PERSONALIZATION IN DIGITAL MARKETING: EXPLORING ITS IMPACT ON CONSUMER TRUST AND LOYALTY

Authors

  • Nabila Cecilia Marasabessy Politeknik Perikanan Negeri Tual, Maluku Tenggara, Indonesia Author
  • Muhammad Hidayat Universitas Persada Bunda Indonesia, Pekanbaru, Riau, Indonesia Author

DOI:

https://doi.org/10.62207/vtnpq392

Keywords:

digital marketing personalization, consumer trust, data transparency, privacy, systematic literature review

Abstract

This research aims to explore how personalization in digital marketing influences consumer trust, focusing on factors that strengthen or weaken that trust. Using a systematic literature review approach with the PRISMA method, we analyzed findings from previous studies related to data-based personalization, transparency, and privacy. The results show that the level of transparency, relevance of content, as well as consumer control over their data play a key role in building trust, while intrusive personalization can undermine it. The practical implications of this research provide guidance for companies in designing ethical and effective digital marketing strategies.

References

Alvi, A. (2023). Exploring the ethical challenges of ai in personalised marketing in the context of beauty and wellness. International Journal of All Research Education & Scientific Methods, 12(02), 12-02. https://doi.org/10.56025/ijaresm.2023.120124482

Aslam, W., Hussain, A., Farhat, K., & Arif, I. (2019). Underlying factors influencing consumers’ trust and loyalty in e-commerce. Business Perspectives and Research, 8(2), 186-204. https://doi.org/10.1177/2278533719887451

Bankins, S. and Formosa, P. (2023). The ethical implications of artificial intelligence (ai) for meaningful work. Journal of Business Ethics, 185(4), 725-740. https://doi.org/10.1007/s10551-023-05339-7

Basimakopoulou, M., Theologou, K., & Tzavaras, P. (2022). A literature review on digital marketing: the evolution of a revolution. Journal of Social Media Marketing, 1(1), 30-40. https://doi.org/10.33422/jsmm.v1i1.901

Bleier, A. and Eisenbeiß, M. (2015). The importance of trust for personalized online advertising. Journal of Retailing, 91(3), 390-409. https://doi.org/10.1016/j.jretai.2015.04.001

Brinson, N. and Britt, B. (2021). Reactance and turbulence: examining the cognitive and affective antecedents of ad blocking. Journal of Research in Interactive Marketing, 15(4), 549-570. https://doi.org/10.1108/jrim-04-2020-0083

Busser, J. and Shulga, L. (2019). Involvement in consumer-generated advertising. International Journal of Contemporary Hospitality Management, 31(4), 1763-1784. https://doi.org/10.1108/ijchm-10-2017-0685

Cavique, L. (2024). Implications of causality in artificial intelligence. Frontiers in Artificial Intelligence, 7. https://doi.org/10.3389/frai.2024.1439702

Chukwurah, E. (2024). Proactive privacy: advanced risk management strategies for product development in the u.s. Computer Science & It Research Journal, 5(4), 878-891. https://doi.org/10.51594/csitrj.v5i4.1047

Deligiannis, A., Argyriou, C., & Kourtesis, D. (2020). Predicting the optimal date and time to send personalized marketing messages to repeat buyers. International Journal of Advanced Computer Science and Applications, 11(4). https://doi.org/10.14569/ijacsa.2020.0110413

Dooley, S., Turjeman, D., Dickerson, J., & Redmiles, E. (2021). Field evidence of the effects of pro-sociality and transparency on covid-19 app attractiveness.. https://doi.org/10.31235/osf.io/gm6js

Dsouza, A. and Panakaje, N. (2023). A study on the evolution of digital marketing. International Journal of Case Studies in Business It and Education, 95-106. https://doi.org/10.47992/ijcsbe.2581.6942.0248

Eggers, F., Beke, F., Verhoef, P., & Wieringa, J. (2023). The market for privacy: understanding how consumers trade off privacy practices. Journal of Interactive Marketing, 58(4), 341-360. https://doi.org/10.1177/10949968221140061

Felzmann, H., Fosch‐Villaronga, E., Lutz, C., & Tamò-Larrieux, A. (2020). Towards transparency by design for artificial intelligence. Science and Engineering Ethics, 26(6), 3333-3361. https://doi.org/10.1007/s11948-020-00276-4

Fox, G. and Lynn, T. (2020). Examining privacy disclosure and trust in the consumer internet of things: an integrated research framework., 123-140. https://doi.org/10.1007/978-3-030-41110-7_7

Fritz, K., Schoenmueller, V., & Bruhn, M. (2017). Authenticity in branding – exploring antecedents and consequences of brand authenticity. European Journal of Marketing, 51(2), 324-348. https://doi.org/10.1108/ejm-10-2014-0633

Fu, S., Ma, R., He, G., Chen, Z., & Liu, H. (2023). A study on the influence of product environmental information transparency on online consumers’ purchasing behavior of green agricultural products. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1168214

Gao, Y. and Liu, H. (2022). Artificial intelligence-enabled personalization in interactive marketing: a customer journey perspective. Journal of Research in Interactive Marketing, 17(5), 663-680. https://doi.org/10.1108/jrim-01-2022-0023

