Autonomous Customer Service Agent Narrative Extraction
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Solution Overview
Problem
Current customer interaction systems, such as IVR, are cost-effective but provide an impersonal and robotic experience, often requiring cumbersome authorization processes and are inefficient due to high wait times and limited ability to handle complex customer issues.
Innovation Solution
An autonomous system that extracts customer narratives from utterances to identify and respond to problems, using processors and memory to perform methods that include generating solutions and updating narratives based on customer interactions, without the need for human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If human customer service representatives are used, then customer experience is personalized and efficient, but operational costs increase substantially
Solution Approach 1:
The system enables customers to interact with an autonomous agent that handles account servicing independently. The agent extracts customer narratives from utterances, identifies problems autonomously, and executes solutions without human intervention, allowing the system to serve itself and reducing dependency on human representatives.
Solution Approach 2:
The patent replaces the mechanical system of human customer service representatives with an autonomous intelligent agent. The agent uses natural language processing to understand customer narratives, extracts problems, and executes solutions, substituting human mechanical interaction with an automated intelligent system that reduces operational costs while maintaining service quality.
2Loss of energy
If IVR systems are used, then operational costs are reduced, but customer experience becomes impersonal and robotic
Solution Approach 1:
The system changes the fundamental parameters of automated customer service by transitioning from scripted, predetermined responses to dynamic, narrative-based interactions. The autonomous agent extracts customer narratives, understands context and emotions, and generates personalized responses, fundamentally altering how automated systems interact with customers while maintaining cost efficiency.
Solution Approach 2:
The patent introduces dynamics into automated customer service by enabling the system to adapt its responses based on extracted customer narratives. The agent dynamically adjusts its interaction style, problem identification approach, and solution execution based on the unique context of each customer situation, making the experience more personalized and less robotic.
3Reliability
If scripted IVR systems are used, then authorization processes are standardized, but each customer-service session requires cumbersome authorization steps
Solution Approach 1:
The autonomous agent performs preliminary actions by extracting and understanding customer narratives before executing any authorization processes. By comprehending the full context of the customer's situation upfront, the system can identify and execute authorizations more efficiently, reducing the number of sequential authorization steps required while maintaining consistency and reliability.
4Adaptability or versatility
If human representatives are staffed, then complex customer issues can be handled effectively, but wait times increase and efficiency decreases
Solution Approach 1:
The autonomous agent handles complex customer issues through self-service capabilities, independently extracting narratives, identifying problems, and executing solutions without requiring human representative intervention. This eliminates wait times associated with human availability while maintaining the ability to handle complex issues, thereby improving account servicing efficiency significantly.
Data Source
AI summary
Consistent with the disclosed embodiments, systems and methods are provided herein for autonomously responding to customer problems. In one example implementation, a system performing a method is provided. The system may receive a customer utterance associated with a customer and define, based on the customer utterance, a first customer narrative comprising a first customer goal. The system may also determine whether the first customer narrative is sufficient to identify a first customer problem corresponding to at least a first problem of a plurality of problems. Responsive to determining that the first customer narrative is sufficient, the system may identify a first response corresponding with the first problem. The system may also customize the first response for the customer based on at least the first customer narrative, and execute the customized response.


