THE IMPACT OF AI DRIVEN PERSONALIZATION ON CUSTOMER ENGAGEMENT AND LOYALTY

Authors

  • Hendra Gunawan Universitas Islam Bandung, West Java, Indonesia Author
  • Adi Suroso Universitas PGRI Kanjuruhan Malang, East Java, Indonesia Author

DOI:

https://doi.org/10.62207/zk1ys496

Keywords:

AI Personalization, Customer Engagement, Customer Loyalty,E-commerce, Trust, Privacy, Algorithmic Bias

Abstract

The rapid growth of the global e-commerce industry, which is expected to reach USD 5.8 trillion by 2023, is driving companies to adopt artificial intelligence (AI)-based personalization to enhance customer experience. Leveraging big data, machine learning, and natural language processing (NLP), AI personalization enables real-time, tailored interactions that have been shown to increase conversions by up to 30% and customer loyalty by up to 84%. However, issues such as data privacy concerns, algorithmic bias, and digital fatigue due to over-personalization are major challenges. This study conducts a narrative review of the impact of AI-based personalization on customer engagement and loyalty in the e-commerce context. The study integrates multidisciplinary perspectives from marketing, information technology, and consumer psychology, and synthesizes selected literature (2015–2025) from Scopus, Web of Science, and Google Scholar databases. The findings suggest that AI personalization enhances customer engagement through recommendation systems, NLP-based chatbots, and predictive analytics, which ultimately drives loyalty. Trust and perceived content relevance act as key mediators in the relationship, while privacy concerns and information fatigue may decrease its effectiveness. This study contributes to the development of a theoretical framework on the AI–engagement–loyalty relationship and provides practical guidance for industry players to design more ethical, transparent, and sustainable personalization strategies.

References

Abdullah, M., Ibrahim, M., Bahtar, A., & Khan, N. (2024). Conceptualizing the implications of artificial intelligence (ai) tools and personalization marketing on consumer purchase intention: insights from the malaysian e-commerce market. Information Management and Business Review, 16(3S(I)a), 430-436. https://doi.org/10.22610/imbr.v16i3s(i)a.4145

Acharya, N., Sassenberg, A., & Soar, J. (2022). Effects of cognitive absorption on continuous use intention of ai-driven recommender systems in e-commerce. Foresight, 25(2), 194-208. https://doi.org/10.1108/fs-10-2021-0200

Adekunle, A. (2024). Application of artificial intelligence and digital technologies in fashion design and innovation in nigeria. International Journal of Fashion and Design, 3(1), 37-48. https://doi.org/10.47604/ijfd.2389

Agbong-Coates, I. (2024). Chatgpt integration significantly boosts personalized learning outcomes: a philippine study. International Journal of Educational Management and Development Studies, 5(2), 165-186. https://doi.org/10.53378/353067

Akhtar, F., Kuthambalayan, T., & Das, N. (2017). The impact of social influence on the relationship between personality traits and perceived investment performance of individual investors. International Journal of Managerial Finance, 14(1), 130-148. https://doi.org/10.1108/ijmf-05-2016-0102

Ameen, N., Tarhini, A., Reppel, A., & Anand, A. (2021). Customer experiences in the age of artificial intelligence. Computers in Human Behavior, 114, 106548. https://doi.org/10.1016/j.chb.2020.106548

Aravindhan, G., Vemuri, V., Ram, N., Singh, A., Jain, A., Kancherla, D., … & Kanakamma, T. (2023). Precision marketing strategy for e-commerce by using artificial intelligence technology.. https://doi.org/10.52783/jier.v3i2.310

Bag, S., Srivastava, G., Bashir, M., Kumari, S., Giannakis, M., & Chowdhury, A. (2021). Journey of customers in this digital era: understanding the role of artificial intelligence technologies in user engagement and conversion. Benchmarking an International Journal, 29(7), 2074-2098. https://doi.org/10.1108/bij-07-2021-0415

Barrons. (2023). Black Friday Shopping: Cyber Monday and the AI Recommendation Engine. https://www.barrons.com/articles/black-friday-shopping-cyber-monday-d31144da

