Posted on Monday, March 12, 2012 by
Advanced Database Marketing brings the latest developments in the domains of customer analytics and database marketing organized around two dimensions: applications and methods. Special attention is given to the way the Internet has changed the nature of the game and the numerous ways in which new types of data can lead to exciting new ways of managing and improving customer relationships. An impressive list of contributors including many of the thought-leaders in database marketing from across the world bring together chapters that combine the best academic research and business applications. The result is a definitive guide and reference for marketing and brand analysts, masters students, teachers and researchers in marketing analytics.
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Koen De Bock is a researcher and lecturer in marketing with specialties in database marketing, Internet marketing and web analytics. He obtained master degrees at the University of Antwerp (M.Sc. in Applied Economics) and Ghent University (M.Sc in Marketing Analysis) in Belgium, and obtained his Ph.D. entitled Enhancing database marketing with ensemble classification from Ghent University, Belgium, in September 2010. He is currently assistant professor of marketing at IÉSEG School of Management (with campuses in Lille and Paris, France). IÉSEG is a well-ranked and EQUIS-accredited grande école de commerce, offering programs recognized by the French government.
At IÉSEG, Koen De Bock is currently in charge of the courses Digital Marketing, Web Advertising, Web Analytics and Operational Marketing in the Master in Management program. In November 2011, he was a visiting professor at the University of Stellenbosch Business School (USB), Cape Town, South Africa where he taught Internet Marketing to MBA students.
He has published in international peer-reviewed journals (see publications section) and collaborated on several business projects.
- Coussement, K., Van Den Bossche, F. and De Bock, K.W., 2012, Data Accuracy’s Impact on Segmentation Performance: Comparing RFM, Logistic Regression and Decision Trees, Forthcoming in Journal of Business Research.
- Coussement, K. and De Bock, K.W., 2013, Customer Churn Prediction in the Online Gambling Industry: The Beneficial Effect of Ensemble Learning, Forthcoming in Journal of Business Research.
- De Bock, K.W. and Van den Poel, D., 2012, Reconciling Performance and Interpretability in Customer Churn Prediction Modeling Using Ensemble Learning Based on Generalized Additive Models, Expert Systems With Applications, 39(8), pp. 6816–6826 (download).