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.

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

Zusammenfassung
The ever-increasing amount of individual-level customer data generated by reward/l- alty programs opens new perspectives for customer relationship management (CRM). Without any question, the potential bene?ts of these data and analytical models for - plaining, extending, and predicting customer behavior is very high. However, recent analyses have shown that a high fraction of CRM projects result in negative return on investment. One of the main reasons for this dilemma is that these data require advanced analytical processing to fully leverage their potential ("analytical CRM"). Yet, research and practice is still in its early stages with respect to analytical CRM. In particular, the so-called "non-contractual settings" remain widely unexplored. Lit- ature refers to a "non-contractual setting" when customer relationships are not governed by a contract that predetermines the monetary value and/or length of the relationship. Examples include hotels, airlines, and most retailers. The most obvious consequence for CRM is that the end of a customer relationship is not directly observable, i.e., a c- tomer can switch providers without notifying the focal provider. Consequently, analysis of customer retention, and future buying behavior is even more problematic than in contractual settings.

Inhalt
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.