Smart Price Forecasting and Trend Analysis System

E-commerce platforms witness constant and unpredictable price fluctuations that make it difficult for consumers to identify the right moment to purchase a product. This paper presents the Smart Price Forecasting and Trend Analysis System, a full-stack web application that automates product price tracking and generates data-driven purchase recommendations using the AutoRegressive Integrated Moving Average (ARIMA) time-series model. The system scrapes real-time product prices from platforms such as Amazon and Flipkart using BeautifulSoup4, stores historical pricing records in MongoDB, and applies ARIMA (5, 1,0) to produce a 30-day forward price forecast. The React.js frontend presents the forecast through interactive Chart.js visualizations and issues clear Buy Now or Wait recommendations based on predicted price trends. Experimental results confirm that the system accurately identifies short-term price movements and provides actionable consumer guidance, validating the effectiveness of statistical machine learning models for real-world e-commerce price intelligence applications.