Developing churn models using data mining techniques and social network analysis /
by Goran Klepac, Robert Kopal and Leo Mrsic.
- PDFs (308 pages).
"Research essentials collection".
Includes bibliographical references.
Churn problem in everyday business -- Setting (realistic) business aims -- Data mining techniques for churn mitigation/detection: intrinsic attributes approach -- Social network analysis (SNA) for churn mitigation/detection: introduction and metrics -- Data preparation and churn detection -- Churn analysis using selected structured analytic techniques -- Attribute relevance analysis -- From churn models to churn solution -- Measuring predictive power -- Churn model development, monitoring, and adjustment -- Churn case studies.
Restricted to subscribers or individual electronic text purchasers.
"This book provides an in-depth analysis of attrition modeling relevant to business planning and management, offering insightful and detailed explanation of best practices, tools, and theory surrounding churn prediction and the integration of analytic tools"--Provided by publisher.
Mode of access: World Wide Web.
9781466662896
10.4018/978-1-4666-6288-9 doi
Customer loyalty. Consumer satisfaction. Data mining.
Attribute relevance analysis Behavioral variables Churn prediction Data sampling Predictive analytics Risk management Web analytics