Data Mining Framework for Direct Marketing: A Case Study of Bank Marketing
Direct marketing has generated an increasing interest among academics and practitioners over the past few years. This is due to competitive market environment, advancement in technology and changing behavior of customers which are difficult to predict. Despite of numerous studies that have provided important insights into the direct marketing, the understanding of this topic of growing interest and importance still remains deficient. Therefore, the objective of this paper is to provide a comprehensive framework to guide research efforts focusing on direct marketing strategy and aid practitioners in their quest to achieve direct marketing success using data mining methods. The framework builds on the literature from direct marketing concepts and data mining methods that provides a systematic approach to users who have little knowledge in data mining in order to carry out effective marketing campaigns. A case study on bank marketing campaigns was used for evaluating the feasibility of the framework.
Keywords: Data Mining, Direct marketing, Decision Tree, Data Mining Framework.
Download Full-Text
ABOUT THE AUTHORS
Lilian Sing\'oei
Lilian Sing’oei received her Bachelor’s degree (Information Technology) from Jomo Kenyatta University of Agriculture and Technology, Kenya in 2007 and is currently pursuing her master’s degree (Computer Application Technology) in Central South University, China. She has previously worked with James Finlay (K) Ltd, Kenya (Tea extract), Kenya Power & Lighting CO. Ltd, Kenya and Universal Work, Health & Safety consultancy Ltd in Kenya at the IT Department. She is certified SPSS Statistical analyst. She is currently pursuing Cisco Certified Network Associate (CCNA). She has two papers that are currently under review. Her research interests include Database Systems, Business Intelligence, Data Mining, Business Information systems, and Internet Technologies.
Jiayang Wang
Jiayang Wang received his Bachelor’s, Master’s and PHD degrees from Central South University. He is a professor in Central South University, school of Information Science and Engineering. His research interests are data mining and rough sets. He has published many papers in different refereed journals and conferences.
Lilian Sing\'oei
Lilian Sing’oei received her Bachelor’s degree (Information Technology) from Jomo Kenyatta University of Agriculture and Technology, Kenya in 2007 and is currently pursuing her master’s degree (Computer Application Technology) in Central South University, China. She has previously worked with James Finlay (K) Ltd, Kenya (Tea extract), Kenya Power & Lighting CO. Ltd, Kenya and Universal Work, Health & Safety consultancy Ltd in Kenya at the IT Department. She is certified SPSS Statistical analyst. She is currently pursuing Cisco Certified Network Associate (CCNA). She has two papers that are currently under review. Her research interests include Database Systems, Business Intelligence, Data Mining, Business Information systems, and Internet Technologies.
Jiayang Wang
Jiayang Wang received his Bachelor’s, Master’s and PHD degrees from Central South University. He is a professor in Central South University, school of Information Science and Engineering. His research interests are data mining and rough sets. He has published many papers in different refereed journals and conferences.
