Markets of One, part three.

I am a science fiction fan, have been since adolescence. It’s one of the early foundations on which my personality, world view and personal creativity was built. Nurturing wacky and imaginative iterations of known science fueled my fantasies, doodles and conversations. I’ve even collected a number of books of science fiction art in addition to the hardback and paperback books that still overflow my shelves and storage. I love this stuff!!

It was no revelation to me, therefore, when about ten years ago the marketing world was agog at the possibilities of data mining. Science fiction writers had been dealing with the potentials of individualized communications technology and messaging since the 1900’s. Now, after some fits and starts, largely at the long term expense of the owners and developers of database technologies, we are apparently at the dawn of the actuality of markets of one. My marker of this is Google’s announcement on their blog of the new default of personalized search results (here’s a bit of explanation at MarketingPilgrim.com and the Google video.)

One of my favorite science fiction fantasies is expressed in a scene from the movie “Minority Report” where Tom Cruise’s character is escaping through a retail space and the kiosks and billboards start bellowing out his name and pitching him with products that might appeal to his demo-, psycho- and sociographics. If the search engine Google can be compared to this metaphorically, we might all be experiencing the same thing already.

I was listening to APM’s Markeplace about a month go and heard an interview with Professor Andreas Weigend, Amazon.com’s former “chief scientist” (I LOVE the way Jeff Bezos celebrates the obvious), now a professor of data mining at Stanford. He was describing the conceptual social framework for one of the retail world’s most powerful personalization concepts: Amazon’s recommendations engine. This amazing enterprise has been monitoring us Amazon.com customers for years (just like many varied data harvesters and manipulators throughout our social and economic environments). My personal experience is that I have definitely upped my consumption of music based on the recommendations fed to me through email notices and while I am online shopping at Amazon. Dr. Weigend points out that Amazon’s contribution to the use of data was its ability to design incentives for users to volunteer information about themselves.

Google’s got it right (although there’s widespread disagreement over whether the search engine user will perceive Google’s record-keeping and results-ranking system to be in their interest). For much of the past decade, the focus of software developers and data mining consultants has been on selling this terribly expensive set of features and services to single companies under the principle that increased customer data will inevitably lead to increased understanding. According to the sales manifesto, that understanding would then make the customer more visible and vulnerable to company influence in their purchasing patterns.

I never believed the sifting of this data within a single silo’s confines would be all that illuminating. Even the financial world, where transactional data gave a much broader view of consumer buying behavior, could never completely uncover the buyer’s motivations. These data became a sort of marketing Holy Grail, with attendant histrionics about their evil power, just like sociologist Vance Packard had written in his “exposes” in the 1950’s such as The Hidden Persuaders. Manipulating responses were one thing. Predicting behavior is an entirely different one.

This is what, in my mind, makes both Amazon and Google’s expressions of their data collections so powerful. Both are geared to suggestive direction, not overt or secret manipulation. And the addition in Amazon of the editorial commentary of buyer reviews and in Google of its reputation for a scrupulous integrity both contribute to the validity and utility of the results of their systems. No one is forcing the consumer’s behavior to a particular end, but rather is organizing information in a way consumers use and internalize data. These systems are more “human” in their expression, more like word of mouth, making them truly marketing to just one person.