I created an account on the website for the social media marketing company called Marketing Wow! and deposited some funds. They offered a number of services that promised to help me to market and promote my company online.
When I deposited the money, this triggered a data-mining search operation in the computers over at the Marketing Wow! headquarters. Public data aggregated across the web linked my email address to my personal blog, my Facebook and Twitter profiles, my account on IMDb, and my comments on The Huffington Post and other news sites.
Every photo I had ever “starred” on Twitter, every celebrity I’d ever “liked” on Facebook, every comment I’d ever left that had asked for my email address as verification was churned through a massive, multivariate analysis.
Within moments, a complex synthesis of all of this information lead to some conclusions about my tastes and preferences. Not just my sexual orientation, which is easy to figure out from Facebook data alone, but a full profile on all of the physical characteristics that I tend to be attracted to.
This was matched against the profiles of the sales team over at Marketing Wow!, and an automated email was sent to one selected sales representative in particular, notifying him to get in touch with me.
Within moments, I received an email from Kyle, a dashing young sales representative at Marketing Wow!. “I’ve noticed that you’ve deposited some money in your account with us, and am wondering if there is any way I can help you!”
Because I use Gmail, and the sales rep from Marketing Wow! uses Gmail and has a Google+ account, I was able to see his Google+ profile picture next to his name in my inbox. Dark hair, youthful face, large captivating eyes, lanky build, and a sly smile. My immediate thought was, “Sure… I’ll talk to you.”
So I hit “reply”…
Marketing Wow! is, of course, fictional. But the basic principles behind the data mining algorithm that I’ve described are not: they are all possible today. Some of them are already being implemented.
Attractive salespeople are not a new innovation, but companies have long suffered under the limitation of having to target the “average” consumer when deploying their sales force. Thus, companies load up their sales teams with generically pretty women and generically successful-looking men, and simply play the odds that the wink and the charming smile, deployed correctly, will have a positive influence on at least a decent portion of potential customers.
With the wealth of information out there today, however, why on earth would any company want to leave such a thing to chance? If an app were available that could analyse massive amounts of publicly available data on a potential sales lead, and spit out a better than chance result (e.g. “There is a 90%per cent chance that this customer is a heterosexual male and a 76 per cent chance that he is attracted to blondes”), then what company would not want to use this information to their advantage?
If you think the idea sounds creepy, remember that this information is already public data, and that you put it there. Many people don’t remember this, as they go about their normal day-to-day social media activities, but consider how much you reveal about your sexual orientation, tastes, desires, and preferences even in mundane operations on the social web.
Every photo you “star” on Twitter is public data. Every time you comment with “cute” or “hot” or “wow” on an Instagram photo, that is public data. Every time you “like” a celebrity, model, or athlete on Facebook, that is public data.
Not to mention all of the people who make lists on various websites. IMDb is rife with lists of “My list of the 100 hottest actresses”, and those, too, are all public data. Every time you favorite or reshare a picture on Tumblr, that is public data.
Any one of these sources, alone, would probably not prove to be very reliable. After all, people “like” celebrities for any number of reasons not related to their attractiveness, and not every picture that you star on Instagram is one that turns you on.
But as the power of computation gets faster, there are almost no limits to how well these different sources can be collated, cross-referenced, and sent through pattern-detecting algorithms. As with all large-scale statistical data mining, the gold is being able to see the overall pattern through the noise of thousands or even millions of data points.
Whether you intended to or not, you have opened a window on your urges and tastes, and allowed anyone on the internet to look inside. You felt safe because you just assumed that actually looking at all of your data would be complicated and tedious, and so nobody would ever bother to do that.
But computers are getting pretty good these days; “complicated” and “tedious” can no longer be viewed as a privacy strategy.
And, I mean, anyway: why shouldn’t companies determine who you are most likely to be attracted to in their sales staff and deploy that person strategically to contact you? In terms of the motivation and reasoning, it’s no different than what they already do today by using generically “attractive” sales people. It’s simply a more well-targeted version of the same strategy.
From a sociocultural point of view, it could even be argued that it would benefit society as a whole. Instead of companies reifying cultural stereotypes about attractiveness, and potentially alienating those who have tastes outside the norm, they are admitting, and even catering to, the intrinsic heterogeneity of human sexual tastes and desires.
The woman who likes balding fat men will be charmed by the balding fat sales representative, instead of being bored by the “Hollywood handsome” sales rep that would have been sent to her in the past. Moreover, the balding fat sales rep ends up getting a much higher rate of closure on his sales because he is paired with customers who will be more intrinsically drawn to his natural charms and style.
It is literally a “win-win”. Moreover, the data is already available. In a sense, it doesn’t matter whether you approve of the idea or not: you may as well get used to it. Because it’s happening.
Coming soon to a database near you, there will be a program that knows exactly who you think is hot … and will have plans to use that information in order to sell you something. Probably washing powder.