Capturing and Evaluating Segments: Using Self-Organizing Maps and K-Means in Market Segmentation

10.6413/AJMHS.200604.0001

Che-Hui Lien；Alex Ramirez；George H. Haines

market segmentation ； cluster analysis ； data mining ； neural networks ； self-organizing maps

Asian Journal of Management and Humanity Sciences

1卷1期（2006 / 04 / 01）

1 - 15

英文

Market segmentation is a vital part of an organization's marketing because it provides the fundamental framework necessary for effective marketing efforts. In recent years, due to their high performance in engineering, artificial neural networks have also been applied in management research. Self-organizing maps, a technique of unsupervised neural networks, are often used for clustering or dimensional reduction. This study employs a modified two-stage approach (SOMs and K-means) to group customers, compares the performance between the tandem approach and direct K-means clustering, and tests for the existence of clusters and segments. The test results show that a media promotion variable would be a basis for segmentation. Based on the segmenting results, a marketing communication strategy is presented to cope with customers' expectations.