> For the complete documentation index, see [llms.txt](https://docs.coupler.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.coupler.io/sources/category/crm/zendesk-chat/data-overview.md).

# Data Overview

Zendesk Chat exposes a wide range of operational and configuration data through Coupler.io. The most analytically valuable entities are **Chats** and **Agent timelines** — these contain the conversation records and activity logs that power support performance reporting.

## Entities at a glance

| Entity           | Best used for                                | Supports date range? |
| ---------------- | -------------------------------------------- | -------------------- |
| Chats            | Conversation analytics, response times, CSAT | Yes                  |
| Agent timelines  | Availability tracking, shift analysis        | Yes                  |
| Agents           | Team roster, capacity planning               | No                   |
| Departments      | Routing analysis, team structure             | No                   |
| Goals            | Performance benchmarking                     | No                   |
| Skills           | Routing logic review                         | No                   |
| Triggers         | Automation audit                             | No                   |
| Shortcuts        | Template usage review                        | No                   |
| Roles            | Permissions audit                            | No                   |
| Bans             | Moderation reporting                         | No                   |
| Routing settings | Configuration documentation                  | No                   |
| Accounts         | Account-level audit                          | No                   |

## Chats entity

#### Conversation identifiers

| Field          | Description                                 |
| -------------- | ------------------------------------------- |
| id             | Unique chat session ID                      |
| session\_id    | Browser session identifier                  |
| visitor\_id    | Unique visitor identifier                   |
| department\_id | Department that handled the chat            |
| agent\_ids     | List of agents involved in the conversation |

#### Conversation details

| Field          | Description                                          |
| -------------- | ---------------------------------------------------- |
| started\_by    | Whether the chat was initiated by visitor or trigger |
| type           | Chat type (chat, offline\_msg)                       |
| channel        | Channel through which the chat arrived               |
| tags           | Labels applied to the chat                           |
| message\_count | Total messages exchanged                             |
| missed         | Whether the chat was missed                          |
| rating         | Visitor satisfaction rating                          |
| comment        | Visitor's CSAT comment                               |

#### Timing fields

| Field          | Description                                |
| -------------- | ------------------------------------------ |
| timestamp      | Chat start time                            |
| end\_timestamp | Chat end time                              |
| duration       | Total chat duration in seconds             |
| wait\_time     | Time visitor waited before agent responded |
| response\_time | Agent's first response time in seconds     |

## Agent timelines entity

#### Activity fields

| Field       | Description                            |
| ----------- | -------------------------------------- |
| agent\_id   | ID of the agent                        |
| start\_time | When the status period began           |
| end\_time   | When the status period ended           |
| duration    | Length of the status period in seconds |
| status      | Agent status (online, away, invisible) |

## Agents entity

#### Agent profile fields

| Field       | Description                         |
| ----------- | ----------------------------------- |
| id          | Unique agent ID                     |
| name        | Agent display name                  |
| email       | Agent email address                 |
| role        | Assigned role                       |
| departments | Departments the agent belongs to    |
| skills      | Skills assigned to the agent        |
| enabled     | Whether the agent account is active |

## Common metric combinations

* **Chats + Agents** (Join on agent\_id) — add agent names and roles to conversation records for team-level reporting
* **Chats + Departments** (Join on department\_id) — analyze volume and CSAT by department
* **Agent timelines + Agents** (Join on agent\_id) — calculate total online hours per agent per day
* **Multiple date ranges of Chats** (Append) — combine data from different periods into a single historical dataset

## Use cases by role

{% tabs %}
{% tab title="Support managers" %}

* Track first response time and chat duration trends over time using the Chats entity
* Monitor agent availability and online hours by joining Agent timelines with Agents
* Compare CSAT ratings across departments to identify coaching opportunities
* Use Aggregate transformation in Coupler.io to summarize daily chat volumes without leaving the platform
  {% endtab %}

{% tab title="Operations teams" %}

* Audit routing rules by exporting Triggers, Skills, and Routing settings into a single spreadsheet
* Use the Departments entity to map team structures and verify correct routing assignments
* Track missed chat rates over time to identify understaffing periods
* Export Goals data to compare actual performance against targets in Looker Studio or BigQuery
  {% endtab %}

{% tab title="AI & analytics" %}

* Send Chats data to ChatGPT or Claude to summarize recurring customer issues or generate weekly support digests
* Use Gemini or Perplexity with agent timeline exports to get plain-language summaries of availability patterns
* Pipe raw chat transcripts and tags into an AI destination for theme detection and auto-labeling
  {% endtab %}
  {% endtabs %}

## Platform-specific notes

* The **start\_date** parameter only applies to the **Chats** and **Agent timelines** entities — all other entities return full records regardless of date
* Chat `duration` is measured in seconds — divide by 60 in your destination tool for minutes
* The `rating` field only populates if CSAT is enabled in your Zendesk Chat account and the visitor submitted a rating
* `agent_ids` on a chat may contain multiple values if the chat was transferred between agents
* Banned users are stored separately in the **Bans** entity and are not flagged within the Chats entity itself


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