B Vijay Kumar, Sai Teja, Rathod Atharv, R Sai Charan Reddy, Saniya Meerja 03 09 The Regional Sales Analysis and Prediction system is designed to analyze historical sales data across different geographical regions and predict future sales performance Regional sales can vary due to factors such as customer demand product category pricing seasonality marketing activities and regional market conditions Analyzing these variations helps organizations identify highperforming regions and improve sales planning The proposed system collects historical sales information such as region sales amount quantity sold product category order date profit and customer details The collected data is cleaned and preprocessed before performing exploratory data analysis Statistical analysis and visualization techniques are used to identify regional sales trends compare performance between regions and determine factors influencing sales Machinelearning algorithms such as Linear Regression Random Forest XGBoost and other suitable forecasting models can be used to predict future regional sales Recent research shows that machinelearning models can incorporate multiple input factors for sales forecasting while regional and spatial information can further improve sales prediction and market analysis The prediction results can be evaluated using metrics such as MAE RMSE MAPE and R to determine model performance An interactive dashboard can display regionwise sales profit sales trends topperforming regions and predicted future sales This allows managers to make datadriven decisions regarding inventory marketing resource allocation and sales strategies Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026