Abstract
A typical target selection problem aims at selecting prospects that are more likely to respond to a promotional campaign. There are varieties of target selection models available in the literature that address this problem. This paper investigates the use of recommender systems for selecting target customers in internet business. The suggested methodology uses the concepts of collaborative filtering and data mining for effectively selecting the target customers. The methodology is experimentally evaluated on a real-life data set and its benefits demonstrated. The experimental results reveal that the suggested methodology provides better predictive capabilities compared to random target selection methods. The methodology could be useful for e-commerce managers in devising suitable promotional strategies whenever a new product is introduced into the online store.
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