Decision-Theoretic Design of Shopbots (Research Seminar, October 25th, 2001) Ramayya Krishnan W. W. Cooper and Ruth F. Cooper Professor of Information Systems The Heinz School, Carnegie-Mellon University Abstract ShopBots are tools used for comparison shopping on the Internet. In response to queries, they search a large number of vendors for price and availability. Typically, the ShopBot searches a predefined set of vendors and reports all results. This can result in lengthy and inefficient searches. In this paper, we use a decision-theoretic approach that maximizes consumer utility to inform ShopBot design. Specifically, we model the operational decisions made by the ShopBot in response to user queries such as which stores to search, how long to wait and which offers to present to users. We calibrate the model to price and response time data collected at online bookstores over a six month period. Results demonstrate that a model-based ShopBot can deliver substantially increased utility to the consumer. We conclude by discussing other potential applications of this methodology.