Beyari, H. and Garamoun, H. (2022). The effect of artificial intelligence on end-user online purchasing decisions: toward an integrated conceptual framework. Sustainability, 14(15), 9637. https://doi.org/10.3390/su14159637

Brodie, R., Hollebeek, L., Jurić, B., & Ilić, A. (2011). Customer engagement. Journal of Service Research, 14(3), 252-271. https://doi.org/10.1177/1094670511411703

Cao, S., Liu, A., & Huang, C. (2024). Designing for appropriate reliance: the roles of ai uncertainty presentation, initial user decision, and user demographics in ai-assisted decision-making. Proceedings of the Acm on Human-Computer Interaction, 8(CSCW1), 1-32. https://doi.org/10.1145/3637318

Chen, Q., Lu, Y., Gong, Y., & Xiong, J. (2023). Can ai chatbots help retain customers? impact of ai service quality on customer loyalty. Internet Research, 33(6), 2205-2243. https://doi.org/10.1108/intr-09-2021-0686

Chugh, P. and Jain, V. (2024). Artificial intelligence (ai) empowerment in e-commerce: a bibliometric voyage. Nmims Management Review, 32(3), 159-173. https://doi.org/10.1177/09711023241303621

Elshahed, H. (2022). Privacy paradox amid e-commerce epoch., 45-64. https://doi.org/10.4018/978-1-6684-5844-0.ch003

Estiri, H., Strasser, Z., Rashidian, S., Klann, J., Wagholikar, K., McCoy, T., … & Murphy, S. (2021). An objective search for unrecognized bias in validated covid-19 prediction models.. https://doi.org/10.1101/2021.10.28.21265629

Feng, Y. and Agosto, D. (2014). Overwhelmed by smartphones? a qualitative investigation into mobile information overload. Proceedings of the American Society for Information Science and Technology, 51(1), 1-2. https://doi.org/10.1002/meet.2014.14505101113

Gartman, I. (2024). The use of artificial intelligence to personalize the search for products in online stores. International Journal of Latest Engineering and Management Research (Ijlemr), 9(10), 44-48. https://doi.org/10.56581/ijlemr.9.10.44-48

Gitnux. (2024). AI in the E-commerce Industry: Statistics and Trends. https://gitnux.org/ai-in-the-ecommerce-industry-statistics

Goti , A. , Querejeta-Lomas , L. , Almeida , A. , Gate , J. , & Lopez–de–Ipiña , D. (2023). Artificial intelligence in business-to-customer fashion retailing: a literature review. Mathematics, 11(13), 2943. https://doi.org/10.3390/math11132943

Harmeling, C., Moffett, J., Arnold, M., & Carlson, B. (2016). Toward a theory of customer engagement marketing. Journal of the Academy of Marketing Science, 45(3), 312-335. https://doi.org/10.1007/s11747-016-0509-2

Ho, S. and Chow, M. (2023). The role of artificial intelligence in consumers’ brand preference for retail banks in hong kong. Journal of Financial Services Marketing, 29(2), 292-305. https://doi.org/10.1057/s41264-022-00207-3

Hollebeek, L., Glynn, M., & Brodie, R. (2014). Consumer brand engagement in social media: conceptualization, scale development and validation. Journal of Interactive Marketing, 28(2), 149-165. https://doi.org/10.1016/j.intmar.2013.12.002

Hollebeek, L. and Macky, K. (2019). Digital content marketing's role in fostering consumer engagement, trust, and value: framework, fundamental propositions, and implications. Journal of Interactive Marketing, 45(1), 27-41. https://doi.org/10.1016/j.intmar.2018.07.003

Holloway, S. (2024). Exploring the role of digital technologies in enhancing supply chain efficiency and marketing effectiveness.. https://doi.org/10.20944/preprints202406.1538.v1

James, B., Joseph, D., & Sharma, T. (2024). Transforming banking services: ai-driven e-loyalty strategies and case study insights on customer satisfaction and loyalty enhancement.. https://doi.org/10.4108/eai.23-11-2023.2343232

Kumar, L. (2025). Fairness in artificial intelligence: a comprehensive review of bias detection: a systematic literature. International Scientific Journal of Engineering and Management, 04(05), 1-9. https://doi.org/10.55041/isjem03725

