Segmenting student markets with a student satisfaction and priorities survey

A market segmentation analysis was conducted on students at a large midwestern urban university using two forms of hierarchical cluster analysis on student characteristics: an agglomerative procedure using a matching-type association measure and a divisive chi-square-based automatic interaction detection (CHAID). The resulting segments were compared for their ability to distinguish among students according to six satisfaction scales and measures of students' priorities for college study derived from a general satisfaction survey. As expected, the CHAID clusters discriminated better among students according to their several measures of satisfaction, one of which was the criterion variable for the analysis. However, both procedures produced differences across only two of six satisfaction scales. The matching-type measure clusters resulted in significant differences on 11 of 18 college study priority items compared to only 6 of 18 for the CHAID clusters. Final discussion describes the usefulness of market segmentation strategies for planning, evaluating, and improving academic and student support programs.Presented al the Thirty-Fourth Annual Forum of the Association for Institutional Research, New Orleans, LA, May 29–June 1, 1994.