Automation & Scale

Using AI to Eliminate Repetitive Support Tickets Forever

Knowledge base + intent detection loops. Creating systems that learn and prevent repeat issues.

Quick Answer

For search, voice, and "just tell me what to do".

AI can eliminate repetitive tickets through three mechanisms: proactive self-service (answering before they ask), intelligent knowledge base surfacing, and root cause identification that fixes underlying issues. The goal is ticket prevention, not just ticket deflection.

Key Takeaways:

  • Prevention beats deflection
  • Every repeat ticket is a system failure
  • AI should learn from patterns to prevent issues
  • Proactive communication reduces inbound volume
  • Knowledge bases should be AI-searchable

Playbook

1

Analyze repeat tickets to find root causes

2

Build proactive notifications for common issues

3

Create AI-powered knowledge base search

4

Implement feedback loops to improve answers

5

Track ticket reduction, not just deflection

Common Pitfalls

  • Deflecting tickets without solving problems
  • Static knowledge bases that don't improve
  • Ignoring the root causes of repeat contacts
  • Measuring success by deflection rather than prevention

Metrics to Track

Repeat contact rate

Self-service resolution rate

Knowledge base effectiveness

Root cause resolution rate

FAQ

How is ticket elimination different from ticket deflection?

Deflection moves tickets away from agents but may not solve problems. Elimination actually resolves issues—through better products, proactive communication, or truly helpful self-service—so tickets never need to be created.

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Next: browse the hub or explore AI Operations.

Salarsu - Consciousness, AI, & Wisdom | Randy Salars