Author Interview: Kenneth Cukier, Co-Author Of 'Big Data' : NPR: "The example comes from Charles Duhigg, who's a reporter at The New York Times, and he's the one who uncovered the story. What Target was doing was they were trying to find out what customers were likely to be pregnant or not. So what they were able to do was to look at all the different things that couples were buying prior to the pregnancy — such as vitamins at one point, unscented lotion at another point, lots of hand towels at another point — and with that, make a prediction, score the likelihood that this person was pregnant, so that they could then send coupons to the people involved... there might be a coupon for a stroller or for diapers ...
Also to note that "why Big Data doesn't care about causes, just correlation"
"They crunched the numbers, and they found out that cars that were orange tended to not have breakdowns compared to other colors of cars ... So why might this be? Well, we can sort of concoct different scenarios. One is that orange tends to be a custom color, and if you order an orange car, perhaps the rest of the car was made in a custom way, a little bit more care was taken into it. We don't know why, and it's frankly, it's not that important. It might just bring us down a rabbit hole for us to try to find out why. But, again, if you just want to buy a car that's not going to break down, go with the correlation."
Full article at: http://www.npr.org/2013/03/07/173176488/the-big-data-revolution-how-number-crunchers-can-predict-our-lives