Published August 16, 2026

Zendesk Explore, Actually Used

Explore can answer almost any question about your support operation, which is exactly why most teams only ever look at the prebuilt dashboards.

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The mental model

Explore is built on datasets, and picking the right one is most of the battle. Support Tickets answers questions about tickets, Support Updates answers questions about what happened to them over time, and the two give different answers to questions that sound identical.

On top of a dataset you add metrics (what you are counting), attributes (how you slice it) and filters (what you exclude). A report that looks wrong is almost always the wrong dataset or a missing filter rather than a broken metric.

The five reports worth building

First reply time, median, by channel, by week. Median rather than average, because one weekend outlier ruins a mean.

Ticket volume by tag, monthly. This is the report that gets product changes made, provided your tagging is disciplined.

Backlog age distribution. Not backlog size. A stable backlog of old tickets is worse than a growing one being worked.

Solved per agent per day, with CSAT alongside. Either number alone drives the wrong behaviour.

Reopen rate. The quiet quality metric. Rising reopens mean tickets are being closed rather than resolved.

Where the numbers lie

Every one of those reports is distorted by duplicate tickets, and in different directions, which is why the dashboard often feels hard to act on.

Volume is inflated, so growth looks worse than it is.

Cost per ticket is deflated, because the denominator grew while total cost rose.

First contact resolution is deflated, since one problem needed two contacts by definition.

Solved-per-agent looks better, because merged and quickly-closed duplicates are cheap solves.

Filter out tickets tagged `closed_by_merge` in your standard reports. It is a one-line change and it makes every number closer to true.

Frequently asked questions

Which Explore dataset should I use?+

Support Tickets for the current state of tickets, Support Updates for what happened over time. Most confusing results come from asking a time-based question of the tickets dataset.

Can Explore report on duplicate tickets?+

Only on the ones already merged, via the `closed_by_merge` tag. It has no way to identify duplicates that were never caught.

Make the dashboard tell the truth

Remove duplicates and volume, cost per ticket and first contact resolution all start describing what actually happened.

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