Most of the choice-based research done today is full profile (FP), where a level from every attribute is shown in every product profile. However, some argue that there comes a point when a FP choice task is too cumbersome and overwhelming, forcing respondents to use a simplification heuristic that could affect the model’s predictability. Since the work of Green and Srinivasan (Green, P. & Srinivasan. 1978), we have been historically taught to use around six attributes (depending on level text, category, and more). One solution to this problem includes Partial Profile (PP). PP is where a level from only a subset of attributes, usually 7 or fewer, is shown in every product profile. The subset of attributes changes across every screen so that respondents evaluate all attributes, but only 7 at a time. (Chrzan, K., & Elrod, T. 1995) This presentation compares the standard approach to PP to a custom approach, where only the levels of an attribute that a respondent says is important, is shown in every product profile. Therefore, the subset of attributes stays the same across every screen so that respondents only evaluate a subset of the total attributes. We call this approach, Bespoke CBC
