Market research had its 100th birthday in 2020! In that year, a fellow named Daniel Starch had a breakthrough moment. He realized that, in order to be worth the money, advertising had to be seen, noted, understood, and most importantly acted upon. He came up with the idea of what we today call “creative testing” as a way of measuring the effectiveness of ads in newspapers and magazines.

In the 1930’s, George Gallup invented public opinion polling. His big breakthrough was that you could use a small sample of respondents and project those findings to larger populations. The Gallup Poll became a pop culture phenomenon that influenced politics, entertainment, and even the library choices of the Book of the Month Club; not to mention the polling we do today.

In the 1950’s, Ernest Dichter pioneered the concept of motivational research. A decade later, Paul Green added conjoint analysis to the mix. In the 1970’s, half a century ago, Jerry Yoram Wind and Richard Cardozo came up with the notion of using different messaging to target differentiated segments of consumers; and the practice of customer segmentation was born.

So, in the thirty years or so between Daniel Starch and segmentation, the fundamental research structures we still use a half century later were pretty much in place. Certainly other tweaks and layers have been added since; the most significant of which has been the most recent harnessing of Artificial Intelligence to the task of data analysis. We can now process columns and rows with blinding speed and with unimaginable capabilities for discerning patterns through algorithms; and therein lies the dilemma.

Simply put, the more sophisticated and powerful the data processing technology becomes, the more it calls into question the nature of the data being collected. In what other part of your life would you intentionally apply a hundred-year-old way of thinking to make the best use of the latest technology?

The time has come to completely rethink the dimensions of what is being fed into the wondrous analytic engines of today. Starch, Gallup, et al, designed their intake mechanisms around the calculating capacities of their day – adding machines, mechanical calculators, and rudimentary punch-card processors. What questions they asked, and how they were asked, had to be conformed to, and were therefore limited by, those limitations.

We can do better. More on that in Part Two of this series – What Are The Missing Links of Customer Intelligence?