Valid and reliable research is pivotal to successful sport marketing strategy. Market research may be gathered via either quantitative or qualitative means. This paper explores the theoretical background and practical applications of qualitative research techniques. It explains the appropriate context for qualitative approaches, and discusses sampling procedures with particular emphasis on the powerful but simple technique known as theoretical sampling. In addition, it clarifies and explores data analysis procedures. The purpose of this paper is to provide sport market research practitioners with a model for implementing qualitative methodologies in sport marketing campaigns.
Successful sport marketing decisions are based on good information. This information, or market research data, provides the sport marketer with reliable data concerning the 'market' and the consumers it contains. Market research is the process of learning what customers want, listening to their desires and expectations, and determining how to satisfy those wants (Mullin, Hardy & Sutton, 1993; Pitts & Stotlar, 1996; Shilbury, Quick, & Westerbeek, 1998; Smith and Stewart, 1999). In addition, it is used to assess how customers react to a marketing plan. Thus, market research cannot only be used to answer specific questions; it is also concerned with the following broad issues about the market:
The answers to these questions may be sufficient to generate a marketing strategy, but they can also be broken down into dozens of others in order to produce greater detail. In general, the more detailed and expansive the information collected, the more effective the marketing program is likely to be. However the catch is, the greater the detail, the greater the cost of the market research. Thus, the problem facing small and resource-challenged sport organisations is that market research is expensive, time consuming and expertise-intensive. For these organisations, the solution is to find a cost-efficient approach while avoiding the pitfalls of poor research. Qualitative techniques provide a tenable alternative to traditional models based on lengthy questionnaires directed to large sample groups, and the subsequent need for costly analysis.
In general there are two primary data collection approaches to market research: quantitative, which generates superficial data from a diverse and sizeable sample, and qualitative, which produces in-depth information from a narrow and relatively small sample. In practical terms, as far as the sports marketer is concerned, this means that information about the marketplace can either be collected through in-depth conversations with key constituents of that market, or by collecting impersonal but generalisable statistical information from a broad representation of the market. Both approaches have their strengths and flaws depending upon the class of the information that the sports marketer wants, and the available resources (Kumar, 1996). However, for the purposes of this paper, we shall confine our discussion to qualitative methods, with the objective of providing a low cost, but valuable market research alternative.
Qualitative research can be defined as a systematic, empirical strategy for answering questions about people in a bounded social context (Golden-Biddle & Locke, 1997), such as a sport market. Like most other methodological approaches, qualitative research seeks to answer the question: "What's going on here?" (Golden-Biddle & Locke, 1997). However, qualitative research differs from conventional scientific inquiry in two major respects: first, the assumptions the researcher makes at the strategic level (how they view the world), and second, the methods employed (how to do it).
In qualitative research, significant attention is paid to the research assumptions, and the subjective views of respondents. This so-called "interpretive" approach emphasises that people's individual and collective thinking and action has a meaning that can be made intelligible (Minichiello 1995). In other words, an interpretive approach seeks to explain the behaviours of people in terms of the meaning it holds for them. Like all sound research, it retains the assumption that the goal is to describe and explain reality without a value bias. However, the interpretive viewpoint rejects the possibility of creating generic laws (Bain, 1989). As a result, qualitative sports market research focuses on the perceptions, opinions, beliefs and practices of individuals, and the assigning of these views with an underpinning meaning (Patton, 1990). The results of qualitative market research must be considered within the "unique" context of each marketplace. That is, each set of results are a 'focused and bounded phenomenon' embedded in a specific place (Miles & Huberman, 1994). To put it another way, it is acceptable to "break down" the views of one specific sport market into a common concept or theme, but it is not acceptable to assume that the data will be relevant or transferable to another sport market.
To summarise thus far, qualitative research is based on the theoretical and methodological principles of interpretive science (Sarantakos, 1993). According to Sarantakos (1993), qualitative analysis contains a minimum of quantitative measurement, standardisation and mathematical techniques. Moreover, the process of qualitative research brings together collection and analysis of the data in such a way that the identification of data leads automatically to its analysis, which in turn directs the area in which data should be sought and identified in order to be analysed again. This ongoing process culminates in the development of new concepts and theories, which can explain market characteristics in ways impossible with quantitative techniques.
