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Inductive Fuzzy Classification in Marketing Analytics: Fuzzy Management Methods

Autor Michael Kaufmann
en Limba Engleză Hardback – 25 iun 2014
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.
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Specificații

ISBN-13: 9783319058603
ISBN-10: 3319058606
Pagini: 148
Ilustrații: XX, 125 p. 35 illus.
Dimensiuni: 155 x 235 x 14 mm
Greutate: 0.39 kg
Ediția:2014
Editura: Springer International Publishing
Colecția Springer
Seria Fuzzy Management Methods

Locul publicării:Cham, Switzerland

Public țintă

Research

Cuprins

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

Notă biografică

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.

Textul de pe ultima copertă

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.

Caracteristici

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