7 strength of qualitative research

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What is Qualitative in Qualitative Research

Patrik aspers.

1 Department of Sociology, Uppsala University, Uppsala, Sweden

2 Seminar for Sociology, Universität St. Gallen, St. Gallen, Switzerland

3 Department of Media and Social Sciences, University of Stavanger, Stavanger, Norway

What is qualitative research? If we look for a precise definition of qualitative research, and specifically for one that addresses its distinctive feature of being “qualitative,” the literature is meager. In this article we systematically search, identify and analyze a sample of 89 sources using or attempting to define the term “qualitative.” Then, drawing on ideas we find scattered across existing work, and based on Becker’s classic study of marijuana consumption, we formulate and illustrate a definition that tries to capture its core elements. We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. This formulation is developed as a tool to help improve research designs while stressing that a qualitative dimension is present in quantitative work as well. Additionally, it can facilitate teaching, communication between researchers, diminish the gap between qualitative and quantitative researchers, help to address critiques of qualitative methods, and be used as a standard of evaluation of qualitative research.

If we assume that there is something called qualitative research, what exactly is this qualitative feature? And how could we evaluate qualitative research as good or not? Is it fundamentally different from quantitative research? In practice, most active qualitative researchers working with empirical material intuitively know what is involved in doing qualitative research, yet perhaps surprisingly, a clear definition addressing its key feature is still missing.

To address the question of what is qualitative we turn to the accounts of “qualitative research” in textbooks and also in empirical work. In his classic, explorative, interview study of deviance Howard Becker ( 1963 ) asks ‘How does one become a marijuana user?’ In contrast to pre-dispositional and psychological-individualistic theories of deviant behavior, Becker’s inherently social explanation contends that becoming a user of this substance is the result of a three-phase sequential learning process. First, potential users need to learn how to smoke it properly to produce the “correct” effects. If not, they are likely to stop experimenting with it. Second, they need to discover the effects associated with it; in other words, to get “high,” individuals not only have to experience what the drug does, but also to become aware that those sensations are related to using it. Third, they require learning to savor the feelings related to its consumption – to develop an acquired taste. Becker, who played music himself, gets close to the phenomenon by observing, taking part, and by talking to people consuming the drug: “half of the fifty interviews were conducted with musicians, the other half covered a wide range of people, including laborers, machinists, and people in the professions” (Becker 1963 :56).

Another central aspect derived through the common-to-all-research interplay between induction and deduction (Becker 2017 ), is that during the course of his research Becker adds scientifically meaningful new distinctions in the form of three phases—distinctions, or findings if you will, that strongly affect the course of his research: its focus, the material that he collects, and which eventually impact his findings. Each phase typically unfolds through social interaction, and often with input from experienced users in “a sequence of social experiences during which the person acquires a conception of the meaning of the behavior, and perceptions and judgments of objects and situations, all of which make the activity possible and desirable” (Becker 1963 :235). In this study the increased understanding of smoking dope is a result of a combination of the meaning of the actors, and the conceptual distinctions that Becker introduces based on the views expressed by his respondents. Understanding is the result of research and is due to an iterative process in which data, concepts and evidence are connected with one another (Becker 2017 ).

Indeed, there are many definitions of qualitative research, but if we look for a definition that addresses its distinctive feature of being “qualitative,” the literature across the broad field of social science is meager. The main reason behind this article lies in the paradox, which, to put it bluntly, is that researchers act as if they know what it is, but they cannot formulate a coherent definition. Sociologists and others will of course continue to conduct good studies that show the relevance and value of qualitative research addressing scientific and practical problems in society. However, our paper is grounded in the idea that providing a clear definition will help us improve the work that we do. Among researchers who practice qualitative research there is clearly much knowledge. We suggest that a definition makes this knowledge more explicit. If the first rationale for writing this paper refers to the “internal” aim of improving qualitative research, the second refers to the increased “external” pressure that especially many qualitative researchers feel; pressure that comes both from society as well as from other scientific approaches. There is a strong core in qualitative research, and leading researchers tend to agree on what it is and how it is done. Our critique is not directed at the practice of qualitative research, but we do claim that the type of systematic work we do has not yet been done, and that it is useful to improve the field and its status in relation to quantitative research.

The literature on the “internal” aim of improving, or at least clarifying qualitative research is large, and we do not claim to be the first to notice the vagueness of the term “qualitative” (Strauss and Corbin 1998 ). Also, others have noted that there is no single definition of it (Long and Godfrey 2004 :182), that there are many different views on qualitative research (Denzin and Lincoln 2003 :11; Jovanović 2011 :3), and that more generally, we need to define its meaning (Best 2004 :54). Strauss and Corbin ( 1998 ), for example, as well as Nelson et al. (1992:2 cited in Denzin and Lincoln 2003 :11), and Flick ( 2007 :ix–x), have recognized that the term is problematic: “Actually, the term ‘qualitative research’ is confusing because it can mean different things to different people” (Strauss and Corbin 1998 :10–11). Hammersley has discussed the possibility of addressing the problem, but states that “the task of providing an account of the distinctive features of qualitative research is far from straightforward” ( 2013 :2). This confusion, as he has recently further argued (Hammersley 2018 ), is also salient in relation to ethnography where different philosophical and methodological approaches lead to a lack of agreement about what it means.

Others (e.g. Hammersley 2018 ; Fine and Hancock 2017 ) have also identified the treat to qualitative research that comes from external forces, seen from the point of view of “qualitative research.” This threat can be further divided into that which comes from inside academia, such as the critique voiced by “quantitative research” and outside of academia, including, for example, New Public Management. Hammersley ( 2018 ), zooming in on one type of qualitative research, ethnography, has argued that it is under treat. Similarly to Fine ( 2003 ), and before him Gans ( 1999 ), he writes that ethnography’ has acquired a range of meanings, and comes in many different versions, these often reflecting sharply divergent epistemological orientations. And already more than twenty years ago while reviewing Denzin and Lincoln’ s Handbook of Qualitative Methods Fine argued:

While this increasing centrality [of qualitative research] might lead one to believe that consensual standards have developed, this belief would be misleading. As the methodology becomes more widely accepted, querulous challengers have raised fundamental questions that collectively have undercut the traditional models of how qualitative research is to be fashioned and presented (1995:417).

According to Hammersley, there are today “serious treats to the practice of ethnographic work, on almost any definition” ( 2018 :1). He lists five external treats: (1) that social research must be accountable and able to show its impact on society; (2) the current emphasis on “big data” and the emphasis on quantitative data and evidence; (3) the labor market pressure in academia that leaves less time for fieldwork (see also Fine and Hancock 2017 ); (4) problems of access to fields; and (5) the increased ethical scrutiny of projects, to which ethnography is particularly exposed. Hammersley discusses some more or less insufficient existing definitions of ethnography.

The current situation, as Hammersley and others note—and in relation not only to ethnography but also qualitative research in general, and as our empirical study shows—is not just unsatisfactory, it may even be harmful for the entire field of qualitative research, and does not help social science at large. We suggest that the lack of clarity of qualitative research is a real problem that must be addressed.

Towards a Definition of Qualitative Research

Seen in an historical light, what is today called qualitative, or sometimes ethnographic, interpretative research – or a number of other terms – has more or less always existed. At the time the founders of sociology – Simmel, Weber, Durkheim and, before them, Marx – were writing, and during the era of the Methodenstreit (“dispute about methods”) in which the German historical school emphasized scientific methods (cf. Swedberg 1990 ), we can at least speak of qualitative forerunners.

Perhaps the most extended discussion of what later became known as qualitative methods in a classic work is Bronisław Malinowski’s ( 1922 ) Argonauts in the Western Pacific , although even this study does not explicitly address the meaning of “qualitative.” In Weber’s ([1921–-22] 1978) work we find a tension between scientific explanations that are based on observation and quantification and interpretative research (see also Lazarsfeld and Barton 1982 ).

If we look through major sociology journals like the American Sociological Review , American Journal of Sociology , or Social Forces we will not find the term qualitative sociology before the 1970s. And certainly before then much of what we consider qualitative classics in sociology, like Becker’ study ( 1963 ), had already been produced. Indeed, the Chicago School often combined qualitative and quantitative data within the same study (Fine 1995 ). Our point being that before a disciplinary self-awareness the term quantitative preceded qualitative, and the articulation of the former was a political move to claim scientific status (Denzin and Lincoln 2005 ). In the US the World War II seem to have sparked a critique of sociological work, including “qualitative work,” that did not follow the scientific canon (Rawls 2018 ), which was underpinned by a scientifically oriented and value free philosophy of science. As a result the attempts and practice of integrating qualitative and quantitative sociology at Chicago lost ground to sociology that was more oriented to surveys and quantitative work at Columbia under Merton-Lazarsfeld. The quantitative tradition was also able to present textbooks (Lundberg 1951 ) that facilitated the use this approach and its “methods.” The practices of the qualitative tradition, by and large, remained tacit or was part of the mentoring transferred from the renowned masters to their students.

This glimpse into history leads us back to the lack of a coherent account condensed in a definition of qualitative research. Many of the attempts to define the term do not meet the requirements of a proper definition: A definition should be clear, avoid tautology, demarcate its domain in relation to the environment, and ideally only use words in its definiens that themselves are not in need of definition (Hempel 1966 ). A definition can enhance precision and thus clarity by identifying the core of the phenomenon. Preferably, a definition should be short. The typical definition we have found, however, is an ostensive definition, which indicates what qualitative research is about without informing us about what it actually is :

Qualitative research is multimethod in focus, involving an interpretative, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Qualitative research involves the studied use and collection of a variety of empirical materials – case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts – that describe routine and problematic moments and meanings in individuals’ lives. (Denzin and Lincoln 2005 :2)

Flick claims that the label “qualitative research” is indeed used as an umbrella for a number of approaches ( 2007 :2–4; 2002 :6), and it is not difficult to identify research fitting this designation. Moreover, whatever it is, it has grown dramatically over the past five decades. In addition, courses have been developed, methods have flourished, arguments about its future have been advanced (for example, Denzin and Lincoln 1994) and criticized (for example, Snow and Morrill 1995 ), and dedicated journals and books have mushroomed. Most social scientists have a clear idea of research and how it differs from journalism, politics and other activities. But the question of what is qualitative in qualitative research is either eluded or eschewed.

We maintain that this lacuna hinders systematic knowledge production based on qualitative research. Paul Lazarsfeld noted the lack of “codification” as early as 1955 when he reviewed 100 qualitative studies in order to offer a codification of the practices (Lazarsfeld and Barton 1982 :239). Since then many texts on “qualitative research” and its methods have been published, including recent attempts (Goertz and Mahoney 2012 ) similar to Lazarsfeld’s. These studies have tried to extract what is qualitative by looking at the large number of empirical “qualitative” studies. Our novel strategy complements these endeavors by taking another approach and looking at the attempts to codify these practices in the form of a definition, as well as to a minor extent take Becker’s study as an exemplar of what qualitative researchers actually do, and what the characteristic of being ‘qualitative’ denotes and implies. We claim that qualitative researchers, if there is such a thing as “qualitative research,” should be able to codify their practices in a condensed, yet general way expressed in language.

Lingering problems of “generalizability” and “how many cases do I need” (Small 2009 ) are blocking advancement – in this line of work qualitative approaches are said to differ considerably from quantitative ones, while some of the former unsuccessfully mimic principles related to the latter (Small 2009 ). Additionally, quantitative researchers sometimes unfairly criticize the first based on their own quality criteria. Scholars like Goertz and Mahoney ( 2012 ) have successfully focused on the different norms and practices beyond what they argue are essentially two different cultures: those working with either qualitative or quantitative methods. Instead, similarly to Becker ( 2017 ) who has recently questioned the usefulness of the distinction between qualitative and quantitative research, we focus on similarities.

The current situation also impedes both students and researchers in focusing their studies and understanding each other’s work (Lazarsfeld and Barton 1982 :239). A third consequence is providing an opening for critiques by scholars operating within different traditions (Valsiner 2000 :101). A fourth issue is that the “implicit use of methods in qualitative research makes the field far less standardized than the quantitative paradigm” (Goertz and Mahoney 2012 :9). Relatedly, the National Science Foundation in the US organized two workshops in 2004 and 2005 to address the scientific foundations of qualitative research involving strategies to improve it and to develop standards of evaluation in qualitative research. However, a specific focus on its distinguishing feature of being “qualitative” while being implicitly acknowledged, was discussed only briefly (for example, Best 2004 ).

In 2014 a theme issue was published in this journal on “Methods, Materials, and Meanings: Designing Cultural Analysis,” discussing central issues in (cultural) qualitative research (Berezin 2014 ; Biernacki 2014 ; Glaeser 2014 ; Lamont and Swidler 2014 ; Spillman 2014). We agree with many of the arguments put forward, such as the risk of methodological tribalism, and that we should not waste energy on debating methods separated from research questions. Nonetheless, a clarification of the relation to what is called “quantitative research” is of outmost importance to avoid misunderstandings and misguided debates between “qualitative” and “quantitative” researchers. Our strategy means that researchers, “qualitative” or “quantitative” they may be, in their actual practice may combine qualitative work and quantitative work.

In this article we accomplish three tasks. First, we systematically survey the literature for meanings of qualitative research by looking at how researchers have defined it. Drawing upon existing knowledge we find that the different meanings and ideas of qualitative research are not yet coherently integrated into one satisfactory definition. Next, we advance our contribution by offering a definition of qualitative research and illustrate its meaning and use partially by expanding on the brief example introduced earlier related to Becker’s work ( 1963 ). We offer a systematic analysis of central themes of what researchers consider to be the core of “qualitative,” regardless of style of work. These themes – which we summarize in terms of four keywords: distinction, process, closeness, improved understanding – constitute part of our literature review, in which each one appears, sometimes with others, but never all in the same definition. They serve as the foundation of our contribution. Our categories are overlapping. Their use is primarily to organize the large amount of definitions we have identified and analyzed, and not necessarily to draw a clear distinction between them. Finally, we continue the elaboration discussed above on the advantages of a clear definition of qualitative research.

In a hermeneutic fashion we propose that there is something meaningful that deserves to be labelled “qualitative research” (Gadamer 1990 ). To approach the question “What is qualitative in qualitative research?” we have surveyed the literature. In conducting our survey we first traced the word’s etymology in dictionaries, encyclopedias, handbooks of the social sciences and of methods and textbooks, mainly in English, which is common to methodology courses. It should be noted that we have zoomed in on sociology and its literature. This discipline has been the site of the largest debate and development of methods that can be called “qualitative,” which suggests that this field should be examined in great detail.

In an ideal situation we should expect that one good definition, or at least some common ideas, would have emerged over the years. This common core of qualitative research should be so accepted that it would appear in at least some textbooks. Since this is not what we found, we decided to pursue an inductive approach to capture maximal variation in the field of qualitative research; we searched in a selection of handbooks, textbooks, book chapters, and books, to which we added the analysis of journal articles. Our sample comprises a total of 89 references.

In practice we focused on the discipline that has had a clear discussion of methods, namely sociology. We also conducted a broad search in the JSTOR database to identify scholarly sociology articles published between 1998 and 2017 in English with a focus on defining or explaining qualitative research. We specifically zoom in on this time frame because we would have expect that this more mature period would have produced clear discussions on the meaning of qualitative research. To find these articles we combined a number of keywords to search the content and/or the title: qualitative (which was always included), definition, empirical, research, methodology, studies, fieldwork, interview and observation .

As a second phase of our research we searched within nine major sociological journals ( American Journal of Sociology , Sociological Theory , American Sociological Review , Contemporary Sociology , Sociological Forum , Sociological Theory , Qualitative Research , Qualitative Sociology and Qualitative Sociology Review ) for articles also published during the past 19 years (1998–2017) that had the term “qualitative” in the title and attempted to define qualitative research.

Lastly we picked two additional journals, Qualitative Research and Qualitative Sociology , in which we could expect to find texts addressing the notion of “qualitative.” From Qualitative Research we chose Volume 14, Issue 6, December 2014, and from Qualitative Sociology we chose Volume 36, Issue 2, June 2017. Within each of these we selected the first article; then we picked the second article of three prior issues. Again we went back another three issues and investigated article number three. Finally we went back another three issues and perused article number four. This selection criteria was used to get a manageable sample for the analysis.

