> For the complete documentation index, see [llms.txt](https://docs-conversational-ai.syntphony.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs-conversational-ai.syntphony.com/insights/analytics.md).

# Analytics

The **Dashboards** page provides built-in metrics and visualizations that help you monitor how your **Virtual Agent** is performing and whether it is achieving your business objectives.

By analyzing conversation data, you can identify usage patterns, monitor engagement, detect drop-off points, and evaluate overall performance. These insights support data-driven decisions that help improve the user experience and optimize your conversational solution.

Examples of the information available include:

* Drop-off points;
* Engagement rates;
* Total users;
* Conversation-related metrics.

The page also provides filters that allow you to customize the displayed information and focus the analysis on a specific time period or data set, just like we can see at the image below:

<figure><img src="https://4008706377-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Fn6zS4HeuuVpRHZEvDiFU%2Fuploads%2FsTxO7lujAtAVTEvTS4ST%2Fimage.png?alt=media&amp;token=6d038b0b-1b43-447a-b656-90a46d6cce43" alt=""><figcaption></figcaption></figure>


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# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs-conversational-ai.syntphony.com/insights/analytics.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