Kumar, V., Rajan, B., Gupta, S., & Pozza, I. (2017). Customer engagement in service. Journal of the Academy of Marketing Science, 47(1), 138-160. https://doi.org/10.1007/s11747-017-0565-2

Li, J. (2022). E-commerce fraud detection model by computer artificial intelligence data mining. Computational Intelligence and Neuroscience, 2022, 1-9. https://doi.org/10.1155/2022/8783783

Logalakshmi, S., Krishnan.M, D., & Maheswari, P. (2023). Carving a brighter path with synergy of digital marketing & ai. International Journal of Trendy Research in Engineering and Technology, 07(05), 18-24. https://doi.org/10.54473/ijtret.2023.7505

Mavrogiorgos, K., Kiourtis, A., Mavrogiorgou, A., Menychtas, A., & Kyriazis, D. (2024). Bias in machine learning: a literature review. Applied Sciences, 14(19), 8860. https://doi.org/10.3390/app14198860

Meeprom, S. and Suttikun, C. (2024). Ai- and employee-based customer services in restaurants: customer engagement leading to loyalty during the covid-19 pandemic. Abac Journal, 44(2). https://doi.org/10.59865/abacj.2024.15

Nalini, R. (2024). Transformative power of artificial intelligence in decision-making, automation, and customer engagement., 189-208. https://doi.org/10.4018/979-8-3693-0712-0.ch009

Ntumba, C., Aguayo, S., & Maina, K. (2023). Revolutionizing retail: a mini review of e-commerce evolution. Journal of Digital Marketing and Communication, 3(2), 100-110. https://doi.org/10.53623/jdmc.v3i2.365

Oyeniran, O., Adewusi, A., Adeleke, A., Akwawa, L., & Azubuko, C. (2022). Ethical ai: addressing bias in machine learning models and software applications. Computer Science & It Research Journal, 3(3), 115-126. https://doi.org/10.51594/csitrj.v3i3.1559

Papić, T., Mihajlović, A., & Gajić, J. (2023). Advanced technologies as a framework for sustainable marketing campaigns (ai application in neuromarketing)., 180-184. https://doi.org/10.15308/sinteza-2023-180-184

Rahevar, M. and Darji, S. (2024). The adoption of ai-driven chatbots into a recommendation for e-commerce systems to targeted customers in the selection of products. IJMEC, 1(2), 128-137. https://doi.org/10.62737/m1vpdq75

Rahmani, Z., Ranjbar, M., Gara, A., & Gorji, M. (2017). The study of the relationship between value creation and customer loyalty with the role of trust moderation and customer satisfaction in sari hospitals. Electronic Physician, 9(6), 4474-4478. https://doi.org/10.19082/4474

Raji, M., Olodo, H., Oke, T., Addy, W., Ofodile, O., & Oyewole, A. (2024). E-commerce and consumer behavior: a review of ai-powered personalization and market trends. GSC Advanced Research and Reviews, 18(3), 066-077. https://doi.org/10.30574/gscarr.2024.18.3.0090

Rangani, D., Sivashankar, P., & Rathnayake, M. (2019). Customer perceived value and customer relationship marketing in b2b agribusinesses: a case of agrochemical market in sri lanka. Journal of Agribusiness and Rural Development, 54(4), 355-361. https://doi.org/10.17306/j.jard.2019.01236

Reddit. (2024). E-commerce growth predictions and market share. https://www.reddit.com/r/Analyzify/comments/1axyn6w

Riedl‬, R. (2022). Is trust in artificial intelligence systems related to user personality? review of empirical evidence and future research directions. Electronic Markets, 32(4), 2021-2051. https://doi.org/10.1007/s12525-022-00594-4

Rua, S., Saldanha, E., & Amaral, A. (2020). Examining the relationships among product quality, customer satisfaction and loyalty in the bamboo institute, dili, timor-leste. Timor Leste Journal of Business and Management, 2, 33-44. https://doi.org/10.51703/bm.v2i2.28

