A design strategy for improving adaptive conjoint analysis

Abstract

Adaptive conjoint analysis (ACA) is a market research methodology for measuring utility in business-to-business and customer studies. Based on partial profiles, ACA tailors an experiment's design to each respondent depending on their previously stated preferences, ordered in a self-assessment questionnaire. The purpose of this paper is to describe advantages and disadvantages of using a partial-profile randomised experiment, the usual system, and to propose a new design strategy for arranging profiles in blocks that improve its performance.