Editor's note: Susan Fader is qualitative researcher at FaderFocus, a New York research firm. 

In order to field any type of research study, one has to interact with people – whether it is an in-person conversation or a self-administered questionnaire. Companies have spent inordinate amounts of money creating demographic and segmentation profiles of their customers, potential customers and “non-users.” They rely on these demographic specifications and segmentation profiles to determine who is or is not included in research. These categorizations are also used as guidelines for organizing databases and determining what potential research participant sample might be purchased. The people included in research are a major prism through which research data/findings are analyzed and business decisions are made.

It is human nature to try to group like things together and it is a major way that helps accelerate processing information, seeing patterns, making connections and discovering opportunities. We start as toddlers matching similar shapes and colors, so it’s not surprising that in this data-rich world, companies generally create a handful of what they think are distinct demographic profile groupings that capture the key demographics of the people they want to do research with. By filtering any research findings through these specific demographic groupings, there is the belief that it will both speed and improve our ability to analyze the data.

Currently, many of the grouping profiles follow the rules that were set in place years, even decades ago. Many rely primarily on traditional demographic parameters (gender, age, relationship status, HHI, education and category engagement) that usually revolve around purchase of a product or service. Some profiles overlay attitudinal questions, which in many cases fall into whether they will be an engaged research participant (e.g., “I like to share my opinion wi...