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Data Design Strategy for Data Governance Applied to Customer Relationship Management

  • Sangwon LEE (Dept. of Computer & Software Engineering, Wonkwang Univ.) ;
  • Joohyung KIM (Dept. of Mathematics Education, Wonkwang Univ.)
  • Received : 2023.08.03
  • Accepted : 2023.08.29
  • Published : 2023.09.30

Abstract

Nowadays, many companies are striving to turn customer value into business value. Customer Relationship Management is a management system that develops effective and efficient marketing strategies by classifying customers in detail based on their information, i.e. databases, and consists of various information technologies. To implement this management system, a customer integration database must be established, and customer characteristics (buying behavior, preferences, etc.) must be analyzed with the databases established and the behavior of each customer must be predicted. This study aims to systematically manage a large amount of customer data generated by companies that apply Customer Relationship Management, in order to develop data design and data governance strategies that should be considered to increase customer value and even company value. We mainly looked at the characteristics of customer relationship management and data governance, and then explored the link between the field of customer relationship management and data governance. In addition, we have developed a data strategy that companies need to perform data governance for customer relationship management.

Keywords

Acknowledgement

This paper was supported by Wonkwang University in 2022.

References

  1. Rigby, D. K., & Ledingham, "CRM done right," Harvard business review, Vol. 82, No. 11, pp. 118-130, 2024.
  2. Ostergaard, D., Dieckmann, P., & Lippert, A. "Simulation and CRM," Best Practice & Research Clinical Anaesthesiology, Vol. 25, No. 2, pp. 239-249, 2011.DOI: https://doi.org/10.1016/j.bpa.2011.02.003
  3. Payne, A., Handbook of CRM. Routledge, 2012.
  4. Nguyen, T. H., Sherif, J. S., & Newby, M., "Strategies for successful CRM implementation. Information management & computer security," Vol. 15, No.2, pp. 102-115, 2007. DOI: https://doi.org/10.1108/09685220710748001
  5. Abraham, R., Schneider, J., & Vom Brocke, J., "Data governance: A conceptual framework, structured review, and research agenda," International journal of information management, Vol. 49, pp. 424-438, 2019. DOI: https://doi.org/10.1016/j.ijinfomgt.2019.07.008
  6. Khatri, V., & Brown, C. V., "Designing data governance," Communications of the ACM, Vol. 53, No. 1, pp. 148-152, 2010. DOI: https://doi.org/10.1145/1629175.1629210
  7. Alhassan, I., Sammon, D., & Daly, M., "Data governance activities: an analysis of the literature," Journal of Decision Systems, Vol. 25, No. sup1, pp. 64-75, 2016. DOI: https://doi.org/10.1080/12460125.2016.1187397
  8. Al-Ruithe, M., Benkhelifa, E., & Hameed, K., "A systematic literature review of data governance and cloud data governance," Personal and Ubiquitous Computing, Vol. 23, pp. 839-859, 2019. DOI: https://doi.org/10.1007/s00779-017-1104-3
  9. Wiederhold, G., Database design, Vol. 1077, McGraw-Hill, 1983.
  10. Schema, C., Relational database design. Prentice Hall Austria, 1995.
  11. Nijssen, G. M., & Halpin, T. A. (Eds.), Conceptual Schema and Relational Database Design: a fact oriented approach. Prentice-Hall, Inc., 1989.
  12. Sagiroglu, S., & Sinanc, D. "Big data: A review," In 2013 international conference on collaboration technologies and systems (CTS), IEEE, pp. 42-47, 2013. DOI: https://doi.org/10.1109/CTS.2013.6567202
  13. Kim, T. H., & Kim, Y. G., "Improvement of IoT sensor data loss rate of wireless network-based smart factory management system", The International Journal of Advanced Smart Convergence, Vol. 12, No. 2, pp. 173-181, 2023. DOI: http://doi.org/10.7236/IJASC.2023.12.2.193