Sculpting Dynamic Intelligence in E-Commerce Vendor-Customer Relations with Advanced Big Data Analytics Integration - Kundavaram, RamMohan Reddy; Roberts, Charlotte; Onteddu, Abhishake Reddy; Devarapu, Krishna (American Journal of Trade and Policy, 2025)
This study examines how sophisticated big data analytics may improve customization, engagement, and operational efficiency in e-commerce vendor-customer relationships. The study focuses on intelligent e-commerce systems using artificial intelligence, machine learning, and predictive analytics to enhance consumer experiences. The paper synthesizes literature on big data applications, problems, and possibilities in e-commerce using secondary data. Big data offers hyper-personalization, real-time client interaction, and operational improvements, but it also raises data privacy, algorithmic bias, and infrastructure scalability problems. The report also suggests that augmented reality, virtual reality, and blockchain will shape customer interaction. Policy implications call for stronger regulatory frameworks that balance innovation, ethics, privacy, and openness. To maximize big data's potential, firms must invest in IT infrastructure, fill talent gaps, and promote ethical data use. This study concludes that data-driven tactics are crucial to creating intelligent and adaptable e-commerce connections, which affect digital market development, trust, and competitiveness.
Keywords: E-commerce; Vendor-Customer Relations; Big Data Analytics; Artificial Intelligence; Machine Learning; Predictive Analytics; Customer Engagement; Data-Driven Strategies