AI-Based Personalized Shopping Assistant report

By offering advice, product recommendations, and recommendations based on a user’s tastes, past purchases, and behaviour, an AI-based personalised shopping assistant aims to improve the shopping experience. The assistant records and examines consumer information, such as browsing habits, past purchases, preferences, and demographics, using machine learning algorithms and data analytics to generate tailored product recommendations and promotions. Natural Language Processing (NLP) enables the assistant to comprehend and reply to consumer enquiries in natural language, directing customers to pertinent items or providing answers to issues concerning compatibility, availability, or cost. Users can upload photographs to find comparable things by integrating computer vision for visual search.As the assistant gains knowledge from user interactions and feedback, its suggestions get becoming more accurate over time. Managing data security, addressing privacy issues, and making sure that recommendations are correct across a variety of user preferences and product categories are among the difficulties. AI-based shopping assistants seek to boost consumer satisfaction, boost conversion rates, and foster customer loyalty by providing a more personalised and engaging shopping experience.