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Infographic: Big Brotherâ¿¿s Big Data Spurs Profits And Privacy Concerns

Tickers in this article: AMZN COST EBAY FB GOOG LNKD MSFT TGT WMT

How much information do you believe Facebook (FB) has on you? What about Google (GOOG) and LinkedIn (LNKD). A lot, clearly. These websites track our every click, adding the information to a gigantic and ever-growing database.

Of course big data collection goes beyond internet usage, it follows your consumer purchases, travel plans, television shows, and much more, making it nearly impossible to be illusive. 

To what end? Why should I care?  

The collection of data makes it easy for a computer to compile and spit out a thorough description of your life: hobbies, personal and professional interests, religious beliefs, family associations, and more. 

Disturbingly, buying a certain combination of products triggers the type of promotions you receive, which are based on some very intimate predictions data collectors make about you. 

This was highlighted in a New York Times article by Charles Duhigg that featured Andrew Pole, a Target (TGT) statistician helping the retail giant identify pregnant customers, even if they were trying to keep it secret. "Pole's computers," Duhigg writes, "are able to identify about 25 products that, when analyzed together, allowed him to assign each shopper a “pregnancy prediction” score. More important, he could also estimate her due date to within a small window, so Target could send coupons timed to very specific stages of her pregnancy." 

Big Data for Big Profits

Perhaps you feel this very specific catering is convenient, or maybe invasive, either way it is incredibly effective. From a financial perspective, the companies that best optimize this kind of data are in the strongest positions to profit. 

Continuing off this pregnancy example. Pole says  "We knew that if we could identify [pregnant women] in their second trimester, there’s a good chance we could capture them for years. As soon as we get them buying diapers from us, they’re going to start buying everything else too."  This strategy is surely optimized by competitors like Amazon (AMZN) and Wal-Mart (WMT) as well. 

Kapitall has created a hepful infographic that quickly walks through the core of big data, and the companies who leverage them.

Click the infographic for a snapshot of all the companies mentioned. The 1-year average return of the stocks listed is 33%.