Analyzing credit card usage behaviours with data mining algorithms and pearson specific campaign offer

In this thesis, 4497 customers received from a private bank were aimed to be directed to the most suitable campaign by examining their credit card movements within 3 months. After the data was pre-processed, two models were implemented with a recommendation system written in the Python programming language and a recommendation system was written according to the successful model. This thesis aims to be an up-to-date and original study as it addresses the use of referral systems in all areas of our lives in the campaign management. Also, this study will contribute to the related literature due to the small number of studies conducted in this field in our country.