Anonymous Real-Time Customer Feedback Capture via NLP
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Solution Overview
Problem
Existing customer feedback systems fail to capture real-time, anonymous feedback effectively, leading to delayed and biased responses that may lose valuable details and compromise privacy.
Innovation Solution
A system using inconspicuously placed microphones that sequentially sample customer conversations, employing multiplexing and natural-language models to identify key words, translate, and categorize feedback in real-time, preserving anonymity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If customer feedback is collected through traditional surveys (email or phone), then customer privacy is protected, but feedback timing is delayed and details are lost
Solution Approach 1:
The system performs preliminary action by capturing feedback in real-time during the customer interaction itself, rather than waiting for a later survey. Microphones continuously monitor conversations and automatically capture relevant feedback moments as they occur, eliminating the time delay between the experience and the feedback collection.
Solution Approach 2:
The patent replaces the mechanical survey system (email/phone requests) with an automated acoustic detection system. Microphones and natural language processing algorithms automatically capture and analyze customer feedback during interactions, substituting human-initiated survey processes with continuous automated monitoring that preserves both timing and detail accuracy.
2Reliability
If customer feedback is collected through identified surveys, then feedback can be traced to specific customers, but customer anonymity is compromised especially for negative feedback
Solution Approach 1:
The system extracts only the essential feedback information from customer conversations while deliberately leaving out identifying personal data. The natural language processing captures the content, sentiment, and key issues discussed, but strips away names, account numbers, and other identifiers, separating useful feedback data from personally identifiable information.
Solution Approach 2:
The patent introduces an intermediary processing layer between the customer conversation and the feedback database. This intermediary system (natural language processing and filtering algorithms) acts as a mediator that captures feedback essence while filtering out identifying information, protecting customer anonymity while maintaining feedback reliability for actionable insights.
3Area of stationary object
If multiple microphones are used to capture feedback from different locations, then coverage is improved, but system complexity increases
Solution Approach 1:
The patent merges multiple microphone inputs into a unified processing system. Rather than treating each microphone as a separate complex system, the signals from multiple microphones are combined and processed through a single natural language processing pipeline, reducing overall system complexity while maintaining broad spatial coverage for capturing customer feedback.
Solution Approach 2:
The system implements a universal processing architecture that handles inputs from multiple microphones through a single multi-functional platform. The same natural language processing, filtering, and analysis algorithms process data from any microphone in the network, allowing the system to scale coverage area without proportionally increasing processing complexity.
Data Source
AI summary
The invention is a system and method for anonymously capturing customer feedback in real time. Multiplexed voice inputs are converted to digital signal equivalents, translated, interpreted, and categorized. The commentary is judged as to positive or negative perception, and reported as anonymous feedback.