Qualitative research can be further distinguished from quantitative research methods by its fundamental approach to solving the research question. For example, quantitative methodologies generally separate the research object from its context, whereas qualitative research assumes that the social world is a human creation, not a discovery (Denzin & Lincoln, 1994; Sarantakos, 1993). Thus, qualitative market research attempts to capture reality as it is; as seen and experienced by the consumers. In addition, qualitative research perceives the researcher and the researched as two equal components in the same situation, where each are viewed as holistic individuals rather than being reduced into their constituent parts. In other words, the researcher and participant engage in an "interactive process" where "words and observable behaviour" become the primary data (Marshall & Rossman, 1995, p. 4). Reducing people into numbers and statistics implicitly causes a loss of perception of the subjective nature of human behaviour (Denzin & Lincoln, 1994; Hamilton, 1994; Sarantakos, 1993). But data collected in qualitative research is gathered verbally, producing descriptive data, presenting the respondent's views and experiences in their own words, which once analysed and conceptualised can provide a revealing explanation of consumer behaviour (Patton, 1990).
Qualitative market research has traditionally been unpopular for exploring sport markets. This is principally the result of confusion concerning the appropriate application of qualitative techniques, and uncertainty about the quality of data they generate. Quantitative procedures provide admirable data when used on broad samples and most managers feel comfortable with an array of numbers and percentages. Moreover, the validity of this quantitative generated data is assessed on the basis of statistical generalisability. While this is obviously important, little attention is given to the validity of the questions asked in the first place. Quantitative methodologies that employ questionnaires and scaled responses rarely generate the "hidden," "deep" or elusive information that is often necessary to solve the research problem. It is for this reason that qualitative data, if collected first, can provide the detail necessary to frame subsequent quantitative inquiries. Therefore, when the aims of sports market research are essentially exploratory, a qualitative approach can be used effectively. In other words, if the focus of the research is on gaining a broad understanding of marketplace issues, then a qualitative methodology is an ideal starting point.
Every market research technique requires a structured and duplicable method of selecting who in the market will be questioned. Qualitative research typically utilises a small sample representing the key constituents in the market under scrutiny. This is usually called "purposeful sampling," which contrasts with quantitative approaches, which "depend on larger samples selected randomly" (Patton, 1990, p. 169). The difficulty is determining the identity of these key constituents, and subsequently selecting an appropriate and representative group of informants. Theoretical sampling is a solution to this problem (Patton, 1990).
Theoretical sampling is one of the most powerful weapons in the arsenal of qualitative market research. Although it is not widely known, it is simple, inexpensive, requires little expertise, and has the potential to change the face of market research approaches.
Theoretical sampling hinges upon the selection of consumers, "respondents" or "informants" on the basis of the relevant categories, issues, themes, and concepts that emerge prior to and during data collection (Minichiello, 1995). The object of theoretical sampling is to uncover diversity by facilitating the identification of a full range of possibilities that are theoretically relevant to the research question (Strauss & Corbin, 1990). Simply speaking, a market researcher may already have pieces of vague data or some educated suspicions about the behaviours and perceptions of customers they are studying. These ideas become "working" theories; serving as beginning points that are confirmed or rejected as the research proceeds, and which point the way to additional data to be collected next in order to explore aspects of the modified working theory that have become important (Sarantakos, 1993). Thus, by using theoretical sampling, the data-collection and data-analysis components of the research are conducted simultaneously (Strauss, 1991). Each piece of analysed data provides information about where to look next for further data. The initial "working" theory is continually modified as a consequence of further investigation, until it stands up to all additional data. At this point the working theory may be considered final.
For example, we may begin with the working theory that males are biologically more aggressive than females, and therefore will have a greater preference for contact sports than females. However, when the notion is explored, other factors, such as class, income, occupation, geographic location, upbringing, nationality, sexuality and personality may also have an impact. The point is that we don't know the range of probable causes and influences until we start to gather information about the question. Thus, through analysis, the market researcher is directed to a wider informant base, who are approached next in order to explore aspects of the working theory that have become important, and may subsequently shift the original theory more in line with "reality" (Sarantakos, 1993).
A colourful example may explain where the prosaic principles fail. Let's assume that we're running a gymnasium, and we're conducting market research to gain an insight into the fundamental question: Are our customers satisfied with the services they being delivered? We want detailed responses, and we recognise that some of the information we require in order to improve our services may be elusive and difficult to extract by using "number-crunching" methods. The only way to gather the information is to talk to a cross section of customers, in an "in-depth" manner. The problem is whom do we talk to? Theoretical sampling provides the answer.
