AI CHATBOARD FOR E-COMMERCE WEBSITE

Abstract

The AI Chatbot for E-Commerce Support is designed to enhance customer service in online shopping platforms by providing automated, intelligent, and real-time responses to user queries. The system is developed using Python and Flask, integrating a machine learning–based chatbot model to understand customer messages and provide appropriate responses based on predefined intents. The chatbot processes user input through natural language preprocessing techniques such as tokenization and bag-of-words representation, enabling the model to classify user queries and return relevant responses stored in the intent dataset. The application also includes a user authentication and management system implemented using SQLite database, allowing users to register, log in, and manage their profiles securely. Once authenticated, users can access a dashboard and interact with the chatbot through a chat interface designed to assist with common e-commerce queries such as product information, order assistance, and general support. The system maintains session management to ensure secure access and smooth navigation across different pages including dashboard, profile, and chatbot interface. By automating customer interaction, the proposed system reduces the need for continuous human support, improves response time, and enhances the overall customer experience. The integration of machine learning with a web-based framework makes the chatbot scalable and efficient for handling multiple user queries simultaneously. This solution demonstrates how intelligent conversational agents can significantly improve support services in modern e-commerce platforms.