Analytics Providers Should Know the Audience
6. Analytics? Who cares? No numbers or stats can top good old-fashioned gut feelings. Wherever that “gut” may reside in a human body (not in the brain, for sure).
Now, here is the major dilemma for people who make living by analyzing big, small, clean and messy data: Who is the audience? How do we even start a conversation about models and advanced analytics, when we start losing your audience at “hello”? How would we evangelize the benefits of analytics in the business world when the majority think that they are not good at math, but are afraid to admit it?
Like in any business setting, one must study the audience first. The business goals may be similar, and the amount of available data and toolsets may be the same, but the way we communicate with the end-users of data and science must be adjusted to the level of the audience, not the data scientist’s level of understanding. Besides, even fellow data geeks may have no patience for all the stories about how it all worked out. Who cares about your 12th attempt that did NOT work? Absolutely no one. You are not dealing with your college professor. Just get to the point, pronto. Let’s get to the business and make some money. And if the presenter doesn’t know the audience? That would be like the Blues Brothers in a Country and Western bar with a chicken wire fence. Good luck with playing that “Rawhide” all night.
For that reason, we the data geeks may have to get out of the habit of presenting the numbers according to the order of operation. We may need to forget about the levels of analytics starting with BI reporting, descriptive analytics, predictive analytics, and ending with prescriptive analytics, whatever that may be.
Or, maybe that word “prescriptive” is onto something. Maybe, people who understand the data and analytics should act more like doctors. Doctors do not show up with prescriptions before they consult their patients. (Some may do that, but that’s a whole new subject). They listen to the patient and examine the symptoms through all kinds of tests before they actually prescribe solutions. Sometimes, they may even admit that they are not the specialists in the field and they call in a new doctor. If their agenda is to push specific drugs or procedures, well then, they just demoted themselves to the level of drug-pushers.
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 president and chief consultant at Willow Data Strategy. Previously, he was the head of analytics and insights at eClerx, and VP, Data Strategy & Analytics at Infogroup. Prior to that, Yu 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.