Is Your AI Chatbot Effective? Ten KPIs Beyond Conversation Volume

1. Task completion rate.
2. Self-service resolution within valid scope.
3. Grounded answer rate.
4. Appropriate abstention.
5. Successful handoff with context.
6. Qualified lead rate.
7. Key-event conversion.
8. P95 latency.
9. Availability and error rate.
10. Cost per completed outcome with quality guardrails.

Definitions matter more than labels. For example, a session without escalation is not automatically resolved, and a phone number is not automatically a qualified lead.

• Do not label every non-handoff session as resolved.
• Do not count unqualified or duplicate leads.
• Do not let retries duplicate response or conversion events.
• Separate bot latency from agent waiting time.
• Do not lower quality to optimize cost.
• Keep unnecessary sensitive content out of analytics.
• Inspect cohorts and intents; totals can hide severe local failures.

Business and technical owners should jointly govern definitions, and changes should be versioned.

What is the most important KPI?

It depends on the use case; cost per completed outcome works well when protected by quality guardrails.

How often should metrics be reviewed?

Severe failures in real time, operations weekly and outcomes monthly or by sales cycle.

Should every session receive a CSAT survey?

Not necessarily. Sampling at the right moment reduces fatigue and bias.

Does high handoff mean poor AI?

Not always. Correct handoff is success for sensitive intents.

How is grounding measured?

Combine source validation, automated rules and risk-stratified human review.

Start with 5–10 actionable metrics. Each should lead to a decision about sources, routing, capacity, scope or cost.

After 30–60 days, compare with the pre-chatbot baseline and segment by intent. That reveals whether AI reduces workload or creates qualified demand rather than merely generating messages.