Relational Learning for Customer Relationship Management

Customer modeling is a critical component of customer relationship management (CRM). Successful customer modeling requires a holistic view and the consolidation of all customer information available to the business, which is typically stored in a relational database. With this understanding, customer modeling in CRM can be viewed as a special case of the relational learning problem, a recent extension of the traditional machine learning problem that aims to model the relational interdependencies within a database containing multiple interlinked tables. We establish in this paper the connection between relational learning and CRM analysis through detailed discussion of the tasks of customer classification and product recommendation, supported by examples of empirical results on seven real-world CRM data sets. We demonstrate that relational learning approaches can be valuable tools for a variety of CRM modeling tasks and discuss limitations and CRM specific extensions of these general relational learning approaches.