Post-Conversation Evaluation System for Call Center Agent Performance
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Solution Overview
Problem
Existing systems struggle to effectively evaluate and provide feedback on the performance of call center agents during conversations, leading to monotonous work conditions and lower customer satisfaction due to the difficulty in grasping emotions or sentiments of the other party in telephone interactions.
Innovation Solution
A system and method for post-conversation evaluation using an electronic device that provides performance metrics, including sentiment and tone analysis, to improve agent performance by offering real-time feedback and gamification, allowing agents to monitor and adapt their speech for better engagement and skill development.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If post-conversation evaluation with performance metrics is implemented, then agent performance and customer satisfaction are improved, but system complexity increases
Solution Approach 1:
The system implements automated post-conversation evaluation that provides performance metrics and feedback to agents. The electronic device automatically analyzes conversation audio, generates performance reports with sentiment and tone metrics, and delivers feedback to agents after calls. This automated feedback loop improves agent performance without requiring complex manual evaluation processes.
Solution Approach 2:
The system enables self-service evaluation where agents receive automated performance metrics and feedback without manual intervention. The electronic device autonomously processes conversation recordings, calculates performance indicators, and presents results to agents, reducing the need for supervisor involvement and simplifying the overall evaluation system.
2Productivity
If real-time feedback and sentiment analysis are provided, then agent engagement and performance improvement are enhanced, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary processing of conversation audio during the call itself, extracting sentiment and tone metrics in real-time. This allows the system to prepare performance data before the conversation ends, enabling rapid generation of post-conversation evaluation reports without requiring extensive processing time after the call terminates.
Data Source
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AI summary
System, electronic device, and related methods, in particular a method of operating a system comprising an electronic device is disclosed, the method comprising obtaining one or more audio signals including a first audio signal of a first conversation; determining a first conversation period of the first conversation, the first conversation period having a first duration; determining first conversation metric data including a first conversation metric based on the first conversation period; determining a second conversation period of the first conversation different from the first conversation period, the second conversation period having a second duration; determining second conversation metric data including a second conversation metric based on the second conversation period; determining a first performance metric based on a change between the first conversation metric data and the second conversation metric data; outputting, via the interface of the electronic device, the first performance metric.