电子设计工程
電子設計工程
전자설계공정
ELECTRONIC DESIGN ENGINEERING
2015年
12期
25-27
,共3页
K-means%客户细分%航空公司%CRM%客户价值
K-means%客戶細分%航空公司%CRM%客戶價值
K-means%객호세분%항공공사%CRM%객호개치
K-means%customer segmentation%airline%CRM%customer value
针对客户关系管理中客户价值这一问题，通过对航空公司现有数据仓库中客户信息的分析，采用数据挖掘技术中的K-means聚类算法建立民航客户细分模型，并通过实验将民航客户细分为3类，提出了对这3类航空客户的相关营销策略。实验结果表明该方法能突出客户之间的行为特征差异，更加准确地划分客户类型，进而使得客户价值约提高30%。
針對客戶關繫管理中客戶價值這一問題，通過對航空公司現有數據倉庫中客戶信息的分析，採用數據挖掘技術中的K-means聚類算法建立民航客戶細分模型，併通過實驗將民航客戶細分為3類，提齣瞭對這3類航空客戶的相關營銷策略。實驗結果錶明該方法能突齣客戶之間的行為特徵差異，更加準確地劃分客戶類型，進而使得客戶價值約提高30%。
침대객호관계관리중객호개치저일문제，통과대항공공사현유수거창고중객호신식적분석，채용수거알굴기술중적K-means취류산법건립민항객호세분모형，병통과실험장민항객호세분위3류，제출료대저3류항공객호적상관영소책략。실험결과표명해방법능돌출객호지간적행위특정차이，경가준학지화분객호류형，진이사득객호개치약제고30%。
This paper aims at studying the problem of customer value in customer relationship management according to current airline data warehouse. The K-means clustering algorithm is used to build an aviation customer segmentation model which makes the customers classified into three types, and the relative marketing strategies were put forward accordingly. Experimental results show that the method can highlight the differences between samples, calculating the customer value more properly, and the customer value is improved by nearly 30%.
