The Strange Case When Too Much Data Isn't Enough Data
Many of our customers come to us with millions of dollars of market data, often “too much data” to be of help as to why their products or those of their competitors are being purchased. As a result, they are unable to do any of the following with the hope that they will succeed:
Strengthening their brand by increasing their customers’ loyalty.
Growing their buyer/user base by communicating a more compelling motivation for purchase.
Poaching competitive brand users by describing what is more compelling about their brand
In fact, what these customers tell us is that with all of their data feeds and data scientists, all they are able to do is to describe who buys, when and how. These “data points” then become the perfect basis for price promotion and subsequent margin erosion the results of which will then be analyzes within the Who-What-Where-When analytic ”box” because without the WHY, that’s all that is available. In fact, some clients have called this the “big data trap” because as perceived brand value brand diminishes from no refreshment of the reasons for purchase, price promotion confirms that there must not be any such reasons sufficiently worthwhile to communicate.
Other clients have identified the data science staff themselves as the basis of the Who-What-Where-When box with their analytic tools as the “hammer” and the “why” of purchase being the “nail.” Unfortunately, behavioral data which are easily machine-collected (Who-What-Where-When) are, by their very nature, unrelated to WHY the behavior occurs in humans. This is perhaps the reason why when these same data science staffers are asked to collect “why” data from humans, the results obtained are so extraordinarily simplistic, e.g. “tastes good,” “I like it,” “I’ve always done that,” these data are of no real value.
So, can we conclude the following?
Big Data, most of which falls into the Who-What-Where-When box, says nothing about the WHY of behavior.
Big Data analysts, skilled in parsing gigabytes of data, probably have the wrong skill sets to uncover and interpret the roots of human purchase behavior, and
The true motivators of purchase have to be not only valid but also sufficiently “deep” to provide the basis of communication, positioning, and brand switching to be of value to the marketer.
Who would you expect to produce such “deep” human purchase motivation information? It is likely that if Big Data alone can’t do it, the providers of this human motivational information are probably “human analysts” (not data analysts) and study how humans make purchase decisions, how they arrive at the “reasons” for these decisions and why they select one brand over another, i.e. preference. Many marketing researchers purport to provide such information but very few have demonstrated a proven ability to understand, model and predict human choice (purchase) behavior.
Behavioral Science Lab in Austin, Texas is one of those handful of companies providing a patent-pending measurement system, BrandEmbrace®, certified by the Marketing Accountability Standards Board (MASB) to be a reliable, valid and calibrated predictor of brand choice behavior and switching. The basis of BrandEmbrace® is not the data in the Who-What-Where-When box, but the human concepts, factors, nuances and perceptions which actually determine human choice behavior.
Picture by Stephen Dawson