Computationally Efficient Methods for MDL-Optimal Density Estimation and Data Clustering

The Minimum Description Length (MDL) principle is a general, well-founded theoretical formalization of statistical modeling. The most important notion of MDL is the stochastic complexity, which can be interpreted as the shortest description length of a given sample of data relative to a model class. The exact definition of the stochastic complexity has gone through several evolutionary steps. The latest instantation is based on the so-called Normalized Maximum Likelihood (NML) distribution which has been shown to possess several important theoretical properties. However, the applications of this modern version of the MDL have been quite rare because of computational complexity problems, i.e., for discrete data, the definition of NML involves an exponential sum, and in the case of continuous data, a multi-dimensional integral usually infeasible to evaluate or even approximate accurately. In this doctoral dissertation, we present mathematical techniques for computing NML efficiently for some model families involving discrete data. We also show how these techniques can be used to apply MDL in two practical applications: histogram density estimation and clustering of multi-dimensional data.

Profitable Customer Management: A Study in Retail Banking

The increasing focus of relationship marketing and customer relationship management (CRM) studies on issues of customer profitability has led to the emergence of an area of research on profitable customer management. Nevertheless, there is a notable lack of empirical research examining the current practices of firms specifically with regard to the profitable management of customer relationships according to the approaches suggested in theory. This thesis fills this research gap by exploring profitable customer management in the retail banking sector. Several topics are covered, including marketing metrics and accountability; challenges in the implementation of profitable customer management approaches in practice; analytic versus heuristic (‘rule of thumb’) decision making; and the modification of costly customer behavior in order to increase customer profitability, customer lifetime value (CLV), and customer equity, i.e. the financial value of the customer base. The thesis critically reviews the concept of customer equity and proposes a Customer Equity Scorecard, providing a starting point for a constructive dialog between marketing and finance concerning the development of appropriate metrics to measure marketing outcomes. Since customer management and measurement issues go hand in hand, profitable customer management is contingent on both marketing management skills and financial measurement skills. A clear gap between marketing theory and practice regarding profitable customer management is also identified. The findings show that key customer management aspects that have been proposed within the literature on profitable customer management for many years, are not being actively applied by the banks included in the research. Instead, several areas of customer management decision making are found to be influenced by heuristics. This dilemma for marketing accountability is addressed by emphasizing that CLV and customer equity, which are aggregate metrics, only provide certain indications regarding the relative value of customers and the approximate value of the customer base (or groups of customers), respectively. The value created by marketing manifests itself in the effect of marketing actions on customer perceptions, behavior, and ultimately the components of CLV, namely revenues, costs, risk, and retention, as well as additional components of customer equity, such as customer acquisition. The thesis also points out that although costs are a crucial component of CLV, they have largely been neglected in prior CRM research. Cost-cutting has often been viewed negatively in customer-focused marketing literature on service quality and customer profitability, but the case studies in this thesis demonstrate that reduced costs do not necessarily have to lead to lower service quality, customer retention, and customer-related revenues. Consequently, this thesis provides an expanded foundation upon which marketers can stake their claim for accountability. By focusing on the range of drivers and all of the components of CLV and customer equity, marketing has the potential to provide specific evidence concerning how various activities have affected the drivers and components of CLV within different groups of customers, and the implications for customer equity on a customer base level.