Technology such as behavioral pricing, advanced buyer segmentation, and dynamic demand pricing enable online retailers to cost discriminate at an even larger scale than before. By combining the huge quantity of customer data available in merchant databases like purchase history, customer demographics, and social media; online merchants can offer unique merchandise at even more personal pricing to every site visitor. Imagine that you tweeted to your friends that you want to buy a brand new PC, and you post about this on your weblog or in a comment section. Let's say a company named AllCoupons4U, knows that you have looked for computers lately. It finds the links to your blog comments that track back to your profile and in case you decide to visit their online store they can dynamically increase the prices on all laptops offered, since they are aware you are keen on getting one. Using browser history, demographics and a complete purchase history, a service provider can up sell goods by bundling a wide variety of items you have bought or are related on them.

Dynamic pricing isn't restricted to web sites and the online world. The New York Mets plan to roll out dynamic pricing for seats across the whole stadium. There has always been a premium on games in which the rival team is has a large following or simply big star power, but imaging getting a lower cost as a result of a star pitcher getting injured or paying extra because the team is suddenly in contention in the month of September. How long will it take before this spreads to grocery stores? Picture paying a little bit more for a bag of Cheerios because Corn Flakes are out of stock, or a quarter more per gallon of gas on the way back from work at 5 o'clock versus the value of the same fuel at eleven o'clock at night.