Oh blurry Facebook user: you could not be more spot on! If you hold an account with Gmail, Youtube, Blogger, Picasa, or any of the other myriad of Google properties, Sergey Brin & Larry Page know exactly who you are, who you interact with, what you eat, where you live, and the exact time you last took a crap… OK, I’m kidding about the last one – Only Apple has data on that.
As online behemoths Facebook and Google battle for social media supremacy, the debate around privacy along the social graph intensifies. Mountain View’s newest offering, Google+, has been built from the group up with user privacy as a key focus. Google has witnessed Facebook’s quick rise to dominance but is banking on people making the jump to their service with promises of unparalleled flexibility around who can – and more importantly, who cannot– see your hilarious status updates and dodgy photos.
The greatest trick Google ever pulled was convincing the world that a publicly traded advertising company isn’t evil
But is this ability to hide content from unwanted creepers the social media holy grail, or actually just smoke and mirrors hiding a fair more pressing concern? Make no mistake, while Google and Facebook may be getting better at keeping you details private to unauthorised parties, they are already excellent at mining this data for their own use.
This right here is the social media end game – building a comprehensive, predictive, and accurate social graph of each user, which will facilitate targeted delivery of goods and services.
With amazing data comes great power, but not necessarily great responsibility. But what these online juggernauts are just now learning is already old hand for another group of equally secretive service providers.
If you ever doubted the power contained within massive datasets of user activity, you need look no further than Amex or Visa to gain insight into how much can be gleamed from seemingly unconnected data.
In his book Super Crunchers, Yale Law School Professor (and data fanatic) Ian Ayres, provides the example of Visa’s ability to predict divorce two years prior to the end of the relationship.
Based on customer demographics, spending patterns, and models of similar customers, Visa gains a 90% accurate insight into the future health of your relationship. Ah, you say “but I’m not even married”. Well wise reader, this matters not to Skynet Amex. Based on hotel stays, flowers from Roses Only, and 2am purchases from 7-11, your card provider can assess when you’re going to get married, and then use that to base the following date of divorce.
As divorce has a huge impact on a person’s ability to repay debt, this data can then drive business decision such as the extension of additional credit, or in extreme cases, can be used a trigger to offer forgiveness of debt – or even cold hard cash rewards – to incite customers to close accounts early.
While Google and Facebook might be catching up, the credit card industry has been an early adopter of number-crunching as a way of predicting how consumers will behave. Thirty years ago, loan officers use to look you in the eye and tell you whether you were the right kind of person to trust for a loan. “That was a really inaccurate approach. Just using FICO scores (or credit reports in Aus) did a much better job,” Ayres says. “Credit card companies started using a similar approach in deciding whether to issue and how to price their card. It’s getting to be a more nuanced statistical game.”