基于数据挖掘的电动汽车用户细分及价值评价方法

Customer segmentation and value evaluation method based on data mining for electric vehicles

用户细分可以掌握不同电动汽车用户充电行为的特征及其之间的差异性,对充电服务运营企业具有重要意义。基于运营管理系统迅速积累的大量充电服务数据,对全量数据进行探索性分析,筛选出细分模型关键变量,给出了基于数据挖掘技术和K均值(K_MEANS)聚类算法的电动汽车用户细分方法,提出了电动汽车用户价值评价方法。针对北京地区电动汽车用户开展分析并得到用户行为特征及价值评价结果。相关结论可为运维管理机制优化和精准营销策略制定提供数据支撑。

Customer segmentation is of great significance for charge service operators to obtain the features of charging behaviors and individual differences between various Electric Vehicle(EV)users.Based on large numbers of charging service data fast accumulated by operations management system,exploratory data analysis is applied to all the historical data in the database.Firstly key variables are screened out to the segmentation model,and then the EV customer segmentation method by data mining technique and K-MEANS algorithm is presented.Secondly the customer value evaluation method is proposed,and charging behavioral features and customer values are analyzed based on Beijing EV customers.At last,conclusions and suggestions are given,which would provide data supports for the improvement of operation and maintenance management and decision-making of the precision marketing.