The CBC System for Choice-Based Conjoint Analysis

The CBC System is a component within Sawtooth Software's SSI Web platform for conducting " choice-based " conjoint analysis studies. The CBC software may be used in web-based data collection, using computers not connected to the web (CAPI mode), or with paper-and-pencil studies. The main characteristic distinguishing choice-based conjoint analysis from other types is that the respondent expresses preferences by choosing concepts from sets of concepts, rather than by rating or ranking them. Although it had been discussed by academics for many years (Louviere and Woodworth, 1983), most large-scale commercial use of choice-based conjoint started to occur in the 1990s. The first version of CBC software was released by Sawtooth Software in 1993. According to surveys of Sawtooth Software customers, we believe CBC became the most widely used conjoint-related method in about 2000. Today, it is clear that CBC is the most widely used flavor of conjoint analysis. This paper discusses the method of choice-based conjoint analysis from a practitioner-oriented point of view and describes Sawtooth Software's CBC System for choice-based conjoint analysis in some detail. It also provides suggestions about how to select a particular conjoint method from the variety of those available, considering characteristics of the research problem at hand. Choice-based conjoint analysis has attracted much interest in the marketing research field. There are several reasons for its position as the most widely used conjoint-related approach today:  The task of choosing a preferred concept is similar to what buyers actually do in the marketplace. Choosing a preferred product from a group of products is a simple and natural task that everyone can understand.  Choice-based conjoint analysis lets the researcher include a "None" option for respondents, which might read "I wouldn't choose any of these." By selecting that option, a respondent can contribute information about the decrease in demand to be expected if, for example, prices of all offered products increased or the products became unattractive in other ways.  Most conjoint analysis studies use "main effects only" assumptions. However, because choice-based conjoint analysis data are analyzed by pooling or borrowing information across respondents, it is feasible to quantify interactions. 3  It is possible in choice-based conjoint analysis to have "product-or alternative-specific" attribute levels. For example, in studying transportation we might consider walking shoes and bicycles. The attributes describing shoes are different from those describing bicycles, and yet one might want to study both kinds of …