The coding process of the 89 references we gathered in our selected review began soon after the first round of material was gathered, and we reduced the complexity created by our maximum variation sampling (Snow and Anderson 1993 :22) to four different categories within which questions on the nature and properties of qualitative research were discussed. We call them: Qualitative and Quantitative Research, Qualitative Research, Fieldwork, and Grounded Theory. This – which may appear as an illogical grouping – merely reflects the “context” in which the matter of “qualitative” is discussed. If the selection process of the material – books and articles – was informed by pre-knowledge, we used an inductive strategy to code the material. When studying our material, we identified four central notions related to “qualitative” that appear in various combinations in the literature which indicate what is the core of qualitative research. We have labeled them: “distinctions”, “process,” “closeness,” and “improved understanding.” During the research process the categories and notions were improved, refined, changed, and reordered. The coding ended when a sense of saturation in the material arose. In the presentation below all quotations and references come from our empirical material of texts on qualitative research.

Analysis – What is Qualitative Research?

In this section we describe the four categories we identified in the coding, how they differently discuss qualitative research, as well as their overall content. Some salient quotations are selected to represent the type of text sorted under each of the four categories. What we present are examples from the literature.

Qualitative and Quantitative

This analytic category comprises quotations comparing qualitative and quantitative research, a distinction that is frequently used (Brown 2010 :231); in effect this is a conceptual pair that structures the discussion and that may be associated with opposing interests. While the general goal of quantitative and qualitative research is the same – to understand the world better – their methodologies and focus in certain respects differ substantially (Becker 1966 :55). Quantity refers to that property of something that can be determined by measurement. In a dictionary of Statistics and Methodology we find that “(a) When referring to *variables, ‘qualitative’ is another term for *categorical or *nominal. (b) When speaking of kinds of research, ‘qualitative’ refers to studies of subjects that are hard to quantify, such as art history. Qualitative research tends to be a residual category for almost any kind of non-quantitative research” (Stiles 1998:183). But it should be obvious that one could employ a quantitative approach when studying, for example, art history.

The same dictionary states that quantitative is “said of variables or research that can be handled numerically, usually (too sharply) contrasted with *qualitative variables and research” (Stiles 1998:184). From a qualitative perspective “quantitative research” is about numbers and counting, and from a quantitative perspective qualitative research is everything that is not about numbers. But this does not say much about what is “qualitative.” If we turn to encyclopedias we find that in the 1932 edition of the Encyclopedia of the Social Sciences there is no mention of “qualitative.” In the Encyclopedia from 1968 we can read:

Qualitative Analysis. For methods of obtaining, analyzing, and describing data, see [the various entries:] CONTENT ANALYSIS; COUNTED DATA; EVALUATION RESEARCH, FIELD WORK; GRAPHIC PRESENTATION; HISTORIOGRAPHY, especially the article on THE RHETORIC OF HISTORY; INTERVIEWING; OBSERVATION; PERSONALITY MEASUREMENT; PROJECTIVE METHODS; PSYCHOANALYSIS, article on EXPERIMENTAL METHODS; SURVEY ANALYSIS, TABULAR PRESENTATION; TYPOLOGIES. (Vol. 13:225)

Some, like Alford, divide researchers into methodologists or, in his words, “quantitative and qualitative specialists” (Alford 1998 :12). Qualitative research uses a variety of methods, such as intensive interviews or in-depth analysis of historical materials, and it is concerned with a comprehensive account of some event or unit (King et al. 1994 :4). Like quantitative research it can be utilized to study a variety of issues, but it tends to focus on meanings and motivations that underlie cultural symbols, personal experiences, phenomena and detailed understanding of processes in the social world. In short, qualitative research centers on understanding processes, experiences, and the meanings people assign to things (Kalof et al. 2008 :79).

Others simply say that qualitative methods are inherently unscientific (Jovanović 2011 :19). Hood, for instance, argues that words are intrinsically less precise than numbers, and that they are therefore more prone to subjective analysis, leading to biased results (Hood 2006 :219). Qualitative methodologies have raised concerns over the limitations of quantitative templates (Brady et al. 2004 :4). Scholars such as King et al. ( 1994 ), for instance, argue that non-statistical research can produce more reliable results if researchers pay attention to the rules of scientific inference commonly stated in quantitative research. Also, researchers such as Becker ( 1966 :59; 1970 :42–43) have asserted that, if conducted properly, qualitative research and in particular ethnographic field methods, can lead to more accurate results than quantitative studies, in particular, survey research and laboratory experiments.

Some researchers, such as Kalof, Dan, and Dietz ( 2008 :79) claim that the boundaries between the two approaches are becoming blurred, and Small ( 2009 ) argues that currently much qualitative research (especially in North America) tries unsuccessfully and unnecessarily to emulate quantitative standards. For others, qualitative research tends to be more humanistic and discursive (King et al. 1994 :4). Ragin ( 1994 ), and similarly also Becker, ( 1996 :53), Marchel and Owens ( 2007 :303) think that the main distinction between the two styles is overstated and does not rest on the simple dichotomy of “numbers versus words” (Ragin 1994 :xii). Some claim that quantitative data can be utilized to discover associations, but in order to unveil cause and effect a complex research design involving the use of qualitative approaches needs to be devised (Gilbert 2009 :35). Consequently, qualitative data are useful for understanding the nuances lying beyond those processes as they unfold (Gilbert 2009 :35). Others contend that qualitative research is particularly well suited both to identify causality and to uncover fine descriptive distinctions (Fine and Hallett 2014 ; Lichterman and Isaac Reed 2014 ; Katz 2015 ).

There are other ways to separate these two traditions, including normative statements about what qualitative research should be (that is, better or worse than quantitative approaches, concerned with scientific approaches to societal change or vice versa; Snow and Morrill 1995 ; Denzin and Lincoln 2005 ), or whether it should develop falsifiable statements; Best 2004 ).

We propose that quantitative research is largely concerned with pre-determined variables (Small 2008 ); the analysis concerns the relations between variables. These categories are primarily not questioned in the study, only their frequency or degree, or the correlations between them (cf. Franzosi 2016 ). If a researcher studies wage differences between women and men, he or she works with given categories: x number of men are compared with y number of women, with a certain wage attributed to each person. The idea is not to move beyond the given categories of wage, men and women; they are the starting point as well as the end point, and undergo no “qualitative change.” Qualitative research, in contrast, investigates relations between categories that are themselves subject to change in the research process. Returning to Becker’s study ( 1963 ), we see that he questioned pre-dispositional theories of deviant behavior working with pre-determined variables such as an individual’s combination of personal qualities or emotional problems. His take, in contrast, was to understand marijuana consumption by developing “variables” as part of the investigation. Thereby he presented new variables, or as we would say today, theoretical concepts, but which are grounded in the empirical material.

Qualitative Research

This category contains quotations that refer to descriptions of qualitative research without making comparisons with quantitative research. Researchers such as Denzin and Lincoln, who have written a series of influential handbooks on qualitative methods (1994; Denzin and Lincoln 2003 ; 2005 ), citing Nelson et al. (1992:4), argue that because qualitative research is “interdisciplinary, transdisciplinary, and sometimes counterdisciplinary” it is difficult to derive one single definition of it (Jovanović 2011 :3). According to them, in fact, “the field” is “many things at the same time,” involving contradictions, tensions over its focus, methods, and how to derive interpretations and findings ( 2003 : 11). Similarly, others, such as Flick ( 2007 :ix–x) contend that agreeing on an accepted definition has increasingly become problematic, and that qualitative research has possibly matured different identities. However, Best holds that “the proliferation of many sorts of activities under the label of qualitative sociology threatens to confuse our discussions” ( 2004 :54). Atkinson’s position is more definite: “the current state of qualitative research and research methods is confused” ( 2005 :3–4).

Qualitative research is about interpretation (Blumer 1969 ; Strauss and Corbin 1998 ; Denzin and Lincoln 2003 ), or Verstehen [understanding] (Frankfort-Nachmias and Nachmias 1996 ). It is “multi-method,” involving the collection and use of a variety of empirical materials (Denzin and Lincoln 1998; Silverman 2013 ) and approaches (Silverman 2005 ; Flick 2007 ). It focuses not only on the objective nature of behavior but also on its subjective meanings: individuals’ own accounts of their attitudes, motivations, behavior (McIntyre 2005 :127; Creswell 2009 ), events and situations (Bryman 1989) – what people say and do in specific places and institutions (Goodwin and Horowitz 2002 :35–36) in social and temporal contexts (Morrill and Fine 1997). For this reason, following Weber ([1921-22] 1978), it can be described as an interpretative science (McIntyre 2005 :127). But could quantitative research also be concerned with these questions? Also, as pointed out below, does all qualitative research focus on subjective meaning, as some scholars suggest?

Others also distinguish qualitative research by claiming that it collects data using a naturalistic approach (Denzin and Lincoln 2005 :2; Creswell 2009 ), focusing on the meaning actors ascribe to their actions. But again, does all qualitative research need to be collected in situ? And does qualitative research have to be inherently concerned with meaning? Flick ( 2007 ), referring to Denzin and Lincoln ( 2005 ), mentions conversation analysis as an example of qualitative research that is not concerned with the meanings people bring to a situation, but rather with the formal organization of talk. Still others, such as Ragin ( 1994 :85), note that qualitative research is often (especially early on in the project, we would add) less structured than other kinds of social research – a characteristic connected to its flexibility and that can lead both to potentially better, but also worse results. But is this not a feature of this type of research, rather than a defining description of its essence? Wouldn’t this comment also apply, albeit to varying degrees, to quantitative research?

In addition, Strauss ( 2003 ), along with others, such as Alvesson and Kärreman ( 2011 :10–76), argue that qualitative researchers struggle to capture and represent complex phenomena partially because they tend to collect a large amount of data. While his analysis is correct at some points – “It is necessary to do detailed, intensive, microscopic examination of the data in order to bring out the amazing complexity of what lies in, behind, and beyond those data” (Strauss 2003 :10) – much of his analysis concerns the supposed focus of qualitative research and its challenges, rather than exactly what it is about. But even in this instance we would make a weak case arguing that these are strictly the defining features of qualitative research. Some researchers seem to focus on the approach or the methods used, or even on the way material is analyzed. Several researchers stress the naturalistic assumption of investigating the world, suggesting that meaning and interpretation appear to be a core matter of qualitative research.

We can also see that in this category there is no consensus about specific qualitative methods nor about qualitative data. Many emphasize interpretation, but quantitative research, too, involves interpretation; the results of a regression analysis, for example, certainly have to be interpreted, and the form of meta-analysis that factor analysis provides indeed requires interpretation However, there is no interpretation of quantitative raw data, i.e., numbers in tables. One common thread is that qualitative researchers have to get to grips with their data in order to understand what is being studied in great detail, irrespective of the type of empirical material that is being analyzed. This observation is connected to the fact that qualitative researchers routinely make several adjustments of focus and research design as their studies progress, in many cases until the very end of the project (Kalof et al. 2008 ). If you, like Becker, do not start out with a detailed theory, adjustments such as the emergence and refinement of research questions will occur during the research process. We have thus found a number of useful reflections about qualitative research scattered across different sources, but none of them effectively describe the defining characteristics of this approach.

Although qualitative research does not appear to be defined in terms of a specific method, it is certainly common that fieldwork, i.e., research that entails that the researcher spends considerable time in the field that is studied and use the knowledge gained as data, is seen as emblematic of or even identical to qualitative research. But because we understand that fieldwork tends to focus primarily on the collection and analysis of qualitative data, we expected to find within it discussions on the meaning of “qualitative.” But, again, this was not the case.

Instead, we found material on the history of this approach (for example, Frankfort-Nachmias and Nachmias 1996 ; Atkinson et al. 2001), including how it has changed; for example, by adopting a more self-reflexive practice (Heyl 2001), as well as the different nomenclature that has been adopted, such as fieldwork, ethnography, qualitative research, naturalistic research, participant observation and so on (for example, Lofland et al. 2006 ; Gans 1999 ).

We retrieved definitions of ethnography, such as “the study of people acting in the natural courses of their daily lives,” involving a “resocialization of the researcher” (Emerson 1988 :1) through intense immersion in others’ social worlds (see also examples in Hammersley 2018 ). This may be accomplished by direct observation and also participation (Neuman 2007 :276), although others, such as Denzin ( 1970 :185), have long recognized other types of observation, including non-participant (“fly on the wall”). In this category we have also isolated claims and opposing views, arguing that this type of research is distinguished primarily by where it is conducted (natural settings) (Hughes 1971:496), and how it is carried out (a variety of methods are applied) or, for some most importantly, by involving an active, empathetic immersion in those being studied (Emerson 1988 :2). We also retrieved descriptions of the goals it attends in relation to how it is taught (understanding subjective meanings of the people studied, primarily develop theory, or contribute to social change) (see for example, Corte and Irwin 2017 ; Frankfort-Nachmias and Nachmias 1996 :281; Trier-Bieniek 2012 :639) by collecting the richest possible data (Lofland et al. 2006 ) to derive “thick descriptions” (Geertz 1973 ), and/or to aim at theoretical statements of general scope and applicability (for example, Emerson 1988 ; Fine 2003 ). We have identified guidelines on how to evaluate it (for example Becker 1996 ; Lamont 2004 ) and have retrieved instructions on how it should be conducted (for example, Lofland et al. 2006 ). For instance, analysis should take place while the data gathering unfolds (Emerson 1988 ; Hammersley and Atkinson 2007 ; Lofland et al. 2006 ), observations should be of long duration (Becker 1970 :54; Goffman 1989 ), and data should be of high quantity (Becker 1970 :52–53), as well as other questionable distinctions between fieldwork and other methods:

Field studies differ from other methods of research in that the researcher performs the task of selecting topics, decides what questions to ask, and forges interest in the course of the research itself . This is in sharp contrast to many ‘theory-driven’ and ‘hypothesis-testing’ methods. (Lofland and Lofland 1995 :5)

But could not, for example, a strictly interview-based study be carried out with the same amount of flexibility, such as sequential interviewing (for example, Small 2009 )? Once again, are quantitative approaches really as inflexible as some qualitative researchers think? Moreover, this category stresses the role of the actors’ meaning, which requires knowledge and close interaction with people, their practices and their lifeworld.

It is clear that field studies – which are seen by some as the “gold standard” of qualitative research – are nonetheless only one way of doing qualitative research. There are other methods, but it is not clear why some are more qualitative than others, or why they are better or worse. Fieldwork is characterized by interaction with the field (the material) and understanding of the phenomenon that is being studied. In Becker’s case, he had general experience from fields in which marihuana was used, based on which he did interviews with actual users in several fields.

Grounded Theory

Another major category we identified in our sample is Grounded Theory. We found descriptions of it most clearly in Glaser and Strauss’ ([1967] 2010 ) original articulation, Strauss and Corbin ( 1998 ) and Charmaz ( 2006 ), as well as many other accounts of what it is for: generating and testing theory (Strauss 2003 :xi). We identified explanations of how this task can be accomplished – such as through two main procedures: constant comparison and theoretical sampling (Emerson 1998:96), and how using it has helped researchers to “think differently” (for example, Strauss and Corbin 1998 :1). We also read descriptions of its main traits, what it entails and fosters – for instance, an exceptional flexibility, an inductive approach (Strauss and Corbin 1998 :31–33; 1990; Esterberg 2002 :7), an ability to step back and critically analyze situations, recognize tendencies towards bias, think abstractly and be open to criticism, enhance sensitivity towards the words and actions of respondents, and develop a sense of absorption and devotion to the research process (Strauss and Corbin 1998 :5–6). Accordingly, we identified discussions of the value of triangulating different methods (both using and not using grounded theory), including quantitative ones, and theories to achieve theoretical development (most comprehensively in Denzin 1970 ; Strauss and Corbin 1998 ; Timmermans and Tavory 2012 ). We have also located arguments about how its practice helps to systematize data collection, analysis and presentation of results (Glaser and Strauss [1967] 2010 :16).

Grounded theory offers a systematic approach which requires researchers to get close to the field; closeness is a requirement of identifying questions and developing new concepts or making further distinctions with regard to old concepts. In contrast to other qualitative approaches, grounded theory emphasizes the detailed coding process, and the numerous fine-tuned distinctions that the researcher makes during the process. Within this category, too, we could not find a satisfying discussion of the meaning of qualitative research.

