Hierarchical Bayes is a relatively new technique for computing individual- level part worths from conjoint data. HB has been described favorably in several recent journal articles. Its strongest point of differentiation is its ability to provide estimates of individual part worths given limited information from each individual. It does this by "borrowing" information from other individuals.
This technical paper describes the functionality of the software and math behind HB. We at Sawtooth Software are not experts in Bayesian data analysis. In producing this software we have been helped by several sources. We have benefited particularly from the materials provided by Professor Greg Allenby in connection with his tutorials at the American Marketing Association's Advanced Research Techniques Forum.