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Developing churn models using data m...
~
Mrsic, Leo, (1973-)
Developing churn models using data mining techniques and social network analysis /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Developing churn models using data mining techniques and social network analysis // by Goran Klepac, Robert Kopal and Leo Mrsic.
Author:
Klepac, Goran,
other author:
Kopal, Robert,
Description:
PDFs (308 pages).
Notes:
"Research essentials collection".
Subject:
Customer loyalty. -
Online resource:
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-4666-6288-9
ISBN:
9781466662896 (ebook)
Developing churn models using data mining techniques and social network analysis /
Klepac, Goran,1972-
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.
ISBN: 9781466662896 (ebook)
Standard No.: 10.4018/978-1-4666-6288-9doi
LCCN: 2014017276Subjects--Topical Terms:
793216
Customer loyalty.
Subjects--Index Terms:
Attribute relevance analysis
LC Class. No.: HF5415.525 / .K56 2014e
Dewey Class. No.: 658.8/342
Developing churn models using data mining techniques and social network analysis /
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print
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print & perpetual access
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Developing churn models using data mining techniques and social network analysis /
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by Goran Klepac, Robert Kopal and Leo Mrsic.
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Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pa., 17033, USA) :
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IGI Global,
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[2014]
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PDFs (308 pages).
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text
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electronic
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online resource
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"Research essentials collection".
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Includes bibliographical references.
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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.
506
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Restricted to subscribers or individual electronic text purchasers.
520
3
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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.
530
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Also available in print.
538
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Mode of access: World Wide Web.
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Customer loyalty.
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Consumer satisfaction.
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Data mining.
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Attribute relevance analysis
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Behavioral variables
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Churn prediction
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Data sampling
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Predictive analytics
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Risk management
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Web analytics
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Kopal, Robert,
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Mrsic, Leo,
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1973-
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IGI Global,
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Chapter PDFs via platform:
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-4666-6288-9
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