A decision support system for market segment driven product design

Abstract

This paper presents a decision support system (DSS) for market segment driven product design. The input for the proposed system is historic market data and design parameters for a new product. Through market segmentation, with Principal Component Analysis (PCA) and k-means, as well as AdaBoost classification, the DSS determines to which market segment a new product belongs. To demonstrate the feasibility of the proposed system, we have conducted a case study, based on US automotive market data. In this case study, the proposed DSS achieved a classification accuracy of 92.40%. The high accuracy levels make us confident that the proposed system can benefit enterprise decision makers by providing an objective second opinion on the question: To which market segment does a new product design belong? Having the information about the market segment implies that the competition is known and marketing can position the product accurately. Furthermore, the design parameters can be adjusted such that (a) the new product fits this market segment better or (b) the new product is positioned in a different market segment. Therefore, the proposed system enables market segment driven product design.

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