Location-Based Prompting System for Physical Item Discovery
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Solution Overview
Problem
Users face challenges in discovering new physical item preferences, especially with the decline of traditional retail experiences, as online retailers struggle to replicate the engagement and discovery processes of physical item venues.
Innovation Solution
A system that utilizes location-based services and artificial intelligence to prompt users when they are near item venues, allowing them to engage with physical items, gather feedback, and determine preferences, enabling targeted promotions and item acquisition recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If online retailers use traditional digital marketing methods, then they can reach users, but they fail to replicate the engagement and discovery processes of physical item venues
Solution Approach 1:
The patent introduces location-based services and mobile devices as intermediaries between online retailers and users. The system uses geographic location data as a mediator to trigger contextual promotions when users are near physical item venues, bridging the gap between digital marketing and physical discovery experiences
Solution Approach 2:
The system changes the parameter of marketing delivery from static digital ads to dynamic location-triggered promotions. By monitoring user location and triggering promotions based on proximity to item venues, the system transforms the engagement model to replicate physical venue discovery processes
2Productivity
If the system sends prompting data to all users, then more users may be engaged, but resource consumption and system complexity increase
Solution Approach 1:
The patent applies local quality by sending prompting data only to users who meet specific location criteria (being near item venues). Instead of universal messaging, the system tailors promotion delivery to specific geographic contexts, reducing overall resource consumption while maintaining high engagement rates among targeted users
Solution Approach 2:
The system performs preliminary actions by pre-defining geographic zones around item venues and pre-configuring promotion rules. When users enter these predefined zones, the system automatically triggers appropriate promotions, eliminating the need for real-time decision-making and reducing computational resource consumption
3Adaptability or versatility
If the system collects and analyzes user feedback data, then personalized promotions can be provided, but data processing complexity and time increase
Solution Approach 1:
The patent implements feedback mechanisms where user responses to prompting data are collected and analyzed. The system examines feedback data to understand user preferences and behavior patterns, then uses this feedback to refine and personalize subsequent promotion delivery, creating a continuous improvement loop
Solution Approach 2:
The system performs preliminary data processing by pre-analyzing user feedback patterns and establishing preference profiles in advance. This preliminary action reduces the computational burden during real-time promotion delivery, enabling fast personalization decisions without excessive processing time
Data Source
AI summary
Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: responsive to a determination that a mobile client computer device is at a location of an item venue, sending to the client computer device prompting data, wherein the client computer device is associated to a user; examining feedback data defined by the user, wherein the feedback data is defined by the user in response to the prompting data; and transmitting to the mobile client computer device second prompting data in dependence on the examining feedback data defined by the user.