Customer Grouping via Detector Station Tracking
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Solution Overview
Problem
Venue operators face challenges in identifying and providing discounts or rewards to associated customers who do not have a mobile phone application, as they cannot determine group membership between connected and non-connected customers within the venue.
Innovation Solution
A system with detector stations and a centralized controller that tracks individuals' locations and generates a confidence level to group connected and associated customers using tracking data, machine learning algorithms, and confirmation processes, allowing for updates to customer accounts and personalized offers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a venue operator uses a mobile phone application to track connected customers, then the operator can provide targeted discounts and rewards, but the operator cannot identify or provide benefits to associated customers who do not have the application
Solution Approach 1:
The patent uses detector stations as intermediaries to track associated customers who do not have the mobile application. These detector stations capture images and data of customers, allowing the system to identify and group associated customers with connected customers without requiring the associated customers to have the application themselves.
Solution Approach 2:
The system creates a digital copy or representation of associated customers through detector station data and images. This allows the system to track and identify associated customers indirectly through their physical presence and characteristics captured by the detector stations, rather than requiring direct interaction through the mobile application.
2Measurement precision
If the operator monitors tracking data of connected customers only, then the system remains simple, but the operator cannot determine group membership between connected and non-connected customers
Solution Approach 1:
The patent divides the tracking system into two segments: detector stations for capturing data of all customers (including associated customers without the application), and the mobile application for connected customers. This segmentation allows the system to handle different customer types through appropriate channels while maintaining overall group identification capability.
Solution Approach 2:
The controller acts as an intermediary that receives and correlates data from both detector stations and mobile applications. It processes image data, tracking information, and application data together to determine group membership, bridging the gap between connected and non-connected customers.
3Adaptability or versatility
If the operator implements a comprehensive tracking system with detector stations and image analysis, then associated customers can be identified, but the system complexity and processing requirements increase significantly
Solution Approach 1:
The system implements feedback through confirmation requests sent to connected customers. When the controller identifies potential associated customers through detector station data, it requests confirmation from the connected customer before finalizing the grouping. This feedback mechanism ensures accuracy while maintaining system automation.
Solution Approach 2:
The system performs partial automation by automatically tracking and identifying potential associated customers through detector stations, but requires manual confirmation only when needed. This approach balances automation efficiency with accuracy, avoiding excessive manual intervention while maintaining high identification capability.
Data Source
AI summary
A system and method for grouping associated customers with connected customers. In various aspects, a controller detects, via data obtained by a plurality of detector stations, a plurality of individuals, including associated and connected customers, entering the venue. The controller monitors, via the data obtained by the plurality of detector stations, a location of each individuals to generate a confidence level that the connected customer and the associated customer are members of a group. The controller determines that the confidence level exceeds a threshold confidence level. In response, the controller updates an account associated with the connected customer based on tracking data associated with the associated customer.