Full-profile conjoint analysis is widely used method to examine consumers' preference in the development of consumer products. As the number of attributes and attribute levels increase, the number of profile cards grows exponentially and the full-profile conjoint analysis becomes more difficult to apply. This paper describes a method of full-profile conjoint analysis to minimize profile cards and to accept incomplete rank ordered data for the design development. To illustrate how the proposed method can be effective, an experimental survey was conducted for the evaluation of the method. The effectiveness of the method was confirmed by the results of the experimental survey, and it was found that the method improve the performance of full-profile conjoint analysis for industrial design and product development.