WayaLabs logo markWayaLabs
All InsightsAI Chatbots

Evaluating chatbot quality beyond deflection

A practical framework for evaluating resolution quality, escalation behavior, and user feedback in a scoped chatbot prototype.

Mar 28, 2026 6 min read

Why this matters

Teams often optimize for deflection in isolation, then discover that unresolved edge cases and poor handoff quality quietly damage customer trust. High deflection is only useful when it preserves experience quality.

Recommended approach

Define success as resolved outcomes, not avoided tickets. Instrument assistant responses by intent, confidence, and final state, then tie those signals to downstream support outcomes.

Implementation checklist

  • Track resolution rate per top 10 intents
  • Measure escalation quality with transcript scoring
  • Compare CSAT for AI-assisted vs. human-only flows
  • Tag failure modes weekly and patch prompts/tools

Metrics to track

  • Resolution rate by intent
  • Escalation quality score
  • CSAT delta
  • Repeat contact within 7 days

Key takeaway

Deflection is a vanity metric unless it is paired with resolution quality and customer sentiment.

Want this implemented in your stack?

We can discuss a scoped project and its research, implementation, and evaluation needs.

Book a Call