Impact of AI Personalization on Customer Retention in E-Commerce

International Journal of Emerging Research in Science, Engineering, and Management
Vol. 2, SI1 (2026), pp. 220227
Proceedings of Selected Papers from the
National Conference on Emerging Trends in Commerce and Management
NCETCM-2K26
2026-03-30 to 2026-03-31
Vijayawada, Andhra Pradesh, India
Organized by Andhra Loyola College, Vijayawada, India
eISSN: 3107-9075

This work is licensed under a Creative Commons Attribution 4.0 International License .

Impact of AI Personalization on Customer Retention in E-Commerce

1S. Gopinathan, 1N. Prakash,2GaddamSravan Kumar

1Assistant Professor, PG & Research Department of Commerce, Patrician College of Arts & Science, Chennai, India
2Assistant Professor, Andhra Loyola College, Vijayawada, India

Abstract

Artificial Intelligence (AI) has become increasingly prevalent in e-commerce, which has drastically altered how businesses interact with their clients, particularly through personalization. The purpose of this study is to investigate the function of AI personalization in relation to e-commerce client retention. Recommendation systems, pricing, content, and marketing are just a few of the AI personalization technologies that are increasingly essential to raising consumer pleasure and engagement. This study's main objective is to assess how perceived personalization affects customer retention, particularly with regard to mediating factors like satisfaction and trust. The study used a quantitative research methodology and collected primary data from e-commerce website customers using a questionnaire survey. To verify the proposed relationship between the variables, statistical methods such as Structural Equation Modeling (SEM) are also used. It is anticipated that the study's findings would demonstrate how well AI-based customisation enhances customer pleasure and trust, both of which support client retention. Additionally, the study looked into how privacy concerns can moderate the relationship between customer retention and personalization. By offering actual proof of the efficiency of AI-based personalization in keeping clients in cutthroat markets, the study adds to the body of previous studies. Additionally, the study offers e-commerce businesses useful advice on how to create ethically sound AI-based personalization strategies. The report also discusses limitations and future research directions .

Keywords: AI-Driven Personalization, Customer Retention, E-Commerce Analytics, Consumer Trust and Satisfaction, Personalized Recommendation Systems.

📄 Download Full Text PDF

DOI: 10.66710/ijersem.v2si1.28

Open Access • Peer Reviewed Article

References

  1. H. Turki, “AI-Powered Personalization in E-Commerce: Governance, Consumer Behavior, and Exploratory Insights from Big Data Analytics,” Technology in Society, vol. 83, p. 103033, Aug. 2025. https://doi.org/10.1016/j.techsoc.2025.103033
  2. H.-C. Lo, W.-J. Chang, and I.-H. Chen, “From Purchase to Return: How Personalized E-Commerce Recommendations Shape Consumer Behavior,” Journal of Retailing and Consumer Services, vol. 88, p. 104459, Aug. 2025. https://doi.org/10.1016/j.jretconser.2025.104459
  3. A. Soy and A. Goswami, “Personalized AI-Based Translation Tools Enhanced for Accurate, Context-Aware Multilingual Text Processing,” Procedia Computer Science, vol. 275, pp. 66–73, Jan. 2026. https://doi.org/10.1016/j.procs.2026.01.009
  4. T. Teepapal, “AI-Driven Personalization: Unraveling Consumer Perceptions in Social Media Engagement,” Computers in Human Behavior, vol. 165, p. 108549, Dec. 2024. https://doi.org/10.1016/j.chb.2024.108549
  5. H. Alserhan, R. Altarawneh, N. Alyami, Y. Alsheyyab, R. Alrababah, and H. Alshamayleh, “The Challenges and Opportunities of Implementing Predictive Analytics in Marketing Strategies and E-Commerce Personalisation Techniques,” Asia Pacific Management Review, vol. 30, no. 4, p. 100409, Sep. 2025. https://doi.org/10.1016/j.apmrv.2025.100409
  6. H. K. L. Chau, T. T. A. Ngo, C. T. Bui, and N. P. N. Tran, “Human-AI Interaction in E-Commerce: The Impact of AI-Powered Customer Service on User Experience and Decision-Making,” Computers in Human Behavior Reports, vol. 19, p. 100725, Jun. 2025. https://doi.org/10.1016/j.chbr.2025.100725
  7. J. A. K. J and P. R. Gotmare, “Impact of Customer Perception of Value Co-Creation for Personalization in Online Shopping,” International Journal of E-Business Research, vol. 18, no. 1, pp. 1–20, Sep. 2022. https://doi.org/10.4018/ijebr.309388
  8. G. Diao, C. Li, Q. Liu, and Z. Liu, “Empirical Study on the Application of Deep Learning in User Behavior Prediction and Personalized Recommendation in E-Commerce,” Journal of Organizational and End User Computing, vol. 37, no. 1, pp. 1–36, Jul. 2025. https://doi.org/10.4018/joeuc.383512
  9. P. M. Nguyen, T. T. M. Hanh, N. P. Hanh, and N. L. Phuong, “E-Service Quality and Customer E-Satisfaction Nexus in the Industry 4.0: Evidence from Vietnam,” Procedia Computer Science, vol. 277, pp. 414–423, Jan. 2026. https://doi.org/10.1016/j.procs.2026.02.083
  10. B. Hemalatha and S. D, “AI-Driven Customer Service and Its Effect on Customer Loyalty and Trust in E-Commerce,” in 2026 5th International Conference on Communication, Computing and Electronics Systems (ICCCES), Coimbatore, India, 2026, pp. 1133–1140. https://doi.org/10.1109/ICCCES62661.2026.11436723
  11. G. Manoharan, R. Gupta, B. B, V. V. Darunkar, S. K. Mishra, and M. Soni, “The Impact of Artificial Intelligence on E-Commerce Customer Experience and Personalization,” in 2025 6th International Conference for Emerging Technology (INCET), Belgaum, India, 2025, pp. 1–5. https://doi.org/10.1109/INCET64471.2025.11140097
  12. R. Vijayalakshmi, S. Velanganni, and M. Aakina Barveen, “E-Commerce and Digital Marketing Trends,” International Journal of Emerging Research in Science Engineering and Management, vol. 2, no. si1, pp. 213–219, May 2026. https://doi.org/10.66710/ijersem.v2si1.27