Gupta, K. (2023). Emerging design trends in social media and its impact on business efficiency and growth in india. Shodhkosh Journal of Visual and Performing Arts, 4(2SE). https://doi.org/10.29121/shodhkosh.v4.i2se.2023.455

Hajli, N. and Nisar, T. (2022). Privacy‐enhancing factors and consumer concerns: the moderating effects of the general data protection regulation. British Journal of Management, 34(4), 2075-2092. https://doi.org/10.1111/1467-8551.12685

Haresamudram, K., Larsson, S., & Heintz, F. (2023). Three levels of ai transparency. Computer, 56(2), 93-100. https://doi.org/10.1109/mc.2022.3213181

Kaikara, C. (2024). Innovative marketing strategies for attracting millennial and gen z travelers. Journal of Modern Hospitality, 3(1), 40-52. https://doi.org/10.47941/jmh.1953

Kang, J., Diao, Z., & Zanini, M. (2020). Business-to-business marketing responses to covid-19 crisis: a business process perspective. Marketing Intelligence & Planning, 39(3), 454-468. https://doi.org/10.1108/mip-05-2020-0217

Malgieri, G. (2021). In/acceptable marketing and consumers' privacy expectations: four tests from eu data protection law. Journal of Consumer Marketing, 40(2), 209-223. https://doi.org/10.1108/jcm-03-2021-4571

Misra, G., Such, J., & Gill, L. (2017). A privacy assessment of social media aggregators.. https://doi.org/10.1145/3110025.3110103

Nkatekho, A. (2024). Leveraging big data analytics for personalized marketing strategies in the hospitality sector. Journal of Modern Hospitality, 3(1), 15-26. https://doi.org/10.47941/jmh.1951

Obudho, K. (2024). The impact of data privacy laws on digital marketing practices. Journal of Modern Law and Policy, 4(1), 35-48. https://doi.org/10.47941/jmlp.2155

Okorie, G. (2024). Leveraging big data for personalized marketing campaigns: a review. International Journal of Management & Entrepreneurship Research, 6(1), 216-242. https://doi.org/10.51594/ijmer.v6i1.778

Senyapar, H. (2024). Artificial intelligence in marketing communication: a comprehensive exploration of the integration and impact of ai. Technium Social Sciences Journal, 55, 64-81. https://doi.org/10.47577/tssj.v55i1.10651

Shin, D. (2021). Embodying algorithms, enactive artificial intelligence and the extended cognition: you can see as much as you know about algorithm. Journal of Information Science, 49(1), 18-31. https://doi.org/10.1177/0165551520985495

Swani, K., Milne, G., & Slepchuk, A. (2021). Revisiting trust and privacy concern in consumers’ perceptions of marketing information management practices: replication and extension. Journal of Interactive Marketing, 56(1), 137-158. https://doi.org/10.1016/j.intmar.2021.03.001

Tal, A., Kuflik, T., & Kliger, D. (2022). Fairness, explainability and in-between: understanding the impact of different explanation methods on non-expert users’ perceptions of fairness toward an algorithmic system. Ethics and Information Technology, 24(1). https://doi.org/10.1007/s10676-022-09623-4

Trepte, S., Reinecke, L., Ellison, N., Quiring, O., Yao, M., & Ziegele, M. (2017). A cross-cultural perspective on the privacy calculus. Social Media + Society, 3(1). https://doi.org/10.1177/2056305116688035

Wattal, S., Telang, R., Mukhopadhyay, T., & Boatwright, P. (2012). What's in a “name”? impact of use of customer information in e-mail advertisements. Information Systems Research, 23(3-part-1), 679-697. https://doi.org/10.1287/isre.1110.0384

Wei-min, O. (2019). Research on the role of algorithm transparency in algorithm accountability.. https://doi.org/10.2991/assehr.k.191221.055

Willis, B., Jai, T., & Lauderdale, M. (2021). Trust and commitment: effect of applying consumer data rights on u.s. consumers' attitudes toward online retailers in big data era. Journal of Consumer Behaviour, 20(6), 1575-1590. https://doi.org/10.1002/cb.1968

Winter, S., Masłowska, E., & Vos, A. (2021). The effects of trait-based personalization in social media advertising. Computers in Human Behavior, 114, 106525. https://doi.org/10.1016/j.chb.2020.106525

Yang, Q. (2024). Ethical ai in financial inclusion: the role of algorithmic fairness on user satisfaction and recommendation.. https://doi.org/10.20944/preprints202407.1655.v1

Yürük, P. (2021). The mediating role of security and privacy on the relationship between customer interface features and e-word of mouth marketing. Turkish Journal of Marketing, 6(2), 125-142. https://doi.org/10.30685/tujom.v6i2.118

Zhang, Z. (2024). Market segmentation and personalized marketing strategy optimization driven by big data analysis.. https://doi.org/10.3233/atde240434

Zhao, F. (2023). Analysis of consumer behavior and discussion of personalized marketing strategy in the era of big data. HC, 1(1). https://doi.org/10.61173/be5jey03

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Published

2025-01-29

How to Cite

PERSONALIZATION IN DIGITAL MARKETING: EXPLORING ITS IMPACT ON CONSUMER TRUST AND LOYALTY. (2025). Management Studies and Business Journal (PRODUCTIVITY), 2(1), 1831-1844. https://doi.org/10.62207/vtnpq392