> ## Documentation Index
> Fetch the complete documentation index at: https://docs.peec.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Sentiment
> The tone and sentiment of your brand mentions.
## Overview
Sentiment measures the overall tone of AI responses when mentioning your brand on a scale from 0 to 100. This metric helps you understand how AI models perceive and describe your brand.
Most sentiment scores fall between 65 and 85, with higher scores indicating more positive language and associations.
## How sentiment is measured
The sentiment score analyzes the language used when AI models mention your brand, looking for:
* **Positive indicators**: Words like "trusted," "reliable," "innovative," "leading," "expert"
* **Neutral indicators**: Factual language with little emotional tone
* **Negative indicators**: Critical language, concerns, or negative associations
The score is calculated based on the overall tone and context of your brand mentions across all AI responses.
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## Why sentiment matters
### Brand reputation
Sentiment directly impacts how users perceive your brand:
* Positive sentiment builds trust and credibility.
* Neutral sentiment maintains professional standing.
* Negative sentiment can damage brand reputation.
### Competitive advantage
Better sentiment means:
* Users are more likely to trust your brand.
* AI models recommend your brand more favorably.
* You have a competitive edge in brand perception.
### Strategic insights
Sentiment analysis helps you:
* Identify reputation issues early.
* Understand how your brand is perceived.
* Track improvements in brand perception over time.
## Related metrics
Learn how your brand's ranking position affects overall performance
Understand how often your brand is mentioned in AI responses