> For the complete documentation index, see [llms.txt](https://docs.abtasty.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.abtasty.com/reporting-and-performances/reporting/reporting-filters/emotionsai-reporting-filter-templates.md).

# EmotionsAI Reporting breakdown and filters

EmotionsAI filter breakdowns allow you to filter the campaign reports based on 10 emotions segments. Those segments will help you decide on which type of element / widgets you can add to increase your conversion rates.

You can apply **filters and breakdowns together** in the reporting tab. This enables deeper exploration, such as crossing EmotionsAI scores with visitor segments (e.g. "new visitors on Safari").

* Filters can be applied **before or after** selecting a breakdown
* Reports now support preloading with EmotionsAI segments, filters, or both
* Breakdowns now highlight **positive and negative segments** when statistical confidence and readiness criteria are met

This unlocks a more flexible and insight-driven analysis workflow using EmotionsAI data.

## Apply breakdowns anf filters <a href="#h_01j6gvx38367rqbkvtz98cr4cw" id="h_01j6gvx38367rqbkvtz98cr4cw"></a>

To apply the breakdowns, click on any available:

<figure><img src="/files/4oofTNPAMQaJ7sb6yz3w" alt=""><figcaption></figcaption></figure>

You can also add filters within the breakdown

<figure><img src="/files/ubAryjl5X8z2cJPUpUvi" alt=""><figcaption></figcaption></figure>

### How to identify winners and losers? <a href="#h_01js1ybt2kw4etwjxnw274q1f7" id="h_01js1ybt2kw4etwjxnw274q1f7"></a>

When you apply a breakdown, the opportunity view with **segment highlights** is selected by default so that you can access the opportunities data infographics. It highlights segmented results that have a high level of statistical significance, allowing you to quickly identify winners and losers at a glance.

Significance is reached at segment level when all 3 criteria are matching :\
\- Conversion's Chance to win = 95% for winners (and Conversion's Chance to win =<5% for="for" losers)="losers)">\
\- Number of Unique Visitors = 5000\
\- Number of Conversions = 300\</5%>

<img src="/files/FkyysDL4V8bLzZhHk6E0" alt="" width="563">

### Detailed View <a href="#h_01jmeabzcnjtkyp43rnxcga63z" id="h_01jmeabzcnjtkyp43rnxcga63z"></a>

You can switch to **Detailed View** to gain deeper insights into your campaigns. These insights include **Audience Size** and **Transaction Gain** (when the goal is transactional). They can help you optimize your campaigns, even when there are no winning or losing variations.

<img src="/files/cAKueRXsWv5rLTCB4NwG" alt="" width="563">

<img src="/files/pvATZq1L8ZGpIdlo4w8F" alt="" width="563">

You can display a description of each column by clicking on the **info icon** in the column headers.

## Clear breakdown <a href="#h_01j6gvx383m7a0zjz0fagn9qcg" id="h_01j6gvx383m7a0zjz0fagn9qcg"></a>

You can clear the applied breakdown by **hovering** on the breakdown and clicking on the **Clear** button.

<figure><img src="/files/9VGSKmFnZFXY6o8XUc3a" alt="" width="237"><figcaption></figcaption></figure>

To learn more about EmotionsAI segments criteria, read the following article: [EmotionsAI Segments criterion](/assets-library/creating-and-managing-segments/list-of-segment-criteria/emotionsai-criterion.md).


---

# 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.abtasty.com/reporting-and-performances/reporting/reporting-filters/emotionsai-reporting-filter-templates.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.
