# Reputation sentiment

> Reputation sentiment is the tone in which AI models describe your brand: positive, neutral or negative.

- **Area:** [AI Visibility](https://be1st.ai/glossary/ai-visibility)
- **Tool:** [AI Visibility](https://be1st.ai/tools/ai-visibility)
- **Page:** https://be1st.ai/glossary/ai-visibility/reputation-sentiment

## Why it matters

Negative sentiment in AI responses can damage brand reputation among thousands of users daily. Unlike a single negative review that a person can put into perspective, an AI model presents a synthesis of all available information as objective fact. That's why it's important to monitor and actively influence sentiment through quality PR and content marketing.

## In practice

When asked 'experiences with company XY', AI responds: 'Company XY has predominantly positive reviews; customers praise fast delivery and quality customer support.' This is positive sentiment. If AI responded: 'Company XY has many negative reviews; customers complain about long delivery times,' the sentiment would be negative and the brand should respond.

## How be1st checks it

Analyzes the sentiment (tone) of AI responses about your brand: whether positive, neutral, or negative. AI models synthesize information from numerous sources, and their responses reflect the overall sentiment that exists about your brand on the internet. The metric evaluates phrasing, descriptors, and the context in which AI mentions you. A positive sentiment earns a +5 bonus in be1st.

[AI Visibility](https://be1st.ai/tools/ai-visibility).

## Sources

- [AI Brand Performance: See How AI Talks About Your Brand](https://www.semrush.com/ai-seo/brand-performance/) (Semrush)
- [How to measure and maximize visibility in AI search](https://searchengineland.com/how-to-measure-and-maximize-visibility-in-ai-search-462953) (Search Engine Land)
- [Gemini Apps Privacy Hub](https://support.google.com/gemini/answer/13594961) (Google AI)

## Related terms

- [Multi-model consistency](https://be1st.ai/glossary/ai-visibility/multi-model-consistency): Multi-model consistency is how closely ChatGPT, Gemini, Perplexity and Grok agree when they describe your brand.
- [Query coverage](https://be1st.ai/glossary/ai-visibility/query-coverage): Query coverage is how many kinds of questions your brand shows up for in AI answers: informational, navigational, transactional and comparison queries.
- [Factual accuracy](https://be1st.ai/glossary/ai-visibility/factual-accuracy): Factual accuracy is whether what AI models say about your brand is true: the right services, location, contact details and other facts.
- [Competitive position](https://be1st.ai/glossary/ai-visibility/competitive-position): Competitive position is where your brand stands next to its competitors in AI answers: how often models name it and how high they rank it.
- [Update freshness](https://be1st.ai/glossary/ai-visibility/update-freshness): Update freshness is how current the information AI models give about your brand is, for example whether they know your latest products and changes.
- [Knowledge level](https://be1st.ai/glossary/ai-visibility/knowledge-level): Knowledge level is how much an AI model knows about your domain and brand when asked directly, from nothing at all to a complete and correct profile.