Defining Qualitative Research

In sum, our analysis shows that some notions reappear in the discussion of qualitative research, such as understanding, interpretation, “getting close” and making distinctions. These notions capture aspects of what we think is “qualitative.” However, a comprehensive definition that is useful and that can further develop the field is lacking, and not even a clear picture of its essential elements appears. In other words no definition emerges from our data, and in our research process we have moved back and forth between our empirical data and the attempt to present a definition. Our concrete strategy, as stated above, is to relate qualitative and quantitative research, or more specifically, qualitative and quantitative work. We use an ideal-typical notion of quantitative research which relies on taken for granted and numbered variables. This means that the data consists of variables on different scales, such as ordinal, but frequently ratio and absolute scales, and the representation of the numbers to the variables, i.e. the justification of the assignment of numbers to object or phenomenon, are not questioned, though the validity may be questioned. In this section we return to the notion of quality and try to clarify it while presenting our contribution.

Broadly, research refers to the activity performed by people trained to obtain knowledge through systematic procedures. Notions such as “objectivity” and “reflexivity,” “systematic,” “theory,” “evidence” and “openness” are here taken for granted in any type of research. Next, building on our empirical analysis we explain the four notions that we have identified as central to qualitative work: distinctions, process, closeness, and improved understanding. In discussing them, ultimately in relation to one another, we make their meaning even more precise. Our idea, in short, is that only when these ideas that we present separately for analytic purposes are brought together can we speak of qualitative research.

Distinctions

We believe that the possibility of making new distinctions is one the defining characteristics of qualitative research. It clearly sets it apart from quantitative analysis which works with taken-for-granted variables, albeit as mentioned, meta-analyses, for example, factor analysis may result in new variables. “Quality” refers essentially to distinctions, as already pointed out by Aristotle. He discusses the term “qualitative” commenting: “By a quality I mean that in virtue of which things are said to be qualified somehow” (Aristotle 1984:14). Quality is about what something is or has, which means that the distinction from its environment is crucial. We see qualitative research as a process in which significant new distinctions are made to the scholarly community; to make distinctions is a key aspect of obtaining new knowledge; a point, as we will see, that also has implications for “quantitative research.” The notion of being “significant” is paramount. New distinctions by themselves are not enough; just adding concepts only increases complexity without furthering our knowledge. The significance of new distinctions is judged against the communal knowledge of the research community. To enable this discussion and judgements central elements of rational discussion are required (cf. Habermas [1981] 1987 ; Davidsson [ 1988 ] 2001) to identify what is new and relevant scientific knowledge. Relatedly, Ragin alludes to the idea of new and useful knowledge at a more concrete level: “Qualitative methods are appropriate for in-depth examination of cases because they aid the identification of key features of cases. Most qualitative methods enhance data” (1994:79). When Becker ( 1963 ) studied deviant behavior and investigated how people became marihuana smokers, he made distinctions between the ways in which people learned how to smoke. This is a classic example of how the strategy of “getting close” to the material, for example the text, people or pictures that are subject to analysis, may enable researchers to obtain deeper insight and new knowledge by making distinctions – in this instance on the initial notion of learning how to smoke. Others have stressed the making of distinctions in relation to coding or theorizing. Emerson et al. ( 1995 ), for example, hold that “qualitative coding is a way of opening up avenues of inquiry,” meaning that the researcher identifies and develops concepts and analytic insights through close examination of and reflection on data (Emerson et al. 1995 :151). Goodwin and Horowitz highlight making distinctions in relation to theory-building writing: “Close engagement with their cases typically requires qualitative researchers to adapt existing theories or to make new conceptual distinctions or theoretical arguments to accommodate new data” ( 2002 : 37). In the ideal-typical quantitative research only existing and so to speak, given, variables would be used. If this is the case no new distinction are made. But, would not also many “quantitative” researchers make new distinctions?

Process does not merely suggest that research takes time. It mainly implies that qualitative new knowledge results from a process that involves several phases, and above all iteration. Qualitative research is about oscillation between theory and evidence, analysis and generating material, between first- and second -order constructs (Schütz 1962 :59), between getting in contact with something, finding sources, becoming deeply familiar with a topic, and then distilling and communicating some of its essential features. The main point is that the categories that the researcher uses, and perhaps takes for granted at the beginning of the research process, usually undergo qualitative changes resulting from what is found. Becker describes how he tested hypotheses and let the jargon of the users develop into theoretical concepts. This happens over time while the study is being conducted, exemplifying what we mean by process.

In the research process, a pilot-study may be used to get a first glance of, for example, the field, how to approach it, and what methods can be used, after which the method and theory are chosen or refined before the main study begins. Thus, the empirical material is often central from the start of the project and frequently leads to adjustments by the researcher. Likewise, during the main study categories are not fixed; the empirical material is seen in light of the theory used, but it is also given the opportunity to kick back, thereby resisting attempts to apply theoretical straightjackets (Becker 1970 :43). In this process, coding and analysis are interwoven, and thus are often important steps for getting closer to the phenomenon and deciding what to focus on next. Becker began his research by interviewing musicians close to him, then asking them to refer him to other musicians, and later on doubling his original sample of about 25 to include individuals in other professions (Becker 1973:46). Additionally, he made use of some participant observation, documents, and interviews with opiate users made available to him by colleagues. As his inductive theory of deviance evolved, Becker expanded his sample in order to fine tune it, and test the accuracy and generality of his hypotheses. In addition, he introduced a negative case and discussed the null hypothesis ( 1963 :44). His phasic career model is thus based on a research design that embraces processual work. Typically, process means to move between “theory” and “material” but also to deal with negative cases, and Becker ( 1998 ) describes how discovering these negative cases impacted his research design and ultimately its findings.

Obviously, all research is process-oriented to some degree. The point is that the ideal-typical quantitative process does not imply change of the data, and iteration between data, evidence, hypotheses, empirical work, and theory. The data, quantified variables, are, in most cases fixed. Merging of data, which of course can be done in a quantitative research process, does not mean new data. New hypotheses are frequently tested, but the “raw data is often the “the same.” Obviously, over time new datasets are made available and put into use.

Another characteristic that is emphasized in our sample is that qualitative researchers – and in particular ethnographers – can, or as Goffman put it, ought to ( 1989 ), get closer to the phenomenon being studied and their data than quantitative researchers (for example, Silverman 2009 :85). Put differently, essentially because of their methods qualitative researchers get into direct close contact with those being investigated and/or the material, such as texts, being analyzed. Becker started out his interview study, as we noted, by talking to those he knew in the field of music to get closer to the phenomenon he was studying. By conducting interviews he got even closer. Had he done more observations, he would undoubtedly have got even closer to the field.

Additionally, ethnographers’ design enables researchers to follow the field over time, and the research they do is almost by definition longitudinal, though the time in the field is studied obviously differs between studies. The general characteristic of closeness over time maximizes the chances of unexpected events, new data (related, for example, to archival research as additional sources, and for ethnography for situations not necessarily previously thought of as instrumental – what Mannay and Morgan ( 2015 ) term the “waiting field”), serendipity (Merton and Barber 2004 ; Åkerström 2013 ), and possibly reactivity, as well as the opportunity to observe disrupted patterns that translate into exemplars of negative cases. Two classic examples of this are Becker’s finding of what medical students call “crocks” (Becker et al. 1961 :317), and Geertz’s ( 1973 ) study of “deep play” in Balinese society.

By getting and staying so close to their data – be it pictures, text or humans interacting (Becker was himself a musician) – for a long time, as the research progressively focuses, qualitative researchers are prompted to continually test their hunches, presuppositions and hypotheses. They test them against a reality that often (but certainly not always), and practically, as well as metaphorically, talks back, whether by validating them, or disqualifying their premises – correctly, as well as incorrectly (Fine 2003 ; Becker 1970 ). This testing nonetheless often leads to new directions for the research. Becker, for example, says that he was initially reading psychological theories, but when facing the data he develops a theory that looks at, you may say, everything but psychological dispositions to explain the use of marihuana. Especially researchers involved with ethnographic methods have a fairly unique opportunity to dig up and then test (in a circular, continuous and temporal way) new research questions and findings as the research progresses, and thereby to derive previously unimagined and uncharted distinctions by getting closer to the phenomenon under study.

Let us stress that getting close is by no means restricted to ethnography. The notion of hermeneutic circle and hermeneutics as a general way of understanding implies that we must get close to the details in order to get the big picture. This also means that qualitative researchers can literally also make use of details of pictures as evidence (cf. Harper 2002). Thus, researchers may get closer both when generating the material or when analyzing it.

Quantitative research, we maintain, in the ideal-typical representation cannot get closer to the data. The data is essentially numbers in tables making up the variables (Franzosi 2016 :138). The data may originally have been “qualitative,” but once reduced to numbers there can only be a type of “hermeneutics” about what the number may stand for. The numbers themselves, however, are non-ambiguous. Thus, in quantitative research, interpretation, if done, is not about the data itself—the numbers—but what the numbers stand for. It follows that the interpretation is essentially done in a more “speculative” mode without direct empirical evidence (cf. Becker 2017 ).

Improved Understanding

While distinction, process and getting closer refer to the qualitative work of the researcher, improved understanding refers to its conditions and outcome of this work. Understanding cuts deeper than explanation, which to some may mean a causally verified correlation between variables. The notion of explanation presupposes the notion of understanding since explanation does not include an idea of how knowledge is gained (Manicas 2006 : 15). Understanding, we argue, is the core concept of what we call the outcome of the process when research has made use of all the other elements that were integrated in the research. Understanding, then, has a special status in qualitative research since it refers both to the conditions of knowledge and the outcome of the process. Understanding can to some extent be seen as the condition of explanation and occurs in a process of interpretation, which naturally refers to meaning (Gadamer 1990 ). It is fundamentally connected to knowing, and to the knowing of how to do things (Heidegger [1927] 2001 ). Conceptually the term hermeneutics is used to account for this process. Heidegger ties hermeneutics to human being and not possible to separate from the understanding of being ( 1988 ). Here we use it in a broader sense, and more connected to method in general (cf. Seiffert 1992 ). The abovementioned aspects – for example, “objectivity” and “reflexivity” – of the approach are conditions of scientific understanding. Understanding is the result of a circular process and means that the parts are understood in light of the whole, and vice versa. Understanding presupposes pre-understanding, or in other words, some knowledge of the phenomenon studied. The pre-understanding, even in the form of prejudices, are in qualitative research process, which we see as iterative, questioned, which gradually or suddenly change due to the iteration of data, evidence and concepts. However, qualitative research generates understanding in the iterative process when the researcher gets closer to the data, e.g., by going back and forth between field and analysis in a process that generates new data that changes the evidence, and, ultimately, the findings. Questioning, to ask questions, and put what one assumes—prejudices and presumption—in question, is central to understand something (Heidegger [1927] 2001 ; Gadamer 1990 :368–384). We propose that this iterative process in which the process of understanding occurs is characteristic of qualitative research.

Improved understanding means that we obtain scientific knowledge of something that we as a scholarly community did not know before, or that we get to know something better. It means that we understand more about how parts are related to one another, and to other things we already understand (see also Fine and Hallett 2014 ). Understanding is an important condition for qualitative research. It is not enough to identify correlations, make distinctions, and work in a process in which one gets close to the field or phenomena. Understanding is accomplished when the elements are integrated in an iterative process.

It is, moreover, possible to understand many things, and researchers, just like children, may come to understand new things every day as they engage with the world. This subjective condition of understanding – namely, that a person gains a better understanding of something –is easily met. To be qualified as “scientific,” the understanding must be general and useful to many; it must be public. But even this generally accessible understanding is not enough in order to speak of “scientific understanding.” Though we as a collective can increase understanding of everything in virtually all potential directions as a result also of qualitative work, we refrain from this “objective” way of understanding, which has no means of discriminating between what we gain in understanding. Scientific understanding means that it is deemed relevant from the scientific horizon (compare Schütz 1962 : 35–38, 46, 63), and that it rests on the pre-understanding that the scientists have and must have in order to understand. In other words, the understanding gained must be deemed useful by other researchers, so that they can build on it. We thus see understanding from a pragmatic, rather than a subjective or objective perspective. Improved understanding is related to the question(s) at hand. Understanding, in order to represent an improvement, must be an improvement in relation to the existing body of knowledge of the scientific community (James [ 1907 ] 1955). Scientific understanding is, by definition, collective, as expressed in Weber’s famous note on objectivity, namely that scientific work aims at truths “which … can claim, even for a Chinese, the validity appropriate to an empirical analysis” ([1904] 1949 :59). By qualifying “improved understanding” we argue that it is a general defining characteristic of qualitative research. Becker‘s ( 1966 ) study and other research of deviant behavior increased our understanding of the social learning processes of how individuals start a behavior. And it also added new knowledge about the labeling of deviant behavior as a social process. Few studies, of course, make the same large contribution as Becker’s, but are nonetheless qualitative research.

Understanding in the phenomenological sense, which is a hallmark of qualitative research, we argue, requires meaning and this meaning is derived from the context, and above all the data being analyzed. The ideal-typical quantitative research operates with given variables with different numbers. This type of material is not enough to establish meaning at the level that truly justifies understanding. In other words, many social science explanations offer ideas about correlations or even causal relations, but this does not mean that the meaning at the level of the data analyzed, is understood. This leads us to say that there are indeed many explanations that meet the criteria of understanding, for example the explanation of how one becomes a marihuana smoker presented by Becker. However, we may also understand a phenomenon without explaining it, and we may have potential explanations, or better correlations, that are not really understood.

We may speak more generally of quantitative research and its data to clarify what we see as an important distinction. The “raw data” that quantitative research—as an idealtypical activity, refers to is not available for further analysis; the numbers, once created, are not to be questioned (Franzosi 2016 : 138). If the researcher is to do “more” or “change” something, this will be done by conjectures based on theoretical knowledge or based on the researcher’s lifeworld. Both qualitative and quantitative research is based on the lifeworld, and all researchers use prejudices and pre-understanding in the research process. This idea is present in the works of Heidegger ( 2001 ) and Heisenberg (cited in Franzosi 2010 :619). Qualitative research, as we argued, involves the interaction and questioning of concepts (theory), data, and evidence.

Ragin ( 2004 :22) points out that “a good definition of qualitative research should be inclusive and should emphasize its key strengths and features, not what it lacks (for example, the use of sophisticated quantitative techniques).” We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. Qualitative research, as defined here, is consequently a combination of two criteria: (i) how to do things –namely, generating and analyzing empirical material, in an iterative process in which one gets closer by making distinctions, and (ii) the outcome –improved understanding novel to the scholarly community. Is our definition applicable to our own study? In this study we have closely read the empirical material that we generated, and the novel distinction of the notion “qualitative research” is the outcome of an iterative process in which both deduction and induction were involved, in which we identified the categories that we analyzed. We thus claim to meet the first criteria, “how to do things.” The second criteria cannot be judged but in a partial way by us, namely that the “outcome” —in concrete form the definition-improves our understanding to others in the scientific community.

We have defined qualitative research, or qualitative scientific work, in relation to quantitative scientific work. Given this definition, qualitative research is about questioning the pre-given (taken for granted) variables, but it is thus also about making new distinctions of any type of phenomenon, for example, by coining new concepts, including the identification of new variables. This process, as we have discussed, is carried out in relation to empirical material, previous research, and thus in relation to theory. Theory and previous research cannot be escaped or bracketed. According to hermeneutic principles all scientific work is grounded in the lifeworld, and as social scientists we can thus never fully bracket our pre-understanding.

We have proposed that quantitative research, as an idealtype, is concerned with pre-determined variables (Small 2008 ). Variables are epistemically fixed, but can vary in terms of dimensions, such as frequency or number. Age is an example; as a variable it can take on different numbers. In relation to quantitative research, qualitative research does not reduce its material to number and variables. If this is done the process of comes to a halt, the researcher gets more distanced from her data, and it makes it no longer possible to make new distinctions that increase our understanding. We have above discussed the components of our definition in relation to quantitative research. Our conclusion is that in the research that is called quantitative there are frequent and necessary qualitative elements.

Further, comparative empirical research on researchers primarily working with ”quantitative” approaches and those working with ”qualitative” approaches, we propose, would perhaps show that there are many similarities in practices of these two approaches. This is not to deny dissimilarities, or the different epistemic and ontic presuppositions that may be more or less strongly associated with the two different strands (see Goertz and Mahoney 2012 ). Our point is nonetheless that prejudices and preconceptions about researchers are unproductive, and that as other researchers have argued, differences may be exaggerated (e.g., Becker 1996 : 53, 2017 ; Marchel and Owens 2007 :303; Ragin 1994 ), and that a qualitative dimension is present in both kinds of work.

Several things follow from our findings. The most important result is the relation to quantitative research. In our analysis we have separated qualitative research from quantitative research. The point is not to label individual researchers, methods, projects, or works as either “quantitative” or “qualitative.” By analyzing, i.e., taking apart, the notions of quantitative and qualitative, we hope to have shown the elements of qualitative research. Our definition captures the elements, and how they, when combined in practice, generate understanding. As many of the quotations we have used suggest, one conclusion of our study holds that qualitative approaches are not inherently connected with a specific method. Put differently, none of the methods that are frequently labelled “qualitative,” such as interviews or participant observation, are inherently “qualitative.” What matters, given our definition, is whether one works qualitatively or quantitatively in the research process, until the results are produced. Consequently, our analysis also suggests that those researchers working with what in the literature and in jargon is often called “quantitative research” are almost bound to make use of what we have identified as qualitative elements in any research project. Our findings also suggest that many” quantitative” researchers, at least to some extent, are engaged with qualitative work, such as when research questions are developed, variables are constructed and combined, and hypotheses are formulated. Furthermore, a research project may hover between “qualitative” and “quantitative” or start out as “qualitative” and later move into a “quantitative” (a distinct strategy that is not similar to “mixed methods” or just simply combining induction and deduction). More generally speaking, the categories of “qualitative” and “quantitative,” unfortunately, often cover up practices, and it may lead to “camps” of researchers opposing one another. For example, regardless of the researcher is primarily oriented to “quantitative” or “qualitative” research, the role of theory is neglected (cf. Swedberg 2017 ). Our results open up for an interaction not characterized by differences, but by different emphasis, and similarities.

Let us take two examples to briefly indicate how qualitative elements can fruitfully be combined with quantitative. Franzosi ( 2010 ) has discussed the relations between quantitative and qualitative approaches, and more specifically the relation between words and numbers. He analyzes texts and argues that scientific meaning cannot be reduced to numbers. Put differently, the meaning of the numbers is to be understood by what is taken for granted, and what is part of the lifeworld (Schütz 1962 ). Franzosi shows how one can go about using qualitative and quantitative methods and data to address scientific questions analyzing violence in Italy at the time when fascism was rising (1919–1922). Aspers ( 2006 ) studied the meaning of fashion photographers. He uses an empirical phenomenological approach, and establishes meaning at the level of actors. In a second step this meaning, and the different ideal-typical photographers constructed as a result of participant observation and interviews, are tested using quantitative data from a database; in the first phase to verify the different ideal-types, in the second phase to use these types to establish new knowledge about the types. In both of these cases—and more examples can be found—authors move from qualitative data and try to keep the meaning established when using the quantitative data.

A second main result of our study is that a definition, and we provided one, offers a way for research to clarify, and even evaluate, what is done. Hence, our definition can guide researchers and students, informing them on how to think about concrete research problems they face, and to show what it means to get closer in a process in which new distinctions are made. The definition can also be used to evaluate the results, given that it is a standard of evaluation (cf. Hammersley 2007 ), to see whether new distinctions are made and whether this improves our understanding of what is researched, in addition to the evaluation of how the research was conducted. By making what is qualitative research explicit it becomes easier to communicate findings, and it is thereby much harder to fly under the radar with substandard research since there are standards of evaluation which make it easier to separate “good” from “not so good” qualitative research.

To conclude, our analysis, which ends with a definition of qualitative research can thus both address the “internal” issues of what is qualitative research, and the “external” critiques that make it harder to do qualitative research, to which both pressure from quantitative methods and general changes in society contribute.

Acknowledgements

Financial Support for this research is given by the European Research Council, CEV (263699). The authors are grateful to Susann Krieglsteiner for assistance in collecting the data. The paper has benefitted from the many useful comments by the three reviewers and the editor, comments by members of the Uppsala Laboratory of Economic Sociology, as well as Jukka Gronow, Sebastian Kohl, Marcin Serafin, Richard Swedberg, Anders Vassenden and Turid Rødne.

Biographies

is professor of sociology at the Department of Sociology, Uppsala University and Universität St. Gallen. His main focus is economic sociology, and in particular, markets. He has published numerous articles and books, including Orderly Fashion (Princeton University Press 2010), Markets (Polity Press 2011) and Re-Imagining Economic Sociology (edited with N. Dodd, Oxford University Press 2015). His book Ethnographic Methods (in Swedish) has already gone through several editions.

is associate professor of sociology at the Department of Media and Social Sciences, University of Stavanger. His research has been published in journals such as Social Psychology Quarterly, Sociological Theory, Teaching Sociology, and Music and Arts in Action. As an ethnographer he is working on a book on he social world of big-wave surfing.

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Contributor Information

Patrik Aspers, Email: [email protected] .

Ugo Corte, Email: [email protected] .

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The word qualitative implies an emphasis on the qualities of entities and on processes and meanings that are not experimentally examined or measured [if measured at all] in terms of quantity, amount, intensity, or frequency. Qualitative researchers stress the socially constructed nature of reality, the intimate relationship between the researcher and what is studied, and the situational constraints that shape inquiry. Such researchers emphasize the value-laden nature of inquiry. They seek answers to questions that stress how social experience is created and given meaning. In contrast, quantitative studies emphasize the measurement and analysis of causal relationships between variables, not processes. Qualitative forms of inquiry are considered by many social and behavioral scientists to be as much a perspective on how to approach investigating a research problem as it is a method.

Denzin, Norman. K. and Yvonna S. Lincoln. “Introduction: The Discipline and Practice of Qualitative Research.” In The Sage Handbook of Qualitative Research . Norman. K. Denzin and Yvonna S. Lincoln, eds. 3 rd edition. (Thousand Oaks, CA: Sage, 2005), p. 10.

Characteristics of Qualitative Research

Below are the three key elements that define a qualitative research study and the applied forms each take in the investigation of a research problem.

• Naturalistic -- refers to studying real-world situations as they unfold naturally; non-manipulative and non-controlling; the researcher is open to whatever emerges [i.e., there is a lack of predetermined constraints on findings].
• Emergent -- acceptance of adapting inquiry as understanding deepens and/or situations change; the researcher avoids rigid designs that eliminate responding to opportunities to pursue new paths of discovery as they emerge.
• Purposeful -- cases for study [e.g., people, organizations, communities, cultures, events, critical incidences] are selected because they are “information rich” and illuminative. That is, they offer useful manifestations of the phenomenon of interest; sampling is aimed at insight about the phenomenon, not empirical generalization derived from a sample and applied to a population.

The Collection of Data

• Data -- observations yield a detailed, "thick description" [in-depth understanding]; interviews capture direct quotations about people’s personal perspectives and lived experiences; often derived from carefully conducted case studies and review of material culture.
• Personal experience and engagement -- researcher has direct contact with and gets close to the people, situation, and phenomenon under investigation; the researcher’s personal experiences and insights are an important part of the inquiry and critical to understanding the phenomenon.
• Empathic neutrality -- an empathic stance in working with study respondents seeks vicarious understanding without judgment [neutrality] by showing openness, sensitivity, respect, awareness, and responsiveness; in observation, it means being fully present [mindfulness].
• Dynamic systems -- there is attention to process; assumes change is ongoing, whether the focus is on an individual, an organization, a community, or an entire culture, therefore, the researcher is mindful of and attentive to system and situational dynamics.

The Analysis

• Unique case orientation -- assumes that each case is special and unique; the first level of analysis is being true to, respecting, and capturing the details of the individual cases being studied; cross-case analysis follows from and depends upon the quality of individual case studies.
• Inductive analysis -- immersion in the details and specifics of the data to discover important patterns, themes, and inter-relationships; begins by exploring, then confirming findings, guided by analytical principles rather than rules.
• Holistic perspective -- the whole phenomenon under study is understood as a complex system that is more than the sum of its parts; the focus is on complex interdependencies and system dynamics that cannot be reduced in any meaningful way to linear, cause and effect relationships and/or a few discrete variables.
• Context sensitive -- places findings in a social, historical, and temporal context; researcher is careful about [even dubious of] the possibility or meaningfulness of generalizations across time and space; emphasizes careful comparative case study analysis and extrapolating patterns for possible transferability and adaptation in new settings.
• Voice, perspective, and reflexivity -- the qualitative methodologist owns and is reflective about her or his own voice and perspective; a credible voice conveys authenticity and trustworthiness; complete objectivity being impossible and pure subjectivity undermining credibility, the researcher's focus reflects a balance between understanding and depicting the world authentically in all its complexity and of being self-analytical, politically aware, and reflexive in consciousness.

Berg, Bruce Lawrence. Qualitative Research Methods for the Social Sciences . 8th edition. Boston, MA: Allyn and Bacon, 2012; Denzin, Norman. K. and Yvonna S. Lincoln. Handbook of Qualitative Research . 2nd edition. Thousand Oaks, CA: Sage, 2000; Marshall, Catherine and Gretchen B. Rossman. Designing Qualitative Research . 2nd ed. Thousand Oaks, CA: Sage Publications, 1995; Merriam, Sharan B. Qualitative Research: A Guide to Design and Implementation . San Francisco, CA: Jossey-Bass, 2009.

Basic Research Design for Qualitative Studies

Unlike positivist or experimental research that utilizes a linear and one-directional sequence of design steps, there is considerable variation in how a qualitative research study is organized. In general, qualitative researchers attempt to describe and interpret human behavior based primarily on the words of selected individuals [a.k.a., “informants” or “respondents”] and/or through the interpretation of their material culture or occupied space. There is a reflexive process underpinning every stage of a qualitative study to ensure that researcher biases, presuppositions, and interpretations are clearly evident, thus ensuring that the reader is better able to interpret the overall validity of the research. According to Maxwell (2009), there are five, not necessarily ordered or sequential, components in qualitative research designs. How they are presented depends upon the research philosophy and theoretical framework of the study, the methods chosen, and the general assumptions underpinning the study. Goals Describe the central research problem being addressed but avoid describing any anticipated outcomes. Questions to ask yourself are: Why is your study worth doing? What issues do you want to clarify, and what practices and policies do you want it to influence? Why do you want to conduct this study, and why should the reader care about the results? Conceptual Framework Questions to ask yourself are: What do you think is going on with the issues, settings, or people you plan to study? What theories, beliefs, and prior research findings will guide or inform your research, and what literature, preliminary studies, and personal experiences will you draw upon for understanding the people or issues you are studying? Note to not only report the results of other studies in your review of the literature, but note the methods used as well. If appropriate, describe why earlier studies using quantitative methods were inadequate in addressing the research problem. Research Questions Usually there is a research problem that frames your qualitative study and that influences your decision about what methods to use, but qualitative designs generally lack an accompanying hypothesis or set of assumptions because the findings are emergent and unpredictable. In this context, more specific research questions are generally the result of an interactive design process rather than the starting point for that process. Questions to ask yourself are: What do you specifically want to learn or understand by conducting this study? What do you not know about the things you are studying that you want to learn? What questions will your research attempt to answer, and how are these questions related to one another? Methods Structured approaches to applying a method or methods to your study help to ensure that there is comparability of data across sources and researchers and, thus, they can be useful in answering questions that deal with differences between phenomena and the explanation for these differences [variance questions]. An unstructured approach allows the researcher to focus on the particular phenomena studied. This facilitates an understanding of the processes that led to specific outcomes, trading generalizability and comparability for internal validity and contextual and evaluative understanding. Questions to ask yourself are: What will you actually do in conducting this study? What approaches and techniques will you use to collect and analyze your data, and how do these constitute an integrated strategy? Validity In contrast to quantitative studies where the goal is to design, in advance, “controls” such as formal comparisons, sampling strategies, or statistical manipulations to address anticipated and unanticipated threats to validity, qualitative researchers must attempt to rule out most threats to validity after the research has begun by relying on evidence collected during the research process itself in order to effectively argue that any alternative explanations for a phenomenon are implausible. Questions to ask yourself are: How might your results and conclusions be wrong? What are the plausible alternative interpretations and validity threats to these, and how will you deal with these? How can the data that you have, or that you could potentially collect, support or challenge your ideas about what’s going on? Why should we believe your results? Conclusion Although Maxwell does not mention a conclusion as one of the components of a qualitative research design, you should formally conclude your study. Briefly reiterate the goals of your study and the ways in which your research addressed them. Discuss the benefits of your study and how stakeholders can use your results. Also, note the limitations of your study and, if appropriate, place them in the context of areas in need of further research.

Chenail, Ronald J. Introduction to Qualitative Research Design. Nova Southeastern University; Heath, A. W. The Proposal in Qualitative Research. The Qualitative Report 3 (March 1997); Marshall, Catherine and Gretchen B. Rossman. Designing Qualitative Research . 3rd edition. Thousand Oaks, CA: Sage, 1999; Maxwell, Joseph A. "Designing a Qualitative Study." In The SAGE Handbook of Applied Social Research Methods . Leonard Bickman and Debra J. Rog, eds. 2nd ed. (Thousand Oaks, CA: Sage, 2009), p. 214-253; Qualitative Research Methods. Writing@CSU. Colorado State University; Yin, Robert K. Qualitative Research from Start to Finish . 2nd edition. New York: Guilford, 2015.

Strengths of Using Qualitative Methods

The advantage of using qualitative methods is that they generate rich, detailed data that leave the participants' perspectives intact and provide multiple contexts for understanding the phenomenon under study. In this way, qualitative research can be used to vividly demonstrate phenomena or to conduct cross-case comparisons and analysis of individuals or groups.

Among the specific strengths of using qualitative methods to study social science research problems is the ability to:

• Obtain a more realistic view of the lived world that cannot be understood or experienced in numerical data and statistical analysis;
• Provide the researcher with the perspective of the participants of the study through immersion in a culture or situation and as a result of direct interaction with them;
• Allow the researcher to describe existing phenomena and current situations;
• Develop flexible ways to perform data collection, subsequent analysis, and interpretation of collected information;
• Yield results that can be helpful in pioneering new ways of understanding;
• Respond to changes that occur while conducting the study ]e.g., extended fieldwork or observation] and offer the flexibility to shift the focus of the research as a result;
• Provide a holistic view of the phenomena under investigation;
• Respond to local situations, conditions, and needs of participants;
• Interact with the research subjects in their own language and on their own terms; and,
• Create a descriptive capability based on primary and unstructured data.

Anderson, Claire. “Presenting and Evaluating Qualitative Research.” American Journal of Pharmaceutical Education 74 (2010): 1-7; Denzin, Norman. K. and Yvonna S. Lincoln. Handbook of Qualitative Research . 2nd edition. Thousand Oaks, CA: Sage, 2000; Merriam, Sharan B. Qualitative Research: A Guide to Design and Implementation . San Francisco, CA: Jossey-Bass, 2009.

Limitations of Using Qualitative Methods

It is very much true that most of the limitations you find in using qualitative research techniques also reflect their inherent strengths . For example, small sample sizes help you investigate research problems in a comprehensive and in-depth manner. However, small sample sizes undermine opportunities to draw useful generalizations from, or to make broad policy recommendations based upon, the findings. Additionally, as the primary instrument of investigation, qualitative researchers are often embedded in the cultures and experiences of others. However, cultural embeddedness increases the opportunity for bias generated from conscious or unconscious assumptions about the study setting to enter into how data is gathered, interpreted, and reported.

Some specific limitations associated with using qualitative methods to study research problems in the social sciences include the following:

• Drifting away from the original objectives of the study in response to the changing nature of the context under which the research is conducted;
• Arriving at different conclusions based on the same information depending on the personal characteristics of the researcher;
• Replication of a study is very difficult;
• Research using human subjects increases the chance of ethical dilemmas that undermine the overall validity of the study;
• An inability to investigate causality between different research phenomena;
• Difficulty in explaining differences in the quality and quantity of information obtained from different respondents and arriving at different, non-consistent conclusions;
• Data gathering and analysis is often time consuming and/or expensive;
• Requires a high level of experience from the researcher to obtain the targeted information from the respondent;
• May lack consistency and reliability because the researcher can employ different probing techniques and the respondent can choose to tell some particular stories and ignore others; and,
• Generation of a significant amount of data that cannot be randomized into manageable parts for analysis.

