Strategies for monitoring, scoring, and continuously improving your AI receptionist's performance.
The Importance of Monitoring š
Just like human staff, AI receptionists benefit from ongoing quality assurance. Regular review of calls ensures accuracy, consistency, and optimal customer experience.
Key Monitoring Metrics
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Call Completion Rate
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Accuracy of Information Provided
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Customer Sentiment Analysis
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Escalation Effectiveness
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Adherence to Script/Workflow
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Agent Tone & Professionalism
Scoring & Feedback Loop š
Scoring Rubric
Develop a clear scoring system. For example:
- 5 Points: Call fully completed as intended.
- 3 Points: Minor deviation, but issue resolved.
- 1 Point: Significant deviation, requires human intervention.
- 0 Points: Failed to meet objective/negative customer experience.
Feedback & Training
Use call reviews to identify areas for improvement. FORAI's AI can adapt and learn from feedback, similar to how human agents are coached.
Tools for QA
Call Recordings & Transcripts
Access detailed records of every interaction for thorough review.
Sentiment Analysis
Automated tools to gauge customer emotion and satisfaction during calls.
Customizable Workflows
Refine AI responses and decision trees based on QA findings to improve future interactions.
šÆ Key Takeaways
- ā¢ Consistent monitoring is crucial for AI performance
- ā¢ Use call recordings and sentiment analysis for insights
- ā¢ Refine AI workflows based on QA feedback for continuous improvement