We may know from membership records that our members are predominantly aged between 20 and 50, consist of both genders (M and F), and appear to use the gymnasium for either health/fitness reasons (H) or to bolster sport performance (S). Our experience "on the floor" with members also indicates that different age groups have different requirements and women generally have different expectations to men. These are our "theoretical" starting points, and are expressed below in Table 1.
As the table shows, we have generated eight categories of consumers. For example, the first is represented by a male between the ages of 20 and 35, and uses the gymnasium for health and fitness reasons, while the second is a male between the ages of 20 and 35, and uses the gymnasium to enhance their sporting performance. Now we have a representative sample (in qualitative terms only - it is not statistically representative) to work with.
A customer from each of these categories may now be approached for an in-depth informal or formal discussion about their opinions, criticisms, ideas, and lifestyle. Of course, you can't expect customers to reveal confidential details, but if treated with respect and courtesy, most are prepared to discuss their needs frankly. How customers are "enticed" into this discussion process is situation specific. In our hypothetical gymnasium, for example, staff are friendly with members, many of whom are willing to spend up to one hour "voicing their opinions" while they performed their stationary cycling. Alternatively, small incentives, such as a week of free solarium use or an extra month of membership would be sufficient to entice most members to reveal their views and opinions to an interviewer.
The beauty of the theoretical sampling method is that it is intrinsically flexible. The anticipation of "discovering" additional factors that may affect the original question is built into the model. For example, after completing several interviews, it may become apparent that there is another motivation for attending the gymnasium that was previously overlooked. The social factor (S) now becomes an important discussion issue. Thus, the data gathering process provides additional detail for a revised sample, which is represented in Table 2.
The theoretical sampling process should continue until no new information is discovered. This may mean that repeat interviews may be conducted in certain categories of consumers. When this "saturation" level had been reached, the collected information can be categorised on the basis of common themes and issues. In our gymnasium example, you may find that safety, instructor qualifications, pool maintenance, reception staff and equipment variety are frequently discussed, and need to be addressed by management. It may also become apparent that some categories of customers will have different responses to other categories of customers. For example, women aged 20-35 who value the social interaction may emphasise staff friendliness, while men aged 36-50 who value fitness may focus on equipment quality and instructor credentials.
The great strength of theoretical sampling is that it not only ensures an appropriate cross section of informants, but also immediately identifies the categories that can be used for assembling and analysing the data.
Formally defined, an interview is a verbal exchange wherein an interviewer attempts to access the opinions or beliefs of an informant (Burns, 1994), or in this case, a sport consumer. In structured or standardised interviews, every informant receives the same questions in the same sequence. This approach forces informants to respond only to the fixed question, and subsequently the information elicited reflects the depth and insight of the questions previously established by the designer of the questionnaire (Patton, 1990). There are several disadvantages to this method of interviewing. Firstly, the researcher has no flexibility to determine the beliefs, feelings, attitudes and perceptions of the respondent beyond those already highlighted by pre-determined questions. Secondly, in using a structured interview, the interviewer must become a neutral, standardised medium wherein questions are presented without bias or subjectivity. As a result, the method fails to acknowledge the inherent "humanness" of the interviewer. Finally, the detachment and impersonal approach required can prevent trust and rapport from developing between the interviewer and the respondent (Burns, 1994). Strictly structured interviews are therefore little better than scaled response questionnaires.
Unstructured interviews dispense with formal interview schedules and ordering of questions, and rely substantially on the interaction between interviewer and informant in order to gain information (Minichiello, Aroni, Timewell, & Alexander, 1995). Unstructured interviews take the form of conversations between the interviewer and the respondent, and according to Burns (1994), they focus on the informant's perception of themselves, of their environment and of their experiences. No questions are pre-determined or standardised. The medium for information gathering is a free-flowing conversation, relying on the interaction between the participants (Patton, 1990). The onus is on the interviewer to use their interpersonal skills to subtly direct the conversation (Fontana & Frey, 1994). The interviewer allows the informant to control the conversation, but at the same time asks questions to clarify issues, or highlight comments made tangentially. The interviewer will only casually and indirectly change topics or subjects.
