基于LRFMC模型和K-means算法的航空公司客户价值分析与客户流失预测

Jin Ran, Xingqi Cheng
{"title":"基于LRFMC模型和K-means算法的航空公司客户价值分析与客户流失预测","authors":"Jin Ran, Xingqi Cheng","doi":"10.1109/ICCSMT54525.2021.00044","DOIUrl":null,"url":null,"abstract":"Due to the increasingly significant competition inside and outside the aviation industry, airlines choose to conduct personalized sales to passengers for the purpose of increasing economic efficiency. In this paper, we select airlines customer information data during the period from 2012 to 2014, segment the value of air customers based on the LRFMC model and K-means algorithm. Then establish an airline customer churn prediction model, define churn customers, select characteristics, train SVM, Adaboost, RandomForest and Xgboost models, and then identify churn customers. Finally, the four models are compared and the optimal model is obtained. This article aims to classify airline customers so that airlines can adopt different marketing strategies for customers of different values to maximize profits. Improve the problem of customer churn, enable airlines to maintain their own markets, and bring high profits to airlines.","PeriodicalId":304337,"journal":{"name":"2021 2nd International Conference on Computer Science and Management Technology (ICCSMT)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Airline Customer Value Analysis and Customer Churn Prediction Based on LRFMC Model and K-means Algorithm\",\"authors\":\"Jin Ran, Xingqi Cheng\",\"doi\":\"10.1109/ICCSMT54525.2021.00044\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to the increasingly significant competition inside and outside the aviation industry, airlines choose to conduct personalized sales to passengers for the purpose of increasing economic efficiency. In this paper, we select airlines customer information data during the period from 2012 to 2014, segment the value of air customers based on the LRFMC model and K-means algorithm. Then establish an airline customer churn prediction model, define churn customers, select characteristics, train SVM, Adaboost, RandomForest and Xgboost models, and then identify churn customers. Finally, the four models are compared and the optimal model is obtained. This article aims to classify airline customers so that airlines can adopt different marketing strategies for customers of different values to maximize profits. Improve the problem of customer churn, enable airlines to maintain their own markets, and bring high profits to airlines.\",\"PeriodicalId\":304337,\"journal\":{\"name\":\"2021 2nd International Conference on Computer Science and Management Technology (ICCSMT)\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 2nd International Conference on Computer Science and Management Technology (ICCSMT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSMT54525.2021.00044\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 2nd International Conference on Computer Science and Management Technology (ICCSMT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSMT54525.2021.00044","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

由于航空业内外的竞争日益激烈,航空公司为了提高经济效益,选择对乘客进行个性化销售。本文选取2012 - 2014年航空公司客户信息数据,基于LRFMC模型和K-means算法对航空公司客户价值进行分割。然后建立航空公司客户流失预测模型,定义流失客户,选择特征,训练SVM、Adaboost、RandomForest和Xgboost模型,识别流失客户。最后,对四种模型进行了比较,得出了最优模型。本文旨在对航空公司的客户进行分类,以便航空公司针对不同价值的客户采取不同的营销策略,实现利润最大化。改善客户流失问题,使航空公司能够维持自己的市场,为航空公司带来高额利润。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Airline Customer Value Analysis and Customer Churn Prediction Based on LRFMC Model and K-means Algorithm
Due to the increasingly significant competition inside and outside the aviation industry, airlines choose to conduct personalized sales to passengers for the purpose of increasing economic efficiency. In this paper, we select airlines customer information data during the period from 2012 to 2014, segment the value of air customers based on the LRFMC model and K-means algorithm. Then establish an airline customer churn prediction model, define churn customers, select characteristics, train SVM, Adaboost, RandomForest and Xgboost models, and then identify churn customers. Finally, the four models are compared and the optimal model is obtained. This article aims to classify airline customers so that airlines can adopt different marketing strategies for customers of different values to maximize profits. Improve the problem of customer churn, enable airlines to maintain their own markets, and bring high profits to airlines.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
相关文献
二甲双胍通过HDAC6和FoxO3a转录调控肌肉生长抑制素诱导肌肉萎缩
IF 8.9 1区 医学Journal of Cachexia, Sarcopenia and MusclePub Date : 2021-11-02 DOI: 10.1002/jcsm.12833
Min Ju Kang, Ji Wook Moon, Jung Ok Lee, Ji Hae Kim, Eun Jeong Jung, Su Jin Kim, Joo Yeon Oh, Sang Woo Wu, Pu Reum Lee, Sun Hwa Park, Hyeon Soo Kim
具有疾病敏感单倍型的非亲属供体脐带血移植后的1型糖尿病
IF 3.2 3区 医学Journal of Diabetes InvestigationPub Date : 2022-11-02 DOI: 10.1111/jdi.13939
Kensuke Matsumoto, Taisuke Matsuyama, Ritsu Sumiyoshi, Matsuo Takuji, Tadashi Yamamoto, Ryosuke Shirasaki, Haruko Tashiro
封面:蛋白质组学分析确定IRSp53和fastin是PRV输出和直接细胞-细胞传播的关键
IF 3.4 4区 生物学ProteomicsPub Date : 2019-12-02 DOI: 10.1002/pmic.201970201
Fei-Long Yu, Huan Miao, Jinjin Xia, Fan Jia, Huadong Wang, Fuqiang Xu, Lin Guo
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Research on the evaluation of innovation ability of high-tech industry from the perspective of integrated development of Yangtze River Delta Based on Entropy Weight-TOPSIS Method Foreign matter detection of coal conveying belt based on machine vision Research on Performance Evaluation of Fiscal Expenditure Efficiency in Old Industrial Cities Detection of Cassava Leaf Diseases Using Self-supervised Learning Research on the Innovation of Online Recruitment mode of small and medium-sized enterprises - Statistical analysis based on recruitment information
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1