摘要
运营商每天有大量的外呼任务,采用传统顺序拨打的方式存在外呼触达效率低和容易对客户造成打扰两个问题,文章基于大数据平台的通信价值、账务、通信行为、业务偏好等B域用户数据及O域网络行为数据进行综合分析,结合熵值法、K-means方法,从"人"的视角进行建模分析,提出一套能够提升外呼一次触达率、有效降低对客户打扰的方法。通过实践验证了该方法的有效性和可行性,在外呼类应用场景上,有一定的指导意义和参考价值。
The telecom operators face issues about low once call capture rate and user disruption when calling users. According to the analysis of the B domain user data and O domain network behavior data,such as communication value, accounting value, communication behavior and so on,an effective method to enhance the once call capture rate and reduce user disruption based on entropy method and K-means is proposed. Practice shows that this method is effective and feasible. Also, it provides an important reference and guidance for similar application scenarios on call capture.
出处
《信息通信技术》
2017年第4期53-59,共7页
Information and communications Technologies
作者简介
硕士,从事大数据平台建设、数据挖掘工作.
硕士,中级工程师,主要从事基于运营商的数据域系统的建设以及大数据价值在企业管理中的应用研究工作.
