Magdalena KuΕ‘telega
- University of Zagreb, Faculty of Organization and Informatics, Pavlinska 2, HR 42000, VaraΕΎdin, Croatia
Iva Gregurec
- University of Zagreb, Faculty of Organization and Informatics, Pavlinska 2, HR 42000, VaraΕΎdin, Croatia
Sandra LovrenΔiΔ
- University of Zagreb, Faculty of Organization and Informatics, Pavlinska 2, HR 42000, VaraΕΎdin, Croatia
Abstract:
Digitalization has empowered companies to enhance their customer relationship management strategy through the use of big data analytics. By collecting and storing huge amounts of customer data in databases, companies can develop more detailed customer profiles and predict their behavior, which ultimately can lead to increased customer satisfaction and higher customer retention rates. This paper provides an overview of existing literature collected from Web of Science Platform and Scopus database, to establish a theoretical framework that examines the connection between big data analytics and customer relationship management. The conducted research indicates that companies use big data analytics to enhance user experience by designing and implementing personalized marketing activities for their βmost valuableβ customers. However, the existing literature also highlights challenges in implementing big data into customer relationship management strategy, including issues with data storage, data quality, and implementation costs. Therefore, this paper provides valuable insight into both the potential benefits and the obstacles that may arise when both concepts are coherent.
Tenth International Scientific-Business Conference LIMEN Leadership, Innovation, Management and Economics: Integrated Politics of Research - LIMEN 2024 - International Scientific-Business Conference β LIMEN 2024: Vol 10. Selected Papers , December 5, 2024
Conference Proceedings published by: Association of Economists and Managers of the Balkans, Belgrade, Serbia
ISBN: 9788680194936 , ISSN: 26836149 , DOI: 10.31410/LIMEN.S.P.2024
Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission.
