> For the complete documentation index, see [llms.txt](https://help.dscout.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.dscout.com/dscout-ai/dscout-ai-studio/explore-your-data.md).

# Explore your data

With Dscout AI, you can get a jump start on analysis by exploring your data in an unstructured, interactive chat. Ask questions about your data, define the specific context, and let Dscout AI find the answers. Then, use the data and sources provided by Dscout AI to dive deeper into participant responses.

### Access explore your data

Select your study type below to learn how to explore your data with Dscout AI:

{% hint style="success" %}
**Tip:** Try clicking the **Explore** button beside AI themes in usability tests and media surveys, or beside AI themes and charts in AI moderated studies, to bring that data directly into a chat as context.
{% endhint %}

{% tabs %}
{% tab title="Usability tests" %}
**To explore your data in a usability test:**

{% stepper %}
{% step %}
Navigate to the **Responses** tab of your study.
{% endstep %}

{% step %}
Click the **Explore your data** icon in the left sidebar.

![](https://content.gitbook.com/content/IKfn7RcT4CW9XaIbqAdd/blobs/i8OywzJUJrlbNPPzlWRi/47543289892244)
{% endstep %}
{% endstepper %}

The **Explore your data** icon is available once your study has at least one response.

Now, a chat window is displayed. Want to quickly identify pain points in a user flow? Need a handful of quotes that support a new marketing strategy? Just enter your question and let Dscout AI do the rest.

<figure><img src="https://3976082747-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FIKfn7RcT4CW9XaIbqAdd%2Fuploads%2FpiX9xQEC7iv3pxqdbkiz%2Fimage.png?alt=media&amp;token=b3fe46c0-3d2b-4754-9407-ca4db75d320a" alt=""><figcaption></figcaption></figure>
{% endtab %}

{% tab title="Media surveys" %}
**To explore your data in a media survey:**

{% stepper %}
{% step %}
Navigate to the **Responses** tab of your study.
{% endstep %}

{% step %}
Click the **Explore your data** icon in the left sidebar.

![](https://content.gitbook.com/content/IKfn7RcT4CW9XaIbqAdd/blobs/i8OywzJUJrlbNPPzlWRi/47543289892244)
{% endstep %}
{% endstepper %}

The **Explore your data** icon is available once your study has at least one response.

Now, a chat window is displayed. Want to quickly identify pain points in a user flow? Need a handful of quotes that support a new marketing strategy? Just enter your question and let Dscout AI do the rest.

<figure><img src="https://3976082747-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FIKfn7RcT4CW9XaIbqAdd%2Fuploads%2FpiX9xQEC7iv3pxqdbkiz%2Fimage.png?alt=media&amp;token=b3fe46c0-3d2b-4754-9407-ca4db75d320a" alt=""><figcaption></figcaption></figure>
{% endtab %}

{% tab title="Intercept studies" %}
**To explore your data in an intercept study:**

{% stepper %}
{% step %}
Navigate to the **Responses** tab of your study.
{% endstep %}

{% step %}
Click the **Explore your data** icon in the left sidebar.

![](https://content.gitbook.com/content/IKfn7RcT4CW9XaIbqAdd/blobs/i8OywzJUJrlbNPPzlWRi/47543289892244)
{% endstep %}
{% endstepper %}

The **Explore your data** icon is available once your study has at least one response.

Now, a chat window is displayed. Want to quickly identify pain points in a user flow? Need a handful of quotes that support a new marketing strategy? Just enter your question and let Dscout AI do the rest.

<figure><img src="https://3976082747-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FIKfn7RcT4CW9XaIbqAdd%2Fuploads%2FpiX9xQEC7iv3pxqdbkiz%2Fimage.png?alt=media&amp;token=b3fe46c0-3d2b-4754-9407-ca4db75d320a" alt=""><figcaption></figcaption></figure>
{% endtab %}

{% tab title="AI moderated studies" %}
**To explore your data in an AI moderated study:**

{% stepper %}
{% step %}
Navigate to the **Responses** tab of your study.
{% endstep %}

{% step %}
Click the **Explore your data** icon in the left sidebar.

