Application of data mining to customer profile analysis in the power electric industry

Abstract

In Japan, the Revised Electric Utility Industry Law went into effect on March 21, 2000. The partial deregulation into the retail electric power supply sector means that electric power for extra-high voltage customers can now be supplied from companies other than the 10 major electric power companies (EPCos) and electricity rates charged to customers can be determined freely according to negotiations for the liberalized sector between these companies and their customers. Due to the introduction of this partial deregulation, the 10 EPCos have found it necessary to form customer strategies against new entrants, power producers and suppliers (PPSs). In other industries (such as retail trade) in which competition with smaller companies is fierce, it is indispensable to assess preferred customers yielding more profits and form marketing strategies (i.e., business intelligence) to strengthen relationships with these preferred customers by providing unique services. Even in the electric power industry, it is expected to become necessary to form the same marketing strategies as these unrelated industries in consideration of future fierce competition. In order to draw up marketing strategies, it is first indispensable to understand customers, that is, the analysis of customer data. Since the nature of electric power differs from the products that the retail trade business targets, it is necessary to carry out a type of customer data analysis that differs from the retail trade business. The authors explain an example of marketing method to establish customer strategies, using data mining technique based on customer profile data.

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