Method And System For Identifying A User Device In A Premises
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Solution Overview
Problem
Current retail environments lack effective data collection and personalized experiences for consumers, limiting retailers' ability to provide targeted marketing and optimize store layouts.
Innovation Solution
A system that uses ranging sensors and cameras to track user devices within a retail premises, matching user profiles to location data and images, enabling targeted advertising and improving store layouts by analyzing consumer behavior and preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If fixed displays and traditional data collection methods are used, then implementation is simple, but consumer engagement and personalized experiences are limited
Solution Approach 1:
The system segments the retail space into multiple zones with ranging sensors distributed throughout, allowing granular tracking of consumer locations and behaviors in different store areas. This segmentation enables personalized experiences by providing tailored information based on which zone the consumer is in, while keeping each sensor node relatively simple.
Solution Approach 2:
The ranging sensors serve multiple functions: tracking consumer location, identifying products of interest, monitoring dwell time, and enabling personalized advertising delivery. This multi-functionality allows the system to provide adaptive consumer experiences without requiring separate specialized devices for each function, thereby managing complexity.
2Loss of information
If no tracking system is implemented, then system complexity is low, but valuable consumer behavior data is unavailable
Solution Approach 1:
The ranging sensors act as intermediaries between consumers and the retail system, passively collecting location and behavior data without requiring direct interaction with consumers. The sensors mediate the data collection process by detecting signals from consumer devices and translating them into actionable insights about consumer behavior, preferences, and patterns.
Solution Approach 2:
The system enables self-service data collection where consumer devices automatically transmit identification signals that are picked up by ranging sensors. Consumers unwittingly provide their own behavior data through their device signals, eliminating the need for manual data collection methods like surveys or observation, thereby reducing operational complexity while maximizing data availability.
3Productivity
If targeted marketing is implemented without precise location data, then marketing can be generalized, but conversion rates and sales effectiveness are reduced
Solution Approach 1:
The system delivers targeted advertising content based on the consumer's precise local position within store zones. Different zones receive different marketing messages tailored to the products and categories in that area. This local quality approach ensures consumers receive relevant information about products they are actually viewing or near, significantly improving sales effectiveness compared to generalized marketing.
Solution Approach 2:
The system uses real-time location data from ranging sensors to dynamically adjust and deliver targeted advertising content to consumer devices. The feedback loop continuously monitors consumer movement and product interest, then adjusts marketing messages accordingly - showing products consumers are actually viewing or have shown interest in, thereby maximizing conversion rates and sales effectiveness.
Data Source
AI summary
A method and system for identifying a user device in a premises includes communicating identifier signals from a user device to a plurality of ranging sensors disposed within a premises. The identifier signals are associated with a user device identifier. The method includes generating ranging signals at the ranging sensors, communicating the ranging signals to an on-premises store controller, communicating the user device identifier to the on-premises store controller, matching a user profile to the user device identifier, generating a first set of locations of the user device within the premises based on the ranging signals, and generating a plurality of camera signals corresponding to respective store zones. The camera signals comprise images. The method further includes, based on the camera signals, comparing the first set of locations, images and the ranging signals to form a comparison and identifying a user of the user device based on the comparison.