Below is our typical daily schedule, although it may vary depending on class needs.
This session introduces participants to discrete choice (CBC) analysis through interactive, hands-on training.
Conjoint methodology: overview, concepts, and objectives
Formulating attributes and levels
Designing conjoint experiments
Best practices / common mistakes related to CBC
Choosing among the four experimental design strategies: Complete Enumeration, Shortcut, Balanced Overlap, and Random
Prohibitions: are they universally bad? Testing the impact of modest to severe prohibitions
Design Testing: How simulated respondent data can help with sample size decisions
This session builds upon concepts learned in the introductory segments of this training. Attendees will also receive practical experience creating surveys in Sawtooth Software’s Lighthouse Studio system and analyzing the results. We'll go beyond the basics of CBC to cover:
Analyzing CBC data using Counts, Logit, Latent Class, and hierarchical Bayes (HB)
Using market simulators to estimate preference for competitive products in market scenarios, including price sensitivity
Introduction to product optimization searches using the market simulator
Conditional Pricing/Display: customizing price ranges and concept display without the use of prohibitions
Introduction to Alternative-Specific Designs
This session introduces participants to two of our most popular survey strategies: MaxDiff (best/worst item scaling) and Adaptive CBC.
1-hour review of programming, fielding, and analyzing CBC experiments
Designing, programming, and analyzing MaxDiff experiments
MaxDiff Analyzer tool and TURF analysis
Benefits and motivation for Adaptive CBC (ACBC)
Designing, programming, and analyzing ACBC studies
When to use non-adaptive CBC and Adaptive CBC (ACBC)
