Choice-Based Conjoint

Choice-based conjoint analysis (CBC) measures how consumers value the features of a product by observing the choices they make among competing, attribute-defined profiles rather than by asking them to rate attributes directly. Each respondent completes a series of choice tasks, picking the single most preferred alternative (often with a 'none' option) from a small set, and the pattern of choices across many tasks reveals the implicit trade-offs people make. The method grew out of Louviere and Woodworth's 1983 integration of conjoint measurement with discrete-choice theory, which showed that controlled choice experiments could be analyzed with the multinomial logit model. Because the choice task mimics a real purchase decision, CBC has become the dominant form of conjoint in commercial marketing research, popularized by Sawtooth Software. Estimation recovers part-worth utilities for every attribute level, either at the aggregate level or, more commonly today, individually through hierarchical Bayes. Those utilities then feed market simulators that predict shares of preference for new or hypothetical product configurations.