Abstract: A method for predicting whether an on-line shopper is converted into becoming a purchaser of an item based on promotions offered by an on-line vendor. A set of data including customer profile information corresponding to a plurality of on-line shoppers; customer log information corresponding to the plurality of on-line shoppers; product information corresponding to a plurality of products offered for sale by the on-line vendor; and promotion attributes corresponding to the plurality of products are stored in a database. Next, a model which simulates shopping behavior as a function of the customer profile information, customer log information, product information, and promotion attributes is constructed. This model is partially based on the traditional logistical regression theory and partially on the maximum utility theories. Thereby, the data corresponding to a new on-line shopper is input to the model which then compute a percentage likelihood that the shopper is converted into becoming a purchaser.