Sales & Service Case Study

Customer Support Automation

62% ticket deflection with 94% CSAT

62%
Ticket Deflection
94%
CSAT Maintained
24/7
Availability
$1.2M
Annual Savings

The Challenge

A B2B SaaS company with 15,000 business customers was scaling rapidly, but their support team couldn't keep pace. Response times were increasing, customer satisfaction was declining, and hiring couldn't solve the problem fast enough.

The support challenges were mounting:

  • 45-minute average wait time during peak hours
  • 70% of tickets were routine questions answered in docs
  • Inconsistent responses - different agents gave different answers
  • No weekend coverage - Monday ticket backlog was massive
  • Knowledge spread across 400+ help articles, internal wikis, and Slack
"Our customers are businesses. When they have a problem, it's costing them money. They can't wait 45 minutes for us to tell them something that's already in our documentation."

— VP of Customer Success

The Solution

We deployed an AI support system that handles routine inquiries instantly while seamlessly escalating complex issues to human agents with full context.

flowchart LR
    Request[Customer Request] --> AI[AI Support]
    Knowledge[Knowledge Base] --> AI
    AI --> Resolve[Resolve or Escalate]
    
    Verify -->|High Confidence| Auto
    Verify -->|Medium| Handoff
    Verify -->|Urgent/Angry| Urgent
                

Unified Knowledge Base

We consolidated knowledge from multiple sources into a single searchable system:

  • 400+ public help articles
  • Internal troubleshooting guides
  • 3 years of resolved ticket history
  • Product release notes and known issues
  • Account-specific configuration data

Context-Aware Responses

The AI knows who's asking and tailors responses accordingly:

  • Account tier and feature access
  • Recent support interactions
  • Product usage patterns
  • Known issues affecting their account

Seamless Escalation

When human help is needed, the handoff is smooth:

  • Full conversation history passed to agent
  • AI summarizes issue and attempted solutions
  • Suggested resolution paths for agent
  • Customer never repeats themselves

Results

After 4 months of deployment:

  • 62% of tickets resolved without human involvement
  • 94% CSAT - actually higher than pre-AI baseline
  • Average wait time dropped from 45 minutes to 2 minutes
  • 24/7 support - customers get help anytime
  • $1.2M annual savings in support costs
  • Support team focused on complex, high-value interactions
"The AI handles the 'how do I export a CSV' questions instantly. Now when a customer reaches me, it's because they have a real problem that needs human judgment. My job is more interesting and customers get better service."

— Senior Support Engineer

Technical Details

Knowledge System

  • RAG with product-tuned embeddings
  • Automated knowledge refresh
  • Source citation in responses
  • Feedback loop for improvements

Quality Controls

  • Confidence-based routing
  • Sentiment-triggered escalation
  • Response accuracy monitoring
  • Regular human QA review

Integrations

  • Intercom chat platform
  • Zendesk ticketing
  • Product analytics (Segment)
  • Customer data platform

Want to scale support without sacrificing quality?

Let's discuss how AI can help your support team.

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