The number one job for marketers is to predict what people will want and then convince them to purchase them. Retailers such as Amazon and Netflix have been using a technique called targeted upselling, which is a system of recommending products or services to their customers. These options are given using collaborative filtering and use suggestions based on a customer’s previous purchase. This is no simple task, as consumers are always changing their minds, on what they like, or if they are buying something for themselves or a gift, which could mean a completely different selection.

The search for a better recommendation continues with numerous companies selling algorithms that promise a retailer more of an edge. For instance, Barneys New York, the upscale clothing store chain, says it got at least a 10 percent increase in online revenue by using data mining software that finds links between certain online behavior and a greater propensity to buy.

Using a system developed by Proclivity Systems, Barneys used data about where and when a customer visited its site and other demographic information to determine on whom it should focus its e-mail messages.

For instance, an e-mail message announcing sales might go to those Web site visitors who had purchased certain products or types of products in the past, but who had done so only when the items were on sale. In the simplest terms, if someone buys only when something is on sale, but never buys anything in December, then the e-mail sale flier might not be sent to that customer in December. “There is a digital trail of interest left by customers,” said Sheldon Gilbert, Proclivity’s chief executive and founder.