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As I mentioned last week in Part I, quantitative research gives consumer insight professionals the answer to their question; qualitative research gives the why and how to improve.  Our experience tells us that researchers gravitate towards the quant because it provides a clear answer, but it doesn’t tell you how to improve the answer so that you provide the best answer.  That’s where qual adds tremendous value when coupled with quant:  it provides insights on how to optimize the concepts and why some are perceived as superior to others.

One of the ways we tackle this quant/qual challenge is employing directional quant where a few hundred respondents are recruited to screen concepts. We absolutely believe that directional quant can an important be part of an Agile Research Methodology.  At GutCheck we do directional quant that helps narrow the playing field of viable concepts, or directionally validate concepts. We often recommend using a combination of directional quant, qual, and rigorous or statistically significant quant.   

An observation over the past several years is that our clients often get to the end of a big quant study and have an answer, but with no understanding of the whys or hows (to optimize the concept). This can cause them to move forward with a suboptimal concept, or to throw out a concept that would have performed as the winner with one minor tweak. 

While final research validation is usually quantitative, in our experience qualitative is often predictive of the quantitative result. We see this all the time that the concept the research subjects gravitate to in qualitative research ends up being the definitive winner in rigorous quant.

Another problem we’ve seen is that sometimes when our clients go to quantitative, they move forward with the predictive analysis but often the product, package, or whatever fails.  Why?  Because there's some nuance about it they don't understand.  They come back to us to understand the why's in qualitative engagement. If they had just done the qualitative research to begin with, they could have avoided the time and cost associated with pushing something to a rigorous quant too quickly.

To wrap up, we’ll summarize when to use the various methods at your disposal to optimize your concepts:


  • Exploration: Use an on-demand community to discover attitudes, usage, pain points, etc.  Use these insights as input into ideation for product concepts, ad copy / creative, package designs, and corporate communications.

  • Screening:  Use on-demand directional quant tool to winnow the number of concepts down to the several most promising ones.

  • Optimization:  Use an on-demand community to understand the why consumers perceived concepts to be superior and how to improve and optimize those concepts prior to the validation phase.

  • Validation:  Use large-scale quant to predict how a concept will perform in the market to select the concept(s) that you will move forward with.


What I hope you’ve taken away from this blog series is that both quant and qual have their place in a consumer insights toolkit and they can be incredibly effective when used together.

To read more on part I, click here

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