> ## Documentation Index
> Fetch the complete documentation index at: https://docs.superlines.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Brand Sentiment

> Understand how AI models perceive and present your brand across engines.

The Brand Sentiment page shows how AI models talk about your brand — whether responses are positive, neutral, or negative. It goes beyond simple mention counting to analyze the tone and context of every AI response that references your brand.

## Brand-specific analysis

The primary view focuses on sentiment extracted specifically about your brand from AI responses.

### Overview metrics

| Metric             | Description                                                      |
| ------------------ | ---------------------------------------------------------------- |
| **Total Analyses** | Number of brand-specific sentiment extractions performed         |
| **Positive Count** | Responses where your brand is presented favorably                |
| **Negative Count** | Responses where concerns are raised about your brand             |
| **Neutral Count**  | Factual mentions without strong sentiment                        |
| **Positive %**     | Percentage of positive mentions, with change vs. previous period |

### Sentiment distribution

A visual bar shows the breakdown of positive, neutral, and negative mentions at a glance. The trend chart below tracks how this distribution changes over time — useful for spotting shifts in how AI models perceive your brand.

### Top mentions

See the actual AI-generated text snippets that mention your brand, categorized as positive or negative. Each snippet shows which engine produced it and which tracked prompt triggered it. This gives you direct visibility into what AI models are saying.

### Brand sentiment by theme

Understand how your brand is perceived across different conversation themes. Each theme shows:

* Sentiment breakdown (positive, negative, neutral percentages)
* Associated keywords
* Theme name and topic area

Filter themes by "Mostly Positive", "Mostly Negative", "Mixed", or search for specific themes.

## Competitor sentiment comparison

A comparison table showing how your brand's sentiment stacks up against competitors:

| Column                     | Description                              |
| -------------------------- | ---------------------------------------- |
| **Brand**                  | Brand name                               |
| **Total Mentions**         | How often this brand is mentioned        |
| **Avg Position**           | Average mention position in AI responses |
| **Sentiment Distribution** | Visual bar of positive/neutral/negative  |
| **Positive %**             | Percentage of positive mentions          |
| **Negative %**             | Percentage of negative mentions          |
| **Avg Sentiment Score**    | Numerical sentiment score                |

Toggle **Show all brands** to see all detected brands beyond your configured competitors.

## Overall response analysis

A secondary view that analyzes the general tone of all AI responses — not just brand-specific mentions. This helps you understand the broader conversation context around your tracked prompts.

Metrics include total responses, brand mentions count, sentiment distribution (shown as a donut chart), and a response sentiment trend chart over time.

## Filters

* **Date range** — select the analysis period
* **LLM engines** — filter by individual engines (ChatGPT, AI Mode, AI Overviews, etc.) using engine buttons
* **Prompt labels** — filter by prompt categories (multi-select)

<Tip>
  Monitor sentiment trends weekly. A gradual shift from positive to neutral might indicate that competitors are gaining ground in AI responses, or that AI models are updating their training data with new information about your brand.
</Tip>

## Recent brand mentions

A live feed of recent AI responses mentioning your brand, showing:

* The response snippet with sentiment indicator
* Which AI engine generated it
* Which prompt triggered it
* The date

Filter by sentiment (All, Positive, Neutral, Negative) and click any mention to open a detailed view with the full response context, model used, position, topic, and cited URLs.

## Related pages

<CardGroup cols={2}>
  <Card title="Key Metrics" icon="chart-bar" href="/metrics/key-metrics">
    How sentiment score is calculated.
  </Card>

  <Card title="Mentions" icon="message" href="/analytics/mentions">
    Explore all brand mentions across AI responses.
  </Card>

  <Card title="Competitor Analysis" icon="users" href="/analytics/competitor-analysis">
    Compare competitor performance on all metrics.
  </Card>

  <Card title="Understanding Responses" icon="file-lines" href="/metrics/responses">
    How AI responses are collected and analyzed.
  </Card>
</CardGroup>