![](https://content.gitbook.com/content/IKfn7RcT4CW9XaIbqAdd/blobs/i8OywzJUJrlbNPPzlWRi/47543289892244)
{% endstep %}
{% endstepper %}

Now, a chat window is displayed. Want to quickly identify pain points in a user flow? Need a handful of quotes that support a new marketing strategy? Just enter your question and let Dscout AI do the rest.

<figure><img src="https://3976082747-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FIKfn7RcT4CW9XaIbqAdd%2Fuploads%2FpiX9xQEC7iv3pxqdbkiz%2Fimage.png?alt=media&amp;token=b3fe46c0-3d2b-4754-9407-ca4db75d320a" alt=""><figcaption></figcaption></figure>
{% endtab %}

{% tab title="Interview studies" %}
**To explore your data in an interview study:**

{% stepper %}
{% step %}
Navigate to the **Sessions** tab of your study.
{% endstep %}

{% step %}
Click the **Explore your data** button in the bottom-right corner.

![](https://content.gitbook.com/content/IKfn7RcT4CW9XaIbqAdd/blobs/EceLUGdB5UsrEN1FoP7L/47543289895060)
{% endstep %}
{% endstepper %}

The **Explore your data** button is available once at least one interview is complete.

Now, a chat window opens in a new tab. Want to quickly identify pain points in a user flow? Need a handful of quotes that support a new marketing strategy? Just enter your question and let Dscout AI do the rest.

<figure><img src="https://3976082747-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FIKfn7RcT4CW9XaIbqAdd%2Fuploads%2FmWiqovHRYLYDX8XJVPMT%2Fimage.png?alt=media&amp;token=27163620-d389-47f3-8082-aef0a61a49cf" alt=""><figcaption></figcaption></figure>
{% endtab %}
{% endtabs %}

### Define chat context

When exploring your data with Dscout AI, you can guide it to certain questions or responses in your prompts. Here are some example prompts:

* In **Q5**, which prototype did participants prefer?
* In the interview sessions with **participant A, participant B, participant C,** what were their biggest concerns or hesitations?

Not sure where to start? A new chat shows suggested prompts, like key takeaways, an executive summary, or pain points with supporting quotes. Scroll to see more, then click one to send it.

### Review response sources

When Dscout AI provides a response, it cites its sources right in the text so you can take a closer look at where the data came from. Each source appears as a chip showing the participant’s name and, when the source is a moment in a recording, a timestamp. When a response draws on several sources, the chip shows stacked participant avatars with a count.

**To review response sources,** hover over or click a source chip in the response. A card opens with the source. In interview studies, the card shows a short quote from the participant. In other study types, it shows the participant’s response. If the response has several sources, the card shows “1 of 3 responses” and you can use the arrows to move between them.

<figure><img src="https://3976082747-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FIKfn7RcT4CW9XaIbqAdd%2Fuploads%2FdAZ8zburSZyKNZF5tS6F%2FEYD_sources.png?alt=media&amp;token=5c16a73f-1273-4e6e-9b80-efa6d393ba0b" alt=""><figcaption></figcaption></figure>

To see the full context, click the link at the bottom of the card. It opens in a new tab and takes you to the participant’s response or, for recordings and interviews, to that moment in the transcript.

### Rate chat responses

To help improve the quality of Dscout AI’s responses, you can rate every response it provides to you. If a response was good, give it a thumbs up. If a response was bad, give it a thumbs down.

<figure><img src="https://3976082747-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FIKfn7RcT4CW9XaIbqAdd%2Fuploads%2F1tErgRxLd7H0VlOC6Xjl%2Fimage.png?alt=media&amp;token=2d153cb7-648e-4c6a-bf8d-5e3caef7fec9" alt=""><figcaption></figcaption></figure>

After you rate a response, a box opens where you can tell us more. Type a comment and press **Enter** to send it. If you don’t type anything, the box closes after a few seconds.

Submitting your feedback will help us continuously improve Dscout AI across all of Dscout, not just when exploring your data.

### Copy a response

To copy a response, click the **Copy response** icon next to the thumbs up and thumbs down buttons. Any sources in the response copy as links.

