As development and training partner of Sawtooth Software, we team up twice a year to give a proven 3-day SKIM/Sawtooth Software choice modeling workshop in Rotterdam, The Netherlands.

About the SKIM/Sawtooth Software Choice Modeling workshop

Whether you have some knowledge about conjoint already or you are just getting started, this popular three-day workshop will provide you with practical solutions about conjoint/choice methodologies in order to improve their research or consulting practice.

This hands-on training covers three current and most popular choice research methodologies:

  • CBC (Choice-Based Conjoint),
  • MaxDiff (Maximum Difference Scaling)
  • ACBC (Adaptive CBC)

All sessions are hosted by senior staff of both SKIM and Sawtooth Software and organized in a personal, hands-on, classroom setting. You will have the chance to create choice surveys yourself and analyze sample data using a team-oriented case study approach, using Sawtooth Software’s Lighthouse Studio (formerly known as SSI Web) platform.


Day 1: Introduction to CBC

On this first day, we introduce discrete choice (CBC) analysis through interactive, hands-on training. Below are some of the topics we’ll cover:

  • 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: Quick Test vs. more advanced test using simulated respondents. How the advanced test can help with sample size decisions

Day 2: Intermediate CBC

On day 2, we’ll build upon the concepts learned in the introductory part of the training. You will receive practical experience while creating surveys in Sawtooth Software’s Lighthouse Studio system and analyzing the results. We will go beyond the basics of CBC and will 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
  • Conditional Pricing/Display: customizing price ranges and concept display without the use of prohibitions
  • Introduction to Alternative-Specific Designs

Day 3: MaxDiff and Adaptive CBC

On day 3, we’ll discuss two of our most popular survey strategies: MaxDiff (best/worst item scaling) and Adaptive CBC. We will cover the following:

  • 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)