Smart Price Comparison and Best Deal Prediction

Abstract

The rapid growth of online retail platforms has created a need for efficient tools that assist consumers in identifying the most economical purchasing options. This paper presents a Smart Price Comparison Assistant, an intelligent web-based system developed to compare product prices across multiple e-commerce platforms and support informed buying decisions. The proposed solution integrates a Python-based backend for data processing, React and Node.js for interactive frontend and server-side functionalities, and MongoDB for scalable data management.The system enables users to search for products and receive consolidated results from different online marketplaces through an intuitive interface. To improve comparison accuracy, machine learning techniques are employed to recognize equivalent or closely related products even when naming conventions, specifications, or listing formats differ across platforms. In addition, the system examines historical and real-time pricing patterns to estimate favorable purchasing periods, allowing users to optimize spending.Beyond price analysis, the platform incorporates product ratings, customer reviews, discount availability, and seller credibility indicators to promote transparency and trust. The architecture is designed to ensure responsiveness, scalability, and efficient retrieval of updated information. By minimizing the time and effort required for manual price comparison, the proposed assistant offers a practical and data-driven approach to modern online shopping.The Smart Price Comparison Assistant demonstrates how intelligent analytics, predictive modeling, and user-centered design can enhance digital commerce experiences by delivering cost-effective recommendations and simplifying purchasing decisions.