CRM Sales Prediction Using Continuous Time-Evolving Classification

被引:0
|
作者
Ali, Mohamoud [1 ]
Lee, Yugyung [1 ]
机构
[1] Univ Missouri, Sch Comp & Engn, Kansas City, MO 64110 USA
来源
THIRTY-SECOND AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTIETH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / EIGHTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE | 2018年
关键词
MANAGEMENT;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Customer Relationship Management (CRM) systems play an important role in helping companies identify and keep sales and service prospects. CRM service providers offer a range of tools and techniques that will help find, sell to and keep customers. To be effective, CRM users usually require extensive training. Predictive CRM using machine learning expands the capabilities of traditional CRM through the provision of predictive insights for CRM users by combining internal and external data. In this paper, we will explore a novel idea of computationally learning salesmanship, its patterns and success factors to drive industry intuitions for a more predictable road to a vehicle sale. The newly discovered patterns and insights are used to act as a virtual guide or trainer for the general CRM user population.
引用
收藏
页码:7727 / 7734
页数:8
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