# How to get AI Agent Analysis

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#### 1. Accessing Your Integration Analytics

1. Go to your Gooey.AI Agent dashboard.
2. Find your AI Agent integration (for example: on Web, WhatsApp, or Voice).
3. At the bottom of the integration details, you will see:
   * A **View Analytics** button
   * An **Analysis Workflows** section

#### 2. Viewing Analytics

1. Click on **View Analytics**.
2. The analytics dashboard will display:
   * When the AI Agent was created and last updated
   * Number of users and trends
   * Breakdown of topics users asked about (e.g., Pricing, Product)
   * Tables listing all conversations and messages
   * Filters for:
     * All messages sent
     * User answers
     * Feedback (positive/negative)
     * If the question was answered successfully or unsuccessfully

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#### 3. Testing Analytics with New Messages

1. Ask the AI Agent Integration a few questions
   1. It cannot answer (example: “What is the weather?”).
   2. Ask a relevant question (example: “How do I use the AI animation tool?”)
   3. Give feedback using the thumbs-up/thumbs-down options.
2. Refresh the analytics dashboard and check updates

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#### 4. Setting Up Richer Analysis using LLM Scripts

**What is an Analysis Workflow?**

Analysis workflows use an LLM script to categorize each question and answer. The script creates structured JSON data for better analysis and charting.

**How to Set Up an Analysis Workflow**

1. Go to your integration and find the **Analysis Workflow** section.
2. Click to add a new Analysis Script.
3. Configure the LLM script. The script should:
   * Categorize each Q\&A pair (e.g., “answer missing” or “answer found”)
   * Identify the subject (e.g., product workflow, pricing, delete account, unrelated)
   * Optionally, tag the language of the conversation
4. Provide example Q\&A pairs in your script to help the LLM categorize accurately.
5. For each new message, the script will analyze and output structured data (JSON) with fields like `subject`, `workflow`, `language`, and if the answer was found.

#### 5. Using the Analysis Dashboard

1. After you have some messages, go to the **Analysis Results** section.
2. Add fields from your analysis JSON (e.g., `subject`, `language`) to the dashboard.
3. Choose how to display each field (for example: Pie Chart).
4. Example: Chart showing question topics—Product, Pricing, Unrelated.
5. Example: Chart showing user languages—English, Spanish.

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#### 6. Multi-language Insights

1. Ask the AI Agent questions in different languages (e.g., Spanish).
2. Refresh the dashboard and see the language breakdown update.

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#### 7. Health Bot Example

1. The same analysis setup can be used for other AI Agents, like a health bot on WhatsApp.
2. Example fields:
   * If the patient’s health was OK
   * Type of visit (monthly, special, house call)
   * Common health concerns (e.g., flu, fever)
3. View counts and breakdowns for each category.

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#### 8. Improving Your AI Agent

Regularly check your analytics dashboard:

* See which topics are most asked
* See what is not being answered
* See user feedback
* Analyze conversation language and user intent

Use this information to refine your AI Agent and improve user experience.