At NetFlix, the online DVD rental company, for example, roughly two-thirds of the films rented were recommended to subscribers by the site – movies the customers might never have thought to consider otherwise, the company says. As a result, between 70 and 80 percent of NetFlix rentals come from the company’s back catalog of 38,000 films rather than recent releases.
Similarly, Apple’s iTunes online music store features a system of recommending new music as a way of increasing customers’ attachment to the site and, presumably, their purchases.
Recommendation engines, which grew out of the technology used to serve up personalized ads on Web sites, now typically involve some level of “collaborative filtering” to tailor data automatically to individuals or groups of users.
Some engines use information provided directly by the shopper, while others rely more on assumptions, like offering a matching shirt to a shopper interested in purchasing a tie. And some sites are now taking personalization to another level by improving not only the collection of data but the presentation of it.
Liveplasma.com, an online site for music and, more recently, movies, graphically “maps” shoppers’ potential interests. A search for music by Coldplay, for example, brings up a graphical representation of what previous customers of Coldplay music have purchased, presented in clusters of circles of various sizes.