Enhancing Customer Experience in E-Commerce Through AI-Powered Personalization: A Case Study

Abstract

Aim: This study is intended to engage in the in-depth study of AI-enabled personalization tactics on the quality of customer experience as competition informs the e-commerce environment. The research employs a case study assessment of a prominent world-wide retailer with the primary aim of revealing the dominant influence of cutting-edge AI personalisation technology in actual applications. Methods: The study applied the mixed-methods research, which was made up of quantitative as well as qualitative research techniques such as sound data analysis and field research approaches to arrive at a comprehensive apprehension of the phenomenon. Data science system features such as studying key customer behaviour metrics, conversions, average order, customer value, and satisfaction, appreciate the company's case from superior data systems. The qualitative side of this study was indicated through the revelation of in-depth interviews that were done with a group of educated customers and an extensive online survey that was designed to capture their preferences, opinions, and perceptions in relation to the personalized shopping experience(Gao & Liu, 2022b). Results: The result shown a superlative boost in a lot of customer experience metrics, such as loyalty, proactivity, predictability, and automation, after the execution of the advanced AI personalization engine. What need to be prominently mentioned is an increase of conversion rate which saw a hike by 25% endorsing the fact that now, more customers on the site would complete their purchase process. Also, there was a remarkable 17% increase in the average order value, showing that personalized suggestions and tailor-made experiences had an impact on how customers would spend more per time they place an order. Customer’s life-time value (CLV) was extended by 12%. User stayed loyal and engaged for the longer time period. This probably was the most impressive outcome of the brand's satisfaction scores, as the jumps of them by 22% show the improvement of the customer experience overall. The analysis of qualitative data reveals that consumers experience genuine appreciation of the personalized shopping experience they get from being offered items that match their personal attributes such as the in-depth interpretations of customer likes and dislikes which the algorithm platform uses, quick discovery of products with minimal scrolling, saving of the time used in the search phase, and emotional closeness to freedom/ your identity, in the case of fashion (Raji et al., 2021). Conclusion: This comprehensive case study provides compelling evidence of the transformative potential of AI-powered personalization in enhancing customer experience within the e-commerce landscape. By leveraging advanced machine learning algorithms and vast customer data repositories, businesses can deliver highly tailored content, product recommendations, and optimized search results that resonate deeply with individual customer preferences and needs. The findings demonstrate that implementing AI personalization strategies can drive improved customer engagement, increased sales, and foster long-term loyalty, ultimately conferring a significant competitive advantage in the rapidly evolving e-commerce industry.