Case note
B2B SaaS
AI-Powered Customer Support: 70% Cost Reduction
Helped a B2B SaaS company reduce support costs from $800K to $240K annually while improving response times.
Problem
A mid-market SaaS company with 5,000 customers was spending $800K annually on customer support. 80% of tickets were routine questions that didn't require human expertise—password resets, feature explanations, basic troubleshooting.
Their support team was drowning in repetitive work, response times were climbing, and customer satisfaction was dropping. They needed to scale support without scaling headcount.
Approach
Phase 1: Data Analysis (Week 1-2)
Analyzed 6 months of support tickets to identify patterns. Found that 50 questions accounted for 78% of all tickets.
Phase 2: AI Agent Development (Week 3-6)
Built a custom AI agent using GPT-4 with access to their documentation, previous ticket resolutions, and knowledge base. Implemented confidence scoring and human handoff for complex issues.
Phase 3: Gradual Rollout (Week 7-12)
Started with 10% of tickets, monitored quality, refined responses. Gradually increased to 100% coverage with human oversight.
Outcome
Results after 6 months:
- Support costs dropped from $800K to $240K annually (70% reduction)
- Average response time improved from 4 hours to 12 minutes
- Customer satisfaction scores increased from 3.2 to 4.1 out of 5
- Support team refocused on complex issues and product feedback
- AI handled 82% of initial responses, with 15% requiring human follow-up
The system paid for itself in 3 months and continues to save $560K annually.