Fuzzy Methods for Customer Relationship Management and Marketing: Applications and Classifications, 1st Edition

  • Andreas Meier
  • Published By:
  • ISBN-10: 1466600969
  • ISBN-13: 9781466600966
  • DDC: 658.8
  • Grade Level Range: College Freshman - College Senior
  • 388 Pages | eBook
  • Original Copyright 2012 | Published/Released November 2012
  • This publication's content originally published in print form: 2012

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Information overload has made it increasingly difficult to analyze large amounts of data and generate appropriate management decisions. Furthermore, data is often imprecise and will include both quantitative and qualitative elements. For these reasons, it is important to extend traditional decision making processes by adding intuitive reasoning, human subjectivity, and imprecision.FUZZY METHODS FOR CUSTOMER RELATIONSHIP MANAGEMENT AND MARKETING: APPLICATIONS AND CLASSIFICATIONS explores the possibilities and advantages created by fuzzy methods through the presentation of thorough research and case studies. This book covers a variety of possible fuzzy logic approaches to customer relationship management and marketing, making it a valuable resource for not only students and researchers but also executives, managers, marketing experts, and project leaders who are interested in applying fuzzy classification to managerial decisions.

Table of Contents

Front Cover.
Title Page.
Copyright Page.
List of Reviewers.
Table of Contents.
Detailed Table of Contents.
1: Applying Fuzzy Logic and Fuzzy Methods to Marketing.
2: Fuzzy Modeling.
3: Fuzzy Soft Social Network Modeling and Marketing.
4: Fuzzy Dynamic Groups: Measures and Implications for Television Audiences.
5: Using Case Data to Ensure ‘Real World’ Input Validation Within Fuzzy Set Theory Models.
6: Customer Relationship Management and Web Analytics.
7: Fuzzy Clustering of Web User Profiles for Analyzing Their Behavior and Interests.
8: Using a Fuzzy-Based Cluster Algorithm for Recommending Candidates in E-Elections.
9: Fuzzy Online Reputation Analysis Framework.
10: Fuzzy Target Groups in Analytic Customer Relationship Management.
11: Web Analytics with Fuzziness.
12: Performance Analysis.
13: Fuzzy Data Warehouse for Performance Analysis.
14: A Fuzzy Logic Approach for the Assessment of Online Customers.
15: A Hybrid Fuzzy Multiple Objective Approach to Lotsizing, Pricing, and Marketing Planning Model.
16: Market Analysis.
17: A Fuzzy Segmentation Approach to Guide Marketing Decisions.
18: Causal Recipes Sufficient for Identifying Market Gurus versus Mavens.
Compilation of References.
About the Contributors.