AI Virtual Support Agent for Proficiency-Based Routing
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Solution Overview
Problem
Current customer support systems face inefficiencies due to repetitive questions, leading to wasted time and negative customer satisfaction, as customers are often routed to support agents with inadequate expertise, resulting in suboptimal problem resolution.
Innovation Solution
Implementing an AI virtual support agent that assesses customer proficiency through a Customer Proficiency Rating, providing personalized customer experiences by assigning support agents based on the customer's skill level, using machine learning to optimize agent allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current support systems route customers to available agents without assessing customer proficiency, then support agents can be allocated quickly, but customers are often routed to agents with inadequate expertise, resulting in suboptimal problem resolution and negative customer satisfaction
Solution Approach 1:
The system performs preliminary assessment of customer proficiency and problem characteristics before routing to support agents. The AI virtual support agent evaluates customer statements and calculates proficiency ratings in advance, so that when customers are routed to human agents, the matching has already been optimized, avoiding wasted time on incompatible pairings.
Solution Approach 2:
An AI virtual support agent is introduced as an intermediary between customers and human support agents. This intermediary assesses customer proficiency, asks clarifying questions, and makes initial routing decisions, thereby improving the quality of human-agent interactions and reducing time losses from mismatched assignments.
2Measurement precision
If support systems ask multiple questions to assess customer proficiency, then more accurate agent matching can be achieved, but customers and service providers waste time with repetitive questions
Solution Approach 1:
The AI virtual support agent performs multiple functions simultaneously: it assesses customer proficiency, gathers problem details, asks clarifying questions, and prepares routing recommendations. By consolidating these tasks into a single multi-functional system, the patent avoids repetitive questioning while achieving accurate assessment.
Solution Approach 2:
The system uses feedback from customer responses to dynamically adjust the assessment process. The AI analyzes customer statements and responses in real-time, calculating proficiency ratings based on the information provided, which reduces the need for extensive repetitive questioning while maintaining assessment accuracy.
3Adaptability or versatility
If manual assessment of customer proficiency is performed, then personalized support can be provided, but the complexity and time required for assessment increases
Solution Approach 1:
The patent replaces manual mechanical assessment processes with an automated AI-based system. The AI virtual support agent automatically calculates customer proficiency ratings using algorithms that analyze customer statements and responses, eliminating the need for manual assessment while providing personalized support experiences.
Solution Approach 2:
The system enables self-service assessment where the AI virtual support agent autonomously evaluates customer proficiency without requiring human intervention. The AI asks questions, analyzes responses, calculates proficiency ratings, and makes routing decisions independently, reducing system complexity from the human operator perspective while maintaining personalized service.
Data Source
AI summary
Embodiments of the present disclosure provide methods, systems, and computer program products for assigning and dynamically managing a Customer Proficiency Rating for a specific customer for implementing enhanced customer support operations for a supported product or service. Disclosed embodiments provide an AI virtual support agent that receives a customer support request for a current problem, obtains a customer statement of understanding for the current problem and provides a set of questions, to obtain customer responses. In an embodiment, the AI virtual support agent evaluates the customer statement and customer responses, and calculates a customer proficiency rating for a specific customer for the support request to identify a customer skill level for the current problem. The AI virtual support agent routes customers to an optimal human support agent based on the customer proficiency rating.