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Guessing the Online Customer’s Next Want

Posted in Data Mining, NYTimes, Online Marketing by Pankaj Gudimella on May 19, 2008

Marketers have always tried to predict what people want, and then get them to buy it.

Among online retailers, pushing customers toward other products they might want is a common practice. Both Amazon and Netflix, two of the best-known practitioners of targeted upselling, have long recommended products or movie titles to their clientele. They do so using a technique called collaborative filtering, basing suggestions on customers’ previous purchases and on how they rate products compared to other consumers.

Figuring that out is not so easy. For one thing, people do not always buy what they like. Someone may buy a sweater for their grandmother even though they dislike it and would never get it again. Similarly, a person who rents a movie may actually detest it but knows her child likes it. Or a film that was seen on a small airplane screen may garner a lower rating than if it were seen at a large multiplex.

More here from NYTimes.

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