Data Geeks Must Learn to Speak to Clients
Last summer, my team hired two promising interns, mainly to build a talent pool for the following year. Both were very bright kids, indeed, and we gave them two seemingly straightforward modeling projects. The first assignment was to build a model to proximate customer loyalty in a B2B setting. I don’t remember the second assignment, as they spent the entire summer searching for the definition of a “loyal customer” to go after. They couldn’t even begin the modeling part. So more senior members in the team had to do that fun part after they went back to school. (For more details about this project, refer to “The Secret Sauce for B2B Loyalty Marketing.”)
Of course, we as a team knew what we were doing all along, but I wanted to teach these youngsters how to approach a project from the very beginning, as no client will define the target for consultants and vendors. Technical specs? You’re supposed to write that spec from scratch.
In fact, determining if we even need a model to reach the business goal was a test in itself. Why build a model at all? Because it’s a cool thing on your resume? With what data? For what specific success metrics? If “selling more things by treating valuable customers properly” is the goal, then why not build a customer value model first? Why the loyalty model? Because clients just said so? Why not product propensity models, if there are specific products to push? Why not build multiple models and cover all bases while we’re at it? If so, will we build a one-size-fits-all model in one shot, or should we consider separating the universe for distinct segments in the footprint? If so, how would you determine such segments then? (Ah, that “segmentation of the universe” part was where the interns were stuck.)
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 firstname.lastname@example.org.