Analytics Blog

Becoming A Qual Champion: A Short Guide For The Quant-Focused Researcher

The market research discipline has its roots in qualitative methods. Many decades ago, major marketing and product decisions relied on information generated by focus groups conducted in two to three geographically dispersed markets.

As technology advanced, the emphasis on qualitative learning gave way to quantitative methods, which offered robust sample sizes and projectability. Although quant research cannibalized some of the qualitative work, the market research industry as a whole expanded. Highly actionable insights were developed based on interwoven qual and quant research. And everyone was happy.

Fast-forward several decades to the present, and we see that companies no longer have the luxury to wait for insights resulting from lengthy, mixed methodological investigations. In many cases, one or more research components are jettisoned to shorten timing and reduce costs.

Qualitative is the portion of the research plan most likely to be axed in favor of a quick, quantitative survey. Grab some fast results from a healthy base of consumers and we’re off to make great business decisions! Well...maybe.

I’ve spent my entire career in the quantitative realm — conducting straightforward analyses and modeling more complex decision processes. You might think that I would not be too concerned about qual work getting the boot. You would be mistaken.

Qualitative research is fascinating. What appears to be magic is, instead, scientific and analytical. Using well-established methodologies, qual uncovers emotions and motivations associated with human decision-making behaviors. Good qual work sets the parameters of the customer journey. What do typical decisions look like? What are the key inputs into the decisions? These are things not easily discovered (if at all) by typical quant survey research.

Qualitative insights frame and then explain quantitative insights. It is impossible to measure something without first defining and understanding it. After a quant deep-dive has been conducted, qual answers the “whys” that inevitably arise — something that quant is ill-equipped to handle. It’s fair to say that qual provides the foundation on which quantitative insights rest. Failing to incorporate qualitative components into research endeavors is tantamount to erecting a house on sand.

In the spirit of fostering insights based on a solid foundation, I offer this friendly advice to my fellow, quant-focused researchers:

• Befriend a qual researcher. This can be someone in your organization, a research partner with whom you’ve worked, or even someone you’ve met at an industry conference. This person ideally will serve as a helpful resource for project scoping. Qual folks happen to be pretty fun to be around, too.
• Get to know the strengths and weaknesses of various qualitative methodologies. Most folks are familiar with the in-person depth interview and the online focus group. But did you know that these larger-style formats are giving way to smaller groups, such as dyads and triads? Are you conversant in the benefits of webcam, one-on-one interviews and online bulletin boards? You don’t have to become an expert (chances are you’re already an expert on quant methods and analysis). You do need to be knowledgeable in qual-speak to help guide your stakeholders toward the most appropriate methodology. This is a great opportunity to leverage your qual researcher bestie.
• Be involved in all research phases. At minimum, review the discussion guide to ensure that the questions being asked will yield the information you need for the quant work. And better yet, attend the focus groups or watch a live, online group. Having a quant person show up in the back room (either in person or virtually) sends a signal to the stakeholders that the broader team views the qual research as highly valuable. I know from personal experience that stakeholders will remember the quant researcher who attended the groups long after a project has concluded.

Qualitative isn’t magic. Yet it reveals the unseen and provides structure to the amorphous. Good qual work facilitates projectable insights, which ultimately enables companies to make better decisions. So go forth and be a qual champion!

Elizabeth Horn

Senior VP, Advanced Analytics

Beth has provided expertise and high-end analytics for Decision Analyst for over 25 years. She is responsible for design, analyses, and insights derived from discrete choice models; MaxDiff analysis; volumetric forecasting; predictive modeling; GIS analysis; and market segmentation. She regularly consults with clients regarding best practices in research methodology. Beth earned a Ph.D. and a Master of Science in Experimental Psychology with emphasis on psychological principles, research methods, and statistics from Texas Christian University in Fort Worth, TX.

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