Real-Time Dynamic Pricing Using Machine Learning: Integrating Customer Sentiment and Predictive Models for E-Commerce.

Authors : Areyfin Mohammed Yoshi, Arafat Rohan, Sohana Afrin Mitu, Md Masud Karim Rabbi, Shahanaj Akther, Khandakar Rabbi Ahmed

Publication date : 2025/9/1

Journal : International Journal of Advanced Computer Science & Applications

Volume : 16

Issue : 9

Description : Dynamic pricing has emerged as a crucial strategy for e-commerce platforms to maximize profitability while remaining competitive in rapidly changing digital markets. Traditional pricing methods often fail to capture the complexity of customer behavior and the rapid evolution of market trends. To address these limitations, this study introduces a machine learning based framework that integrates transactional, behavioral, and contextual data with multilingual sentiment analysis from customer reviews. The framework employs multiple algorithms, including Random Forest, Gradient Boosting, Neural Networks, and XGBoost, with extensive feature engineering and model evaluation. Experimental results on a large-scale retail and e-commerce dataset show that the proposed XGBoost-based approach achieved superior performance, with a Mean Absolute Error (MAE) of 1.29, RootMean Squared Error (RMSE) of 1.65, and …