RETAILER LINKED DIALOGUES: CHATTING, CARTING, AND CARING

Smart overview of the Invention

The patent application focuses on a deep learning method designed to enhance search and dialogue capabilities. It leverages advanced models to connect search engines with external and factual knowledge available on the internet. This approach aims to gather relevant information about products, including their price, reviews, and features, thereby enriching the user experience with comprehensive data.

Integration with Dialogue Systems

A significant aspect of the method is its ability to integrate retrieved knowledge with dialogue history. This integration allows for more informed and contextually relevant responses within conversational interfaces. By doing so, the system supports improved interaction quality and user satisfaction in digital conversations.

Connection with Retail Platforms

The application highlights a novel connection between Alexa socialbots and the Amazon Store. This linkage enables a variety of new functionalities, such as enhanced product recommendations and conversational shopping guidance. Users can benefit from a seamless experience where product queries are addressed with precision and relevance.

Advanced Shopping Features

Beyond basic inquiries, the system can automatically seek out new product types based on user interactions and preferences. This feature provides a dynamic shopping experience that adapts to individual user needs, offering personalized suggestions that align with their purchasing habits and interests.

Personalization and User Engagement

The method's emphasis on personalization is evident in its ability to tailor responses and recommendations according to user-specific data. By understanding user preferences through dialogue history and search behavior, the system enhances engagement and fosters a more interactive and satisfying shopping journey.