Brian Gaynor wrote in the NZ Herald:
Target, the huge American discount retailer, has developed a sophisticated software programme that can determine when a woman is pregnant because purchasing data shows that women change their shopping behaviour when this occurs.
The New York Times Magazine tells the story of a man who went to a Target store in Minneapolis and criticised the store manager because his daughter was being bombarded with pregnancy-related coupons.
“She’s still in high school and you’re sending her coupons for baby clothes and cribs.
Are you trying to encourage her to get pregnant?” the man asked.
The manager apologised and called the father a few days later to apologise again.
This time he received a much more subdued response and was told, “It turns out there’s been some activities in my house I haven’t been completely aware of, she’s due in August”.
That’s impressive targeting. But that is minor compared to what Amazon is looking at:
Move over, drone delivery robots, there’s a new way to cut delivery times. It’s unique, it’s exciting and it’s the talk of the etail town.
All-seeing, all-knowing Amazon was recently granted a patent for anticipatory shipping – basically sending you stuff before you even order it. In essence, Amazon thinks it knows you better than you know yourself. The sad thing is that this may well be true.
Not relying completely on unworldly powers, this kind of technological sixth sense comes courtesy of advanced analytics. The masses of data Amazon collects – think order history, basket contents, wish lists and even how long cursers hover over particular items – could be used to identify your heart’s desire, even though you might not know what that is yet. Your anticipated must-have item could then wing its way to you, only to land on your doormat mere moments after you’ve sealed the inevitable deal.
Anticipatory shipping! There’s a risk you won’t order the item and hence won’t pay for it. But if they get it right, then you’ll get stuff you really want, even quicker.Tags: Amazon, data