Why model? Uh, because someone is ridiculously good looking, like Derek Zoolander? No, seriously, why model when we have so much data around?
The short answer is because we will never know the whole truth. That would be the philosophical answer. Physicists construct models to make new quantum field theories more attractive theoretically and more testable physically. If a scientist already knows the secrets of the universe, well, then that person is on a first-name basis with God Almighty, and he or she doesn't need any models to describe things like particles or strings. And the rest of us should just hope the scientist isn't one of those evil beings in "Star Trek."
Another answer to "why model?" is because we don't really know the future, not even the immediate future. If some object is moving toward a certain direction at a certain velocity, we can safely guess where it will end up in one hour. Then again, nothing in this universe is just one-dimensional like that, and there could be a snowstorm brewing up on its path, messing up the whole trajectory. And that weather "forecast" that predicted the snowstorm is a result of some serious modeling, isn't it?
What does all this mean for the marketers who are not necessarily masters of mathematics, statistics or theoretical physics? Plenty, actually. And the use of models in marketing goes way back to the days of punch cards and mainframes. If you are too young to know what those things are, well, congratulations on your youth, and let's just say that it was around the time when humans first stepped on the moon using a crude rocket ship equipped with less computing power than an inexpensive passenger car of the modern days.
Anyhow, in that ancient time, some smart folks in the publishing industry figured that they would save tons of money if they could correctly "guess" who the potential buyers were "before" they dropped any expensive mail pieces. Even with basic regression models—and they only had one or two chances to get it right with glacially slow tools before the all-too-important Christmas season came around every year—they could safely cut the mail quantity by 80 percent to 90 percent. The savings added up really fast by not talking to everyone.
Stephen H. Yu is a world-class database marketer. He has a proven track record in comprehensive strategic planning and tactical execution, effectively bridging the gap between the marketing and technology world with a balanced view obtained from more than 30 years of experience in best practices of database marketing. Currently, Yu is principal and chief product officer at BuyerGenomics. Previously, Yu was the head of analytics and insights at eClerx, and VP, Data Strategy & Analytics at Infogroup. Prior to that, he was the founding CTO of I-Behavior Inc., which pioneered the use of SKU-level behavioral data. “As a long-time data player with plenty of battle experiences, I would like to share my thoughts and knowledge that I obtained from being a bridge person between the marketing world and the technology world. In the end, data and analytics are just tools for decision-makers; let’s think about what we should be (or shouldn’t be) doing with them first. And the tools must be wielded properly to meet the goals, so let me share some useful tricks in database design, data refinement process and analytics.” Reach him at email@example.com.