Product Recommendation for Small-Scale Retailers

Abstract

Product recommendation in e-commerce is a widely applied technique which has been shown to bring benefits in both product sales and customer satisfaction. In this work we address a particular product recommendation setting — small-scale retail websites where the small amount of returning customers makes traditional user-centric personalization techniques inapplicable. We apply an item-centric product recommendation strategy which combines two well-known methods – association rules and text-based similarity – and demonstrate the effectiveness of the approach through two evaluation studies with real customer data.