Customer-oriented marketing is a strategy that aims to recommend the right product(s) to the right customer(s). It is low-cost, low-risk, and profit-driven. It typically involves two components: customers and products. One of the critical challenges of targeted marketing is identifying products with potential market value for customers. In this paper, we studied an instance of this general problem. This paper finds the k-most preferable products (k-MPP) from a set of products under study to be offered to a customer for targeted marketing. We model the k-MPP problem as a multicriteria ranking problem and propose an algorithmic framework for customer-oriented marketing. Our framework utilizes a multicriteria outranking approach to solve the k-MPP problem. The framework's effectiveness is demonstrated by conducting a case study to find the k-most preferable restaurants for a customer in a Mexican city.

Targeted marketing, customer-oriented marketing strategy, multicriteria decision analysis, outranking approach, ELECTRE III method, information retrieval