When pricing and product leaders seek to understand what customers truly value, choice-based conjoint analysis is the definitive methodology of choice. However, transforming a strategic research question into a mathematically sound, field-ready survey is a highly technical process. Organizations frequently stumble during the foundational setup – either by overloading respondents with too many product attributes or by failing to account for real-world market constraints. This webinar peels back the operational curtain, offering market researchers and data strategists a transparent look at the mechanics required to build robust, statistically valid conjoint models.
The session provides a comprehensive, step-by-step walkthrough of the entire experimental design pipeline. You will learn the technical best practices for defining product attributes and levels, ensuring they are mutually exclusive and collectively exhaustive to prevent skewed utility scores. The discussion dives deep into experimental efficiency, demonstrating how modern algorithms generate optimal survey blocks that maximize information gain while keeping respondent fatigue to an absolute minimum. Rather than treating conjoint as a black box, this webinar arms you with the fundamental principles needed to ensure your underlying data is clean, reliable, and actionable.
Beyond the initial survey architecture, the webinar shifts focus to data synthesis and advanced simulation capabilities. You will see first-hand how individual choice data is aggregated into Hierarchical Bayesian (HB) models to estimate precise individual-level utilities. The session concludes with a practical demonstration of how these utility scores feed into interactive market simulators. You will learn how to configure these tools to model complex market dynamics, allowing you to accurately forecast how structural changes to your product portfolio will shift market share. Watch the full session below to master the execution of conjoint analysis and bring predictive precision to your research infrastructure.
