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Balancing Customer Personalization and Data Privacy using Advanced Analytics
American Journal of Economics and Business Management,
Vol. 7 No. 12 (2024): December
Abstract
Customer personalization has become a critical strategy for businesses to enhance customer experience and loyalty. However, the increasing reliance on advanced analytics to deliver tailored services has raised significant concerns regarding data privacy. This paper explores the tension between personalization and privacy, offering a comprehensive analysis of how advanced analytics can balance these objectives. It examines regulatory frameworks, ethical considerations, and technological innovations that enable businesses to deliver personalized services while safeguarding customer data. The findings underscore the importance of transparency, consent, and privacy-preserving technologies in achieving this balance.
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- Chen, L., Zhang, X., & Wang, H. (2021). Privacy challenges in customer analytics: A review. Journal of Consumer Data Science, 7(3), 45-60.
- Davis, R., Lee, K., & Patel, S. (2022). Consumer attitudes toward personalization and privacy: Implications for business strategy. Marketing Insights Quarterly, 9(2), 12-25.
- Kumar, R., Singh, A., & Gupta, P. (2023). Advances in privacy-preserving analytics: Techniques and applications. Journal of Artificial Intelligence Research, 15(4), 100-120.
- Smith, J., & Johnson, M. (2022). Personalization in the age of data privacy: Balancing act for businesses. Data Analytics Review, 18(1), 23-37.
- Taylor, B., & Martin, D. (2020). Regulatory frameworks for data privacy: An international perspective. Journal of Law and Technology, 11(2), 89-105.
References
Chen, L., Zhang, X., & Wang, H. (2021). Privacy challenges in customer analytics: A review. Journal of Consumer Data Science, 7(3), 45-60.
Davis, R., Lee, K., & Patel, S. (2022). Consumer attitudes toward personalization and privacy: Implications for business strategy. Marketing Insights Quarterly, 9(2), 12-25.
Kumar, R., Singh, A., & Gupta, P. (2023). Advances in privacy-preserving analytics: Techniques and applications. Journal of Artificial Intelligence Research, 15(4), 100-120.
Smith, J., & Johnson, M. (2022). Personalization in the age of data privacy: Balancing act for businesses. Data Analytics Review, 18(1), 23-37.
Taylor, B., & Martin, D. (2020). Regulatory frameworks for data privacy: An international perspective. Journal of Law and Technology, 11(2), 89-105.