Fuzzy targeting of customers based on product attributes

Finding the right set of target customers for a given product is an important problem in business-to-consumer (B2C) e-commerce. We propose an approach to solve this problem based on product attributes. Our approach is based on the assumption that the interest of a customer in a product depends on the customer´s interest towards its attributes. We use a collection of membership estimators to compute the degree to which a customer might be interested in a product. Each estimator is based on a particular product attribute, and takes into consideration purchase information about other products that are similar to the given one from the point of view of the attribute. Thus, each estimator generates a membership value for each customer in the target customer set based on a specific attribute. We then use these memberships and other customer information to predict the target customers. Our experimental results show a significant improvement in prediction accuracy when the proposed approach is used