Natural language processing system for automated customer support ticket classification and routing to optimize response times and resolution quality
A software company's customer support team was overwhelmed with manually categorizing and routing thousands of support tickets daily. Their manual triage process led to delays, misrouted tickets, and inconsistent response quality as tickets weren't always assigned to agents with the most relevant expertise for specific technical issues.
We implemented an intelligent NLP system that automatically analyzed ticket content, extracted key information, and classified issues by type, urgency, and required expertise. The system used transformer-based models to understand context and intent, automatically routing tickets to the most qualified agents while learning from resolution outcomes to improve future assignments.
The intelligent routing system achieved 91% accuracy in ticket classification and agent assignment, significantly outperforming manual processes. Average response times decreased by 58% as tickets reached appropriate specialists immediately. First-contact resolution rates improved by 34%, leading to higher customer satisfaction and reduced support costs through more efficient ticket handling.