Relevant Items MaxDiff: its Origin, Motivation, and Options

Relevant Items MaxDiff was introduced as a cutting-edge method by Chris Chapman and Eric Bahna at the 2018 Sawtooth Research Conference. Relevant Items MaxDiff is an adaptive MaxDiff methodology that tailors the set of items shown to each respondent, displaying only those that are deemed “relevant” to the respondent based on prior screening. Relevant Items MaxDiff was released in Sawtooth's Lighthouse Studio in 2020 and it was recently included in Sawtooth's Discover in May 2025. In this presentation, Chris discusses the importance and use cases for Relevant Items MaxDiff, including its applications and considerations for designing a survey. He presents empirical data from a case study at Google, and discusses crucial analysis options. Bring your questions to this presentation, which is guaranteed to inspire you to conduct new varieties of MaxDiff surveys! Chris Chapman is founder and president of the Quantitative User Experience Association, an industry educational nonprofit organization that offers classes and an annual conference, Quant UX Con. Previously he worked in user research and marketing analytics for 24 years at Google, Microsoft, and Amazon. Chris's books include R for Marketing Research and Analytics with Elea Feit (Springer, 2019) which has been used as a textbook in more than 160 colleges and universities and translated into Chinese and Japanese; Python for Marketing Research and Analytics with Jason Schwarz and Elea Feit (Springer, 2020); and most recently, Quantitative User Experience Research with Kerry Rodden (Apress, 2023).