Details

Inductive Fuzzy Classification in Marketing Analytics


Inductive Fuzzy Classification in Marketing Analytics


Fuzzy Management Methods

von: Michael Kaufmann

96,29 €

Verlag: Springer
Format: PDF
Veröffentl.: 04.06.2014
ISBN/EAN: 9783319058610
Sprache: englisch

Dieses eBook enthält ein Wasserzeichen.

Beschreibungen

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.
A Gradual Concept of Truth.- Fuzziness and Induction.- Analytics and Marketing.- Prototyping and Evaluation.- Precisiating Fuzziness by Induction.​
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.
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.
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

Diese Produkte könnten Sie auch interessieren:

Supply Chain Management: Models, Applications, and Research Directions
Supply Chain Management: Models, Applications, and Research Directions
von: Joseph Geunes, Panos M. Pardalos, H. Edwin Romeijn
PDF ebook
149,79 €