Research Tip

Human Subject Research and Institutional Review Board Approval

Almost every socio-behavioral study requires you to submit your proposed research plan to an Institutional Review Board. The role of the Board is to evaluate your research proposal and determine whether it will be conducted ethically and under the regulations, institutional polices, and Code of Ethics set forth by the university. The purpose of the review is to protect the rights and welfare of individuals participating in your study. The review is intended to ensure equitable selection of respondents, that you have met the requirements for obtaining informed consent , that there is clear assessment and minimization of risks to participants and to the university [read: no lawsuits!], and that privacy and confidentiality are maintained throughout the research process and beyond. Go to the USC IRB website for detailed information and templates of forms you need to submit before you can proceed. If you are  unsure whether your study is subject to IRB review, consult with your professor or academic advisor.

Chenail, Ronald J. Introduction to Qualitative Research Design. Nova Southeastern University; Labaree, Robert V. "Working Successfully with Your Institutional Review Board: Practical Advice for Academic Librarians." College and Research Libraries News 71 (April 2010): 190-193.

Another Research Tip

Finding Examples of How to Apply Different Types of Research Methods

SAGE publications is a major publisher of studies about how to design and conduct research in the social and behavioral sciences. Their SAGE Research Methods Online and Cases database includes contents from books, articles, encyclopedias, handbooks, and videos covering social science research design and methods including the complete Little Green Book Series of Quantitative Applications in the Social Sciences and the Little Blue Book Series of Qualitative Research techniques. The database also includes case studies outlining the research methods used in real research projects. This is an excellent source for finding definitions of key terms and descriptions of research design and practice, techniques of data gathering, analysis, and reporting, and information about theories of research [e.g., grounded theory]. The database covers both qualitative and quantitative research methods as well as mixed methods approaches to conducting research.

SAGE Research Methods Online and Cases

NOTE :  For a list of online communities, research centers, indispensable learning resources, and personal websites of leading qualitative researchers, GO HERE .

For a list of scholarly journals devoted to the study and application of qualitative research methods, GO HERE .

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What is qualitative research?

"Qualitative research is a type of research that explores and provides deeper insights into real-world problems. [1]  Instead of collecting numerical data points or intervene or introduce treatments just like in quantitative research, qualitative research helps generate hypotheses as well as further investigate and understand quantitative data."

"Qualitative research at its core, ask open-ended questions whose answers are not easily put into numbers such as ‘how’ and ‘why’. [2]  Due to the open-ended nature of the research questions at hand, qualitative research design is often not linear in the same way quantitative design is. [2]  One of the strengths of qualitative research is its ability to explain processes and patterns of human behavior that can be difficult to quantify. [3]  Phenomena such as experiences, attitudes, and behaviors can be difficult to accurately capture quantitatively, whereas a qualitative approach allows participants themselves to explain how, why, or what they were thinking, feeling, and experiencing at a certain time or during an event of interest."

• Qualitative Study - Steven Tenny; Grace D. Brannan; Janelle M. Brannan; Nancy C. Sharts-Hopko. This article details what qualitative research is, and some of the methodologies used.

Examples of Qualitative Research

• Quantitative vs Qualitative Chart Chart showing examples of quantitative vs. qualitative research.

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Qualitative Research : Definition

Qualitative research is the naturalistic study of social meanings and processes, using interviews, observations, and the analysis of texts and images.  In contrast to quantitative researchers, whose statistical methods enable broad generalizations about populations (for example, comparisons of the percentages of U.S. demographic groups who vote in particular ways), qualitative researchers use in-depth studies of the social world to analyze how and why groups think and act in particular ways (for instance, case studies of the experiences that shape political views).   

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Qualitative Research 101: Everything you need to know

How to choose the right software for qualitative research

What does psychology say about qualitative research via webcam?

Which is better - online or face-to-face qual (according to psychology)?

If you are keen on learning more about qualitative research, it can be hard to find an overview of all the key things you need to know, and how to apply everything that is available in the qualitative research sphere to your particular needs. This article has been designed to be that overview - a "pillar page" that will provide everything you need to know before spreading your search further into specific areas that interest you or that directly relate to what you are trying to achieve using the latest qualitative research tools and methods.

In this article you will discover:

The difference between qualitative and quantitative research The difference between online and offline qualitative research Common qualitative research methodologies The powerful market research trend towards video that is changing the qualitative research landscape Modern approaches to qualitative data analysis How to choose qualitative research software

When talking about research methods, there are generally two distinct styles of research that need to be considered - qualitative and quantitative. Any discussion about qualitative research, what it is, and how it can be used inevitably must also consider how it is different from quantitative research - so that is where we will begin!

Qualitative vs quantitative research

Quantitative research: all about the numbers.

Quantitative research is most often associated with the social sciences, natural sciences, and business administration. It often involves measuring the impact of certain events on a population. Specifically, it is research that measures something with numbers.

For example, in medicine, a researcher might investigate the efficacy of a new vaccine on patients by conducting a quantitative research study. A simpler example might be finding out how many people have heard of a particular brand, and how many like the brand.

Data collection for quantitative studies is often through running Web surveys, and there are a large number of platforms available to create such surveys, ranging from the relatively cheap Survey Monkey through to Confirmit and Qualtrics at the high end.

Due to the nature of quantitative research - the collection and analysis of numbers - research is heavily biased towards online methods, and data analysis takes advantage of all the intrinsic benefits of computers ("crunching" large amounts of data, performing analytics to uncover trends and producing digestible summaries of big data sets).

Qualitative research: Analysis of non-numerical data

Qualitative research is literally everything quantitative research is not. It involves the collection and analysis of non-numerical data (e.g., text, video, audio). Rather than resulting in "statistics", it results in "insights" (i.e. it helps to understand concepts, opinions, or experiences). The goal is often to delve into what problems exist or to generate new ideas for research.

The purpose of qualitative research is to "explain rather than describe". Qualitative research projects are often exploratory rather than explanatory, aiming to explore phenomenon rather than test a hypothesis. As such, the research may be used to generate or contribute evidence towards new hypotheses.

One of the biggest concerns when conducting qualitative research is sampling. Because most studies aim to understand a larger group through intensive observation (e.g. ethnography), samples are typically smaller than in quantitative research where random sampling is more common. Sampling may also be more purposive rather than random. Participants may be selected by convenience, snowball, or judgemental methods, which raises concerns that findings cannot be generalised beyond the sample.

An effort is usually made to avoid this problem by collecting data from multiple, diverse sources and triangulating findings so that different perspectives are considered at the same time. Rather than looking for statistical significance in the results, "thematic findings" are what is important in qualitative research.

Factors to determine your sample size for qualitative research

Qualitative research is often overshadowed by quantitative research due to the sheer size of the quantitative research industry, and the ease with which the benefits of quantitative methods can be understood and applied. The broadness of qualitative research is both a strength and a weakness. While it provides insights that are impossible to get through numbers, the broadness of approaches and the ever-improving suite of tools and technologies available can make it harder to understand (and keep up with).

Gaining an understanding of qualitative research methods and approaches and applying them to your clients can distinguish you from your competitors, so it is certainly worth the effort to understand what is possible. Providing something different, and better, that results in deeper insights is always going to be of greater value than a "quant only" offering.

The best way to expand your quant-based research firm is to move into qual and provide a hybrid approach that gives clients the best of both worlds. Because of the more open-ended and emergent nature of the qualitative inquiry, the field is more amenable to using mixed-methods approaches. For instance, researchers can use a qualitative methodology such as ethnography to guide the focus of a larger, quantitative survey.

How to conduct qualitative market research successfully

Online vs. offline qualitative research

The qualitative research methods being used most commonly today fall into two distinct "camps" - online and offline. Online qualitative research is defined as research where the qualitative data is collected "digitally" - usually over the Internet. Offline research is where more traditional data collection methods are used involving physical contact between moderators and participants.

Online research methods are on the rise

Online research is on the rise because it enables fast and wide-scale access to participants (e.g. through social media recruitment) without needing any specific fieldwork abilities (e.g. recruiting on the street). Furthermore, it enables researchers to be more flexible with whom they can communicate with (e.g. online focus groups that involve geographically remote participants).

Advantages of online research: Why you should move your project online

Due to these advantages, more and more researchers are embracing digital technologies for at least some of their qualitative research data collection. Lastly, it can be argued that digital research not only enhances but also move beyond traditional qualitative methods such as interviews and observations.

As with any form of research, it is important to take all of the key advantages and disadvantages of going online into account before making a final decision about which way to take a particular project.

The top 7 advantages of online research

Data can be collected from anywhere in the world (e.g., recruitment through social media) Approach participants quickly and with minimal costs (e.g., data is crowd-sourced) Data can be analyzed automatically (e.g., using an online platform that analyses textual data such as words and phrases used or frequency of self-reported emotions). Enables researchers to be more flexible with whom they can communicate with (e.g., online focus groups) Allows researchers to easily create their own coding schemes when using specific platforms for data collection. Data provides insight into unmeasured or under-researched phenomena that are not typically covered by traditional qualitative methods (e.g., consumer loyalty) The ability to protect anonymity and confidentiality of respondents due to its largely distance-based nature

Offline qualitative research methods are still important

Online research is never going to completely replace offline methods. Regardless of any other reasons, online methods are simply not right for every circumstance.

Critics of online research believe that the main disadvantages in collecting qualitative data digitally are related to the quality and reliability of the data being collected. Some of their specific concerns are:

That without in-depth knowledge about how these platforms work, researchers might not be able to prevent participants from breaking their anonymity rules for example. In some cases it is difficult if not impossible for researchers to identify who exactly is behind a certain set of data. Data which is collected online will most likely only give one interpretation, since there is no way to verify what respondents mean/intend by their responses . Because of the lack of control over study participants (e.g. drop out rates), drawing definitive conclusions about phenomena becomes harder.

What is interesting about all of these concerns is they all appear to be the result of poor platform choice, platform training, or project management. For researchers who what to take the lead into online research, a key point from all of these concerns is going online requires both careful research and personal commitment to make these online research methods work.

How to choose qualitative research software

The reason offline qualitative research will continue to be important has nothing really to do with pitfalls of going online that can be avoided with the right platform and training. It has much more to do with the simple fact that offline will always be better in certain circumstances . An example would be a taste test or a group trial of a physical product where initial reactions are key.

Common qualitative research methodologies

Qualitative research methods are designed to discover what people "think" about a particular topic. It can involve looking at how they behave, and what their perceptions are. While there are many different types of research that can be classed as "qualitative research" - including things like document analysis - here we will focus on the main types of research requested from market research professionals by their clients.

In-depth interviews

These are known by various names - including one-on-one interviews and "IDIs". This method involves directly asking research participants questions in order to gain their opinions on specific subjects.

Focus groups

Focus groups are one of the more commonly used qualitative research methods, and they play an important role in many qualitative research projects. A focus group usually includes a relatively small group of respondents (usually between 6-10) who will meet together either (i.e. in a "group") in person or virtually on a zoom call or through an online platform.

The use of a focus group has some benefits and some disadvantages when compared to one-on-one interviews as discussed below.

Advantages over in-depth interviews

Focus groups allow for more people to be covered in a shorter period of time so you can reach more people outside your group faster than you could with just one-on-one interviews Because multiple people are involved it's easier to see how certain people may affect others' thoughts and opinions It allows for a much faster response time because all of your information is being collected from multiple sources at once.

Disadvantages to in-depth interviews

Much can be lost in translation when trying to interpret everyone's answers Much depends on the quality and experience of the moderator It may be difficult for people who are interacting with other people to remain completely unbiased.

Taking focus groups online is one of the key "battlegrounds" between online and offline research methods. There is a lot to consider when deciding if taking your next project online is a good option.

Online consumer research panels: Are they the right method for your next project?

Ethnography

Another common method of qualitative research is known as "Ethnography". This type of research involves immersing yourself within a group or culture for an extended period of time.

For example, you might want to learn about the daily life of teenagers living on their own or what it's like to be a stay-at-home mom.

Online-specific research methodologies

The research methodologies that we have discussed above all have a common trait - they existed before online research was even an option. There is a long history of these research methods being used, and the move to online for all of these methodologies does not change their fundamental structure and purpose.

For example, video groups on Zoom and other video-based platforms can replicate focus groups and one-on-one interviews. These are still essentially the same "methodologies" - they are just conducted online rather than offline.

New online methodologies

The rise of online research has led to the creation of a whole series of new online tools that have created opportunities for completely new methodologies that have no equivalent in the offline research world. Since they have been designed specifically for online, they provide an optimised digital experience for participants.

Online discussions

Online discussions can have many different names, including bulletin boards, forums and short-term communities. Regardless of what they are called, they all have the same traits:

They generally have between 10-60 participants (though they can have more)

The discussion is run over a few days of weeks

Generally there will be a couple of activities each day to complete

A moderator will probe participants for further information or engage with them in other ways to help get deeper insights

Participants may be able to engage with each other to give more of a "community feel" to a particular activity.

Advanced activities - like ideations - may provide specific functionality for certain types of research that can be conducted within a wider discussion project.

Online discussions can be accessed on any modern device - including mobile phones, tablets and laptops - making access easy regardless of where a participant is at any particular time. This makes them perfect for longer term research that will need participants to be involved for multiple days or weeks. Such involvement would be impossible in the "real world" because the amount of time that would have to be allocated to performing activities in person would be impossibly high.

The technologies available to you to complete online discussions is extensive, with a number of platforms offering suites of 15 or more activity types for all types of data collection. These collection methods can be mixed and matched to create a more engaging experience for the people taking part - perhaps a video and a quick poll today, followed by a pin task and some picture taking tomorrow.

Long-term communities

For many years, long-term communities were simply "panels". They existed mainly as a pool of people that could be used as respondents to Web surveys. Qualitative research wasn't part of the research process, and these panels were just a means to get the people required to collect quantitative data.

Over the years, as qualitative research grew online, qualitative researchers started see whether they could run a qualitative study as a semi structured project directly from within these panels. What they found was using a new research method with people who were used to Web surveys meant they didn't always get the quality of results they expected.

This has led to the growth of something designed to be used in qualitative research from the very start - smaller panels of people (as small as a few hundred up to a thousand people in total) specifically recruited to provide valuable qualitative insights for a long period of time.

Long-term communities differ from short-term communities (i.e. discussions) in a number of ways:

Discussions tend to be very structured - e.g. three days of activities, with four activities on each day. Long-term communities are much less structured - "add a task whenever needed" is a common approach. Clients often use a long-term community as an easily accessible pool of people to ask opinions of at a moment's notice. Discussions are very "ad-hoc" - it's all over in a matter of days or weeks. Long-term communities are much more of a commitment for participants. They feel more like their own Web site, and things like logins, ongoing rewards and additional content like blogs are much more common. Discussions are quicker to set up and recruit for, but once they are done, the recruits are gone. Each discussion usually needs to be recruited for all over again. Long-term communities require more set up including theming and various content pages, but once set up and recruited for you don't necessarily have to recruit again - you keep going back to the same pool of people.

From a qualitative research perspective, the thing that is the same regardless of whether you are doing a short-term or long-term community is the suite of activities available to you.

The powerful market research trend towards video

We live in a world right now, however, where the speed of change is being forced upon a market research professional is much faster than normal. Remote working has become much more common, and all manner of research (for example - tracking a customer journey) has had to be adjusted to consider new restrictions on practical aspects of conducting market research - particularly in terms of how data collection will need to be done.

Online research has primarily grown through the use of technology to add to the existing research methods in ways that can not be replicated in the "real world". Huge scale, the ability to leverage social media, and the ability to crunch a lot of data are just some of the things that have made certain online research methods so important for literally decades.

As an increasing slice of new projects moves online, the replacement for "in-person" will primarily be "on video". It will be easier to get participants (because being in the vicinity of a central location is no longer necessary, and attending virtually is less of a "hassle"), and moderator location is also unimportant. Incentives can be less, and some costs - like the cost of a group room - will disappear completely.

