基于大数据技术的电力营销群体划分研究  

Research on Power Marketing Group Segmentation Based on Big Data Technology

作　　者：孔德勇 KONG Deyong(State Grid Yili Yihe Power Supply Co.,Ltd.,Yili Xinjiang 835000,China)

机构地区：[1]国网伊犁伊河供电有限责任公司,新疆伊犁835000

出　　处：《信息与电脑》2024年第24期154-156,共3页Information & Computer

摘　　要：文章旨在通过大数据挖掘方法实现电力营销中的客户群体划分,进而为制定个性化营销策略提供理论依据。为此,文章采用了随机森林算法对电力企业的客户数据进行分析,并针对客户基本信息、用电行为等特征进行了多维度挖掘,以实现客户群体划分。实验结果表明,随机森林算法在客户群体划分中的准确率达到96.3%,召回率为93.5%,F1分数为0.91,显著优于分类与回归树(Classification and Regression Trees,CART)决策树模型。研究结论表明,随机森林算法能有效提升客户群体划分的准确性,为电力企业制定个性化营销策略提供了可靠的技术支持。The purpose of this paper is to realize the division of customer groups in power marketing through big data mining methods,and then provide a theoretical basis for formulating personalized marketing strategies.To this end,this paper uses random forest algorithm to analyze the customer data of power enterprises,and conducts multi-dimensional mining according to the characteristics of customer basic information and electricity consumption behavior to realize the division of customer groups.Experimental results show that the accuracy of the random forest algorithm in customer group division reaches 96.3%,the recall rate is 93.5%,and the F1 score is 0.91,which is significantly better than the classification and regression trees(CART)decision tree model.The results show that the random forest algorithm can effectively improve the accuracy of customer group segmentation,and provides reliable technical support for power enterprises to formulate personalized marketing strategies.

关 键 词：大数据技术 电力营销策略 客户群体划分 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]