"The Right Product for the Right Person: Product Recommendation from Infrequent Events at Clickthrough" by Marty Vrieze, David Freed, Brendan Kitts They authors describe five years of work developing, analyzing, and running one-to-one marketing systems in a successful cross-channel retailer. The problem is targeting the right customer with the right product. Previously our participating retail chain, Clickthrough, had sent e-mails to opt-in customers featuring products chosen by the marketing department. In 1999 they ran a pilot study in which they replaced the static products with product offers selected by a probabilistic one-to-one recommendation algorithm.  The pilot test was very successful. Clickthrough increased profit by 40%, revenue by 38%, and units sold by 61%. The full system was deployed in October 2000 that generated a response rate increase of over 100%. From 2000–2005, the recommendation system has continued to be used each week, and the retailer continues to maintain control groups and report on performance.