In a fascinating blog post, Adam Ozimek makes the case that we will see much more individualized pricing (which economists call “first degree price discrimination”) as more data mining becomes available. For instance, in a new working paper, Ben Shiller is able to use big data to massively improve his ability to predict demand for Netflix subscriptions by any given individual:
Adding the full set of variables … including web-browsing histories and variables derived from them, substantially improves prediction – predicted probabilities range from close to zero to 91%….I find that web browsing behavior substantially raises the amount by which person-specific pricing raises variable profits.
As more and more data become available, it’s easy to imagine retailers using these data to offer personalized prices for each consumer, especially for information goods where margins are large and pricing flexibility is greatest. “You want to watch Elysium tonight? Special price just for you!”
However, that’s not the end of the story. Remember that big data can work for consumers, too. Thanks to Google and other tools, consumers also have more and better search engines and recommendation services available. That can intensify competition among sellers, which tends to increase consumers’ surplus.