Abstract

Author:
Binaebi Gloria Belloa, Ganiyu Bolawale Omotoyeb, Azeez Jason Kess-Momohc, Sunday Tubokirifuruar Tulad, Andrew Ifesinachi Daraojimbae

Doi: 10.26480/bosoc.01.2024.32.39

This is an open access article distributed under the Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

The rapid evolution of e-commerce platforms has intensified the need for effective data analytics strategies to enhance user experiences and drive business growth. This paper presents a comprehensive review of advanced data analytics techniques employed in the realm of e-commerce, with a specific focus on personalized strategies. The objective is to understand how personalization techniques contribute to business growth and customer satisfaction. The review encompasses a diverse range of personalization methods, including collaborative filtering, content-based filtering, and hybrid approaches. Each technique is examined in terms of its applicability, strengths, and limitations within the e-commerce context. Additionally, the paper explores the integration of emerging technologies such as machine learning and artificial intelligence in refining personalization strategies, thereby providing a forward-looking perspective on the future of e-commerce analytics. Furthermore, the impact of personalized approaches on key performance indicators, such as conversion rates, customer retention, and revenue generation, is thoroughly analyzed. Case studies and real-world examples are incorporated to illustrate successful implementations of
personalization techniques in various e-commerce domains. The findings highlight the pivotal role of advanced data analytics in tailoring the online shopping experience to individual preferences, fostering customer loyalty, and ultimately driving business growth. The paper concludes with a discussion on the challenges and ethical considerations associated with implementing personalized strategies, offering insights into potential avenues for future research in this dynamic and evolving field. Overall, this review contributes
to a deeper understanding of the symbiotic relationship between advanced data analytics, personalization techniques, and the sustained success of e-commerce enterprises.