Abstract
The rapid growth of e-commerce has necessitated the adoption of advanced data analytics to remain competitive. Predictive analytics, which leverages historical data to forecast future trends, offers e-commerce businesses a significant edge in decision-making. This paper explores the application of predictive analytics in e-commerce, focusing on its impact on inventory management, customer behavior analysis, and sales forecasting. By integrating machine learning algorithms and big data techniques, e-commerce businesses can maximize their operational efficiency and enhance customer satisfaction. The findings underscore the transformative potential of predictive analytics in driving business outcomes.
Cite
CITATION STYLE
Jakkula, A. R. (2023). Predictive Analytics in E-Commerce: Maximizing Business Outcomes. Journal of Marketing & Supply Chain Management, 1–3. https://doi.org/10.47363/jmscm/2023(2)158
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