Facial Recognition Data Bridge for Anonymous Browser Correlation
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Solution Overview
Problem
Current technologies lack effective methods to correlate and attribute anonymous website visitors to their subsequent in-store visits, leading to a disconnect between online and in-person sales processes and limited cross-selling opportunities between online and physical environments.
Innovation Solution
A system and method that utilize sensor data collection, facial and speaker recognition, and neural network technology to identify and correlate anonymous online users with their in-person interactions at physical stores, enabling personalized experiences and seamless sales continuity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If anonymous browsing is maintained to protect user privacy, then user privacy is preserved, but the ability to correlate online visitors with in-store customers is lost
Solution Approach 1:
The patent introduces facial recognition technology as an intermediary mechanism that bridges the gap between anonymous browsing and identified in-store customer data. The system captures facial images at both online and offline touchpoints, using the facial recognition data as a mediator to correlate anonymous web visitors with identified in-store customers without requiring traditional personal identifiable information during browsing.
2Loss of information
If traditional tracking methods are used to identify online visitors, then customer attribution is improved, but user privacy and acceptance are reduced
Solution Approach 1:
The patent replaces traditional mechanical tracking systems (cookies, device identifiers, form submissions) with biometric-based facial recognition technology. This substitution enables continuous customer identification across online and offline channels without requiring users to actively participate in tracking mechanisms, thereby reducing privacy intrusion while maintaining attribution capability.
3Productivity
If online to in-person sales transition is enabled, then sales continuity is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal facial recognition system that serves multiple functions: identifying customers across different channels (online and offline), tracking customer journeys, enabling personalized marketing, and facilitating sales attribution. This multi-functional approach consolidates what would otherwise require separate systems for each function, managing complexity through consolidation rather than proliferation of specialized components.
Data Source
AI summary
Embodiments described herein provide systems and methods for correlating anonymous user data with in-person user sensor data. In some embodiments, a user interacts with a web interface which collects sensor data (e.g., video and audio) and stores that sensor data with other customer information (e.g., browsing history). The collected data is sent to a local interaction device which collects its own sensor data, which is compared to the data in the packets to correlate the in-person user with the online user, and continue the customer experience.