Internet purchasing is booming in the current e-commerce landscape. As a result, there is room for advancement in product recommendation systems. Because users need a connection to the system. The user experiences personalised attraction as a relationship progresses. The technology encourages customers to return and spend more money in addition to monitoring and analysing their purchasing behaviour. The tiresome task of people looking through endless categories for what they want is eliminated by the suggestion system. Instead, they use the conversation to weed out superfluous information and provide the consumer what they want. Online shopping provides many benefits, but there are also restrictions and disadvantages that need to be taken into account. The consumer can be upset if the requested product and the one actually received do not always match. Enhancing the current functioning of these systems has become essential since customer requirements change on a regular basis. The history of internet shopping indicates that there will soon be a big need for recommendation systems. A conversational bot that recommends things to customers based on their requirements is being introduced by research. With little user input, the chat bot effectively processes orders and suggests the best item. The product database is utilised in this instance, however this may be done on a much larger scale. The consumer communicates details about the scent to the chatbot. Based on the user’s description, it will also suggest relevant items.