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Practical Messiness Masked by the Qualitative and Quantitative Distinction

Posted By Aimée Caffrey , Tuesday, December 10, 2019
Updated: Monday, December 9, 2019

Practical Messiness Masked by the Qualitative and Quantitative Distinction

This blog post discusses the practical messiness that can be masked by the qualitative/quantitative distinction and offers an approach for thinking about and dealing with that messiness.

Like many anthropologists, I have an abiding interest in the ways in which people construct and reproduce boundaries. During my doctoral work, my primary focus was on boundaries such as ethnicity, caste, and nationality. The professional path I have taken in more recent years has in part shifted my attention toward boundaries of another variety—the boundaries that demarcate scientific knowledge practices in industry, and toward a particular boundary with which the readers of this blog are already quite familiar—that between quantitative and qualitative. In my present role, I conduct and help support research that by most definitions would count as qualitative. At the same time, this work almost always feeds into, or follows on the heels of, research that by most definitions is quantitative. It might entail using IDIs, focus groups, or journaling exercises to better understand terminology or relevant dimensions of experience prior to writing a survey. At the other end of things, it might entail using these data collection formats in an effort to make sense of survey findings—when we have discovered the what but are uncertain of the why.

Working at this intersection instills a perhaps exaggerated awareness of, and sensitivity to, the risks of accepting the quant/qual boundary at face value. Like others of its type, this distinction is a productive shorthand for organizing and talking about a variety of practices; however, it can mask the messiness of reality. A very experienced industry researcher gestured toward this messiness on a recent L&E webinar when he remarked on the "under-powered quant" that can be at work when focus group moderators ask for a show of hands. Alternatively, consider that many of what are generally marketed as mobile ethnography or online qual tools often contain what we otherwise think of as quantitative question types (e.g., multiple choice). To offer another example, I regularly assist fellow researchers with the development of interview and focus group discussion guides, and often this assistance centers in part on rephrasing "how much" (i.e., quantitative) kinds of questions to help us make sure we are in fact collecting qualitative data.

These examples of the messiness relate to a tension between the method deployed and the data gathered. When we think of the boundary between qualitative and quantitative as pertaining to a (reporting) distinction between numbers and words, the lines are similarly blurred—we discover the use of stories and images to help explain the findings of quantitative analysis and the use of quantitative adjectives to convey insights from qualitative analysis. This isn't terribly surprising: If there is "terror in numbers," as Darrell Huff wrote in How to Lie with Statistics, the tensions and nuances at the very human heart of qualitative data can also induce discomfort. But, just as the pictures (e.g., graphs) we draw to quell the disquietude of quant can exaggerate the story that the numbers tell, so too can the words we use to describe our qualitative findings be misleading. What is more important than policing the qualitative/quantitative boundary? It is being watchful for what the messiness around that boundary might signal—that there is a misalignment somewhere among the objectives in mind, the method deployed, the data gathered, and ultimately, the claims that are made.

There may be justifiable and even good reasons to ask for a show of hands in a focus group—for example, as a quick "pulse check", or to help warm up participants at the start of the discussion. But whether we think of our work as quant or qual—and whether we are thinking of our questions, our methods, or our claims in making that determination—let's be deliberate and mindful about the implications of actively inviting that messiness into the picture.

Author Bio:

aimee caffreyAimée Caffrey is a cultural anthropologist and UX researcher. Since 2017, she has worked in the Advanced Analytics Group at Bain & Company, where she collaborates with consultants, developers, designers, and fellow researchers to help clients solve some of today’s most exciting business challenges. If you wish to get in touch, please email her at Aimee.Caffrey@Bain.com.

Tags:  QRCA Digest  qualitative  qualitative research  quantitative 

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Qual or Quant? Choosing the best method for your research study

Posted By Jennifer Dale, Tuesday, September 17, 2019

Qual or Quant? Choosing the best method for your research study

Quantitative and qualitative research are both scientific methods for data collection and analysis. They can be applied alone, or in combination, to maximize insights.

The Basic Difference: Going Beyond What vs. Why

QUANT

Quantitative research relies on large sample sizes to collect numerical data that can be mathematically analyzed for statistically significantfindings. Surveys are structured, questions are typically closed-ended, and answer choices are fixed. However, quantitative research may also include a limited number of short-answer open-ended questions to help clarify why people responded the way they did to a closed-ended question. Eye tracking, facial coding, and even Big Data fall under the umbrella of quantitative research, with computers analyzing enormous volumes of data incredibly fast.

Quantitative studies produce numerical data, which allows for statistical analysis and ultimately precise findings. The US Census is a great example of a quantitative research study – fixed and close-ended questions, an enormous sample size, a collective review of many respondents, and measured population segments.

QUAL

In contrast, qualitative research seeks to understand the reasons behind the numbers, as well as what is not yet known. Sample sizes are smaller, questions are unstructured, and results more subjective. Unlike quantitative research, qualitative studies insert the researcher into the data collection process. The researcher probes responses and participants provide more detail. Qualitative data is collected through interviews, group discussions, diaries, personal observations, and a variety of other creative and ever-expanding means.

Qual studies work with textual and visual data, interpreted and analyzed for directional findings. Qualitative research studies include fluid and open-ended questions, a smaller sample size, an in-depth review of each respondent, and emerging themes.

 

I like to think of the difference visually, where a quant study collects specific data from a large number of people, and a qual study goes deeper to collect greater insights from a small number of people.

How to Choose

The answer to whether you proceed with quantitative or qualitative research lies in your research objective and available resources.

  • Why you’re doing the research
  • What you need to know
  • Your budget, staff, + schedule
  • How the findings will be used

Consider these possible scenarios the next time you’re stuck and don’t know which way to go:

Quant + qual can come together in other ways. A questionnaire with open-ended questions, while ultimately coded numerically, can offer a window into the unknown. Focus groups that also include poll questions or surveys can produce hard data when analyzed in total, even if the results are not statistically significant.

With good planning, quantitative and qualitative research come together like a dance, guiding the marketer’s success with every step.

I Say Hybrid, You Say Multimethod

Combining quantitative and qualitative research approaches is an ancient strategy, but the names continue to change with the times. I did a bit of research and found the following terms being used to describe that ideal combination of quantitative and qualitative research. What term do you use? And why? ;)

 

 

 

 

Jennifer Dale, President + CEO Inside Heads, is a seasoned marketing professional and pioneer in online market research. Her passion for marketing, human behavior, and technology keep InsideHeads on the short list of research providers for some of the world’s most discriminating clients. Jennifer is co-author of Qual-Online, The Essential Guide and has published a number of articles in VIEWS, Alert! and Quirk’s Marketing Research Review.

 

Tags:  QRCA Digest  qualitative  qualitative research  quantitative  research methodologies  research methodology 

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