Understanding the bigger picture by including video as part of any research project is considered to be extremely important by clients who want to make informed decisions, understand the biggest trends and get a better understanding of what various different types of people think - regardless of whether they are looking at consumers online through, people using social media, employees of many companies or anyone else. Video is almost always a powerful tool to go beyond text-based responses.

As the amount of video being collected grows, and the level of analysis and quality of expected outputs also becomes higher - this all begs the question... how is this even achievable? Watching hours and hours of video and trying to make sense of it all is extremely time-consuming, so manually solving this problem is expensive at best, and near-impossible at worst.

Fortunately, analysis of the ever-growing amount of video being collected is made feasibly through the use of automated "video analytics". Harnessing these new technologies has been made possible by taking the capabilities of Google, Microsoft, Amazon and others, and using them as building blocks to create a solution that is specific to market research.

The 3 Market Research Trends taking the industry by storm

Modern approaches to qualitative data analysis

The process of analyzing data and your research findings is critical when it comes to making decisions; this is why it's vital you make the process of analysing qualitative data as easy and as simple as possible.

Traditional analysis is undertaken by researchers while in the room with focus groups or conducting the interviews - benefiting from the social context of being able to read and individuals emotions and keep participants from straying off course. The quality of the analysis is directly related to the skill and experience of the researchers themselves, which can be a limiting factor.

Online approaches to qualitative study help foster creativity and ingenuity - with researchers always looking for new ways of engaging with participants. The great thing about modern online data analysis is that sky is indeed the limit in terms of developing new ideas and methodologies when collecting data and how to analyse it.

Qualitative analysis does not need to take up your time - modern approaches enable you to receive responses in real-time so that you can start to analyze data right from the get-go. As part of any campaign, you should be given access to a dashboard that provides you with the tools to start your data analysis.

Your dashboard is the start of your qualitative data analysis and shows you how your sample is responding or engaging to your research questions; it'll display all data collected and the level of engagement from your sample.

The modern approach of using a dedicated platform empowers the researcher to track respondent behaviour and the wider community.

How to make qualitative data analysis easy and simple

Any venture into the world of online qualitative research necessitates to use of a platform to create and run your projects. Finding the right platform can be a daunting task, but there are a few basic things to consider when taking this journey of discovery.

Avoid lock-in to untried solutions

Unfortunately, we live in a world where "subscriptions are king" and locking you into a particular platform - preferably for a few years - is the end goal of many platform providers. Big promises linked to a long-term commitment or large upfront costs are quite common.

There is no need to lock into anything, ever, if you don't want to . A number of providers will offer very reasonable per-project pricing that will not only suit your existing project but will also let you try the platform, set up your project design, and show your client a preview of what they will be getting before making you pay for anything. Providers who are happy to back their platform and show you everything you need to make an informed decision without trying to first lock you in are the ones to look for.

Ensure you will get the support you need

Even the best qualitative research platforms can fall down due to poor support - particularly when you are new to the platform. Confirm what support is provided - and if it costs extra factor this into your costs. Online research often requires quick support response times - particularly when you are dealing with real-time research like a live group.

There are various levels of support available, but some of the things to look out for:

You may be able to get free setup included for your first project - some suppliers offer this to help make this first experience as smooth as possible, and to help you get the most out of the platform from day one.

Some platforms give you instant access to the support team through an online chat. Often this is also a great way to get quick access to their knowledgebase.

When looking at testimonials for a platform, pay particular attention to what is said about support - the quality and level of support is hard to gauge prior to getting involved in a project (it's easy to promise good support - harder to confirm the promises).

Try to discover the true capabilities of a platform

At first glance, all platforms can seem very similar. Same promise about how great they are. Similar list of qualitative research methods is available to you. Similar indications that they would be perfect for "you". The trick is to look around the edges of all these claims to determine whether what you need is truly available. Examples of things to consider are:

Does the platform use an app on phones and tablets? A few years ago apps were necessary to support some of the more advanced activities, however advances in browsers make them redundant nowadays, so all you are left with is their limitations. If they don't install as expected or crash when running, fixing the specific issue with a specific device is near impossible. Completely browser-based solutions can be used by participants on any device from a single link. Access is instant, and if a device is playing up, simply move to another one. Does the platform do what you want with videos? This point leads on from what we discussed earlier in this article - the rise of video in qualitative research. If you don't need video, or you just want to collect the video and deal with it yourself this is not a big issue - all platforms will do that. If, however, the idea of video analytics excites you (and more importantly your clients) make sure you pick a platform with powerful analytics features. All platforms will offer some sort of text transcription - the question is whether they go beyond that to identify sentiment and themes, and whether they help you build showreels (often also known as highlight reels). Does the platform cost rise steeply as the number of participants or days rise? Platforms can often appear to be around the same price, but always make sure you get a final price based on your exact needs. So of the pricing offered by platforms is for as few as 10 participants, while other platforms provide the same price all the way to 200 participants. If you have a discussion with 50 participants, the final cost between these platforms is likely to be substantial.

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As the preceding sections have suggested, qualitative interviews are an excellent way to gather detailed information. Whatever topic is of interest to the researcher can be explored in much more depth by employing this method than with almost any other method. Not only are participants given the opportunity to elaborate in a way that is not possible with other methods, such as survey research, but, in addition, they are able share information with researchers in their own words and from their own perspectives, rather than attempting to fit those perspectives into the perhaps limited response options provided by the researcher. Because qualitative interviews are designed to elicit detailed information, they are especially useful when a researcher’s aim is to study social processes, or the “how” of various phenomena. Yet another, and sometimes overlooked, benefit of qualitative interviews that occurs in person is that researchers can make observations beyond those that a respondent is orally reporting. A respondent’s body language, and even her or his choice of time and location for the interview, might provide a researcher with useful data.

As with quantitative survey research, qualitative interviews rely on respondents’ ability to accurately and honestly recall whatever details about their lives, circumstances, thoughts, opinions, or behaviors are being examined. Qualitative interviewing is also time-intensive and can be quite expensive. Creating an interview guide, identifying a sample, and conducting interviews are just the beginning of the process. Transcribing interviews is labor-intensive, even before coding begins. It is also not uncommon to offer respondents some monetary incentive or thank-you for participating, because you are asking for more of the participants’ time than if you had mailed them a questionnaire containing closed-ended questions. Conducting qualitative interviews is not only labor intensive but also emotionally taxing. Researchers embarking on a qualitative interview project with a subject that is sensitive in nature should keep in mind their own abilities to listen to stories that may be difficult to hear.

Research Methods, Data Collection and Ethics Copyright © 2020 by Valerie Sheppard is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Chapter 10: Qualitative Data Collection & Analysis Methods

10.7 Strengths and Weaknesses of Qualitative Interviews

As the preceding sections have suggested, qualitative interviews are an excellent way to gather detailed information. Whatever topic is of interest to the researcher can be explored in much more depth by employing this method than with almost any other method. Not only are participants given the opportunity to elaborate in a way that is not possible with other methods, such as survey research, but, in addition, they are able share information with researchers in their own words and from their own perspectives, rather than attempting to fit those perspectives into the perhaps limited response options provided by the researcher. Because qualitative interviews are designed to elicit detailed information, they are especially useful when a researcher’s aim is to study social processes, or the “how” of various phenomena. Yet another, and sometimes overlooked, benefit of qualitative interviews that occurs in person is that researchers can make observations beyond those that a respondent is orally reporting. A respondent’s body language, and even her or his choice of time and location for the interview, might provide a researcher with useful data.

As with quantitative survey research, qualitative interviews rely on respondents’ ability to accurately and honestly recall whatever details about their lives, circumstances, thoughts, opinions, or behaviors are being examined. Qualitative interviewing is also time-intensive and can be quite expensive. Creating an interview guide, identifying a sample, and conducting interviews are just the beginning of the process. Transcribing interviews is labor-intensive, even before coding begins. It is also not uncommon to offer respondents some monetary incentive or thank-you for participating, because you are asking for more of the participants’ time than if you had mailed them a questionnaire containing closed-ended questions. Conducting qualitative interviews is not only labor intensive but also emotionally taxing. Researchers embarking on a qualitative interview project with a subject that is sensitive in nature should keep in mind their own abilities to listen to stories that may be difficult to hear.

Research Methods for the Social Sciences: An Introduction Copyright © 2020 by Valerie Sheppard is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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4.2 Definitions and Characteristics of Qualitative Research

Qualitative research aims to uncover the meaning and understanding of phenomena that cannot be broken down into measurable elements. It is based on naturalistic, interpretative and humanistic notions. 5 This research method seeks to discover, explore, identify or describe subjective human experiences using non-statistical methods and develops themes from the study participants’ stories. 5 Figure 4.1 depicts major features/ characteristics of qualitative research. It utilises exploratory open-ended questions and observations to search for patterns of meaning in collected data (e.g. observation, verbal/written narrative data, photographs, etc.) and uses inductive thinking (from specific observations to more general rules) to interpret meaning. 6 Participants’ voice is evident through quotations and description of the work. 6 The context/ setting of the study and the researcher’s reflexivity (i.e. “reflection on and awareness of their bias”, the effect of the researcher’s experience on the data and interpretations) are very important and described as part of data collection. 6 Analysis of collected data is complex, often involves inductive data analysis (exploration, contrasts, specific to general) and requires multiple coding and development of themes from participant stories. 6

Reflexivity- avoiding bias/Role of the qualitative researcher

Qualitative researchers generally begin their work with the recognition that their position (or worldview) has a significant impact on the overall research process. 7 Researcher worldview shapes the way the research is conducted, i.e., how the questions are formulated, methods are chosen, data are collected and analysed, and results are reported. Therefore, it is essential for qualitative researchers to acknowledge, articulate, reflect on and clarify their own underlying biases and assumptions before embarking on any research project. 7 Reflexivity helps to ensure that the researcher’s own experiences, values, and beliefs do not unintentionally bias the data collection, analysis, and interpretation. 7 It is the gold standard for establishing trustworthiness and has been established as one of the ways qualitative researchers should ensure rigour and quality in their work. 8 The following questions in Table 4.1 may help you begin the reflective process. 9

Table 4.1: Questions to aid the reflection process

Philosophical underpinnings to qualitative research

Qualitative research uses an inductive approach and stems from interpretivism or constructivism and assumes that realities are multiple, socially constructed, and holistic. 10 According to this philosophical viewpoint, humans build reality through their interactions with the world around them. 10 As a result, qualitative research aims to comprehend how individuals make sense of their experiences and build meaning in their lives. 10 Because reality is complex/nuanced and context-bound, participants constantly construct it depending on their understanding. Thus, the interactions between the researcher and the participants are considered necessary to offer a rich description of the concept and provide an in-depth understanding of the phenomenon under investigation. 11

An Introduction to Research Methods for Undergraduate Health Profession Students Copyright © 2023 by Faith Alele and Bunmi Malau-Aduli is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

Quantitative and Qualitative Research

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What is qualitative research?

Qualitative research is a process of naturalistic inquiry that seeks an in-depth understanding of social phenomena within their natural setting. It focuses on the "why" rather than the "what" of social phenomena and relies on the direct experiences of human beings as meaning-making agents in their every day lives. Rather than by logical and statistical procedures, qualitative researchers use multiple systems of inquiry for the study of human phenomena including biography, case study, historical analysis, discourse analysis, ethnography, grounded theory, and phenomenology.

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23 Advantages and Disadvantages of Qualitative Research

Investigating methodologies. Taking a closer look at ethnographic, anthropological, or naturalistic techniques. Data mining through observer recordings. This is what the world of qualitative research is all about. It is the comprehensive and complete data that is collected by having the courage to ask an open-ended question.

Print media has used the principles of qualitative research for generations. Now more industries are seeing the advantages that come from the extra data that is received by asking more than a “yes” or “no” question.

The advantages and disadvantages of qualitative research are quite unique. On one hand, you have the perspective of the data that is being collected. On the other hand, you have the techniques of the data collector and their own unique observations that can alter the information in subtle ways.

That’s why these key points are so important to consider.

What Are the Advantages of Qualitative Research?

1. Subject materials can be evaluated with greater detail. There are many time restrictions that are placed on research methods. The goal of a time restriction is to create a measurable outcome so that metrics can be in place. Qualitative research focuses less on the metrics of the data that is being collected and more on the subtleties of what can be found in that information. This allows for the data to have an enhanced level of detail to it, which can provide more opportunities to glean insights from it during examination.

2. Research frameworks can be fluid and based on incoming or available data. Many research opportunities must follow a specific pattern of questioning, data collection, and information reporting. Qualitative research offers a different approach. It can adapt to the quality of information that is being gathered. If the available data does not seem to be providing any results, the research can immediately shift gears and seek to gather data in a new direction. This offers more opportunities to gather important clues about any subject instead of being confined to a limited and often self-fulfilling perspective.

3. Qualitative research data is based on human experiences and observations. Humans have two very different operating systems. One is a subconscious method of operation, which is the fast and instinctual observations that are made when data is present. The other operating system is slower and more methodical, wanting to evaluate all sources of data before deciding. Many forms of research rely on the second operating system while ignoring the instinctual nature of the human mind. Qualitative research doesn’t ignore the gut instinct. It embraces it and the data that can be collected is often better for it.

4. Gathered data has a predictive quality to it. One of the common mistakes that occurs with qualitative research is an assumption that a personal perspective can be extrapolated into a group perspective. This is only possible when individuals grow up in similar circumstances, have similar perspectives about the world, and operate with similar goals. When these groups can be identified, however, the gathered individualistic data can have a predictive quality for those who are in a like-minded group. At the very least, the data has a predictive quality for the individual from whom it was gathered.

5. Qualitative research operates within structures that are fluid. Because the data being gathered through this type of research is based on observations and experiences, an experienced researcher can follow-up interesting answers with additional questions. Unlike other forms of research that require a specific framework with zero deviation, researchers can follow any data tangent which makes itself known and enhance the overall database of information that is being collected.

6. Data complexities can be incorporated into generated conclusions. Although our modern world tends to prefer statistics and verifiable facts, we cannot simply remove the human experience from the equation. Different people will have remarkably different perceptions about any statistic, fact, or event. This is because our unique experiences generate a different perspective of the data that we see. These complexities, when gathered into a singular database, can generate conclusions with more depth and accuracy, which benefits everyone.

7. Qualitative research is an open-ended process. When a researcher is properly prepared, the open-ended structures of qualitative research make it possible to get underneath superficial responses and rational thoughts to gather information from an individual’s emotional response. This is critically important to this form of researcher because it is an emotional response which often drives a person’s decisions or influences their behavior.

8. Creativity becomes a desirable quality within qualitative research. It can be difficult to analyze data that is obtained from individual sources because many people subconsciously answer in a way that they think someone wants. This desire to “please” another reduces the accuracy of the data and suppresses individual creativity. By embracing the qualitative research method, it becomes possible to encourage respondent creativity, allowing people to express themselves with authenticity. In return, the data collected becomes more accurate and can lead to predictable outcomes.

9. Qualitative research can create industry-specific insights. Brands and businesses today need to build relationships with their core demographics to survive. The terminology, vocabulary, and jargon that consumers use when looking at products or services is just as important as the reputation of the brand that is offering them. If consumers are receiving one context, but the intention of the brand is a different context, then the miscommunication can artificially restrict sales opportunities. Qualitative research gives brands access to these insights so they can accurately communicate their value propositions.

10. Smaller sample sizes are used in qualitative research, which can save on costs. Many qualitative research projects can be completed quickly and on a limited budget because they typically use smaller sample sizes that other research methods. This allows for faster results to be obtained so that projects can move forward with confidence that only good data is able to provide.

11. Qualitative research provides more content for creatives and marketing teams. When your job involves marketing, or creating new campaigns that target a specific demographic, then knowing what makes those people can be quite challenging. By going through the qualitative research approach, it becomes possible to congregate authentic ideas that can be used for marketing and other creative purposes. This makes communication between the two parties to be handled with more accuracy, leading to greater level of happiness for all parties involved.

12. Attitude explanations become possible with qualitative research. Consumer patterns can change on a dime sometimes, leaving a brand out in the cold as to what just happened. Qualitative research allows for a greater understanding of consumer attitudes, providing an explanation for events that occur outside of the predictive matrix that was developed through previous research. This allows the optimal brand/consumer relationship to be maintained.

