Sawtooth Software: The Survey Software of Choice

Choice Modeling Workshop - Anaheim - October 2017

On October 9-12, 2017, Sawtooth Software will host two back-to-back training events at the Disneyland Hotel in Anaheim, California. The first event is a two-and-a-half day introduction to CBC (Choice-Based Conjoint) and MaxDiff (Maximum Difference Scaling). The second event is a day-and-a-half exploration of ACBC (Adaptive Choice-Based Conjoint) which builds on the foundation presented in the first workshop. Throughout both events, participants will create choice surveys and analyze sample data using a team-oriented case study approach.

CBC/Max Diff

Monday: Introduction to CBC

This session introduces participants to discrete choice (CBC) analysis through interactive, hands-on training. Attendees will also receive practical experience creating surveys in Sawtooth Software’s Lighthouse Studio system and analyzing the results.

  • Conjoint methodology overview
  • Formulating attributes and levels
  • Designing conjoint experiments
  • 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
  • Best practices / common mistakes related to CBC

Tuesday: Intermediate CBC

This session builds upon concepts learned in the introductory segments of this training. We'll go beyond the basics of CBC to cover:

  • Choosing among the four questionnaire design strategies: Complete Enumeration, Shortcut, Balanced Overlap, and Random
  • Prohibitions: are they universally bad? Testing the impact of modest to severe prohibitions
  • Design Testing: Quick Test vs. more advanced test using simulated respondents. How the advanced test can help with sample size decisions
  • Conditional Pricing: customizing price ranges without the use of prohibitions
  • Introduction to Partial Profile, Constant Sum, Alternative-Specific Designs

Wednesday Morning: MaxDiff

This half-day session introduces participants to MaxDiff (best/worst item scaling).

  • When to use MaxDiff vs. CBC
  • Designing, programming, and analyzing MaxDiff experiments