Burns (1994), argued that there are many advantages to in-depth or open-ended interviews. One advantage is the greater degree of informality involved, leading to a stronger rapport. Secondly, the informant's perspective is more easily expressed, rather than the perspective of the researcher being imposed. Thirdly, the informant has the opportunity to express themselves in language natural to them, instead of being forced to fit their language within the context and concepts of the study. Finally, the conversation medium of the in-depth or open-ended interview affords the informant equal status to the researcher, thereby enhancing rapport and trust (Burns, 1994; Fontana & Frey, 1994).
Burns (1994), May (1993), and Minichiello et al. (1995), all caution that unstructured, open-ended interviews should be used judiciously. Open-ended, unstructured interviews are appropriate when the objective of the research is to obtain an individual's subjective experiences reported in their own language; when access to activities, or events cannot be directly observed by the researcher; when more subjects are needed to be studied than can be practically achieved using observational techniques; and when more than one individual is being interviewed at one time.
The major disadvantage of open-ended, unstructured interviews is that the researcher is vulnerable to the interpretations and insights of the informant. As a result, the researcher may be drawn into the informant's world-view. According to Burns (1994), this problem of validity is inconsequential if the informant's behaviour is congruent with their perception of reality. However, the problem remains that the researcher is unable to view first hand the context in which the informant's reported perceptions occur, and not being able to observe the informant's behaviour. In this setting for example, if an informant indicates that the gymnasium facility is over-crowded at certain times, it is impractical to replicate the over-crowding, or to observe their behaviour in other crowd situations. It would be prudent to acknowledge that this is a limitation of the in-depth interviewing research technique. Nevertheless, the in-depth, unstructured interview remains the chief information-gathering tool for the qualitative market researcher.
The fundamental tool of qualitative market research is the interview, which can be applied in a variety of situations. One potent method of integrating interview data is the focus group. In focus groups, a number of respondents from the population being studied are gathered in an informal setting, and encouraged to talk about specific issues (Linda, 1982). The participants of a focus group typically share some characteristics and features that are of particular interest to researchers. The involvement of a moderator who can coordinate the group without inhibiting, intimidating or leading the respondents is necessary, so that ideas are free-flowing and all opinions are expressed (Krueger, 1994). The directed group discussion is repeated with other participants until some consensus is reached and dominant trends, patterns and opinions have come to the fore. Ultimately, the systematic coding and analysis of focus group data can provide market researchers with insights into how products or services are perceived, whether they are delivered satisfactorily and what opportunities may exist for future product and service innovations. (Coe & MacLachlan, 1980).
Once market research data is collected, it needs to be compiled, interpreted and analysed. Coding is a critical method of data organisation and analysis. According to Miles and Huberman (1994), analysis involves reviewing notes, audio or videotapes, transcribing or synthesising them, then dissecting them meaningfully, while keeping the relations between the parts intact. They specified that coding is the part of analysis wherein the researcher differentiates and combines the data retrieved, and reflects upon this information. Miles and Huberman (1994), defined the term "codes" as tags or labels for assigning units of meaning to the descriptive or inferential information compiled during research. Polgar and Thomas (1991), take a similar view, and indicated that coding is a process in which data obtained from interviews is systematically organised and classified. Subsequently, these codes are attached to "chunks" of varying size; words, phrases, sentences, or whole paragraphs (Miles & Huberman, 1994).
Any information obtained from an interview should first be broadly studied to gain a general familiarity of the contents. During this process, dominant concepts, themes, and issues should be noted to form categories; these categories becoming the codes with which the transcript will be interpreted and meanings developed. Thus, coding by using keywords is a tool of analysis used by researchers in order to categorise or classify the text (Sarantakos, 1993). During the coding process, keywords are applied to sections of the text, which give specific meanings to the text as well as providing a label for the section. As Miles and Huberman (1984) acknowledged, these codes help to reduce and analyse data and direct the researcher toward trends, themes, patterns, and causal processes.
There are many types of coding. Coding may be used at different levels of analysis, ranging from the descriptive to the inferential. It can also occur at different times during analysis (usually the descriptive first then the inferential), and can reduce data, combining it for easier analysis (Miles & Huberman, 1994). However, the basis of coding is the reduction of large amounts of data into small amounts of data, through the process of categorisation. Take, for example, the gym case referred to earlier. After examining several interviews, some common themes may emerge like safety, instructor qualifications, reception staff friendliness and equipment variety.
