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    Frankenmetrics: Neuromarketing and the Really Cool End of Privacy

Frankenmetrics: Neuromarketing and the Really Cool End of Privacy

For all their intrusiveness, companies like Facebook really don’t want to hurt us. They want to sell us stuff. And for that reason, we tolerate the cognitive dissonance created by our love for technology and our desire for privacy.

So, it is with the mixed emotions all of us share about such matters that I say, “Facebook studied our neurological patterns and they found out some really cool stuff.”

Chief among the findings was for all our handwringing about dwindling screen sizes, it turns out people are more focused on their mobile screens than their television screens, not less. Equally important, it seems we trust that small screen more, as well. What that means for, say, politicians or the producers of YouTube cat videos is that the advent of mobile has not resulted in a qualitative loss in terms of the ability to communicate with video.

Facebook commissioned the neurological study (basically studying how your body responds to different stimuli) to answer the burning question on every marketer’s mind, namely, “If you keep making screens smaller, will we still be able to sell stuff?” Now, granted, when the government does these kinds of studies, it’s a lot creepier.   Corporations get that, which explains why companies like Facebook and Google hate to see their names linked to government data collection.

This study was done by SalesBrain, itself the brainchild of Christophe Morin and Patrick Renvoisé. Renvoisé’s bio humbly states that he “discovered the buy button inside the brain” which, just for the record, I’m not sure I buy. In any case, the study itself is fascinating in the way watching one’s own autopsy would be fascinating. The “them “of the study is us. And yes, we do act and […]

Data Mining and The Princess Bride

Political consultants and the campaigns they work for are poised to spend millions in the coming cycle on data mining. For some, that’s going to be a great decision.  For others – unless they take the time to understand what data mining is and what it isn’t – they just may wake up with a bad case of buyer’s remorse.

Data mining has its roots in the pragmatic-oriented fields of business and computer science. Its main contribution has been the capability of using ever-expanding computing power to process large volumes of data and find important patterns and anomalies. Financial institutions have been able to improve their ability to detect fraud in credit card transactions using these techniques.

The idea is that with enough computing power, data, and variables thrown into a regression, eventually something “interesting” will emerge. This serendipitous approach is why many statisticians dismissed data mining as a forecasting tool early on, warning like those mutual fund notices that “past results are not necessarily an indication of future performance.”

The problem, of course, is that political strategists are far less interested in a history lesson than they are in a crystal ball that will predict the future.  As much as we may wish for data mining to be that crystal ball, that’s simply not what this tool is all about.

Statisticians are concerned with making inferences (generalizations) that can be used for making predictions. Professor David J. Hand, in his 2008 article for the International Journal of Forecasting, writes, “Forecasting is fundamentally an inferential problem. That is, it is not simply a question of summarizing data, but is rather a question of generalizing from the available data to new data — and in particular to new situations […]