Fuzzy Classification of Online Customers
This book introduces a fuzzy classification approach, which combines relational databases with fuzzy logic for more effective and powerful customer relationship management (CRM). It shows the benefits of a fuzzy classification in contrast to the tradition
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Nicolas Werro
Fuzzy Classification of Online Customers
Fuzzy Management Methods Series editors Andreas Meier, Fribourg, Switzerland Witold Pedrycz, Edmonton, Canada Edy Portmann, Bern, Switzerland
More information about this series at http://www.springer.com/series/11223
Nicolas Werro
Fuzzy Classification of Online Customers
123
Nicolas Werro Villars-sur-Glane Switzerland
ISSN 2196-4130 Fuzzy Management Methods ISBN 978-3-319-15969-0 DOI 10.1007/978-3-319-15970-6
ISSN 2196-4149 (electronic) ISBN 978-3-319-15970-6
(eBook)
Library of Congress Control Number: 2015932422 Springer Cham Heidelberg New York Dordrecht London © Springer International Publishing Switzerland 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer International Publishing AG Switzerland is part of Springer Science+Business Media (www.springer.com)
To my love Delia and my parents Monique and René for their patience and support during these last years.
Foreword
Over the past decade, with the incredible rise of the Internet in general and e-commerce in particular, new and interesting avenues of research have opened in the broad field of Customer Relationship Management. The problem goes beyond the establishment of a sophisticated relational database coupled with a user-friendly web interface for managing the customers, their orders and the company stocks. Indeed, thanks to the large amount of personal data collected on customers, particularly those using the web for their purchases, it becomes possible to highly customize their management in order to retain them. To achieve this objective, it is necessary to segment (classify) customers based on various criteria in order to offer them benefits such as discounts, gift certificates or other promotions. In this context, traditional (sharp 0, 1) classification techniques lack of nuance and often can only register the damage when a loyal customer goes “brutally” in the lost ones category. To overcome this problem,
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