Is there a long-term cost for using algorithms in qualitative recruiting?

Editor's note: Amy Boren is president of DecisionPoint Marketing and Research, Canton, Ohio.

When I began writing this article I was looking for a simple definition of an algorithm, as it relates to marketing research. To quote from Merriam Webster’s Collegiate Dictionary’s definition, an algorithm is “a step-by-step procedure for solving a problem or accomplishing some end.” In our industry this is leveraged for improved analysis to generate more efficient and effective marketing communications and better optimization.

My experience with algorithms in marketing research usually begins with a product or brand manager requesting a marketing segmentation study, which results in a quantitative methodology study. This leads to findings being analyzed by behavioral variables, grouped into buckets and named. Typically, a follow-up quantitative study is conducted to test the efficacy of the segmentation strategy. With that, a corporate brand algorithm is born. This is the foundation on which the brand story builds over time and allows market research to explain and understand marketing directly to each segment.

When moving into the qualitative phase of research, a product or brand manager extracts the key attributes of the segments and creates a screener for which qualitative recruiters set out to find these characteristics and bring them to life in a focus group facility.

Let me be honest: There is not a project manager in this country that is not intimidated by the task of replicating what the statisticians found quantitatively and relating it back to the general public, within their market, but we do it every day. For example, I work with crisis recruiting for low-incidence studies and I had a client ask me to find males in Chicago who preferred premium plain chocolate ice cream (my client claimed 10 percent incidence). While this sounds simple enough, with all the other ice cream options out ther...