SaaS
Customer Support Automation
Intelligent ticket classification and routing to slash response times
Industry
SaaS Platform C
Timeline
3 months from project start to production launch
Team Size
4 engineers (1 NLP specialist, 2 backend, 1 frontend)
Technologies
6+
Overview
SaaS Platform C was drowning in support tickets. With 10,000+ tickets per month and only 15 support agents, response times were ballooning and customer satisfaction was dropping. They needed intelligent automation to route tickets efficiently and help agents resolve issues faster.
The Challenge
The support team was overwhelmed and inefficient: • 10,000+ monthly support tickets across email, chat, and web forms • Average response time of 24+ hours • Manual ticket categorization and routing taking valuable agent time • Inconsistent quality of responses across different agents • No visibility into urgent or high-value customer issues • Critical bugs buried in the ticket queue • Customer satisfaction score dropping to 72% • High agent burnout and turnover • Difficulty tracking recurring issues and patterns
Our Solution
We built an intelligent support automation system powered by modern NLP: **NLP Classification Engine:** • Fine-tuned BERT model for ticket categorization • Multi-label classification (category, priority, product area) • Sentiment analysis to identify frustrated customers • Intent detection to route to appropriate specialists • 94% classification accuracy on validation set **Intelligent Routing System:** • Automatic assignment to best-qualified agent based on expertise • Priority queue management putting urgent issues first • Load balancing across available agents • VIP customer identification and prioritization • Escalation detection for complex issues **Agent Assistance Tools:** • Real-time suggested responses using similar resolved tickets • Knowledge base article recommendations • Automated information extraction from tickets • Smart replies for common questions • Context panel showing customer history and previous interactions **Analytics Dashboard:** • Real-time ticket volume and response time metrics • Trend analysis identifying recurring issues • Agent performance tracking and coaching opportunities • Customer satisfaction monitoring • Product team feedback loop for bug prioritization **Technical Implementation:** • FastAPI backend for real-time classification • MongoDB for flexible ticket storage • Elasticsearch for lightning-fast ticket search • React dashboard for agents and managers • Integration with Zendesk, Intercom, and email
Technologies Used
Impact & Results
60%
Response Time Reduction
$500K
Annual Cost Savings
92%
Customer Satisfaction
94%
Classification Accuracy
100%
Tickets Auto-Categorized
45%
Agent Productivity Increase
Our support team can now handle 3x the ticket volume without adding headcount. The AI categorization is incredibly accurate, and agents love the suggested response feature. Customer satisfaction has never been higher.
Maria Rodriguez
Head of Customer Success, SaaS Platform C
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