Enhancing conjoint analysis with hierarchical factor analysis for efficient attribute clustering

Recently, competitive advantage was achieved by those firms able to develop their product/service to fulfill a consumer’s need. The market preferences following adequate evaluation of how people measure different features of an individual product. The product or service design using Conjoint analysis, a quantitative research tool widely employed in product management and marketing struggled the over information overload for decision-making in the ranking preference value. Our proposed method, the integration of Hierarchical Factor analysis and conjoint analysis, can improve the product design more efficiently. The experiment on electric pump design has found that the seven attributes were segmented into five clusters, and each cluster consisted of full factorial design with suitable product concepts for a man-kind decision-making.