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Big Data Analytics Case Study from the Marketing Perspective : Emphasis on Banking Industry

마케팅 관점으로 본 빅 데이터 분석 사례연구 : 은행업을 중심으로

  • 박성수 (성균관대학교 경영대학) ;
  • 이건창 (성균관대학교 경영대학/삼성융합의과학원)
  • Received : 2018.02.20
  • Accepted : 2018.04.26
  • Published : 2018.06.30

Abstract

Recently, it becomes a big trend in the banking industry to apply a big data analytics technique to extract essential knowledge from their customer database. Such a trend is based on the capability to analyze the big data with powerful analytics software and recognize the value of big data analysis results. However, there exits still a need for more systematic theory and mechanism about how to adopt a big data analytics approach in the banking industry. Especially, there is no study proposing a practical case study in which big data analytics is successfully accomplished from the marketing perspective. Therefore, this study aims to analyze a target marketing case in the banking industry from the view of big data analytics. Target database is a big data in which about 3.5 million customers and their transaction records have been stored for 3 years. Practical implications are derived from the marketing perspective. We address detailed processes and related field test results. It proved critical for the big data analysts to consider a sense of Veracity and Value, in addition to traditional Big Data's 3V (Volume, Velocity, and Variety), so that more significant business meanings may be extracted from the big data results.

Keywords

References

  1. Beulke, D., "Big Data Impacts Data Management : The 5 Vs of big data", 2011, Available at http://davebeulke.com/big-data-impacts-data-management-the-five-vs-ofbig-data (Accessed Jan 30. 2017).
  2. Chang, M.S. and H.J. Kim, "A Customer Segmentation Scheme Base on Big Data in a Bank", Journal of Digital Contents Society, Vol.19, No.1, 2018, 85-91. (장민석, 김형중, "빅데이터를 활용한 은행권 고객 세분화 기법 연구", 한국디지털콘텐츠학회 논문지, 제19권, 제1호, 2018, 85-91.) https://doi.org/10.9728/DCS.2018.19.1.85
  3. Choi, B.J., H.J. Kim, J.H. Kim, and S.H. Jin, "Data Analytics for CRM in the Age of Big Data", Entrue Journal of Information Technology, Vol.11, No.1, 2012, 19-27. (최병정, 김혜진, 김자호, 진서훈, "빅 데이터 시대의 CRM을 위한 데이터 분석", Entrue Journal of Information Technology, 제11권, 제1호, 2012, 19-27.)
  4. Danesi, I.L. and C. Rea, "A Customer Relationship Management Case Study Based on Banking Data", In International Workshop on Machine Learning, Optimization and Big Data, Springer, Cham, 2016, 224-235.
  5. Davenport, T.H., P. Barth, and R. Bean, "How 'Big Data' is Different", MIT Sloan Management Review, Vol.54, No.1, 2012, 43-46.
  6. Duan, L. and Y. Xiong, "Big data analytics and business analytics", Journal of Management Analytics, Vol.2, No.1, 2015, 1-21. https://doi.org/10.1080/23270012.2015.1020891
  7. Gartner, "Big Data", 2012, Available at http://www.gartner.com/it-glossary/big-data/ (Accessed Jan 30. 2017).
  8. Kim, S.S., "A study on development method for practical use of Big Data related to recommendation to financial item", Journal of the Korea Society of Computer and Information, Vol.19, No.8, 2014, 73-81. (김석수, "금융 상품 추천에 관련된 빅 데이터 활용을 위한 개발 방법", 한국컴퓨터정보학회논문지, 제19권, 제8호, 2014, 73-81.) https://doi.org/10.9708/jksci.2014.19.8.073
  9. Labrinidis, A. and H.V. Jagadish, "Challenges and opportunities with big data", Proceedings of the VLDB Endowment, Vol.5, No. 12, 2012, 2032-2033.
  10. Lee, S.K., "A Review of Big Data Analysis Based on Marketing Perspective", Korean Journal of Business Administration, Vol.28, No.1, 21-35, 2015. (이서구, "빅 데이터 분석에 관한 마케팅적 접근", 대한경영학회지, 제28권, 제1호, 2015, 21-35.)
  11. Manyika, J., M. Chui, B. Brown, J. Bughin, R. Dobbs, C. Roxburgh, and A. Byers, "Big data : The next frontier for innovation, competition, and productivity", 2011, Available at http://www.mckinsey.com/insights/mgi/research/technology_and_innovation/big_data_the_next_frontier_for_innovation (Accessed Jan 30. 2017)
  12. McAfee, A., E. Brynjolfsson, T.H. Davenport, D. Patil, and D. Barton, "Big data. The Management Revolution", Harvard Business Review, Vol.90, No.10, 2012, 61-67.
  13. McKinsey, "The future of bank risk management", 2016, Available at http://www.mckinsey.com/business-functions/risk/our-insights/the-future-of-bank-risk-management (Accessed Jan 30. 2017).
  14. Mervis, J., "Agencies rally to tackle big data", Science, Vol.336, No.6077, 2012, 22-22. https://doi.org/10.1126/science.336.6077.22
  15. Russom, P., "The three Vs of big data analytics", TDWI Best Practices Report, Fourth Quarter, Vol.18, 2011, 1-35.
  16. Schroeck, M., R. Shockley, J. Smart, D. Romero- Morales, and P. Tufano, "Analytics : The real-world use of big data", IBM Global Business Services, 2012, 1-20.
  17. Sun, N., J.G. Morris, J. Xu, X. Zhu, and M. Xie, "iCARE : A framework for big data-based banking customer analytics", IBM Journal of Research and Development, Vol.58, No. 5/6, 2014, 4-1.
  18. Wamba, S.F., S. Akter, A. Edwards, G. Chopin, and D. Gnanzou, "How 'big data'can make big impact : Findings from a systematic review and a longitudinal case study", International Journal of Production Economics, Vol.165, 2015, 234-246. https://doi.org/10.1016/j.ijpe.2014.12.031
  19. Wang, G., A. Gunasekaran, E.W. Ngai, and T. Papadopoulos, "Big data analytics in logistics and supply chain management : Certain investigations for research and applications", International Journal of Production Economics, Vol.176, 2016, 98-110. https://doi.org/10.1016/j.ijpe.2016.03.014
  20. Wixom, B.H., B. Yen, and M. Relich, "Maximizing value from business analytics", MIS Quarterly Executive, Vol.12, No.2, 2013, 111-123.
  21. Xu, Z., G.L. Frankwick, and E. Ramirez, "Effects of big data analytics and traditional marketing analytics on new product success : A knowledge fusion perspective", Journal of Business Research, Vol.69, No.5, 2016, 1562-1566. https://doi.org/10.1016/j.jbusres.2015.10.017
  22. Zhou, Z.H., N.V. Chawla, Y. Jin, and G.J. Williams, "Big data opportunities and challenges : Discussions from data analytics perspectives", IEEE Computational Intelligence Magazine, Vol.9, No.4, 2014, 62-74. https://doi.org/10.1109/MCI.2014.2350953