Zendesk is where your support tickets, requesters, and organizations live, along with the metrics around how fast you resolve them. Connecting it as a data source through the Connectors library syncs those tables into your Alta workspace, where they become training data for Alta and a foundation for your metrics, dashboards, and Luna analysis. Once it's flowing, you can measure ticket volume, resolution times, and CSAT — and ask Luna questions in plain English. Zendesk connects with credentials (an API token).

Who this is for: Support, CX, and RevOps teams who want Zendesk ticket data measured alongside the rest of their customer data in Alta.

Before you start

Have your Zendesk subdomain, an admin/agent email, and an API token (Admin Center → Apps and integrations → APIs → Zendesk API).
Connect a source only once per workspace. If Zendesk already shows Connected, edit the existing connection.

Connect Zendesk

Open Connectors from the sidebar.
Find Zendesk via the CRM / Ticketing tab or the Search data sources box.
Click the Zendesk card to open the Create connector screen.
Fill in the connection fields shown (subdomain, email, API token), then click Create.
Alta runs a connect test. If it fails you'll see The connect test has failed with Zendesk's error — fix the field and retry.
The card then shows Connected and Data is syncing until the first sync finishes.

Choose which tables sync

Open the connection. Zendesk brings in tables like tickets, users, organizations, and ticket metrics.
Use the Synced toggle in the Zendesk tables section to control what's pulled in.
Turn off Show only synced tables to see everything available.

Key tables and fields synced

tickets — id, status (new/open/pending/solved/closed), priority, created_at, updated_at, assignee_id, organization_id, via (channel)
ticket_metrics — ticket_id, first_resolution_time_in_minutes, full_resolution_time_in_minutes, reply_time_in_minutes
users — requesters and agents: id, role, email, name, organization_id
organizations — id, name, custom org fields
satisfaction_ratings — id, score (good/bad), ticket_id, created_at

What you can ask this data

Once it's syncing, build it into metrics and dashboards or just ask Luna / Ask AI. For example:

"How many tickets did we solve last week?" — counts tickets where status = solved by date.
"What's our average first resolution time?" — averages ticket_metrics.first_resolution_time_in_minutes.
"Which organizations open the most tickets?" — groups tickets by organization_id.
"What's our CSAT this month?" — uses satisfaction_ratings.score.
"What's ticket volume by channel?" — groups tickets by via.

Build your first metric (worked example)

Confirm tickets shows Last sync — Succeeded.
In Metrics, create a metric on tickets with measure count of rows and date field created_at.
Add a filter status = solved to measure solved volume, set the period to weekly.
Group by assignee_id (joined to users) to get a per-agent view.
Save and add to a dashboard, then ask Luna "how many tickets did we solve last week?" to confirm.

Example use cases

Support operations dashboard. Volume, backlog, resolution time, and CSAT trended over time and by agent.
Account risk. Join ticket volume and CSAT to organizations to spot unhappy accounts for CS follow-up.
Channel & priority mix. Where tickets come from and how priority affects resolution time.
Support + revenue. Combine with CRM data to make sure high-value accounts get fast resolutions.

Keep it in sync

Sync status shows Last sync (Succeeded/Failed) and the Sync frequency.
Click Sync now to refresh immediately; it's disabled while a sync runs.
Use the overflow menu (⋯) to Disable, Enable, or Delete.

Tips and common pitfalls

Resolution times live in ticket_metrics. Sync that table (not just tickets) to report SLAs.
Auth needs all three parts. Subdomain, email, and token must match — a wrong subdomain is a common failure.
Sync only what you need to keep syncs fast.
Deleting is permanent. Disable instead to pause.