Coding is generally undertaken in three stages, as first recommended by Strauss and Corbin (1994). They call the stages open, axial and selective. These three coding methods are not different, but sequential and interrelated. Each is built upon the previous. In this way, the lines between each type of coding are artificial (Strauss & Corbin, 1990). Thus, in a session of coding, it is possible to move between one form of coding and another. The reason for this, as Strauss and Corbin (1990) appreciated, is that during the third or final stage of coding, there are always some concepts that remain undeveloped and ambiguous. At the same time, during the first stage of coding, some concepts will naturally progress to the more developed stages achieved later. For the purposes of market research, to simplify the process, we recommend coding in two, rather than three stages.
The first stage of coding involves breaking down, examining, comparing, conceptualising, and categorising data (Strauss & Corbin, 1990). Interview transcripts should be studied with the objective of assigning a code or label to every relevant piece of information. In this initial phase, the categories are broad and inclusive, rather than specific and selective. Note that in Table 3, below, despite the broad range of issues that arise, only one code category is assigned to the piece of information collected from our hypothetical gym research project.
|Sample category: Male, 20-35, Fitness focus, Interview transcript||Code category|
|Actually I find the gym staff quite helpful and friendly. Most of the time they're quite prepared to help out whatever you're doing. Although sometimes I get a bit annoyed when they're just chatting away to each other. It's like they don't even realise that they're at work and should be looking for ways to help. Even if they were just cleaning up or something. I often end up kicking a dumbbell or some piece of equipment that's been left around. I know we're not supposed to leave them around, but people do, so someone's got to put them back, or else sooner or later someone's going to trip over and really hurt themselves one day. But if you ask them for help with something, whether it's just advice or help in adjusting equipment or something like that, they're great. Happy to help.||GYM STAFF|
The purpose of this initial coding stage is to reduce the data into a more condensed form, allowing broad, but definitive categories to emerge. Once particular phenomena are identified in the data, concepts are grouped around them. This is done in order to further reduce the volume of data. Thus, codes break the data into more manageable chunks, or preliminary concepts, ready for subsequent and more precise reduction in the second stage. Thus, the coding process moves in descending order, always combining and reducing data. It is helpful at this point to restrict the number of codes to no more than ten, and once applied, should be removed by category and placed in separate computer files.
In the second stage of coding, deeper patterns, strategies, categories and concepts are identified from the first codes and sub-categories/codes are developed. Table 4 illustrates this process for our gym research.
|"Gym Staff"||Sub-code category|
|Actually I find the gym staff quite helpful and friendly.||Positive service|
|Most of the time they're quite prepared to help out whatever you're doing.||Positive service|
|Although sometimes I get a bit annoyed when they're just chatting away to each other. It's like they don't even realise that they're at work and should be looking for ways to help.||Negative Service|
|Even if they were just cleaning up or something.||Suggestive service|
|I often end up kicking a dumbbell or some piece of equipment that's been left around.||(Removed and place in code category "SAFETY")|
|I know we're not supposed to leave them around, but people do, so someone's got to put them back, or else sooner or later someone's going to trip over and really hurt themselves one day.||(Removed and place in code category "SAFETY")|
|But if you ask them for help with something, whether it's just advice or help in adjusting equipment or something like that, they're great. Happy to help.||Positive service|
Table 4 highlights three sub-codes that help break down the volume of information initially obtained from the interview. Note that two sections of the transcript were removed and sent to another category. As before, all common sub-codes should be removed as well and placed within a separate file. Each sub-category subsequently informs the marketer about the results of the research. For instance, if the information from this example were consistent with results from interviews with customers representing other sampling categories, then we have some clear feedback concerning the service quality provided by gymnasium staff. If however, the results from each sampling category are different, there may be justification for undertaking further analysis.
The fact that qualitative market research is typically conducted on a small number of selected participants is troublesome for ensuring the generalisability of findings. This is exacerbated by the arduous nature of data collection and analysis that limits the quantity of practical activities that can be undertaken within a short time period. Naturally, qualitative market research data is not strictly generalisable, but does, of course, provide depth of insight that cannot be achieved by statistical procedures. The limited generalisability, therefore, may be considered a legitimate price to pay for a corresponding improvement in depth and quality (Krueger, 1994). However, the goal in qualitative market research is to understand reality and reveal underlying meanings and values. The inductive nature of qualitative market research allows researchers to gain a greater appreciation of the manner in which respondent's perceive the problem in question. The outcome for the researcher is a comprehensive idea of how the respondent perceives the issue, which in turn should allow the researcher to generalise these understandings to other respondents who share similar characteristics.