What Are the Disadvantages of Qualitative Research?

1. The quality of the data gathered in qualitative research is highly subjective. This is where the personal nature of data gathering in qualitative research can also be a negative component of the process. What one researcher might feel is important and necessary to gather can be data that another researcher feels is pointless and won’t spend time pursuing it. Having individual perspectives and including instinctual decisions can lead to incredibly detailed data. It can also lead to data that is generalized or even inaccurate because of its reliance on researcher subjectivisms.

2. Data rigidity is more difficult to assess and demonstrate. Because individual perspectives are often the foundation of the data that is gathered in qualitative research, it is more difficult to prove that there is rigidity in the information that is collective. The human mind tends to remember things in the way it wants to remember them. That is why memories are often looked at fondly, even if the actual events that occurred may have been somewhat disturbing at the time. This innate desire to look at the good in things makes it difficult for researchers to demonstrate data validity.

3. Mining data gathered by qualitative research can be time consuming. The number of details that are often collected while performing qualitative research are often overwhelming. Sorting through that data to pull out the key points can be a time-consuming effort. It is also a subjective effort because what one researcher feels is important may not be pulled out by another researcher. Unless there are some standards in place that cannot be overridden, data mining through a massive number of details can almost be more trouble than it is worth in some instances.

4. Qualitative research creates findings that are valuable, but difficult to present. Presenting the findings which come out of qualitative research is a bit like listening to an interview on CNN. The interviewer will ask a question to the interviewee, but the goal is to receive an answer that will help present a database which presents a specific outcome to the viewer. The goal might be to have a viewer watch an interview and think, “That’s terrible. We need to pass a law to change that.” The subjective nature of the information, however, can cause the viewer to think, “That’s wonderful. Let’s keep things the way they are right now.” That is why findings from qualitative research are difficult to present. What a research gleans from the data can be very different from what an outside observer gleans from the data.

5. Data created through qualitative research is not always accepted. Because of the subjective nature of the data that is collected in qualitative research, findings are not always accepted by the scientific community. A second independent qualitative research effort which can produce similar findings is often necessary to begin the process of community acceptance.

6. Researcher influence can have a negative effect on the collected data. The quality of the data that is collected through qualitative research is highly dependent on the skills and observation of the researcher. If a researcher has a biased point of view, then their perspective will be included with the data collected and influence the outcome. There must be controls in place to help remove the potential for bias so the data collected can be reviewed with integrity. Otherwise, it would be possible for a researcher to make any claim and then use their bias through qualitative research to prove their point.

7. Replicating results can be very difficult with qualitative research. The scientific community wants to see results that can be verified and duplicated to accept research as factual. In the world of qualitative research, this can be very difficult to accomplish. Not only do you have the variability of researcher bias for which to account within the data, but there is also the informational bias that is built into the data itself from the provider. This means the scope of data gathering can be extremely limited, even if the structure of gathering information is fluid, because of each unique perspective.

8. Difficult decisions may require repetitive qualitative research periods. The smaller sample sizes of qualitative research may be an advantage, but they can also be a disadvantage for brands and businesses which are facing a difficult or potentially controversial decision. A small sample is not always representative of a larger population demographic, even if there are deep similarities with the individuals involve. This means a follow-up with a larger quantitative sample may be necessary so that data points can be tracked with more accuracy, allowing for a better overall decision to be made.

9. Unseen data can disappear during the qualitative research process. The amount of trust that is placed on the researcher to gather, and then draw together, the unseen data that is offered by a provider is enormous. The research is dependent upon the skill of the researcher being able to connect all the dots. If the researcher can do this, then the data can be meaningful and help brands and progress forward with their mission. If not, there is no way to alter course until after the first results are received. Then a new qualitative process must begin.

10. Researchers must have industry-related expertise. You can have an excellent researcher on-board for a project, but if they are not familiar with the subject matter, they will have a difficult time gathering accurate data. For qualitative research to be accurate, the interviewer involved must have specific skills, experiences, and expertise in the subject matter being studied. They must also be familiar with the material being evaluated and have the knowledge to interpret responses that are received. If any piece of this skill set is missing, the quality of the data being gathered can be open to interpretation.

11. Qualitative research is not statistically representative. The one disadvantage of qualitative research which is always present is its lack of statistical representation. It is a perspective-based method of research only, which means the responses given are not measured. Comparisons can be made and this can lead toward the duplication which may be required, but for the most part, quantitative data is required for circumstances which need statistical representation and that is not part of the qualitative research process.

The advantages and disadvantages of qualitative research make it possible to gather and analyze individualistic data on deeper levels. This makes it possible to gain new insights into consumer thoughts, demographic behavioral patterns, and emotional reasoning processes. When a research can connect the dots of each information point that is gathered, the information can lead to personalized experiences, better value in products and services, and ongoing brand development.

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10 Advantages and Disadvantages of Qualitative Research

  — August 5th, 2021

Research is about gathering data so that it can inform meaningful decisions. In the workplace, this can be invaluable in allowing informed decision-making that will meet with wider strategic organizational goals.

However, research comes in a variety of guises and, depending on the methodologies applied, can achieve different ends. There are broadly two key approaches to research -- qualitative and quantitative.

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Qualitative v quantitative – what’s the difference.

Qualitative Research is at the touchy-feely end of the spectrum. It’s not so much about bean-counting and much more about capturing people’s opinions and emotions.

“Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context.” (simplypsychology.org)

Examples of the way qualitative research is often gathered includes:

Interviews are a conversation based inquiry where questions are used to obtain information from participants. Interviews are typically structured to meet the researcher’s objectives.

Focus Groups

Focus group discussions are a common qualitative research strategy . In a focus group discussion, the interviewer talks to a group of people about their thoughts, opinions, beliefs, and attitudes towards a topic. Participants are typically a group who are similar in some way, such as income, education, or career. In the context of a company, the group dynamic is likely their common experience of the workplace.

Observation

Observation is a systematic research method in which researchers look at the activity of their subjects in their typical environment. Observation gives direct information about your research. Using observation can capture information that participants may not think to reveal or see as important during interviews/focus groups.

Existing Documents

This is also called secondary data. A qualitative data collection method entails extracting relevant data from existing documents. This data can then be analyzed using a qualitative data analysis method called content analysis. Existing documents might be work documents, work email , or any other material relevant to the organization.

Quantitative Research is the ‘bean-counting’ bit of the research spectrum. This isn’t to demean its value. Now encompassed by the term ‘ People Analytics ’, it plays an equally important role as a tool for business decision-making.

Organizations can use a variety of quantitative data-gathering methods to track productivity. In turn, this can help:

• To rank employees and work units
• To award raises or promotions.
• To measure and justify termination or disciplining of staff
• To measure productivity
• To measure group/individual targets

Examples might include measuring workforce productivity. If Widget Makers Inc., has two production lines and Line A is producing 25% more per day than Line B, capturing this data immediately informs management/HR of potential issues. Is the slower production on Line B due to human factors or is there a production process issue?

Quantitative Research can help capture real-time activities in the workplace and point towards what needs management attention.

The Pros & Cons of the Qualitative approach

By its nature, qualitative research is far more experiential and focused on capturing people’s feelings and views. This undoubtedly has value, but it can also bring many more challenges than simply capturing quantitative data. Here are a few challenges and benefits to consider.

• Qualitative Research can capture changing attitudes within a target group such as consumers of a product or service, or attitudes in the workplace.
• Qualitative approaches to research are not bound by the limitations of quantitative methods. If responses don’t fit the researcher’s expectation that’s equally useful qualitative data to add context and perhaps explain something that numbers alone are unable to reveal .
• Qualitative Research provides a much more flexible approach . If useful insights are not being captured researchers can quickly adapt questions, change the setting or any other variable to improve responses.
• Qualitative data capture allows researchers to be far more speculative about what areas they choose to investigate and how to do so. It allows data capture to be prompted by a researcher’s instinctive or ‘gut feel’ for where good information will be found.

Qualitative research can be more targeted . If you want to compare productivity across an entire organization, all parts, process, and participants need to be accounted for. Qualitative research can be far more concentrated, sampling specific groups and key points in a company to gather meaningful data. This can both speed the process of data capture and keep the costs of data-gathering down.

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• Sample size can be a big issue. If you seek to infer from a sample of, for example, 200 employees, based upon a sample of 5 employees, this raises the question of whether sampling will provide a true reflection of the views of the remaining 97.5% of the company?
• Sample bias - HR departments will have competing agendas. One argument against qualitative methods alone is that HR tasked with finding the views of the workforce may be influenced both consciously or unconsciously, to select a sample that favors an anticipated outcome .
• Self-selection bias may arise where companies ask staff to volunteer their views . Whether in a paper, online survey , or focus group, if an HR department calls for participants there will be the issue of staff putting themselves forward. The argument goes that this group, in self-selecting itself, rather than being a randomly selected snapshot of a department, will inevitably have narrowed its relevance to those that typically are willing to come forward with their views. Quantitative data is gathered whether someone volunteered or not.
• The artificiality of qualitative data capture. The act of bringing together a group is inevitably outside of the typical ‘norms ’ of everyday work life and culture and may influence the participants in unforeseen ways.
• Are the right questions being posed to participants? You can only get answers to questions you think to ask . In qualitative approaches, asking about “how” and “why” can be hugely informative, but if researchers don’t ask, that insight may be missed.

The reality is that any research approach has both pros and cons. The art of effective and meaningful data gathering is thus to be aware of the limitations and strengths of each method.

In the case of Qualitative research, its value is inextricably linked to the number-crunching that is Quantitative data. One is the Ying to the other’s Yang. Each can only provide half of the picture, but together, you get a more complete view of what’s occurring within an organization.

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Qualitative vs Quantitative Research Methods & Data Analysis

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

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What is the difference between quantitative and qualitative?

The main difference between quantitative and qualitative research is the type of data they collect and analyze.

Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed in numerical terms. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.

Qualitative research , on the other hand, collects non-numerical data such as words, images, and sounds. The focus is on exploring subjective experiences, opinions, and attitudes, often through observation and interviews.

Qualitative research aims to produce rich and detailed descriptions of the phenomenon being studied, and to uncover new insights and meanings.

Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.

What Is Qualitative Research?

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality.

Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.

Qualitative research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Denzin and Lincoln (1994, p. 2)

Interest in qualitative data came about as the result of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as behaviorists (e.g., Skinner ).

Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research since it fails to capture the totality of human experience and the essence of being human.  Exploring participants’ experiences is known as a phenomenological approach (re: Humanism ).

Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.

Qualitative research aims to understand the social reality of individuals, groups, and cultures as nearly as possible as participants feel or live it. Thus, people and groups are studied in their natural setting.

Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people.

Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context. It can be used to generate hypotheses and theories from the data.

Qualitative Methods

There are different types of qualitative research methods, including diary accounts, in-depth interviews , documents, focus groups , case study research , and ethnography.

The results of qualitative methods provide a deep understanding of how people perceive their social realities and in consequence, how they act within the social world.

The researcher has several methods for collecting empirical materials, ranging from the interview to direct observation, to the analysis of artifacts, documents, and cultural records, to the use of visual materials or personal experience. Denzin and Lincoln (1994, p. 14)

Here are some examples of qualitative data:

Interview transcripts : Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings.

Observations : The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices.

Unstructured interviews : generate qualitative data through the use of open questions.  This allows the respondent to talk in some depth, choosing their own words.  This helps the researcher develop a real sense of a person’s understanding of a situation.

Diaries or journals : Written accounts of personal experiences or reflections.

Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings, and so on, can be considered qualitative data. Visual data can be used to understand behaviors, environments, and social interactions.

Qualitative Data Analysis

Qualitative research is endlessly creative and interpretive. The researcher does not just leave the field with mountains of empirical data and then easily write up his or her findings.

Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006), or discourse analysis.

For example, thematic analysis is a qualitative approach that involves identifying implicit or explicit ideas within the data. Themes will often emerge once the data has been coded .

Key Features

• Events can be understood adequately only if they are seen in context. Therefore, a qualitative researcher immerses her/himself in the field, in natural surroundings. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted.
• Qualitative researchers want those who are studied to speak for themselves, to provide their perspectives in words and other actions. Therefore, qualitative research is an interactive process in which the persons studied teach the researcher about their lives.
• The qualitative researcher is an integral part of the data; without the active participation of the researcher, no data exists.
• The study’s design evolves during the research and can be adjusted or changed as it progresses. For the qualitative researcher, there is no single reality. It is subjective and exists only in reference to the observer.
• The theory is data-driven and emerges as part of the research process, evolving from the data as they are collected.

Limitations of Qualitative Research

• Because of the time and costs involved, qualitative designs do not generally draw samples from large-scale data sets.
• The problem of adequate validity or reliability is a major criticism. Because of the subjective nature of qualitative data and its origin in single contexts, it is difficult to apply conventional standards of reliability and validity. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies.
• Also, contexts, situations, events, conditions, and interactions cannot be replicated to any extent, nor can generalizations be made to a wider context than the one studied with confidence.
• The time required for data collection, analysis, and interpretation is lengthy. Analysis of qualitative data is difficult, and expert knowledge of an area is necessary to interpret qualitative data. Great care must be taken when doing so, for example, looking for mental illness symptoms.

Advantages of Qualitative Research

• Because of close researcher involvement, the researcher gains an insider’s view of the field. This allows the researcher to find issues that are often missed (such as subtleties and complexities) by the scientific, more positivistic inquiries.
• Qualitative descriptions can be important in suggesting possible relationships, causes, effects, and dynamic processes.
• Qualitative analysis allows for ambiguities/contradictions in the data, which reflect social reality (Denscombe, 2010).
• Qualitative research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to qualitative reports to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.

What Is Quantitative Research?

Quantitative research involves the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.

The goals of quantitative research are to test causal relationships between variables , make predictions, and generalize results to wider populations.

Quantitative researchers aim to establish general laws of behavior and phenomenon across different settings/contexts. Research is used to test a theory and ultimately support or reject it.

Quantitative Methods

Experiments typically yield quantitative data, as they are concerned with measuring things.  However, other research methods, such as controlled observations and questionnaires , can produce both quantitative information.

For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g., “yes,” “no” answers).

Experimental methods limit how research participants react to and express appropriate social behavior.

Findings are, therefore, likely to be context-bound and simply a reflection of the assumptions that the researcher brings to the investigation.

There are numerous examples of quantitative data in psychological research, including mental health. Here are a few examples:

Another example is the Experience in Close Relationships Scale (ECR), a self-report questionnaire widely used to assess adult attachment styles .

The ECR provides quantitative data that can be used to assess attachment styles and predict relationship outcomes.

Neuroimaging data : Neuroimaging techniques, such as MRI and fMRI, provide quantitative data on brain structure and function.

This data can be analyzed to identify brain regions involved in specific mental processes or disorders.

For example, the Beck Depression Inventory (BDI) is a clinician-administered questionnaire widely used to assess the severity of depressive symptoms in individuals.

The BDI consists of 21 questions, each scored on a scale of 0 to 3, with higher scores indicating more severe depressive symptoms. 

Quantitative Data Analysis

Statistics help us turn quantitative data into useful information to help with decision-making. We can use statistics to summarize our data, describing patterns, relationships, and connections. Statistics can be descriptive or inferential.

Descriptive statistics help us to summarize our data. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).

• Quantitative researchers try to control extraneous variables by conducting their studies in the lab.
• The research aims for objectivity (i.e., without bias) and is separated from the data.
• The design of the study is determined before it begins.
• For the quantitative researcher, the reality is objective, exists separately from the researcher, and can be seen by anyone.
• Research is used to test a theory and ultimately support or reject it.

Limitations of Quantitative Research

• Context: Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the questions they may have for those participants (Carr, 1994).
• Researcher expertise: Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation (Black, 1999).
• Variability of data quantity: Large sample sizes are needed for more accurate analysis. Small-scale quantitative studies may be less reliable because of the low quantity of data (Denscombe, 2010). This also affects the ability to generalize study findings to wider populations.
• Confirmation bias: The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation.

Advantages of Quantitative Research

• Scientific objectivity: Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective and rational (Carr, 1994; Denscombe, 2010).
• Useful for testing and validating already constructed theories.
• Rapid analysis: Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003).
• Replication: Quantitative data is based on measured values and can be checked by others because numerical data is less open to ambiguities of interpretation.
• Hypotheses can also be tested because of statistical analysis (Antonius, 2003).

