Call Center – Sentiment and Performance Analytics

Overview

A global call center required a data-driven approach to evaluate agent performance and understand customer sentiment. Manual reviews were inconsistent and time-consuming. An AI-powered sentiment analytics system was developed to automate evaluation using call transcripts.

Challenges Faced

• Subjective and inconsistent performance reviews.
• Lack of insights into call tone, empathy, and compliance.
• Delays in feedback and training cycles.

Solution Implemented

• Applied NLP-based sentiment and performance scoring on call transcripts.
• Identified emotions, tone, and compliance adherence automatically.
• Created Power BI dashboards for real-time performance and sentiment monitoring.

Results Achieved

• 40% faster evaluation cycle.
• Objective, consistent performance insights.
• Improved agent quality and customer satisfaction.

Conclusion

The AI sentiment analysis system brought objectivity to performance reviews, enabling data-driven coaching and better customer experience management.