Volume 2 - Issue 3, May - June 2026

The rapid expansion of e-commerce platforms has resulted in the generation of large volumes of transactional data, creating opportunities for advanced analytics and predictive modelling. Accurate sales forecasting is essential for effective inventory management, demand planning, and strategic decision-making. This paper presents a Machine Learning-Based Intelligent E-Commerce Sales Prediction and Analytics Platform that leverages historical data to generate reliable sales forecasts. The proposed system incorporates data preprocessing techniques, including data cleaning, feature extraction, and encoding, to enhance data quality. An XGBoost-based regression model is employed due to its efficiency and high predictive performance on structured data. The system follows a modular architecture integrating a user-friendly frontend interface, a backend API, and a machine learning model for prediction. Additionally, interactive visualization techniques are used to present insights and trends in an intuitive manner.

Raksha H B, Chiranjeevi M R, "Machine Learning Based Intelligent E-Commerce Sales Prediction and Analytics Platform with Interactive Visualizations" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(3): Page(104-108) May-June 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.