计算机科学
付款
客户情报
客户关系管理
分割
人工智能
市场细分
机器学习
数据挖掘
客户保留
数据库
营销
万维网
业务
服务质量
服务(商务)
标识
DOI:10.1109/idap.2018.8620892
摘要
Customer segmentation is important both in customer relationship management literature and softwares. The most common way to separate one customer from another is to promote a group of customers as premium and the remaining customers as standard. In this work, a company's manually segmented customer data is analyzed. The study aims to solve the company's data segmentation problem by using its real data regarding its customers' payments. Since, machine learning methods are useful to solve problems about data management, the solution is searched within machine learning methods. Different classification methods which are used to discriminate between premium and standard customers belonging to a company's database are compared. Two dimensional payment information of customers are used as input variables (features) and the methods are compared according to their separation performances.
科研通智能强力驱动
Strongly Powered by AbleSci AI