Qual at Quant Scale

Quantitative and Qualitative – Not Much Longer.

Most that have been in the research industry for more than a couple of years have experienced the following situation as we’ve sat behind the glass with our client:

• Marketing: Did you hear what that person just said. That’s brilliant. That’s our solution.
• Researcher: That was good, but it’s just one voice. We are exploring right now. We’ll validate this idea in the next phase.
• Marketing: I think we have our answer.

This is an overt oversimplification for illustration purposes, but the reality is often not far off point. The problem really comes from the alignment of an idea that has been uncovered in qualitative research and the marketing manager’s predisposition to a particular solution. Add several weeks in order for the manager to advocate before all the results are in – and researchers frequently find that the “answer” has been acted on before the research is completed.

Reducing or eliminating the time from exploration to validation has been a goal of research for many years. We’ve been through quant/qual to explore the results of quantitative research through qualitative exploration with a subset of respondents (or vice versa). Communities offer some of this capability and there have been others as well, but they have all left some gaps.

Several newer types of tools have improved our capabilities to address traditionally qualitative topics at the scale of quantitative research. These tools can be roughly broken into three categories; methodologies, crowd-sourced approaches, or approaches built on artificial intelligence. Several approaches use multiple categories, but are usually dominated by one category.

• In terms of methodologies, arguably the most important advancements have been made in emotional measurement, particularly implicit. All aspects of a brand should be aligned to a promise, and the execution of the brand experience should be aligned to make good on that promise. Emotional measurement allows us to understand how the brand is aligning itself to the heart of the consumer. Until recently, exploring and validating emotions was not only difficult, but was disconnected from the time it took to do each. New methodologies can do both, at scale, and cost-efficiently. The methodologies are drawn from traditional tools in psychology and marketing research, but adapted for speed and scale by technology.
• Crowd-sourcing is a tool that has been around for hundreds of years – but has come into its own the past few years. The premise that the crowd has capabilities that a more limited pool does not have is applicable to a number of problems qualitative research has typically addressed. Ideation, concept evaluation, marketing communications, and even competitive assessment can be addressed both qualitatively and quantitatively at the same time through tools like prediction markets, mobile ethnography, and some communities.
• Artificial intelligence is the newest tool and the one with perhaps the most potential to disrupt the line between exploration and validation. These tools can analyze large amounts of data coming in various forms (images, videos, and text analysis – voice is still a little far from practical as of this posting). The analysis can be near real time – allowing for the automated development of a follow up hypothesis, data gathering and analysis of that hypothesis. And so on. Sound familiar? All of this can be done with hundreds of respondents.

Many of these approaches will change over the next three to five years as technology allows continued improvements in access to people and speed of analysis. Artificial intelligence will have similar changes, primarily in the quality and nuance of the analysis. These improvements, and others happening in the industry, will make the difference between qualitative and quantitative research a false distinction.