Applying Recommendation Techniques In Conventional Grocery Retailing

In grocery retailing, promotions and recommendations, derived from traditional data mining techniques, apply uniformly to all customers and not to individual ones, thus failing to meet each customer’s personal needs. On the other hand, recommender systems have been widely explored in the field of e-commerce managing to provide targeted personalized recommendations for products and services. Despite the great success of recommender systems in internet retailing, their application in many other fields remains practically unexplored. RFID and pervasive networking technologies now offer the potentials to utilize recommender systems in physical environment. The scope of this paper is to examine the individual characteristics of the new domain along with the applicability of various recommendations techniques. The results indicate the superiority of the e-commerce recommendation techniques against the traditional approaches currently used in grocery retailing