Marisa S. Viveros

Personalization of Supermarket Product Recommendations

We describe a personalized recommender system designed to suggest new products to supermarket shoppers. The recommender functions in a pervasive computing environment, namely, a remote shopping system in which supermarket customers use Personal Digital Assistants (PDAs) to compose and transmit their orders to the store, which assembles them for subsequent pickup. The recommender is meant to provide an alternative source of new ideas for customers who now visit the store less frequently. Recommendations are generated by matching products to customers based on the expected appeal of the product and the previous spending of the customer. Associations mining in the product domain is used to determine relationships among product classes for use in characterizing the appeal of individual products. Clustering in the customer domain is used to identify groups of shoppers with similar spending histories. Cluster-specific lists of popular products are then used as input to the matching process.The recommender is currently being used in a pilot program with several hundred customers. Analysis of results to date have shown a 1.8% boost in program revenue as a result of purchases made directly from the list of recommended products. A substantial fraction of the accepted recommendations are from product classes new to the customer, indicating a degree of willingness to expand beyond present purchase patterns in response to reasonable suggestions.

A Case Study in Information Delivery to Mass Retail Markets

The growth in the capabilities of hand-held computers coupled with improvements in database systems and communication infrastructure have brought us closer to enabling truly ubiquitous access to information. In this paper, we describe the SmartPad system, a software solution in the consumer space, providing consumers with ubiquitous access to interactive shopping. This solution enables end-users to shop remotely using personalized content, searching and selecting in incremental mode and disconnected from the network. This is achieved by combining in-store and on-line transactions, by leveraging current efforts in data mining, and by delivering information through hand-held devices. SmartPad is currently used by several hundred consumers with very encouraging initial feedback.