OpenNash
AI evaluation domain · 5 source-backed records

Customer Support AI Benchmarks

Customer-support evals should measure resolved user goals, correct tool and CRM actions, grounded policy answers, and high-quality handoffs—not just conversational fluency.

5 benchmarksVerified 2026-07-15JSON data ↓
Decision guidance

What should a customer-support agent benchmark measure?

Start with end-to-end resolution and final system state. Add checks for policy compliance, tool side effects, knowledge grounding, escalation timing, and whether a human receives enough context to finish the job.

5

Benchmarks in this domain

Sources first · alphabetical collection order

Runnability describes access to a usable repository, dataset, or harness—not whether setup is easy.

CRMArena

watchpartial
2026-07-15
Tests
CRM workflows for service agents, analysts, and business operations.
Best for
CRM and customer-ops agents
Classification
agent benchmark · emerging · mixed

tau-bench

recommendedrunnable
2026-07-15
Tests
Customer-service agents in retail and airline domains using APIs and policy guidelines.
Best for
Support-agent reliability
Classification
agent benchmark · current · open

tau-knowledge

watchpartial
2026-07-15
Tests
Knowledge-intensive support extension to the tau-bench family.
Best for
Support agents that retrieve policy knowledge
Classification
agent benchmark · emerging · mixed

tau-voice

recommendedrunnable
2026-07-15
Tests
Full-duplex voice customer-service tasks scored against final database state.
Best for
Voice support agents
Classification
agent benchmark · current · open

tau2-bench / tau3-bench

recommendedrunnable
2026-07-15
Tests
Customer-service simulation framework with text, voice, policies, tools, multiple domains, and tau3 task-fix updates.
Best for
CX eval harness design
Classification
agent benchmark · current · open