Sentiment Analysis - Atlas
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Know how AI talks about your brand

See whether AI describes your brand positively, neutrally, or negatively. Follow sentiment across assistants, prompts, and time, then inspect the responses behind the trend.

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Sentiment across tracked answers

Positive 64%
Neutral 29%
Negative 7%
positive best photography portfolio platform ChatGPT
neutral Luminary Studio vs Pixieset pricing Claude
negative Luminary Studio customer support reviews Perplexity
How it works

Turn AI responses into a clear sentiment picture

Sentiment is classified as Atlas captures answers to your tracked prompts.

01

Track real customer questions

Atlas runs your active prompts across the AI assistants included with your plan and stores each response.

02

Classify the language

Atlas evaluates how each response refers to your brand and labels the sentiment positive, neutral, or negative.

03

Spot changes and investigate

Review sentiment over time, compare assistants, and open the prompt-level results to understand what is driving a shift.

What you can do

From a sentiment label to useful context

Find the patterns behind changing AI perception and decide where to look closer.

Three-way classification

Every classified brand mention is grouped as positive, neutral, or negative, making the tone easy to scan.

Thirty-day trend history

See whether your sentiment mix is changing over time instead of relying on a single answer.

Early warning signals

Notice increases in negative sentiment and investigate the prompts and responses contributing to them.

Assistant comparisons

Compare sentiment across AI assistants to see where brand descriptions differ.

Prompt-level detail

Find which tracked questions are associated with positive, neutral, or negative descriptions.

CSV reporting

Include sentiment classifications in exported prompt-run data for analysis and client reporting.

Sentiment over time

See whether AI perception is shifting

Track the balance of positive, neutral, and negative mentions over a rolling period. A change in the trend gives you a reason to investigate the answers behind it.

  • Thirty-day sentiment trend
  • Assistant-by-assistant comparison
  • Prompt-level context for each result
Prompt-level detail

Read the response behind the classification

A sentiment label is a useful starting point. Pair it with response excerpts to understand what an assistant said and why the tone may have changed.

  • Sentiment labels on prompt results
  • Filter results to review negative mentions
  • Exportable data for further analysis
Explore Response Excerpts
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Response Excerpts

Read the sentences behind an answer and understand the context of a sentiment result.

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Follow how consistently AI assistants mention your brand over time.

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Competitor Share of Voice

Compare your brand’s presence with competitors across AI answers.
A closer look

Sentiment analysis questions

How Atlas classifies and presents sentiment in AI answers.

What does Atlas classify as sentiment?

Atlas classifies the tone of a response when it refers to your brand as positive, neutral, or negative. It is an indicator of language in captured answers, not a measure of customer satisfaction.

Can I see which answer produced a sentiment result?

Yes. Sentiment is available alongside prompt-level results. Response Excerpts provides additional answer context on eligible plans.

Does sentiment update over time?

New classifications are generated as Atlas runs your active prompts. The dashboard presents recent results and trends over time.

Which plans include sentiment analysis?

Sentiment analysis is included with Pro, Agency, and Enterprise plans.

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Understand how AI describes your brand

Track sentiment across AI answers and investigate the changes that matter.

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