Predicting the Opinion of Customers at Rabobank using Data Mining Techniques

Abstract

Rabobank aims to have an excellent customer experience. This thesis explores various facets of modeling the opinion of each individual Rabobank customer. A qualitative research is done to find potential applications of predicting performance indicators (PIs) and key drivers. A data mining implementation is made in an attempt to predict PIs and key drivers using information about customers and information about recent contact moments. Customer Feedback Monitor is introduced as a new framework to combine knowledge about customers and to enable more personalized interactions. This newly introduced approach is evaluated amongst stakeholders and a plan is made for implementation.