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Inductive Fuzzy Classification in Marketing Analytics

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Inductive Fuzzy Classification in Marketing Analytics Synopsis

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.

About This Edition

ISBN: 9783319381602
Publication date:
Author: Michael Kaufmann
Publisher: Springer an imprint of Springer International Publishing
Format: Paperback
Pagination: 125 pages
Series: Fuzzy Management Methods
Genres: Business mathematics and systems
Expert systems / knowledge-based systems
E-commerce: business aspects
Computer applications in the social and behavioural sciences
Mathematical theory of computation
Sales and marketing
Data mining
Applied computing
Business applications