Data Mining For Database Marketing AtGaranti Bank

Abstract

This paper summarises the data mining applications implemented on Garanti Bank's customer database. There has been an upsurge of interest in using data mining applications for converting historical data into actionable business information and this has become well justified in Garanti's example. Garanti bank carried out two major applications that will be presented in this paper: Customer segmentation and database scoring for marketing purposes. A wellmaintained central datawarehouse made it possible to prepare the data in the most efficient manner for the applications. Customer segmentation was carried out with the demographic algorithm, while database scoring was implemented with various classification and predictive modelling techniques: Decision trees, neural networks and radial-basis-functions were used to score the database. A business unit at the bank (Customer Relationship Management) exploited these scores for marketing purposes: Several pilot campaigns were launched and the response rates obtained in these campaigns were highly satisfactory. Encouraged by the promise of the initial data mining applications, the bank has decided to pursue a more aggressive marketing strategy supported with the results of the analysis.