Qualitative market research's claim of validity can sometimes be a contentious issue. Validity is the degree to which a method or procedure actually measures that which it purports to measure (Krueger, 1994). In qualitative research, validity is based in the relationship between the researcher and the respondent. According to Mariampolski, 1984), it is the researcher's capacity to probe, challenge and seek truthful responses that allows qualitative approaches to yield insightful results.
In qualitative market research, validity is measured in two major ways. The first is known as face validity, which refers to the extent to which results appear valid. Qualitative market research results tend to have high face validity, which is an outcome of the believability of the comments from participants. The other type of validity is known as convergent validity. It measures the degree to which results are confirmed by future behaviours, experiences and events, (Morgan & Spanish, 1984). Both face and convergent validity are strengthened when the data is based on deep responses from a variety of respondents that range from the normal to the eccentric. In other words, the responses are genuine and authentic (Berg, 1998, p. 203).
One of the strengths of qualitative research is its capacity to provide rich and evocative stories. At the same time, these stories may contain a variety of meanings, and are therefore subject to multiple interpretations (Denzin, 1994). The problem of interpretation can be compounded by researcher bias (Miles & Huberman, 1994). This begs the question as to which interpretation is the more credible and dependable.
A number of strategies can be used to improve the credibility of the results, and confirm the findings. First the researcher should always give appropriate space to respondents who, while on the surface, may be excessively different, may also provide especially insightful views. These extreme cases can provide a counter-balance to the researcher's pre-dispositions, and challenge the views of the more conservative respondents (Miles & Huberman, 1994). Second, the researcher should aim to triangulate the data. This involves obtaining data from more than one source, and using more than method to get it (Berg, 1998). Take for example, the gymnasium case we referred to previously. An employee interview may provide a passionate statement about the importance intensive activity, but it would be prudent to seek confirmation from a sample of users, and some quantitative data on gym usage rates.
According to Minichiello et al. (1995), typologising is a method that researchers commonly use to understand phenomena more completely by grouping ideas and then forming ideal types. In other words, it is a method of making sense of complex or abstract ideas. Summarising the data contained in each sampling category generates these ideal types. Ideal types are so termed because they do not exist in reality, but instead are intellectual constructs that represent reality for the purpose of understanding reality. While the purpose of typology construction, like all analysis procedures in qualitative research, is to clarify and summarise large volumes of data, is also has the added benefit of signalling potential market segmentation strategies. An example from our gym research appears below in Table 5 below. Again, it highlights the strength of our theoretical sampling model, which provides the foundation for the typologies.
In any research it is necessary to acknowledge the limitations intrinsic to the system of data collection and analysis used. Firstly, it is clear the great strength of qualitative strategies is their usefulness in uncovering deep responses. The corollary of this strength, however, is that qualitative research is severely limited in its ability to ensure a broad coverage of responses. In other words, only small segments of the population can be used in the sample. Subsequently, qualitative data does not lend itself to statistical manipulation. As a result, data obtained from qualitative sources are subject to lengthy analysis and discussion, but are rarely statistically representative in any way. The data is statistically reliable, and cannot be summarised in numerical form alone.
Another consequence of this style of market research is the relative importance of sample selection. As there are comparatively few respondents, they must be chosen carefully. Theoretical sampling will usually provide a good cross section of the population or market being studied. It will therefore extract an appropriately broad range of information from the research question. The risk of working with unrepresentative and seriously biased samples will be minimised by good theoretical sampling design.
All market research has cost limitations. It can be time-consuming and resource-intensive to conduct in-depth interviews or focus groups just as it is to develop a generic questionnaire, mail it and feed the results into statistical software. According to Krueger (1994), qualitative research and analysis has three principal phases, each of which will incur a cost upon an organisation. The first phase is planning and background research. While this step can vary considerably in scope, it does not necessarily have to incur any physical expenditure, but will require time. The second phase is data collection. Again, despite the time-consuming nature of the data gathering tools used in qualitative research such as in-depth interviews, there are few cost burdens. Typically, a mini-cassette recorder and tapes are the only equipment required. Finally, qualitative research involves an analysis phase. Assuming interviews have been transcribed, it may take between four and five hours to code the results of one hour of data. Additional costs associated with qualitative market research techniques may include travel expenses, phone costs and tapes / batteries. In general, qualitative techniques are time-consuming, but lack the need for expensive software or equipment. Table 6 provides a summary of the costs and sacrifices associated with various forms of market research.
