Application of data mining in power customer satisfaction evaluation

Abstract

In traditional power supply system, satisfaction data gained through customer revisit only been analyzed by on-line analytical processing(OLAP) method. Just as many other OLAP model, data used in the course of analysis are multidimensional, and most of potential values of data are difficult to be found in simple OLAP model based on multidimensional, data are need to be mined further so as to provide decision support to managers and decision-makers. This paper made research and elaboration to application of data mining technology in power customer relationship management(CRM). The entire model-building process adopted industrial recognized CRISP-DM data mining methodology with a certain degree of influences; the data mining algorithms used in this project were Clustering Algorithm and Principal Component Analysis; in the part of model verification, disordered matrix and income statement model were adopted. © 2012 Springer-Verlag GmbH.