Last August, the travel site Orbitz found itself in a kerfuffle when the Wall Street Journal reported that the site was showing Mac users higher-priced hotel rooms than the ones it displayed to PC users. Orbitz retorted that its tracking data revealed that Mac users do, in fact, spend an average of $20-30 more per night on hotels than their apparently less-toney Windows-using peers, and it was just trying to keep the customer satisfied.
Eyebrows were raised. But whatever you may think of Orbitz’s tactic, it was a savvy use of predictive analytics—and a harbinger of a future in which prices for many consumer products will be keyed to each and every one of us individually, based on our unique buying habits. Variable pricing is nothing new; the difference is that in the past it was applied to groups (frequent flyers, seniors, etc.), or was driven by availability. Now the granularity afforded by big data plus predictive analytics is going to allow pricing to be assigned customer-by-customer in real time.
Moreover, personalized pricing is going to expand beyond e-commerce to brick-and-mortar retail. Safeway began experimenting with this model over the summer, adjusting prices at checkout based on a shopper’s loyalty card history. And an iPhone app called Scan It!, launched in 2011, lets people scan items while they shop and get personalized offers based on their loyalty cards.
Expect further controversy. As Joseph Turow, a professor at the Annenberg School for Communication said, “There’s a sense of fairness that’s derailed here.”
But retailers argue that customers want personalization, and they accurately point out that individualized coupons have succeeded wildly. One shopper in Maryland told the New York Times, “It’s a little bit creepy, but I figure they’re checking everything anyway. I might as well get a good deal out of it.”
If enough people feel the way she does, “price tags” may become yet another item on that growing list of arcane artifacts we will one day be explaining to our grandchildren.