SHOPSAGE: SMART E-COMMERCE WISHLIST WITH DYNAMIC PRICE PREDICTION AND COMPARISON ENGINE

Abstract

The exponential growth of e-commerce has revolutionized shopping habits by offering diverse options and competitive pricing. However, price variations across platforms often lead to confusion among consumers seeking the best deal. To address this, the proposed system ShopSage introduces a smart ecommerce wishlist and price comparison engine that leverages machine learning and data mining techniques to analyze, track, and predict product prices in real time. The system aggregates data from multiple online retailers, providing users with dynamic insights into pricing trends, discounts, and optimal purchase timings. By integrating web scraping, predictive analytics, and recommendation algorithms, ShopSage not only compares current prices but also forecasts future price drops. The platform empowers users to make informed buying decisions while saving time and money. The incorporation of user personalization, real-time alerts, and AI-driven trend analysis positions ShopSage as a next-generation smart shopping assistant for today’s digital consumers.