Study On Application Of Power Customer Segmentation Management In Era Of Big Data

Full implementation of customer grouping management,proper understanding,satisfaction,guide customer demand,snug fit customer needs to develop differentiated service strategy to provide customers with safe,reliable,efficient and convenient,green with the international advanced level comparable power supply services,It is the supply enterprises to establish "good service,good management,good image," Miyoshi service image of an inevitable requirement.Firstly,from a variety of data mining success stories,leads the current power supply companies due to the long accumulation have mastered a lot of covers production,customers(including basic data,operational data,measurement data and service data)and other operating aspects of the data assets thus described the goal of this paper is by digging large marketing data,customer implementation of a comprehensive,scientific and rational customer segmentation.Secondly,the power supply enterprise to customer segmentation management architecture,including: the concept of customer segmentation management and the need to manage the implementation of customer segmentation;data-based customer segmentation,namely the power marketing large data segment in which valuable character;intends to customer divided into several groups in order to provide personalized service strategy.Finally,application of customer segmentation management model in Z Power Supply Bureau.Z Power Supply Bureau Power Marketing Big Data,with clustering customer value and service channel activity were grouped using a logistic regression model for customer outage risk sensitivity and arrears clustering,decision tree model for customers conduct electrical safety grouping.Through a variety of customer behavior database variables precise segmentation,and customer behavior patterns and customer value analysis to accurately determine and,in order to achieve different customers Z provide differentiated services strategy.At the same validity and effectiveness also proposed customer segmentation management data model for verification.