Zendesk Verified Resolution Report

After Zendesk’s 2026 AI reporting changes, automated resolution stopped being a clean quality signal. The number can rise because more conversations were counted as contained, even if the share of outcomes actually confirmed as complete did not improve.

That is why a Zendesk verified resolution report matters. It isolates the AI outcomes that carry the strongest confirmation signal and the cleanest connection to billing. Use it with your Zendesk Verified vs Contained Resolution Report and support metrics dashboard so AI success is measured with the same discipline as human support quality.

What verified resolution measures

For the formal definition, see verified resolution. In practical terms, verified resolution is the subset of AI-resolved work where Zendesk has additional signals that the customer’s need was actually completed.

This report should answer:

How many AI conversations ended as verified resolution?
What share of automated outcomes are verified instead of only contained resolution?
Which use cases, channels, or languages produce the strongest verified outcomes?
Do verified outcomes correlate with lower repeat contact rate and lower reopen rate?

How to build the report in Zendesk

Use the AI agents reporting workspace for the fast overview and Explore for ticket-level follow-up.

1. Build the verified trend

Track verified resolutions over time as:

absolute count
share of all AI conversations
share of automated resolutions only

The third view is the most useful quality view because it controls for volume changes in AI adoption.

2. Compare verified against contained

Do not report verified resolution in isolation. Pair it with contained resolution so you can see whether AI is ending more conversations without producing stronger confirmation.

3. Break it down by use case and channel

Slice by:

AI agent or flow
use case
channel group
language

This is where real improvement opportunities show up. Password-reset flows may verify cleanly while billing or account-change flows contain more often than they verify.

4. Join it to downstream quality

In Explore, connect resolution tier to:

repeat contact rate
reopen rate
CSAT, if volume allows
downstream resolution time for assisted escalations

Verified resolution becomes truly useful when it predicts what did not come back.

How to interpret the patterns

This is the classic post-change reporting trap. Automation volume may have broadened, but automation quality has not improved. Do not claim a quality win from the blended number alone.

Verified resolution is strong in one use case and weak in another

That is usually good news, because it shows where AI is genuinely mature versus where the flow should stay narrower or hand off earlier.

Verified count is stable, but contained grows quickly

Containment may be expanding into weaker flows. Check whether those conversations later generate more repeat contact or follow-up tickets.

Verified resolution is high, but assisted escalations also rise

That is not contradictory. It can mean the easy work verifies well while harder work still benefits from AI assistance before human completion.

Common mistakes

Treating automated resolution rate as a verified-resolution proxy. They are not the same number anymore.
Reading verified resolution as a pure cost metric. It matters for billing, but it is also a stronger quality signal than blended automation counts.
Ignoring use-case differences. A healthy verified rate overall can still hide one automation flow that quietly creates follow-up demand.
Looking only inside the AI dashboard. Ticket-level quality signals live outside the conversation summary and should be reviewed too.
Comparing old exports with current dashboards. Historical AI data was re-mapped under the new framework.

What to do when verified resolution is weaker than expected

Find the use cases where verified share is lowest.
Read a sample of those conversations to see whether customers confirmed, disappeared, or restated the problem.
Compare follow-up tickets and repeat contacts after contained versus verified outcomes.
Tighten the flow scope or improve the confirmation step before broadening automation further.
Re-measure verified share after the change, not just overall automated resolution rate.

Where this report fits in your dashboard

Keep it beside:

Together these reports show how much automation you have, how much of it was strongly confirmed, and how much demand still came back anyway.

FAQ

Why should I track verified resolution separately? Because it is the cleanest AI outcome signal after the 2026 reporting change. It tells you more about confirmed quality than blended automated resolution rate.

Is verified resolution the same as contained resolution? No. Contained means AI ended the interaction without human help. Verified adds stronger confirmation that the outcome was complete.

Can verified resolution help with billing analysis? Yes. It is the resolution tier most closely tied to how Zendesk counts automated resolutions for billing purposes.

How often should I review it? Weekly for the headline trend and monthly by use case or channel.

Track the AI resolutions that actually hold up after the chat ends - start free