. However, where other studies of a similar kind have taken place before, it is expected that the results will contribute to this existing and developing body of knowledge.

Web based Resources and Useful Links:

The website for the ‘Centre for Assessment and Policy Development’. This website includes tools and resources to help evaluate racial equality issues. Includes an array of PDF files examining all elements of research process to ensure a valid strategy and process is adopted:

An analysis of the author’s own research, looking at women’s doctoral research experiences. She looks in particular at the use of narrative and grounded theory in practice.

15 methods of data analysis in qualitative research. compiled by Donald Ratcliff:

Journal Articles

Addis, M & Podesta, S. 2005.  Long life to marketing research: a postmodern view. In: European Journal of Marketing. 39 (3/ 4) pp. 386 – 412.

Burns-McCoy, N. Water is to Chocolate like story is to Qualitative Research. a web article using story as qualitative research. In which it questions credibility and narrative study, it also refers to the notion of validity & impact in qualitative research.

Coffey, A; Holbrook, B & Atkinson, P.1996. Qualitative Data Analysis: Technologies and Representations. Sociological Research Online, vol. 1, no. 1,

Gummesson, E. 2005. Qualitative research in marketing. Road-map for a wilderness of complexity and unpredictability.  European Journal of Marketing. 39 (3/4) pp.309 – 327.

Pope, C; Ziebland, S. & Mays, N. 2000.  Qualitative research in health care: analysing qualitative data. British Medical Journal. 320. January 8. pp.114-116. BMJ article on assessing quality in qualitative research

Electronic Books from Ebrary

Ebrary is a database containing a range of electronic resources consisting mainly of books. Access is restricted to QMUC staff and students only. You will need an Athens username and password for BOTH on-campus and off-campus access

Auerbach, C. F & Silverstein, L.B. 2003.  Qualitative Data: An Introduction to Coding and Analysis. New York, New York University Press. Guidance for interpreting qualitative data. Reassuring for new researchers as it takes you through the whole process. Part three focuses specifically on making the text manageable, effective listening and developing theory.

Daymon, C. & Holloway, I. 2002. Qualitative Research Methods in Public Relations and Marketing Communications. Florence, KY, USA: Routledge. Chapter 16, written by Matt Holland, explains the processes involved in analysing qualitative data. It contains:  useful definitions; how to organise data; coding and categorising including specific examples and a full example on p.236, figure 16.2. How to look for patterns; identify broad themes and interpret the data; developing theoretical concepts; evaluating interpretation; confirming your findings; reflexivity and a list of analytical issues.

Decrop, A. 2006. Vacation Decision-Making. Wallingford, Oxfordshire, UK: CABI Publishing, 2006. p ix. A book which follows the findings of an in depth qualitative interpretive study examining vacation decision making processes of 25 Belgian households. Uses grounded theory method and also gives an over view of decision making paradigms and their relevance to travel behaviour and tourism marketing.

Heaton, J. 2004. Reworking Qualitative Data. London, Sage Publications, Incorporated. Introduction to the concept of using existing data sets for qualitative analysis. Chapter 3 examines ways of analysing secondary qualitative data. It covers supplementary analysis; amplified analysis; supra analysis and assorted analysis where new data is gathered to compare with existing archived data sets. On p.47 it describes how supplementary analysis was used by Whyte in ‘Street Corner Society’.

Holbrook, M.B. 1998. Consumer value: analysis and research. London; New York, Routledge. Contents cover consumer behaviour and consumers research methodology including looking at

value as excellence in the consumption experience

Laws, E. 2004.  Improving Tourism and Hospitality Services. Cambridge, MA, USA: CABI Publishing. Chapter 3 analyses service experiences in tourism and hospitality.

Ten Have, Pl.2004. Understanding Qualitative Research and Ethnomethodology. London, Sage Publications, Incorporated.  Chapter 7 discusses the analysis of qualitative data in particular the origins and use of grounded theory. Includes an appendix covering transcription conventions to help understand ways of coding notes.

Wagner, S. A. 1997. Understanding Green Consumer Behavior: A Qualitative Cognitive Approach. London, UK: Routledge. Chapter 3 takes you through the collection of data and the methods then employed to analyse them qualitatively.   Chapter 4 discusses classification and cluster analysis in relation to consumers.

Yanow, D & Schwartz-Shea, P. eds. 2006. Interpretation and method empirical research methods and the interpretive turn. Armonk, N.Y., M.E. Sharpe. Contents cover: Ordinary language interviewing; Interpretive content analysis; stories and arguments in analytic documents; ‘Talking our way to meaningful explanations : a practice-centered view of interviewing for interpretive research’.

Books (in print) in QMU Library Catalogue

Finn, Mick. et al. 2000. Tourism and leisure research methods: data collection, analysis and interpretation. Harlow, Longman. QMU Library 338.4791072 FIN. Study skills collection.

Janesick, V. J. 2004. “Stretching” exercises for qualitative researchers. 2nd ed. London, Sage. QMU Library: 300.72 JAN. Study skills collection. Content includes the scientific method of observation and qualitative reasoning.

Lehmann, D.R. 1989. Market research and analysis. 3rd ed.

Irwin. QMU Library: 658.83 LEH

Miles,M.B. Huberman, A.M. 1994. Qualitative data analysis. 2nd ed.

Thousand Oaks, Calif., Sage Publications. QMU Library: 300.723 MIL. Study skills collection.

Silverman, D. 2001.Interpreting qualitative data: methods for analysing talk, text and interaction. 2nd ed. London, Sage. QMU Library: 300.723 SIL. Study skills collection.

Original Sources ‘Analysing Qualitative Data’ Lecture Material:

Laffin, T. 2007. MBA Research methods for Business Lecture Notes. Edinburgh, Queen Margaret University.

Randall, S. 2000. Research Module Lecture Notes and workbooks. Edinburgh, Queen Margaret University.