Segijn, C. and Ooijen, I. (2020). Differences in consumer knowledge and perceptions of personalized advertising: comparing online behavioural advertising and synced advertising. Journal of Marketing Communications, 28(2), 207-226. https://doi.org/10.1080/13527266.2020.1857297

Shah, T., Kautish, P., & Mehmood, K. (2023). Influence of robots service quality on customers' acceptance in restaurants. Asia Pacific Journal of Marketing and Logistics, 35(12), 3117-3137. https://doi.org/10.1108/apjml-09-2022-0780

So, K., King, C., Sparks, B., & Ying, W. (2014). The role of customer engagement in building consumer loyalty to tourism brands. Journal of Travel Research, 55(1), 64-78. https://doi.org/10.1177/0047287514541008

Soto‐Acosta, P., Molina‐Castillo, F., López‐Nicolás, C., & Colomo‐Palacios, R. (2014). The effect of information overload and disorganisation on intention to purchase online. Online Information Review, 38(4), 543-561. https://doi.org/10.1108/oir-01-2014-0008

Sreerama, J. and Krishnamoorthy, G. (2022). Ethical considerations in ai addressing bias and fairness in machine learning models. Journal of Knowledge Learning and Science Technology Issn 2959-6386 (Online), 1(1), 130-138. https://doi.org/10.60087/jklst.vol1.n1.p138

Stanić, I., Bektaš, I., & Hinek, S. (2021). Information: stress or lifestyle. Informatologia, 54(1-2), 88-99. https://doi.org/10.32914/i.54.1-2.8

Thakur, R. (2016). Understanding customer engagement and loyalty: a case of mobile devices for shopping. Journal of Retailing and Consumer Services, 32, 151-163. https://doi.org/10.1016/j.jretconser.2016.06.004

Tobia, K., Nielsen, A., & Stremitzer, A. (2020). When does physician use of ai increase liability?. Journal of Nuclear Medicine, 62(1), 17-21. https://doi.org/10.2967/jnumed.120.256032

Trang, N. and Thư, P. (2024). The role of ai in improving student learning outcomes: evidence in vietnam. International Journal of Multidisciplinary Research and Analysis, 07(06). https://doi.org/10.47191/ijmra/v7-i06-48

Tung, D. (2024). Ai-powered customer experience: personalization, engagement, and intelligent decision-making in crm. jes, 20(5s), 55-71. https://doi.org/10.52783/jes.1832

Ullah, F., Kumar, S., & Furuoka, F. (2022). Online hedonic consumers’ privacy awateness and privacy paradox: a systematic literature review. Malaysian Journal of Business and Economics (Mjbe), 9(2). https://doi.org/10.51200/mjbe.v9i2.4359

Wang, Q., Luo, X., Tu, R., Xiao, T., & Hu, W. (2022). Covid-19 information overload and cyber aggression during the pandemic lockdown: the mediating role of depression/anxiety and the moderating role of confucian responsibility thinking. International Journal of Environmental Research and Public Health, 19(3), 1540. https://doi.org/10.3390/ijerph19031540

WiFi Talents. (2024). AI in the E-commerce Industry: Market Data and Insights. https://wifitalents.com/ai-in-the-e-commerce-industry-statistics

World Metrics. (2024). AI in E-Commerce: Market Size, Benefits, and Impact. https://worldmetrics.org/ai-in-ecommerce-statistics

Ye, T., Xue, J., He, M., Gu, J., Lin, H., Bin, X., … & Cheng, Y. (2019). Psychosocial factors affecting artificial intelligence adoption in health care in china: cross-sectional study. Journal of Medical Internet Research, 21(10), e14316. https://doi.org/10.2196/14316

Zhuk, A. and Yatskyi, O. (2024). The use of artificial intelligence and machine learning in e-commerce marketing. Technology Audit and Production Reserves, 3(4(77)), 33-38. https://doi.org/10.15587/2706-5448.2024.305280

Downloads

Published

2025-04-30

How to Cite

THE IMPACT OF AI DRIVEN PERSONALIZATION ON CUSTOMER ENGAGEMENT AND LOYALTY. (2025). Management Studies and Business Journal (PRODUCTIVITY), 2(4), 2511-2525. https://doi.org/10.62207/zk1ys496