Allocation of Marketing Resources to Optimize Customer Equity

To stay competitive, companies spend billions of
dollars each year on building long-term relationships
with their customers. Marketing managers are
therefore constantly challenged with the problem of
how to allocate a limited marketing budget across
customers and competing marketing initiatives. This
work addresses the problem of how to efficiently
allocate marketing resources to maximize the
financial value generated by marketing investments.
Advanced stochastic models addressing the following
three issues are proposed: a) maximization of
customer lifetime value by linking marketing actions
to the financial value generated during the
relationship with the company, b) estimation of the
financial profile of customers and, c) use of risk
management techniques to select the optimal customer
portfolio. This research has been done while the
author was working at the Math & Computer Science
Department of the IBM Zurich Research Laboratory in
Rüschlikon, Switzerland.

Autorentext

Giuliano Tirenni holds a doctoral degree from the University of St.Gallen, master's degrees from Politecnico di Milano and ENSTA,and a MBA from the Collège des Ingénieurs. He received an IBMResearch Division Award and the INFORMS Practice Price 2005.

Klappentext

To stay competitive, companies spend billions of dollars each year on building long-term relationships with their customers. Marketing managers are therefore constantly challenged with the problem of how to allocate a limited marketing budget across customers and competing marketing initiatives. This work addresses the problem of how to efficiently allocate marketing resources to maximize the financial value generated by marketing investments. Advanced stochastic models addressing the following three issues are proposed: a) maximization of customer lifetime value by linking marketing actions to the financial value generated during the relationship with the company, b) estimation of the financial profile of customers and, c) use of risk management techniques to select the optimal customer portfolio. This research has been done while the author was working at the Math & Computer Science Department of the IBM Zurich Research Laboratory in Rüschlikon, Switzerland.