电信科学 ›› 2019, Vol. 35 ›› Issue (11): 117-124.doi: 10.11959/j.issn.1000-0801.2019271

• 电力信息化专栏 • 上一篇    下一篇

电力潜在敏感客户预测的大数据方法应用

陈小峰,赵雅迪,张利鹏,朱峰   

  1. 北京国网信通埃森哲信息技术有限公司,北京 100032
  • 修回日期:2019-10-10 出版日期:2019-11-01 发布日期:2019-12-23
  • 作者简介:陈小峰(1980- ),男,现就职于北京国网信通埃森哲信息技术有限公司,主要研究方向为企业管理、精益生产和大数据挖掘|赵雅迪(1993- ),女,现就职于北京国网信通埃森哲信息技术有限公司,主要研究方向为业务数据分析和数据挖掘|张利鹏(1988- ),男,现就职于北京国网信通埃森哲信息技术有限公司,主要研究方向为业务数据分析和数据挖掘|朱峰(1988- ),男,现就职于北京国网信通埃森哲信息技术有限公司,主要研究方向为财金业务分析和咨询

Application of big data method in forecasting potential sensitive customers of electric power

Xiaofeng CHEN,Yadi ZHAO,Lipeng ZHANG,Feng ZHU   

  1. State Grid Information &Telecommunication Accenture Information Technology Co.,Ltd.,Beijing 100032,China
  • Revised:2019-10-10 Online:2019-11-01 Published:2019-12-23

摘要:

随着 95598 业务的不断发展延伸,人工话务强度增大。为了进一步加深对客户隐性特征以及诉求的认识和理解,提升 95598 人工精细化客户服务水平,对投诉倾向等客户服务中的典型应用场景进行了需求细化。基于电力服务工单数据,选取建模关键指标,通过熵权法、主成分分析和决策树等数据挖掘算法,对潜在投诉倾向客户和计划停电敏感客户进行识别,以便有针对性地进行服务资源调度,充分做好应对措施,有效减少投诉压力,提升服务精度。

关键词: 投诉工单, 数据挖掘, 熵权法, 决策树

Abstract:

With the continuous development and extension of 95598 business,the intensity of manual telephone traffic increases.In order to further deepen the consciousness and understanding of the hidden features and the demands of the customers,improve the customer service level of 95598,the typical application scenarios in the customer service such as the tendency of the complaint were refined.Based on the data of power service orders,the key index of modeling was selected.Through entropy weight method,principal component analysis and decision tree and other data mining algorithms,potential complaint propensity customers and planned blackout sensitive customers in order to carry out targeted service resource scheduling were identified,fully do a good job of response measures,effectively reduce complaint pressure and improve service accuracy.

Key words: complaint work order, data mining, entropy weight method, decision tree

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