|SPEED||Telemarketing questionnaire||COST & DEPTH|
|DETAIL||Interviews: Focus groups or theoretical sampling||BREADTH & TIME|
|BREADTH||Mail out detailed questionnaire||COST & TIME|
|LOW COST||Suggestion boxes / complaint analysis / interviews||TIME & BREADTH|
|ACCURACY||Theoretical sampling combined with mail out detailed questionnaires||TIME & COST|
|CONVENIENCE||Nothing is convenient||EVERYTHING|
|VERSATALITY||Interviews: Theoretical sampling or focus groups||BREADTH & TIME|
|LOW EXPERTISE||Suggestion boxes & complaint analysis||BREADTH & DEPTH|
|VALUE FOR LITTLE OR NO MONETARY INVESTMENT||Theoretical sampling||BREADTH & TIME|
|VALUE FOR MONEY||Telemarketing questionnaire||COST & DEPTH|
It is also worth noting the challenges and pitfalls that qualitative market researchers may encounter. The first typical revolves around the acceptance of qualitative techniques in a research climate that is accustomed to statistical procedures. The principle objection is one of generalisability. However, as we noted earlier in this paper, qualitative market research is not designed for broad generalisation, but for in-depth insight into the ways in which participants understand the issues under consideration.
The second challenge is that data are more difficult to collect and analyse than conventional quantitative approaches. It requires skill to adequately tease out the appropriate information from respondents and considerable experience to analyse the subsequent data systematically. In addition, the end product is not necessarily as easily digestible or as concrete as a simple numerical solution.
Finally, respondents can vary in usefulness. Some are highly cooperative, can provide detailed personal opinions, and can add substantial depth to a study. Others offer monosyllabic, superficial responses that add nothing to the final data set. Participant groups are always patchy, and require constant evaluation and monitoring to ensure that saturation has genuinely occurred.
Qualitative market research can provide pivotal information about the values, beliefs and behaviours of sport consumers. We examined the principles of qualitative market research techniques, and explained how effective sampling procedures can be put in place. We also demonstrated the process for analysing and interpreting qualitative data. An integrated approach to qualitative research will consequently generate a rich source of market information that goes beyond a summary of bias and dislike. Its great strength is that it not only teases out the underlying motivations and needs of customers, but also allows the researcher to establish a valuable typology of sport customer responses and behaviours.
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+Aaron Smith,Ph.D., has worked as a Senior Lecturer in Deakin University's Sport Management Program, specialising in change management and qualitative research. He also previously taught at Victoria University for five years. Aaron is the co-director of Manage to Manage Australasia which has consulted to professional sport clubs, national and state sport associations, entertainment companies, local government and private enterprise, offering consulting and market research services. He is the author of numerous journal articles and the book, Sports Management: A Guide to Professional Practice, published by Allen & Unwin in 1999. Aaron holds a doctorate in business management and is an active proponent of qualitative research techniques. Correspondence regarding this article can be addressed to Bowater School of Management and Marketing, Deakin University, 221 Burwood Highway, Burwood, 3125 Melbourne, Australia or firstname.lastname@example.org.
+Bob Stewart, Ph.D., is an Associate Professor in the Sport Management Unit at Victoria University, Melbourne, Australia. Bob is the co-author of Sports Management: A Guide to Professional Practice. Bob is also the co-author of More Than A Game: An Unauthorised History of Australian Football, published by Melbourne University Press in 1998. Bob holds a doctorate in corporate history. He is currently undertaking qualitative research on sport fan formation, identification and loyalty. Correspondence regarding this article can be addressed to the School of Human Movement, Recreation & Performance, Victoria University of Technology, PO Box 14428, Melbourne City MC 8001 or email@example.com.
Smith, A., & Stewart, B. (2001, June). "Beyond number crunching:" Applying qualitative techniques in sport marketing research. [54 paragraphs]. The Qualitative Report [On-line serial], 6(2). Available: http://www.nova.edu/ssss/QR/QR6-2/smith.html
Aaron Smith and Bob Stewart
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