THE ROLE OF DATA ANALYTICS IN ENHANCING E-COMMERCE REVENUE PERFORMANCE IN THE U.S.
DOI:
https://doi.org/10.48047/j9cnt517Keywords:
E-commerce, Revenue growth, predictive analysis, AI personalization, Customer behavior prediction.Abstract
This study explores the growth potential of e-commerce in driving U.S. revenue through a data-driven approach. It examines how technological innovations, changing consumer behavior, mobile commerce, and artificial intelligence (AI) are transforming online shopping. Special focus is given to Gen Z and Millennials, who prefer convenience, mobile-based shopping, personalized recommendations, and the ability to purchase from anywhere. Leading platforms like Amazon and Shopify leverage augmented reality (AR), virtual reality (VR), voice shopping, subscription models, and AI-driven recommendation systems to enhance customer engagement and revenue. The research employs data analytics tools, including word clouds, Voyant tools, concordance analysis, and machine learning models such as Random Forest, LSTM, Support Vector Regression, Isolation Forest, and Convolutional Neural Networks. These methods analyze customer behavior, detect anomalies, forecast trends, and generate personalized suggestions. Historical and projected data from sources like Neural Information Processing Systems and the Cognitive Science Society (1987–2027) indicate that U.S. e-commerce revenue grew from $586.9 billion in 2019 to $792 billion in 2020, with projections reaching $1.5 trillion by 2026. Random Forest excels in classification tasks, while LSTM effectively predicts future trends. Despite challenges such as cybersecurity, logistics, and trust concerns, AI-driven e-commerce demonstrates strong potential to sustain economic growth, enhance the shopping experience, and integrate online and in-store options efficiently. The study concludes that combining data analytics and machine learning can significantly improve decision-making, optimize customer engagement, and strengthen long-term e-commerce performance in the U.S. by combining online and in-store options, and focusing on being eco-friendly.
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