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ClickZ columnist Jack Aaronson relates ICS's capabilities to his past cross-selling work at barnesandnoble.com:

Having spent several years as director of personalization at barnesandnoble.com, I can immediately think of easy applications. When my team created the "People who bought this product also bought..." functionality, we very carefully analyzed the importance of metadata over various book categories. The publisher is very important to techies buying books on programming, for example. The author is very important to people buying fiction. Genre is very important to people buying nonfiction. This method of weighing metadata enabled us to create lists of cross-sells that were much more targeted based on the kind of book in question than collaborative filtering or simple statistical analysis could provide.

If we could have imported that information into CNET Channel's rules-based engine, I suspect the process would have been greatly simplified. We could have also created internal lists of New York Times Best Sellers, Oprah's book lists, award winners, books currently in the news, and the like and weighted recommendations based on that data. We could have added business rules on top of that to harness even finer metadata (such as not recommending books that are too heavy and would therefore increase shipping costs to the extent where we'd risk losing the sale).

Read the full article at ClickZ.