Passive Customer Ratio Detection via Mobile Signal Analysis
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Solution Overview
Problem
Current methods fail to accurately differentiate between visitors and customers in a merchant location, making it difficult for merchants to determine the number of actual purchasers, their paths, and dwell times within the store, which hampers efficient store operations and employee scheduling.
Innovation Solution
A system that uses signals emitted from mobile devices to determine visitor geographic information and status by capturing unique identifiers and signal strengths, allowing for the tracking of visitor paths and dwell times, and correlating this data with transaction information to identify actual customers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional visitor counting methods are used, then the number of visitors can be tracked, but the differentiation between visitors and actual customers is insufficient
Solution Approach 1:
The system segments visitors into different categories (prospective customers vs. actual customers) by analyzing their behavior patterns, dwell time, and transaction correlations. This segmentation enables precise identification of actual customers while maintaining information about all visitor types.
Solution Approach 2:
The patent uses mobile device signals as an intermediary to track and differentiate visitors. By capturing unique device identifiers and analyzing signal patterns, the system can distinguish between different visitor types without direct intervention, resolving the information loss problem.
2Loss of information
If detailed tracking of visitor paths and behavior is implemented, then customer behavior information is obtained, but system complexity increases
Solution Approach 1:
The system uses a universal approach by leveraging existing mobile device signals that visitors already carry. This multi-functional system not only tracks visitor paths and behavior but also enables customer identification, dwell time analysis, and purchase pattern recognition without requiring separate specialized tracking devices for each function.
Solution Approach 2:
The tracking system utilizes the visitor's own mobile device as the tracking tool. The mobile device's inherent radio emissions are captured and analyzed, eliminating the need for complex external tracking infrastructure. The visitor essentially serves their own tracking through their device's normal operations.
3Productivity
If passive signal capture from mobile devices is used, then visitor tracking is enabled, but signal strength variations affect measurement accuracy
Solution Approach 1:
The system compensates for signal strength variations by analyzing multiple parameters simultaneously rather than relying on signal strength alone. By combining unique device identifier matching with transaction data correlation and behavioral pattern analysis, the system transforms the variable signal strength parameter into a reliable tracking mechanism that maintains both productivity and precision.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables merchants to efficiently manage store operations by accurately determining the ratio of customers to visitors, optimizing employee scheduling and store layout, and improving customer service through real-time data analysis.
Implementation Method 1
receiving, by the processor, a hello message from a radio associated with one or more handheld devices
Data Source
AI summary
A method and system for determining a status of a visitor to a physical location and associated with a handheld device using a computer device coupled to a database are provided. The method includes receiving, by the processor, a hello message from a radio associated with one or more handheld devices, capturing a unique identifier of the handheld device from the received hello message, determining visitor geographic information based on the captured unique identifier and a determined signal strength of the hello message, and outputting the visitor information.