Sales performance analysis for retail business using machine learning and Power BI

Abstract

Sales performance analysis is vital for retail businesses to boost revenue and make informed decisions. This study applies machine learning models like Regression, XGBoost, and Decision Tree to predict sales trends and uncover key factors such as pricing, seasonality, and customer behavior. While Regression highlights linear patterns, XGBoost improves prediction through boosting, and Decision Trees enhance interpretability. Results are visualized in Power BI dashboards for real-time sales monitoring, enabling better demand forecasting, inventory management, and marketing. This AI-powered integration streamlines analysis, automates reporting, and supports data-driven strategies, ultimately improving profitability and operational efficiency.