Optimizing Contact Center Efficiency for India’s Leading General Insurer
Overview
In the competitive landscape of customer service, contact centers are under constant pressure to deliver exceptional experiences. To address this challenge, we developed an Agent Score Modeling solution that leverages advanced audio call analysis and AI-driven insights to evaluate, score, and train contact center personnel. By analyzing communication quality, sentiment, and call dynamics, this solution identifies key performance metrics and provides actionable feedback to enhance overall contact center performance.
Solution
- Transcription: Leveraged tools like AWS Transcribe, Azure Speech Service, and OpenAI Whisper to achieve 98% transcription accuracy and 97% speaker identification accuracy.
- Audio Analysis: Evaluated call dynamics using parameters such as signal-to-noise ratio, articulation rate, and pitch variability to generate multi-dimensional KPI insights.
- NLP Processing: Utilized advanced generative AI models, including GPT-4, for sentiment analysis, topic extraction, and summarization, enabling structured insights for decision-making.
Impacts
Enhanced Customer Satisfaction: By providing structured insights into communication quality and sentiment, the solution improved response quality, leading to a 15% increase in customer satisfaction scores.
Targeted Agent Improvement: KPI-based scoring enabled managers to identify specific improvement areas, resulting in a 20% reduction in customer complaints and a 10% increase in agent performance metrics.
