Marketing, transportation, environmental, and other researchers need to understand how people make choices. Researchers design experiments, collect data, and fit models to understand people’s preferences. This talk will explain some commonly used methods for designing choice experiments along with a series of SAS tools that you can use to design and evaluating choice experiments. Design methods include generic and alternative-specific choice designs, partial profiles, and MaxDiff designs. Building blocks include orthogonal arrays and balanced incomplete block designs. Combinatorial constructions and computerized searches are discussed. Frequently, researchers want to restrict their designs, and methods for placing restrictions on the design are also discussed.