Investigation and Application of Cluster Analysis in Service Industries

Analytical models are critical in service Industries. In every phase of the credit cycle - marketing, acquisitions, customer management, collections, and recovery. While such models are now commonplace, the search for competitive advantage requires continuous improvement in the models. Customization of the models for each segment of the population is a crucial step towards achieving that end. Segments in the population may be defined judgmentally using one or two variables, but cluster analysis is an excellent statistical tool for multivariate segmentation. The clusters may be used to drive the model development process, to assign appropriate strategies, or both. This paper discusses the FASTCLUS procedure as a tool for segmentation of a population. The first phase involves preparing the data for clustering, which includes handling missing values and outliers, standardizing, and reducing the number of variables using tools such as the FACTOR procedure. The FASTCLUS discussion emphasizes the assumptions, the options available, and the interpretation of the SAS output. Finally, the business interpretation of the cluster analysis is provided within the context of this specific industry. This enables the analyst to identify the appropriate number of clusters to use in model development or strategic planning.