Abstract: Disclosed below is a system and method for facilitating search or browse mode and chat mode in an online ecommerce platform. Further, it allows users to switch between both the modes anytime. This enables a user to get product specific answers quickly while browsing, by switching from browse mode to chat mode and asking the chat bot. With the additional information in hand, the user can make a better decision while shopping.

Abstract: Disclosed herein is a system and method for enhancing online shopping experiences through a personalized product discovery platform implemented on an eCommerce platform. This system comprises a memory that stores instructions alongside product data such as attributes, ratings, and user reviews. A processor, configured to execute these instructions, dynamically generates product-specific questions for each user query to facilitate deeper user engagement. The system adapts its questioning and search algorithms based on user responses, enabling a more tailored shopping experience. Additionally, it updates the product database in real-time, reflecting changes based on user interactions and preferences. This innovative approach utilizes advanced machine learning and natural language processing technologies to interpret user inputs and refine interactions, thus offering a more intuitive and personalized user interface.

Abstract: Disclosed below is a system and method for facilitating interactive product inquiry in an online ecommerce platform, which can be accessed from the product page itself. It allows users to switch to an interactive mode, wherein the users can ask any questions they have regarding the products and a conversational agent shall provide appropriate answers. This enables a user to get answers quickly unlike traditional systems. With ease of obtaining information without wasting any time, users can make a better decision while shopping.

Abstract: Disclosed herein is a system and a computer implemented method that aims to improve the quality of product information on an online ecommerce store by enriching the catalog data. This is achieved by analyzing free form user search queries and grouping them into domain clusters. A domain specific context is then generated for each cluster and used to enrich the product catalog data. Each product category in the product catalog data is assigned to a specific domain cluster and enriched with relevant information based on the domain specific context and class relations derived from a product ontology. The goal of this process is to provide more relevant search results for users and improve the overall shopping experience on the ecommerce store.

Abstract: Disclosed are methods, circuits, devices, systems and functionally associated computer executable code for digital catalog augmentation. A digital catalog interface module reads from a digital catalog data storage, directly or indirectly, one or more catalog data records constituting an offer listing within a digital catalog, wherein the offer listing may include a description of a specific product or service offering and/or links to execute a transaction relating to the offering. The system includes a Review Criteria and Sentiment Extractor (RCSE) to identify and convert one or more reviews posted on a review forum into one or more data records used to augment the offer listing within the digital catalog.

Abstract: Disclosed are methods, circuits, devices, systems and functionally associated computer executable code for digital catalog augmentation. A digital catalog interface module reads from a digital catalog data storage, directly or indirectly, one or more catalog data records constituting an offer listing within a digital catalog, wherein the offer listing may include a description of a specific product or service offering and/or links to execute a transaction relating to the offering. The system includes a Review Criteria and Sentiment Extractor (RCSE) to identify and convert one or more reviews posted on a review forum into one or more data records used to augment the offer listing within the digital catalog.

Abstract: Disclosed are methods, circuits, devices, systems and functionally associated computer executable code for digital catalog augmentation. A digital catalog interface module reads from a digital catalog data storage, directly or indirectly, one or more catalog data records constituting an offer listing within a digital catalog, wherein the offer listing may include a description of a specific product or service offering and/or links to execute a transaction relating to the offering. The system includes a Review Criteria and Sentiment Extractor (RCSE) to identify and convert one or more reviews posted on a review forum into one or more data records used to augment the offer listing within the digital catalog.