Step 1: Let like-minded customers merchandise your products for you.

Since the beginning of time, the societal norm has been to trust experts -- our teachers, doctors, lawyers, etc. It was the best strategy available when we could interface with only a few people at a time. The increasingly social nature of the Web has changed this dynamic. James Surowiecki reveals in his best-selling book, The Wisdom of Crowds, something that scientists have known for years: Random groups of informed people can predict outcomes far more accurately than any individual expert. Since that time, companies such as Netflix and Amazon have popularized the use of recommendation engines to identify new patterns in behavior as customers browse and purchase online.

Leveraging crowd wisdom is especially important in content -- and product-rich "long tail" sites where manual merchandising and editorializing is neither cost- nor time-effective. Long tail is the concept of selling fewer units of many different special-interest products, as opposed to selling large quantities of fewer popular products, such as the iPhone. Instead of asking a merchandiser to define the thousands of niche segments along the long tail, why not let the crowd of site visitors self-define those segments? By tapping into the wisdom of these like-minded shoppers, your customers can effectively recommend products to one another and actually sell for you.

Step 2: Pinpoint customer sentiment ahead of the curve.

Leading industry analysts at market research firms Gartner, based in Stamford, Conn., and Forrester Research, in Cambridge, Mass., have both been giving a lot of attention to the concept of studying customer sentiment to make predictions on future consumer trends. Forrester calls this "customer intelligence," and Gartner has dubbed it "pattern-based strategy" (PBS). According to Gartner, PBS "provides a framework to seek, model, and adapt to leading indicators, often-termed "weak" signals, that form patterns in the marketplace. This is something that transactional-based systems, such as business intelligence (BI) and complex event processing (CEP), simply haven't been able to deliver. (continued...)

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