Segmenting the Higher Education Market: An Analysis of Admissions Data Using K-Means Clustering

Abstract

One of the affecting factors of marketing strategy in educational institutions is determining clear marketing objectives including suitable segmentation. This study develops a market segmentation for private HEIs considering the potential academic records of targeting schools and geographic factors. K-Means clustering method is exploited to cluster around 260 data with eight attributes. The elbow method and silhouette coefficient are used to determine the appropriate number of clusters. Findings suggest that schools within Cluster 1 and Cluster 4, with approximately 42% market share, are the primary market segment for deploying a robust and targeted marketing strategy.