Data Scientists Mike Serpetti and Dan Yardley presented “A Researcher’s Guide to Studying Large Attribute Sets in Choice-Based Conjoint” at the 21st Sawtooth Software Conference in San Diego, California. The presentation was awarded “Best Paper/Presentation” at the conference.
There is no arguing that choice-based methods have become dominant in the industry. Yet, there is no clear answer on what a researcher should do if the number of attributes is high. Different conjoint techniques including Partial Profile and Adaptive Choice-Based conjoint offer solutions, but past research has yet to crown a winner. This presentation will set out to explore and validate these two methods in comparison to Full-Profile Choice-Based Conjoint (CBC) with real respondents on a set of up to 20 attributes to determine which method is best across multiple scenarios.
The 21st Sawtooth Software Conference is an industry-favorite forum held to exchange ideas, network, and learn about conjoint/choice/MaxDiff analytics and market segmentation. For more information on this event, and/or to register please visit here.