Analytical CRM

Developing and Maintaining Profitable Customer Relationships in Non-Contractual Settings
2009
ISBN: 978-3-8349-1278-7
Verlag: Gabler Verlag

Buch, Englisch, 263 Seiten, Paperback, Format (B × H): 148 mm x 210 mm, Gewicht: 386 g

Reihe: Applied Marketing Science / Angewandte Marketingforschung

The ever-increasing amount of individual-level customer data generated by loyalty programs opens new perspectives for customer relationship management (CRM). Yet, recent analyses have shown that a huge fraction of CRM projects fail to deliver the good at the bottom line. One of the main reasons for this dilemma is that these data require advanced analytical processing to fully leverage their potential (“analytical CRM”). Research and practice are still in its early stages with respect to analytical CRM.


Markus Wübben focuses on analytical CRM for developing and maintaining buyer-seller relationships in non-contractual settings, i.e. settings, in which buyer-seller relationships are not governed by a contract that predetermines the monetary value and/or length of the relationship. This is a common scenario for many businesses such as retailers, hotels, and airlines. Using empirical analyses on the basis of sound theoretical foundations, the author shows how customer relationships can be broadened, meaning how customers’ cross-buying behavior can be stimulated and how customers’ relationship length and depth, i.e. customers’ activity and purchase-levels, can be predicted. Finally, he derives implications for research and practice.

Zielgruppe

Research

Autoren/Hrsg.

Wübben, Markus

Weitere Mitwirkende

von Wangenheim, Prof. Dr. Florian

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Kundenbeziehungsmanagement, Kundenpflege

Inhaltsverzeichnis

Fundamentals of Customer Relationship Management.- The Drivers of Cross-Buying Behavior in Non-Contractual Settings.- Stochastic Models for Predicting Customer Activity and Future Best Customers in Non-Contractual Settings.- Support Vector Machines for Predicting Customer Activity and Future Best Customers in Non-Contractual Settings.- Reflections on Developing and Maintaining Customer Relationships in Non-Contractual Settings.- Customer Relationship Management in the 21st Century.

Über Autor(innen)

Dr. Markus Wübben ist wissenschaftlicher Mitarbeiter bei Prof. Dr. Florian von Wangenheim am Lehrstuhl für Dienstleistungs- und Technologiemarketing der Technischen Universität München.