Antonius, R. (2003). Interpreting quantitative data with SPSS . Sage.

Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics . Sage.

Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology . Qualitative Research in Psychology , 3, 77–101.

Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research : what method for nursing? Journal of advanced nursing, 20(4) , 716-721.

Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill.

Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc.

Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4) , 364.

Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire.

Punch, K. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches. London: Sage

Further Information

• Designing qualitative research
• Methods of data collection and analysis
• Introduction to quantitative and qualitative research
• Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?
• Qualitative research in health care: Analysing qualitative data
• Qualitative data analysis: the framework approach
• Using the framework method for the analysis of
• Qualitative data in multi-disciplinary health research
• Content Analysis
• Grounded Theory
• Thematic Analysis

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5 Strengths and 5 Limitations of Qualitative Research

Lauren Christiansen

Insight into qualitative research.

Anyone who reviews a bunch of numbers knows how impersonal that feels. What do numbers really reveal about a person's beliefs, motives, and thoughts? While it's critical to collect statistical information to identify business trends and inefficiencies, stats don't always tell the full story. Why does the customer like this product more than the other one? What motivates them to post this particular hashtag on social media? How do employees actually feel about the new supply chain process? To answer more personal questions that delve into the human experience, businesses often employ a qualitative research process.

10 Key Strengths and Limitations of Qualitative Research

Qualitative research helps entrepreneurs and established companies understand the many factors that drive consumer behavior. Because most organizations collect and analyze quantitative data, they don't always know exactly how a target market feels and what it wants. It helps researchers when they can observe a small sample size of consumers in a comfortable environment, ask questions, and let them speak. Research methodology varies depending on the industry and type of business needs. Many companies employ mixed methods to extract the insights they require to improve decision-making. While both quantitative research and qualitative methods are effective, there are limitations to both. Quantitative research is expensive, time-consuming, and presents a limited understanding of consumer needs. However, qualitative research methods generate less verifiable information as all qualitative data is based on experience. Businesses should use a combination of both methods to overcome any associated limitations.

Strengths of Qualitative Research

• Captures New Beliefs - Qualitative research methods extrapolate any evolving beliefs within a market. This may include who buys a product/service, or how employees feel about their employers.
• Fewer Limitations - Qualitative studies are less stringent than quantitative ones. Outside the box answers to questions, opinions, and beliefs are included in data collection and data analysis.
• More Versatile - Qualitative research is much easier at times for researchers. They can adjust questions, adapt to circumstances that change or change the environment to optimize results.
• Greater Speculation - Researchers can speculate more on what answers to drill down into and how to approach them. They can use instinct and subjective experience to identify and extract good data.
• More Targeted - This research process can target any area of the business or concern it may have. Researchers can concentrate on specific target markets to collect valuable information. This takes less time and requires fewer resources than quantitative studies.

Limitations of Qualitative Research

• Sample Sizes - Businesses need to find a big enough group of participants to ensure results are accurate. A sample size of 15 people is not enough to show a reliable picture of how consumers view a product. If it is not possible to find a large enough sample size, the data collected may be insufficient.
• Bias - For internal qualitative studies, employees may be biased. For example, workers may give a popular answer that colleagues agree with rather than a true opinion. This can negatively influence the outcome of the study.
• Self-Selection Bias - Businesses that call on volunteers to answer questions worry that the people who respond are not reflective of the greater group. It is better if the company selects individuals at random for research studies, particularly if they are employees. However, this changes the process from qualitative to quantitative methods.
• Artificial - It isn't typical to observe consumers in stores, gather a focus group together, or ask employees about their experiences at work. This artificiality may impact the findings, as it is outside the norm of regular behavior and interactions.
• Quality - Questions It's hard to know whether researcher questions are quality or not because they are all subjective. Researchers need to ask how and why individuals feel the way they do to receive the most accurate answers.

Key Takeaways on Strengths and Limitations of Qualitative Research

• Qualitative research helps entrepreneurs and small businesses understand what drives human behavior. It is also used to see how employees feel about workflows and tasks.
• Companies can extract insights from qualitative research to optimize decision-making and improve products or services.
• Qualitative research captures new beliefs, has fewer limitations, is more versatile, and is more targeted. It also allows researchers to speculate and insert themselves more into the research study.
• Qualitative research has many limitations which include possible small sample sizes, potential bias in answers, self-selection bias, and potentially poor questions from researchers. It also can be artificial because it isn't typical to observe participants in focus groups, ask them questions at work, or invite them to partake in this type of research method.

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Types of qualitative research methods, when to conduct qualitative research, get the best of both worlds with attest market research platform.

Is your marketing or product development a bit weak and under the weather, or isn’t it as punchy as it used to be? Qualitative research might just be the pick-me-up it needs. Now, not just any type of qualitative market research (it’s not some magic cure-all). You need to pick the right type of qualitative research — and we’re here to help you do that.

But what you need to know about qualitative research at its core, is that it’s about exploring the qualities and nuances of human behavior and preferences. Using discussions, observations, and analysis, you try to uncover not just what people do, but why they do it.

Conducting qualitative research provides you with rich, detailed feedback that gives depth to – and compliments – quantitative research, and can help you formulate direct actions to take. Here’s which qualitative methods we’ll be exploring today.

• Focus groups
• Observation
• Content analysis 
• Narrative analysis
• Historical records management and case studies
• Ethnographic research
• Phenomenological research
• Grounded theory method
• Action research

1. Qualitative research surveys

Surveys are great for tapping into the minds of your audience: you can ask direct questions to gather feedback on everything, in a variety of formats.

With the flexibility to reach a broad audience and the ability to tailor your questions for specific insights, surveys are one of the most used tools for gathering qualitative data at scale, and in record speed.

• Collect feedback from a wide range of participants quickly.
• Tailor surveys to explore various aspects of consumer behavior, from product preferences to brand perception.
• Compared to other qualitative methods, surveys are relatively low-cost and can be distributed widely with minimal resources.

Challenges and solutions:

• Formulating questions that get deep, meaningful responses can be tricky. Focus on open-ended questions and avoid leading or biased phrasing.
• Keeping respondents interested and encouraging thoughtful responses is tricky. Offer incentives and ensure the survey is quick and clear to boost engagement and completion rates.
• The pile of qualitative data from open-ended survey responses can be a lot to work through, xo make sure you’re prepped for your qualitative data analysis.

When to use:

Use surveys to explore consumer sentiments, identify unmet needs and pain points, and evaluate what drives brand loyalty.

Send out survey questions and collect written answers or even video responses with Attest . Our platform takes care of everything, from survey templates to get you started, to best-in-class research advice to help you run truly great research.

See how qual research with Attest works

You can get high-quality video responses from your target audiences with Attest, and our team of research pros is on hand to help you run awesome research

2. Interviews

If you want to go deep, and not necessarily get a lot of data from different participants, interviews are your thing. By sitting down for a one-on-one with people from your target audience you can gather detailed feedback and personal stories

• You can follow the conversation wherever it leads, asking follow-up questions that bring out detailed or surprising insights.
• Human-to-human interactions can lead to more genuine responses, giving you a clearer picture of your audience.
• Interviews take a lot of time to conduct and analyze. Using transcription software and focusing your questions can speed things up.
• People might tell you what they think you want to hear. Make sure you create a comfortable setting and assure anonymity to encourage brutal honesty and fight bias.
• Data from interviews can be hard to compare. Sticking to a set of core questions while allowing for (controlled) personal exploration can help.

Use Interviews for qualitative research when developing new products or features to deeply understand user needs and reactions, and for branding or campaigns to gather stories and emotions that tie people to your brand, enriching your next marketing initiative.

3. Focus groups

Learn to read the room. Focus groups bring together a small group of people from your target market to discuss their opinions and experiences regarding your product or service. The setup of these groups often encourages participants to share their thoughts and ideas.

• Bringing together a variety of viewpoints and hearing how they compare to each other helps you understand the nuances of your target audience.
• Group discussions can lead to surprising angles and new insights into consumer attitudes and perceptions that individual interviews may not capture.
• Participants might sway towards consensus opinions. Encouraging open dialogue and using a skilled moderator can help avoid this. And make sure your group is diverse enough as well.
• Individuals can be overlooked in group settings. Feel like some voices are overpowering? Complement focus groups with one-on-one interviews for deeper insights.
• Organizing focus groups is pretty resource-intensive. Virtual focus groups or streamlined in-person sessions are more flexible.

Use focus groups for brand perception studies to delve into group discussions about your brand and for concept testing to gather immediate reactions to new product ideas, packaging, or marketing strategies.

4. Observation

Watching how people interact with your product or service in their natural environment (in person or through video recordings), without interference, is a great way to get real-life insights into user behavior, preferences, and potential improvements that might not be revealed through direct questioning.

• Beat assumptions and get a contextual understanding of how people interact with your product or service in real-world settings.
• Body language and other non-verbal signals can tell you a lot about how consumers feel when handling your product.
• the presence of an observer might make people change their behavior. Unobtrusive methods like video recording can help avoid that.
• Observers might interpret actions through their own bias. Make sure they are well-trained to avoid this, and that you work with multiple observers to compare interpretations.
• Translating observations into actionable data can be challenging. Structured observation guides and analytical frameworks can streamline your analysis.

Use Observation for user experience research to see how people interact with your product in real settings and for environmental impact studies to understand how different environments influence consumer behavior towards your brand.

5. Content analysis 

The words, images or videos related to your brand or product that people create and share tell a story. With content analysis, you collect all these elements and try to find themes, patterns or issues that stand out.

• You don’t have to worry about getting brand-new data in, which also makes it a more cost-effective and sometimes faster qualitative research method.
• With social listening and content analysis, you can identify emerging trends early in. All you need to do is really zoom in.
• The amount of available content is probably going to be overwhelming, but there are plenty of software tools for sentiment analysis out there that do the heavy lifting for you.
• Unhappy customers might be louder than the happy ones, so the content might not represent the broader audience. Balance your content analysis with direct research methods like surveys or interviews to mitigate this bias.

Use content analysis for uncovering insights into brand perception and evaluating the impact of marketing campaigns on public sentiment through social media content analysis.

6. Narrative analysis

Narrative analysis delves into the stories people tell about their experiences with your product or service. It focuses on understanding the sequence of events, the context, and the emotional journeys described by consumers.

• Unpacks the emotional journey and personal experiences of consumers, offering a rich understanding of their relationship with your product or service.
• By analyzing stories, you capture not just the facts but the context around consumer decisions and experiences, revealing deeper motivations.
• Stories often reflect broader cultural and social influences, helping you see how these factors impact consumer behavior.
• Personal biases can influence how narratives are interpreted. Establishing a clear analytical framework and involving multiple analysts can reduce bias.
• Narrative analysis can be detail-oriented and time-consuming. Using software to assist in data coding and thematic analysis can streamline the process.
• It can be challenging to ensure that the narratives collected are directly relevant to your research questions. Carefully designing the prompt and selection criteria for participants can help focus the stories gathered.

Use narrative analysis to map out detailed consumer journeys from first awareness to loyalty and to craft compelling brand stories that resonate deeply with your audience.

7. Historical records management and case studies

This method involves analyzing existing documents and records related to your market or industry, and conducting case studies on specific examples within your field. You look at historical trends, previous campaigns, product launches, and customer feedback over time, providing a context for current market dynamics and guiding future strategies.

• Offers a perspective on how consumer behaviors and market trends have evolved, giving you context for current data.
• You can measure the impact of changes or interventions tend to make in your marketing strategy or product development.
• Historical records may be scattered or difficult to access, so digitize records and maintain a centralized database now for future researchers.
• Ensuring that historical data is still relevant to current contexts can be challenging, so regularly update your data collection and analysis methods to reflect current market conditions.

Use historical records management and case studies for analyzing long-term market trends, assessing the effectiveness of marketing campaigns over time, and understanding the evolution of product life cycles influenced by consumer preferences.

8. Ethnographic research

Ethnographic research immerses you in the everyday lives of your target audience, observing them in their natural settings to understand their behaviors, rituals, and the social context of product usage. This gives you culturally grounded insights into how and why your product fits into consumers’ lives.

• By observing people in their natural environments, you get to see how they genuinely interact with products or services, unfiltered by self-reporting biases.
• You get detailed descriptions of people’s lives and interactions, and much more nuanced insights than numbers and charts.
• You’ll need significant time in the field and enough resources to do it right. Streamlining focus areas and using digital tools for data collection can help manage the workload.
• Immersion in a community or culture can lead to biased perspectives. Regular reflection sessions and involving multiple researchers can help maintain a balanced viewpoint.

Use ethnographic research to understand how user environments and cultures affect product use, tailor offerings for specific markets or cultural groups, and innovate with designs centered on real-world user behavior.

9. Phenomenological research

Phenomenological research focuses on the lived experiences of individuals regarding a particular phenomenon. Through in-depth interviews and discussions, you gather detailed personal accounts, looking for the underlying meanings and emotions attached to experiences with your product or service.

• It centers on the lived experiences of users, giving you a true-to-life image of understanding their needs, desires, and motivations.
• Captures the essence of consumer experiences, delivering authentic insights that can guide more empathetic and effective marketing strategies.
• The depth of phenomenological data can make analysis challenging. Working with thematic analysis and seeking expert advice can make it more manageable.
• Finding participants willing to share deeply personal experiences may be difficult. Offer assurances of confidentiality and create a safe, respectful environment.

Use phenomenological research to dive deep into the emotions and experiences of new market segments, refine user experiences for greater satisfaction, and create brand messages that forge stronger emotional connections with your audience.

10. Grounded theory method

The grounded theory method starts with data collection without a predefined hypothesis, allowing theories to emerge from the data itself. Through continuous comparison of data from interviews, surveys, or observations, you develop a theory that explains a particular aspect of consumer behavior or market trends.

• Exploring data without preconceived theories is ideal for uncovering fresh insights and new perspectives on consumer behavior.
• Based on the data, you can develop theories that explain patterns and relationships within your market, setting up a strong foundation for strategic decisions.
• As data collection and analysis proceed in tandem, you can refine your research focus based on emerging insights, ensuring the relevance and depth of findings.
• The open-ended nature of grounded theory means you’ll get piles of data. Using software for data management and employing selective sampling techniques to focus the research.
• The iterative process of coding and recoding data to develop a theory is complex. Training in grounded theory methods and regular team discussions can help clarify the process.

Use the grounded theory method to innovate products, tackle complex consumer issues, and craft strategies that deeply align with consumer preferences and behaviors.

11. Action research

Action research is a participatory method where researchers work alongside participants to identify and solve problems or improve practices. In the context of market research, it could involve collaborating with consumers to co-create solutions or enhance product design.

• Findings and insights can be applied in real-time, allowing for fast adjustments to products, services, or marketing strategies.
• Active involvement from participants, leads to a deeper engagement with your brand and a sense of ownership over the solutions developed.
• Balancing the input and engagement of participants without overwhelming them can be challenging. Set clear expectations and provide structured feedback.
• The focus on immediate solutions might overlook deeper, underlying issues. Supplement with other qualitative methods to provide a more comprehensive understanding.
• The cyclical nature of action research, with its continuous cycles of planning, acting, observing, and reflecting, requires dedication and flexibility. Agile project management techniques can keep the project on track.

Use action research to develop products informed by user feedback, enhance customer experiences through targeted improvements, and strengthen relationships with communities or stakeholders through collaborative engagement.

Conduct qualitative research when you need in-depth understanding of consumer attitudes, feelings, or behaviors—areas where quantitative research’s numbers and statistics can’t provide the full picture.

Qualitative research is best used in tandem with quantitative research – they really do compliment each other. You can use qualitative research to help inspire you at the beginning of a project, or to flesh out ideas that emerge during preceding quantitative research.

It’s especially useful for exploring new concepts, enhancing product development, or deepening brand engagement, complementing quantitative data by adding context and depth to the insights gained.

With Attest’s market research platform, you can seamlessly blend qualitative and quantitative data, giving you the insights you need for smarter marketing and better product development. See how Attest is helping businesses in a variety of industries to better understand their audiences.

Andrada Comsa

Principal Customer Research Manager 

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