Earticle

초록

영어

Customer churn warning prediction is one of the most important problems in customer relationship management (CRM). Its aim is to monitor customer loss conditions, explore for internal loss rules of mass transaction data, give early warning about customer loss inclination and retain valuable customers to maximize the profit of a company. Under the circumstance of rapidly emerging customer churn warning research under the big data background, we attempt to explore for mass security customer data and to focus on analysis and design on customer churn warning model based on data mining technologies and the theory of customer churn management process.

목차

Abstract
 1. Introduction
 2. Background Knowledge
  2.1. C5.0 Algorithm
  2.2. K-Means Algorithm
 3. Data Pre-Processing
  3.1. Data Description
  3.2. Data Cleaning
  3.3. Data Combination
  3.4. Variable Management
  3.5. Sample Management
  3.6. Importance of Variables
 4. Model of Customer Churn Warning
  4.1. Set the Model Parameter
  4.2. Data Flow
  4.3. Results
 5. Segmentation Model of Customer Churn
  5.1. Data Flow of Segmentation Model
  5.2. Results of Customer Churn Segmentation
 6. Model Evaluation
  6.1. Model of Customer Churn Warning
  6.2. Model of Customer Churn Segmentation
 7. Conclusions
 References

키워드

저자

• Yihua Zhang [ School of Business Administration, Jimei University, Xiamen 361021, China ]
• Yuan Wang [ School of Business Administration, Jimei University, Xiamen 361021, China ]
• Chunfang He [ School of Business Administration, Jimei University, Xiamen 361021, China ]
• TingTing Yang [ School of Business Administration, Jimei University, Xiamen 361021, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605