Choice-Based Conjoint (CBC), also known as Discrete Choice Experiments, is commonly used by researchers to study how people make choices. Such applications are common to market research, economics, and psychology, to name the key fields that employ discrete choice experiments.
CBC studies are useful for situations in which people make choices among different alternatives, where the alternatives (the product concepts) are made up of two or more attributes. CBC questionnaires show respondents hypothetical choice scenarios where the competing alternatives are described using varying combinations of attributes (factors) and levels, such as shown in question below:
By observing respondents' choices to such scenarios, we can build models that capture the preference weights (utilities) associated with those attribute levels that seem to be driving those choices. With that information, researchers can predict using a what-if market simulator what people would choose when facing a multitude of potential choice scenarios.
This CBC software within Discover leverages the best things we at Sawtooth Software have learned over 30+ years of working with conjoint analysis and discrete choice experiments. It uses similar algorithms (in some cases slightly better ones) as Sawtooth Software's commercial Windows-based platform, Lighthouse Studio.
Discover-CBC is appropriate for standard CBC studies involving from 2 to 8 attributes with 2 to 15 levels each, where all attributes are used in common to describe all product alternatives (generic rather than alternative-specific designs).