Cluster analysis is a frequently used technique in marketing as a method to develop partitions or classifications for market segmentation, product positioning, test market selection, etc. Because of the vast diversity in the assortment of clustering algorithms available, it is often times not obvious which algorithm or technique should be employed. It is often recommended that the marketer perform more than one cluster analysis on the same data set and compare representations as a reliability check. A methodology for evaluating the consistency of different clusterings is introduced via contingency table analysis by log-linear models. In addition, insight is provided as to selecting a “best” representative clustering by examining Stewart and Love's (1968) redundancy measures.