Skip to main content
SpringerLink
Log in
Book cover

Inductive Fuzzy Classification in Marketing Analytics

  • Book
  • © 2014

Overview

Authors:
  1. Michael Kaufmann

    1. Engineering and Architecture, Lucerne University of Applied Sciences and Arts, Horw, Switzerland

    View author publications

    You can also search for this author in PubMed   Google Scholar

  • Provides a solid foundation of fuzzy classification and inductive logic and their application in marketing
  • Includes a case study of a real world application at a financial institute
  • Visualizes the abstract concepts with numerous illustrations
  • Includes supplementary material: sn.pub/extras

Part of the book series: Fuzzy Management Methods (FMM)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (5 chapters)

  1. Front Matter

    Pages i-xx
    Download chapter PDF

  2. Gradual Concept of Truth

    • Michael Kaufmann
    Pages 1-5

  3. Fuzziness and Induction

    • Michael Kaufmann
    Pages 7-34

  4. Analytics and Marketing

    • Michael Kaufmann
    Pages 35-58

  5. Prototyping and Evaluation

    • Michael Kaufmann
    Pages 59-75

  6. Precisiating Fuzziness by Induction

    • Michael Kaufmann
    Pages 77-82

  7. Back Matter

    Pages 83-125
    Download chapter PDF
Back to top

Keywords

About this book

To enhance marketing analytics, approximate and inductive reasoning can be applied to handle uncertainty in individual marketing models. This book demonstrates the use of fuzzy logic for classification and segmentation in marketing campaigns. Based on practical experience as a data analyst and on theoretical studies as a researcher, the author explains fuzzy classification, inductive logic and the concept of likelihood and introduces a blend of Bayesian and Fuzzy Set approaches, allowing reasonings on fuzzy sets that are derived by inductive logic. By application of this theory, the book guides the reader towards a gradual segmentation of customers which can enhance return on targeted marketing campaigns. The algorithms presented can be used for visualization, selection and prediction. The book shows how fuzzy logic can complement customer analytics by introducing fuzzy target groups. This book is for researchers, analytics professionals, data miners and students interested in fuzzy classification for marketing analytics.

Authors and Affiliations

  • Engineering and Architecture, Lucerne University of Applied Sciences and Arts, Horw, Switzerland

    Michael Kaufmann

About the author

Michael Kaufmann is a computer scientist with specialization in analytics and machine learning. Currently he is working as a business analyst at FIVE Informatik, where he consults executive boards of small and medium enterprises. He was data architect at Swiss Mobiliar and a Data Warehouse Analyst at Post Finance. He is a postdoctoral researcher publishing scientific articles on applications of fuzzy classification. He got his degree of Doctor Scientiarum Informaticarum (Dr. sc. Inf.) in 2012 and his Master's and Bachelor's degrees in Computer Science in 2004 and 2005, respectively, from the University of Fribourg, Switzerland.

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation