AR intelligent shopping guide interaction method and system applied to store management

By acquiring and analyzing user interaction data in stores, generating AR shopping guide interactive content and integrating it with physical scenes, it solves the lack of personalization of traditional shopping guide methods and the immersive experience problem of existing systems, and realizes a personalized and efficient shopping experience.

CN120338933BActive Publication Date: 2025-10-03SHANGHAI PINSHANG LIFE NETWORK TECHNOLOGY CO LTD +1
5 Cites 0 Cited by

Patent Information

Application Number
CN202510822200.3
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-06-19
Publication Date
2025-10-03
Estimated Expiration
2045-06-19

AI Technical Summary

Technical Problem

Traditional store shopping guides rely on manual services and find it difficult to provide consistent and high-quality personalized shopping recommendations. Existing electronic shopping guide systems lack in-depth analysis of customer behavior and integration with physical scenarios, resulting in insufficient customer experience.

Method used

By acquiring user interaction data within the store, including location movement trajectories, product attention action sequences, and voice consultation content, we analyze user intent, generate AR shopping guide interaction content, spatially align and integrate it with the physical scene, and adjust the interaction process in real time to optimize the user experience.

Benefits of technology

It provides personalized shopping suggestions, enhances users’ immersive shopping experience and the accuracy of shopping guides, and improves store operational efficiency and customer satisfaction.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The present invention provides an AR smart shopping guide interaction method and system for store management. First, a user interaction data set in the store is obtained, covering the user's location movement trajectory, product attention action sequence and voice consultation content. Then, the interaction data set is analyzed for user intention to obtain product demand characteristics and interaction preference characteristics. Based on the product demand characteristics and interaction preference characteristics, AR shopping guide interaction content adapted to the user is generated, including three-dimensional product display information and interaction guidance instructions. The AR shopping guide interaction content is aligned and integrated with the store's physical scene space to generate an AR shopping guide interaction scene that can be displayed in real time. Finally, in response to user interaction operations in the AR shopping guide interaction scene, feedback information is generated and the interaction data set is updated to trigger iterative optimization of the interaction process, thereby providing a personalized and immersive shopping guide experience and improving store operation efficiency and customer satisfaction.
Need to check novelty before this filing date? Find Prior Art