Data mining approach to professional education market segmentation: a case study

Abstract

In this research, a combination of both quantitative and qualitative approaches is used to identify different market segments in the education industry. To solve the research problem, an exploratory approach to data mining is used and, using a series of interviews with experts, the factors affecting segmentation are identified. Then, using the clustering method (in the form of specific two-step and K-means algorithms), customers are clustered and features of each cluster are identified. This research is based on data provided by a large Iranian research and education company. After examining the clusters identified in both methods, it is determined that the clusters provided by the two-step algorithm are more in line with the organizational and market reality of the business. Finally, the marketing mix model is used to formulate strategic approaches and actions.

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