Venue Zone Notification System Using Interaction Matching
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Solution Overview
Problem
Existing location-based services (LBS) struggle to effectively send notifications to mobile devices based on user interactions and location within specific zones of a venue, such as when a user interacts with products, leading to missed opportunities for targeted promotions.
Innovation Solution
A computer-implemented method and system that receives floor area, zone, trigger interaction, and notification data, determining if user interactions match zone and location data to automatically send notifications to mobile devices regarding product purchases, using machine learning to optimize promotional actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If location-based services send notifications based on user location and interactions, then customer engagement and purchasing experiences are enhanced, but the system complexity and data processing requirements increase
Solution Approach 1:
The venue floor area is divided into multiple zones with specific characteristics (e.g., high-margin product zones, promotional zones). Each zone has predefined trigger interactions and associated notifications. This segmentation allows the system to manage complexity by handling zone-specific rules independently rather than processing all possible user interactions globally.
Solution Approach 2:
The system pre-configures zone data, trigger interaction data, and notification data before deployment. When a user enters a zone and performs a trigger interaction, the system simply matches the interaction against predefined rules and sends the corresponding notification, rather than making complex real-time decisions about what notification to send.
2Measurement precision
If the system monitors user location and interactions in real-time, then notification accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The system monitors only the specific parameters needed for zone matching (location coordinates and predefined trigger interactions) rather than all possible user actions. This selective monitoring reduces processing overhead while maintaining accuracy for the intended application.
Solution Approach 2:
The system uses mobile device location data and interaction data that are already being collected by the device's operating system and applications. Rather than creating new sensing mechanisms, the patent leverages existing data streams from the mobile device to determine zone presence and trigger interactions.
3Productivity
If the system sends notifications based on multiple criteria (location, interactions, products), then promotional effectiveness increases, but data processing and matching complexity increase
Solution Approach 1:
Each zone is assigned specific trigger interactions and notification templates based on its characteristics and the products available in that zone. The system matches user interactions against zone-specific rules rather than evaluating all possible interactions against all zones, reducing computational complexity while maintaining promotional effectiveness.
Solution Approach 2:
The mobile device itself performs initial data collection and transmission of location and interaction information to the venue system. The venue system then performs straightforward matching against predefined zone rules and sends notifications, distributing the processing workload and simplifying the central system's task.
Data Source
AI summary
Methods, computer program products, and systems are presented. The methods include, for instance: receiving, by one or more processor, floor area data, zone data, trigger interaction data, and notification data associated with the products offered for sale in the different zones. The method can include receiving, by the one or more processor, triggering event data regarding a product or products in response to user interaction with a mobile device in the venue and location data of the mobile device in the venue at the time of the triggering event data, automatically determining whether the received triggering event data and the received location data match an associated zone data and trigger interaction data, and automatically sending an associated notification to the mobile device regarding purchase of a product or products in the venue.