Abstract
Abstract: E-commerce applications are growing and becoming complex day by day. Every new feature is taking the time of the user and reducing the speed or the process of purchasing anything. Consumers demand comfortability, usability, authenticity on E-commerce websites, and hence to provide with these needs Machine learning should be introduced in the E-commerce website. In this paper, we will learn various methods to help boost E-commerce using Machine Learning. Product Recommendation will severely help reduce the time of users on purchasing a product as it recommends products based on history. Cloth size estimation can be used for taking measurements for helping users purchase clothes with accurate measurements. Dynamic Pricing can be used to generate discounts and prices based on user history for maintaining users. Fake Review Prediction can be used to filter the reviews for better business. A chatbot can be used to help users during any stage of purchase or after the purchase as support. All of this can contribute towards the personalized experience of consumers and will be discussed in this paper. Keywords: Ecommerce, Machine Learning, Dynamic pricing, Chatbot, Product Recommendation, Cloth Size Estimation, Fake Review Prediction, Ecommerce
Published Version
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