Abstract:

Online shopping is the most common trend for obtaining products delivered to people's doorsteps. Consumers consistently strive to find the best products within their price range. Users browse numerous websites, which takes a high time, to look up product prices and offers. Products on e-commerce websites frequently alter in price. It becomes challenging for users to keep track of costs and choose the best online offer. So, we proposed a Customer Targeted E-Commerce application that uses a web scraping technique. It is a user-friendly ecommerce application designed in such a way that the application gathers all the required information, like names, features, prices, reviews, and ratings of particular products, from all the websites. Sentiment analysis done on reviews. A string-matching algorithm is applied to find the similarity in the features of those products, and among these similarly featured products, the best is figured out based on reviews, ratings, and price. The application includes a rule-based chatbot to interact with and help users with price analysis negotiation, commonly called "Price Negotiation." Customers can also provide feedback on our application either in the form of reviews or ratings. Our application prioritizes both customer and seller happiness

Description:

Web scraping, Rule-based chatbot, Review analysis, Electronic commerce, Selenium