Intelligent Inquiry Resolution Control System for Agent Selection
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Solution Overview
Problem
Conventional client inquiry systems are inefficient in selecting the appropriate agent to resolve customer issues, often taking more time than the agent needs to resolve the issue, and they typically require structured forms that do not accommodate free-form natural language communications, leading to frustration for both clients and providers.
Innovation Solution
A computerized method that parses natural language inquiries to identify issues, determines relevant parameters and context, and selects a qualified agent from a pool based on agent qualifications and conditions, using a test to ensure high client satisfaction, while dynamically updating data repositories for improved efficiency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional agent selection systems are used, then agent assignment can be made, but the selection process takes more time than the agent needs to resolve the issue
Solution Approach 1:
The system pre-processes and structures client inquiries into standardized data fields with identified issues, parameters, and context before agent selection. This preliminary structuring of natural language data enables rapid agent matching without time-consuming analysis during the selection process itself.
Solution Approach 2:
The patent introduces an intermediary processing layer that converts unstructured natural language inquiries into structured data formats with identified issues, parameters, and context. This intermediary structure serves as a bridge between client communication and agent selection, enabling efficient matching without direct time-consuming analysis.
2Ease of operation
If structured forms are required for client inquiries, then data can be systematically processed, but client frustration increases due to lack of freedom in communication
Solution Approach 1:
The system dynamically changes the parameters of data processing by adapting to different natural language structures and styles. Instead of requiring fixed form parameters, the system extracts and structures relevant parameters (issues, context, metadata) from variable natural language inputs, maintaining both client freedom and processing reliability.
Solution Approach 2:
The patent creates a universal data structure that can accommodate multiple forms of natural language communication while maintaining systematic processing capabilities. The structured data format with issues, parameters, and context fields serves as a multi-functional intermediary that works with diverse client input styles without requiring specific form templates.
3Adaptability or versatility
If natural language parsing is performed to identify issues, then client communication freedom is maintained, but system complexity increases
Solution Approach 1:
The system segments the complex natural language processing task into distinct components: identifying issues, extracting parameters, and determining context. Each segment is handled by specialized processing logic that converts natural language into structured data fields, reducing overall system complexity through functional decomposition.
Data Source
AI summary
Aspects of the disclosure provide a computerized method and system that intelligently selects a qualified agent who is available to timely resolve a client issue that was expressed to a processor in a free form natural language communication. In examples, agent selection is accomplished from beginning to end, free from human involvement. Further, unique feedback functionalities are provided, which improve selection functionality by electronically recognizing trending resolution preferences and adapting the provided computerized method and system based thereon.