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Developing churn models using data m...
~
Mrsic, Leo (1973-)
Developing churn models using data mining techniques and social network analysis
紀錄類型:
書目-語言資料,印刷品 : 單行本
作者:
KlepacGoran, 1972-
其他作者:
MrsicLeo, 1973-
其他作者:
KopalRobert, 1964-
其他團體作者:
IGI Global
面頁冊數:
PDFs (308 pages).
標題:
Data mining. -
標題:
Consumer satisfaction. -
標題:
Customer loyalty. -
標題:
Attribute relevance analysis
標題:
Behavioral variables
標題:
Churn prediction
標題:
Data sampling
標題:
Predictive analytics
標題:
Risk management
標題:
Web analytics
電子資源:
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-4666-6288-9
附註:
Content Type: text
摘要註:
"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.
ISBN:
9781466662896
內容註:
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.
Developing churn models using data mining techniques and social network analysis
Klepac, Goran
Developing churn models using data mining techniques and social network analysis
/ by Goran Klepac, Robert Kopal and Leo Mrsic. - PDFs (308 pages)..
Churn problem in everyday business.
Content Type: textMedia type: electronicCarrier type: online resource"Research essentials collection".Restricted to subscribers or individual electronic text purchasers..
Includes bibliographical references..
ISBN 9781466662896ISBN 9781466662889ISBN 9781466662919
Data mining.Consumer satisfaction.Customer loyalty.
Attribute relevance analysisBehavioral variablesChurn predictionData samplingPredictive analyticsRisk managementWeb analytics
Mrsic, Leo
Developing churn models using data mining techniques and social network analysis
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Churn problem in everyday business
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Setting (realistic) business aims
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Data mining techniques for churn mitigation/detection: intrinsic attributes approach
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Social network analysis (SNA) for churn mitigation/detection: introduction and metrics
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Data preparation and churn detection
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Churn analysis using selected structured analytic techniques
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Attribute relevance analysis
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From churn models to churn solution
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Measuring predictive power
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Churn model development, monitoring, and adjustment
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Churn case studies.
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"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.
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Consumer satisfaction.
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Customer loyalty.
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Attribute relevance analysis
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-4666-6288-9
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