Shoplytics

Abstract

Shoplytics is a smart feedback analysis tool designed to automate the process of gathering and analyzing product reviews from e-commerce websites. By leveraging Python scripts and sentiment analysis models like BERT, it transforms large volumes of unstructured review data into meaningful insights.
The system scrapes user reviews, product prices, and ratings directly from product pages using Selenium, then stores them securely in MongoDB. These reviews are processed to identify sentiment—positive, neutral, or negative—and the results are presented through intuitive visualizations.
Shoplytics eliminates the need for manual data handling, improves analysis accuracy, and enhances the online shopping experience for customers and vendors alike.
Its modular design allows for flexibility, and its centralized data storage ensures organized management of large-scale feedback. By combining web scraping, sentiment classification, and report generation, Shoplytics enables e-commerce platforms to make smarter decisions, boost customer satisfaction, and tailor product recommendations based on actual consumer sentiment.