Super Crunchers by Ian Ayres Read Free Book Online Page A

closer to the travel date. With just a little data, the student could make pretty accurate forecasts about whether it was a good idea to buy early or wait.
    Etzioni ran with the idea in a big way. What he did is a prime example of how consumer-oriented Super Crunching can counteract the number-crunching price manipulations of sellers. He created Farecast.com, a travel website that lets you search for the lowest current fare. Farecast goes further than other fare-search sites; it adds an arrow that simply points up or down telling you which way Farecast predicts fares are headed. Even a prediction that the fare is likely to go up is valuable, because it lets consumers know that they should hurry up and pull the trigger.
    â€œWe’re doing the same thing the weatherman does,” said Hugh Crean, Farecast’s chief executive. “We haven’t achieved clairvoyance, nor will we. But we’re doing travel search with a real level of advocacy for the consumer.” Henry H. Harteveldt, a vice president and principal travel analyst at Forrester Research in Cambridge, says Farecast is trying to level the informational playing field for travelers. “Farecast provides guidance, much like a stockbroker, about whether you should take action now, or whether you should wait.”
    The company (which was originally named Hamlet and had the motto “to buy or not to buy”) is based on a serious Super Crunch. In a five-terabyte database, it keeps fifty billion prices that it purchased from ITA Software, a company that sells price data to travel agents, websites, and computer reservation services. Farecast has information on nearly all the major carriers except Jet Blue and Southwest (who do not provide data to ITA). Farecast can indirectly account for and even predict Jet Blue and Southwest pricing by looking at how other airlines on the same routes react to price changes of the two missing competitors.
    Farecast bases its predictions on 115 indicators that are reweighed every day for every market. It pays attention not just to historic pricing patterns, but also to a host of factors that will shift the demand or supply of tickets—things like the price of fuel or the weather or who wins the National League pennant. It turns all this information into an up-arrow if it predicts the price will go up, or a down-arrow if it predicts the price will go down. “It’s like going to the ballet,” Harteveldt says. “We don’t see the many years of practice and toil and blood and sweat and strain that the ballet dancer has experienced. We’re only there in the auditorium watching them as they dance gracefully on the stage. With Farecast, we see the graceful dancing onstage. We don’t see the data-crunching, we don’t really care about the data-crunching.”
    Farecast turns the tera-crunching tables on the airlines. It uses the same databases and even some of the same statistical techniques that airlines have been using to extract money from consumers. But Farecast isn’t the only service that has been crunching numbers to help the little guy.
    There are a bunch of other services popping up that crunch large datasets to predict prices. Zillow.com in just a few months has become one of the most visited real estate sites on the net. Zillow crunches a dataset of over sixty-seven million home prices to help both buyers and sellers price their homes.
    And if you can predict the selling price of a house, why not the selling price of a PDA? Accenture is doing just that. Rayid Ghani, a researcher at Accenture’s Information Technology group, for the past two years has been mining the data from 50,000 eBay auctions to predict the price that PalmPilots and other PDAs will ultimately sell for. He hopes to convince insurance companies or eBay itself to offer sellers price-protection insurance that guarantees a minimum price they’ll receive. Explains Ghani, “You’ll put a nice