A choice experiment studies customer preferences for a set of product or process (in the case of a service) attributes. Respondents are presented sets of product attributes, called profiles. Each respondent is shown a small set of profiles, called a choice set, and asked to select the preference that he or she most prefers. Each respondent is usually presented with several choice sets. Use the Choice platform to analyze the results of a choice experiment.
Note: You can design your choice experiment using the Choice Design platform. See Discrete Choice Designs in Design of Experiments Guide.
The Choice platform allows respondents to not make a choice from among a set of profiles. The no choice option is treated as a product with a single attribute (“Select none of these”) that respondents are allowed to select. The parameter estimate for the No Choice attribute can then be interpreted in many ways, depending on the assumptions of the model. The Choice platform also enables you to obtain subject-level information, which can be useful in segmenting preference patterns.
If there are not sufficient data to specify “By groups,” you can segment in JMP by clustering subjects using the Save Gradients by Subject option. The option creates a new data table containing the average Hessian-scaled gradient on each parameter for each subject. For an example, see Example of Segmentation. For details about the gradient values, see Gradients.