I’m a marketing person that in one way or another has been tangled up with the technical / engineering world all of my professional life. Cable Television, TV Shopping, Wireless, Internet. I have always been dealing with brand new business models having no historical reference, while swimming in data to make sense of, and dealing with engineering folks as the people who “make things happen”.
I have also been really fortunate to work with many Ph.D. level statisticians who had the patience to answer all my questions about higher level modeling and explain things to me in a language I could understand.
Because of this history, I’ve been a long-time student of the “intersection” between Marketing and Technology. I’ve in effect become a “translator” in many ways – taking ideas from each side and converting them into the language of the other side. Distilling the complexity of Technology down to the “actionable” for Marketing, while converting the gray world of Marketing into the White / Black – On / Off world for Technology.
With no offense to either side, to generate some kind of tangible progress, sometimes you just have to strip out all the crap from both sides to get to the core value proposition of working together. You have to start somewhere. Then you can build out from there.
And so I try with posts like Will Work for Data to define this intersection for others, to help both sides understand each other, and it’s tough, especially with an unknown audience varying widely in their knowledge of either side. I try to create a “middle” both sides can understand.
Marketing folks are in the middle of a giant struggle right now with the whole accountability thing. But it’s not so much accountability itself, because many of the best marketers have always been accountable in one way or another. No, it’s the granularity of the accountability that is the issue; the movement from accountability defined at the “impression” and “audience” level to accountability at the “action” and “individual” level.
Here’s the challenge for Marketers: the data is different. Impression and audience are defined by demographics but response and individual are defined by behavior.
Perhaps this will “translate” poorly, but the Technology parallel would be folks who have built a skill set around a certain programming language and then are told that language is now obsolete. This is extremely disruptive when you have spent 20 years understanding your craft from a particular perspective.
So here’s what we need to do to make this work. We have to find common ground. This will mean being a little “less scientific” on the Technical side and a little “more specific” on the Marketing side. And we work down through all this to the core.
This is the same struggle web analytics folks deal with every day, but due to the early work of many writing on this topic, the web analysts were always urged to connect analysis to business outcome. Many are getting pretty good at it; they don’t suffer the “too much science” problems their peers in marketing research seem to run up against.
But web analytics is just a microcosm of the whole Analytical Enterprise, which may or may not be (background info this link) Competing on Analytics at this time, but is probably headed in this direction.
I submit it’s a bit early to teach most Marketing folks about statistical significance, about what types of data sets CHAID works best with, the difference between Nearest Neighbor and Clustering models, and so forth. We can always get there after we reach the core understanding.
Right now, what we need to do is figure out how to get to the core.
I think where I might take this is to propose some fundamental rules of understanding and see if we get both Marketers and Analysts to understand and agree on them.
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