### View chat history

Analysis can send you in many directions, so it can sometimes be helpful to revisit previous chat threads. Pick up where you left off, ask further questions, and continue analysis you already started.

{% hint style="info" %}
**Note:** You only have access to your own previous chats, and the chat history is study-specific. You’ll only see chats from the study through which you access Dscout AI.
{% endhint %}

**To view your chat history,** click the **History (clock)** icon in the left sidebar:

<figure><img src="https://3976082747-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FIKfn7RcT4CW9XaIbqAdd%2Fuploads%2Fdmo0pbVfjGCYaaT7zhhT%2Fimage.png?alt=media&amp;token=795b71e5-3443-4354-a93c-4343189a4dcb" alt=""><figcaption></figcaption></figure>

Now, a list of your previous chats is displayed. Click any chat to open it again right where you left off:

<figure><img src="https://3976082747-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FIKfn7RcT4CW9XaIbqAdd%2Fuploads%2FoXTJaxMJJIKQS3niMG73%2Fimage.png?alt=media&amp;token=48bccb8a-0448-4969-ac90-dcf1014912fb" alt=""><figcaption></figcaption></figure>

### Start a new thread

If you want to explore a new idea within your data, you can start a new thread. This leaves your existing thread in its current state.

**To start a new thread,** click the **New thread (plus)** icon in the left sidebar:

<figure><img src="https://3976082747-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FIKfn7RcT4CW9XaIbqAdd%2Fuploads%2FiG76n2rlpG2bkXjL8gQ6%2Fimage.png?alt=media&amp;token=ee7f9a03-67df-4f03-aab7-0a23806457d9" alt=""><figcaption></figcaption></figure>

Now, a new chat opens where you can talk through new ideas and explore your data from the beginning.

### What can I ask?

When using Dscout AI, it’s important to keep in mind the general strengths and weaknesses of any generative AI tool. We’ve put together a list of things Dscout AI excels at as well as a list of some things that might be best saved for manual analysis to help guide your interactions.

#### Excels at

Dscout AI is great for the following types of requests:

| Category                           | Examples                                                                                                                                                       |
| ---------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Understanding qualitative data** | <ul><li>What are some themes in responses about feature X?</li><li>Summarize participant feedback on the onboarding process collected in Question 3.</li></ul> |
| **Finding specific information**   | <ul><li>Show me 3–5 quotes that mention usability issues.</li><li>What did participants say about the checkout experience?</li></ul>                           |
| **Generating insights**            | <ul><li>What are some of the pain points users experienced?</li><li>What suggestions did participants offer in Question 8 for improving the feature?</li></ul> |
| **Exploring sentiment**            | <ul><li>How did participants feel about the new interface?</li><li>What aspects of the product received positive feedback?</li></ul>                           |

### May struggle with

Dscout AI may have difficulty with the following types of requests:

| Category                                               | Examples                                                                                                                                                                               |
| ------------------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Segment comparison**                                 | <ul><li>How do responses vary based on age? Compare 18–24 yr olds to 25–30 yr olds.</li><li>How do feelings towards this feature differ between paid and unpaid subscribers?</li></ul> |
| **Auto-filtering or study modification**               | <ul><li>Find me video responses from frequent users.</li><li>Tag all responses that mentioned X with “X” tag.</li></ul>                                                                |
| **Quantification or quantitative analysis**            | <ul><li>How many participants experienced X issue with the feature?</li><li>What was the average amount of time spent on task #2?</li></ul>                                            |
| **Analysis with studies that were edited post-launch** | Changing a study post-launch affects how data is stored, which can lead to unreliable AI responses.                                                                                    |

To learn more about how Dscout AI can help speed up your research, see [Dscout AI](https://help.dscout.com/hc/en-us/articles/27341160440468).

For information on how Dscout works to keep your data safe when building AI features, see [AI privacy and security in Dscout](https://help.dscout.com/hc/en-us/articles/36270310945428).


---

# Agent Instructions
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## Querying This Documentation
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Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://help.dscout.com/dscout-ai/dscout-ai-studio/explore-your-data.md?ask=<question>&goal=<user_goal>
```

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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.