This paper introduces an application of multidimensional scaling for marketing-mix modification of products at the maturity stage of product life cycle. The application is based upon the concept that marketers would benefit from mining the consumer behaviors to assist their marketing decisions. Using the preference map of multidimensional scaling method and influence-satisfaction matrix, the proposed methodology promotes marketers to analyze their current level of consumer satisfaction in the market and modify the marketing-mix based upon the current consumer preference and satisfaction.The proposed methodology adopts multidimensional preference (MDPREF) algorithm, which is designed to do multidimensional scaling of preference or evaluation data. While most applications with the multidimensional scaling have been to understand the position of a set of brands or products, the proposed methodology with MDPREF algorithm is to understand the similarities and dissimilarities among a set of marketing elements of a brand in consumer’s perception. A case example for the mobile phone category is provided.