Good points, smkinoshita. I actually remember the newton as well.
You reinforce Kim's point, that you need to better understand the customer so that you can "solve their problem" versus selling them something. The ability to use customized analytics and find the right timing, the right solution, and the right way to solve their problem becomes key.
As Kim points out, the focus is truly the customer and I agree that B2B is far behind the B2C. Therein lies great opportunity!
Apple tried to market the Newton -- the ancestor of the iPhone -- back the late 80's to 90's in the form of a PDA. The market just wasn't ready for it, but stripped down versions of the same device became successful in forms like the Palm Pilot.
It's not really a matter of predictive analysis as much as it is asking the right questions. If the question was "Do people want a PDA?" back in the early 90's, the answer would have been "Yes" -- but it negelcts some critical points like the features desired. Perhaps the better set of questions would have been "How easily do people want to access their data? When will our networks be able to distribute this data in a way that's affordable? What is 'affordable'? What market segment are we talking about?".
So yes and no. "Yes", I think the technology is there, but "No", we don't know how to ask the right questions yet.
Yes without a doubt we have come along way from the salad days during the heyday of the Etruscans when attempts at reading the future meant inspecting the entrails of newly sacrificed animals - haruspicy. I am waiting to see a job listing for a Haruspex. What are the chances?
"Predictive analytics can point the way to the next offer, the next action, and the next customer need, in a way that feels more like providing a service than marketing a product."
I know that has to be the ultimate goal of predictive analytics but are we there yet? Arewe certain of predicting the next offer, the next action and the next customer need? Is it fair to say that this burgeoning marketing revolution hinges on the success and credibility of the results of predictive analytics?
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