A Methodology for Improving Complex Sales Success in CRM Systems

被引:0
作者
Rotovei, Doru [1 ]
Negru, Viorel [1 ]
机构
[1] West Univ Timisoara, Dept Comp Sci, Timisoara, Romania
来源
2017 IEEE INTERNATIONAL CONFERENCE ON INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS (INISTA) | 2017年
基金
欧盟地平线“2020”;
关键词
Customer Relationship Management; Classification; Multi-Adaptive Regression Splines; Expert Systems; Random Forests; Decision Trees; !text type='Java']Java[!/text] Expert System Shell; ADAPTIVE REGRESSION SPLINES; MODEL; MACHINE; PATTERN;
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
In this paper we propose a methodology for extracting complex sales expert rules by analyzing the data from the past lost/won deals stored in Customer Relationship Management Systems. We first used Multi-Adaptive Regression Splines model to identify the features importance, then we created a classification tree of lost/won sales using Random Forest and lastly we used the tree for extraction of the expert rules that gives insights into the rules of successful complex sales. The proposed methodology was successfully validated using complex sales data from a CRM application and the results are presented and discussed in this paper.
引用
收藏
页码:322 / 327
页数:6
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