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

# Agent analysis and optimization

Welcome to the Agent Analytics & Optimization section! Here you'll find the tools and information you need to monitor, analyze, and improve your AI assistant's performance. Whether you're trying to better understand user engagement, optimize response times, or sharpen the quality of interactions, this section gives you everything you need to reach your goals.

In this section, we'll explore:

* [**Statistics**](/en/analytics/agent-analysis/statistics.md): learn how to use analytics data to get valuable insights on:
  * How visits to your Agent trend over time;
  * Detailed usage broken down by individual user (number of chats, messages exchanged, and AI responses);
  * Exporting usage data in CSV format for in-depth analysis
* [**Conversation history**](/en/analytics/agent-analysis/conversations.md): learn how to browse and analyze past interactions to spot trends, improve response quality, and better understand what your users need;
* [**Response speed**](/en/analytics/agent-analysis/response-speed.md): explore strategies and techniques for optimizing your assistant's response times, balancing speed with accuracy.

Analytics and optimization are ongoing processes that will help you continuously refine your AI assistant's performance. With the monitoring tools available, you'll be able to understand in detail how your Agent is used and who your most active users are.

Keep reading to learn how to use AIsuru's data to turn your Agent into an even more effective and high-performing tool! 📊🚀


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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 dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.aisuru.com/en/analytics/agent-analysis.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.