THE ROLE OF ARTIFICIAL INTELLIGENCE IN PERSONALIZING CONSUMER EXPERIENCES: A STUDY ON PREDICTIVE ANALYTICS IN THE E-COMMERCE SECTOR
Keywords:
Artificial Intelligence (AI) in E-commerce, Personalization and Predictive Analytics, Customer Engagement and Loyalty, Ethical AI Practices, and Market Performance OptimizationAbstract
Artificial Intelligence (AI) has completely changed the way companies communicate with customers in the e-commerce industry. This has had a profound impact on customization, customer experience, and market dynamics. This research investigates how customization techniques and predictive analytics might improve customer experiences using AI. Artificial Intelligence (AI) allows e-commerce systems to provide highly customized suggestions by analyzing large datasets created by online consumers. This leads to greater customer happiness, higher conversion rates, and enhanced loyalty. The study also demonstrates the competitive advantage of e-commerce platforms that use AI-driven customization, highlighting their better market performance in a quickly changing digital economy.
But the report also discusses the difficulties and moral questions raised by the use of AI, notably those pertaining to algorithmic prejudice and data privacy. These issues pose serious obstacles to the general use of AI, calling for the creation of moral AI procedures and open decision-making procedures. Future recommendations include expanding AI customization throughout omnichannel shopping, investing in Explainable AI (XAI), developing ethical AI, and continuously innovating AI systems to stay competitive.
The results highlight the strategic significance of AI in contemporary e-commerce and provide useful guidance to companies wishing to use AI technology to improve customer experiences and outperform competitors in the market. This study adds to the continuing conversation about how artificial intelligence will influence e-commerce in the future by providing insightful advice for companies attempting to manage the challenges associated with adopting AI.
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References
• Bhuiyan, M. S. (2024). The role of AI-enhanced personalization in customer experiences. Journal of Computer Science and Technology Studies, 6(1), 162-169.
• Gupta, C. P., Kumar, V. R., & Khurana, A. (2024, February). Artificial Intelligence application in e-commerce: Transforming customer service, personalization, and marketing. In 2024 11th International Conference on Computing for Sustainable Global Development (INDIACom) (pp. 10-16). IEEE.
• Ifekanandu, C. C., Anene, J. N., Iloka, C. B., & Ewuzie, C. O. (2023). Influence of artificial intelligence (AI) on customer experience and loyalty: Mediating role of personalization. Journal of Data Acquisition and Processing, 38(3), 1936.
• Krishnan, C., & Mariappan, J. (2024). The AI revolution in e-commerce: Personalization and predictive analytics. In Role of Explainable Artificial Intelligence in E-Commerce (pp. 53-64). Cham: Springer Nature Switzerland.
• Pardeshi, K., Pathak, P., & Alsadoon, Z. (2023, September). Applications of artificial intelligence and machine learning in e-commerce. In AIP Conference Proceedings (Vol. 2736, No. 1). AIP Publishing.
• Raji, M. A., Olodo, H. B., Oke, T. T., Addy, W. A., Ofodile, O. C., & Oyewole, A. T. (2024). E-commerce and consumer behavior: A review of AI-powered personalization and market trends. GSC Advanced Research and Reviews, 18(3), 066-077.
• Tran, M. T. (2024). Unlocking the AI-powered customer experience: Personalized service, enhanced engagement, and data-driven strategies for e-commerce applications. In Enhancing and Predicting Digital Consumer Behavior with AI (pp. 375-382). IGI Global.
• Upreti, K., Gangwar, D., Vats, P., Bhardwaj, R., Khatri, V., & Gautam, V. (2023, August). Artificial neural networks for enhancing e-commerce: A study on improving personalization, recommendation, and customer experience. In International Conference on Electrical and Electronics Engineering (pp. 141-153). Singapore: Springer Nature Singapore.
• Amazon.com, Inc. (2024). Annual Report 2023. Retrieved from https://www.amazon.com/-investor-relations/annual-reports
• Alibaba Group. (2024). Harnessing AI for personalized e-commerce experiences. Retrieved from https://www.alibabagroup.com/en/about/innovation/ai-personalization
• Netflix, Inc. (2024). Personalized Content Recommendations: Leveraging AI to Enhance Viewer Experience. Retrieved from https://www.netflix.com/research/personalization
• Chen, H., Chiang, R. H. L., & Storey, V. C. (2019). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165-1188. https://doi.org/10.2307/41703472
• Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108-116.
• Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137-144. https://doi.org/10.1016/j.ijinfomgt.2014.10.007
• McCarthy, J., Minsky, M. L., Rochester, N., & Shannon, C. E. (2006). A proposal for the Dartmouth Summer Research Project on Artificial Intelligence, August 31, 1955. AI Magazine, 27(4), 12-14.
• Pariser, E. (2011). The filter bubble: What the Internet is hiding from you. New York, NY: Penguin Press.
• Smith, A., & Anderson, M. (2018). AI, robotics, and the future of jobs. Pew Research Center. Retrieved from https://www.pewresearch.org/internet/2018/03/14/ai-robotics-and-the-future-of-jobs/
• Stone, P., Brooks, R., Brynjolfsson, E., Calo, R., Etzioni, O., Hager, G., & Press, G. (2016). Artificial intelligence and life in 2030: Onehundred year study on artificial intelligence. Stanford University. Retrieved from https://ai100.stanford.edu/2016-report.