Author(s)

Ma Junjuan, Qiu Lingyun, Wang Qin

Corresponding Author

Ma Junjuan

Abstract

Electricity, as an indispensable resource in the real world, provides great convenience for our life and work, among which power enterprises play a vital role as a bridge between power generation and consumption. The main factors involved in power customer grouping are customer value, customer demand and customer behavior, etc. In customer grouping management, customer data mining algorithm is used to realize automatic classification of objective customer groups. The analysis of different customer needs is based on the customer segmentation theory. In the management of power customer group, different power products, power sales and power services can be provided according to different customer value, demand and behavior. This paper classifies the customer groups according to the credit rating of power users, and puts forward the service quality improvement methods for different power users, so as to provide personalized customized services for power customers and reduce the burden of power enterprises.

Keywords

Electric power enterprises, Customer base, Credit rating