Some of us grew into the market research profession seeing a more or less clear distinction between qualitative and quantitative research. While there have always been professionals comfortable with both types of studies and tools, the line was pretty much distinct between what was quantitative and what was qualitative. While the same thing can be said today, the limit itself looks very different from what it did 15 years ago.
There was a time when quantitative meant media research, trackers, and surveys. Qualitative research meant research derived from listening to respondents or observational research. A few things occurred that have blurred things:
- Advent of big data. With the amplification of data, we have seen a democratization of tools to facilitate data analysis. Putting together a big analysis is arguably easier. And in trying to decipher the whys, quantitative researchers have been pushed to delve into qualitative methods.
- Emergence of quantification techniques for qualitative data analysis. Large language models and text analytics have helped provide clarity and confirmation to efforts that were mostly based on logic and classic content analysis. Qualitative researchers are now incorporating a growing number of quantitative techniques in their projects.
- Do it yourself qualitative and quantitative research. There was a time when online surveys required programming and clunky tools. Needless to say, this is not the case today. Deploying qualitative and quantitative studies is just very easy from a technological and programming point of view. A good in-depth survey today is expected to have both quantitative and qualitative components.
- Emergence of social media and passive data generation. Reams of data and supplementary qualitative input resulted in the proliferation of mixed methods research, particularly in this area.
As we can see, there has been more use of quantitative methods within qualitative research and easier incorporation of qualitative methods within quantitative research. Artificial Intelligence (AI) should accelerate these trends. Technically speaking, the more sophisticated customer satisfaction surveys today should be able to incorporate predictive analytics and explanatory modeling founded on large language models. Assuming appropriate written or spoken respondent input, qualitative research proper could enter the picture one step later in the research process. If until very recently, one could tell who was a qualitative or quantitative researcher based on the product of their work, in the not so far out future this might no longer be possible. One might have to rely more on the initial type of data and nature of the questions each type of researcher started with for the answer. The essence of what is qualitative and quantitative will not be lost, in my opinion, but each type of research will likely evolve to include a wider spectrum of quantitative and qualitative tools.
