Predictive technology is often used to predict patterns of behavior or events. One application for this technology is in the area of predicting customer behavior to help optimize marketing programs for online retailers. Companies such as Net Perceptions offer predictive technology based upon collaborative filtering techniques. The most widely recognized example of this type of technology is in use at Amazon.com, where book recommendations are made based upon what other buyers of a particular book have also purchased. This type of recommendation works best for generic commodity type products that have a high personal taste factor built into product selection, such as books, films and music. For more complex purchase selections, involving many more aspects of personal choice, companies are turning to more sophisticated predictive technology using multiple predictive algorithms to determine customer behavior. eBags for example, an online retailer of bags and luggage, has implemented predictive technology from Applied Predictive Technologies (APT) to help predict how customers will respond to alternative cross-selling messages in the checkout process. eBags uses “aptAdviser” to determine the best cross-sell message to display for each customer. More details of this technology and how it is being adopted by eBags can be found in the eRetailNews Report on Wish Lists. FREE NEWSLETTER, click here | 