Chiaki Doi, M. Katagiri, T. Araki, Daizo Ikeda, H. Shigeno
{"title":"Is he Becoming an Excellent Customer for us? A Customer Level Prediction Method for a Customer Relationship Management System","authors":"Chiaki Doi, M. Katagiri, T. Araki, Daizo Ikeda, H. Shigeno","doi":"10.1109/AINA.2018.00056","DOIUrl":null,"url":null,"abstract":"This paper proposes a method that predicts customer value by focusing on purchasing behavior. The method generates a relevance model for purchase days and amount in each period between customer value and purchasing histories beforehand based on a consumer panel survey. The authors adopt the random forest method to generate the prediction model. The proposed method facilitates the provisioning of smart customer management to each customer according to level such as suggesting products or services.","PeriodicalId":239730,"journal":{"name":"2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AINA.2018.00056","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper proposes a method that predicts customer value by focusing on purchasing behavior. The method generates a relevance model for purchase days and amount in each period between customer value and purchasing histories beforehand based on a consumer panel survey. The authors adopt the random forest method to generate the prediction model. The proposed method facilitates the provisioning of smart customer management to each customer according to level such as suggesting products or services.