Sentiment Analysis: how positively AI describes your brand

Sentiment Analysis classifies how positively or negatively AI models discuss your brand. The analyzer uses the main brand name and the matching names configured for your project or competitor. The page shows classification coverage so you can compare detected mentions with completed sentiment results. Available on Growth plans and above.

With Sentiment Analysis, you can:

• See whether ChatGPT, Perplexity, and Gemini describe your brand positively, negatively, or neutrally
• Track your Net Sentiment Score against competitors over time
• Find the topics and prompts where AI sentiment turns negative, so you know what to address
• Measure how sentiment shifts after a launch, a campaign, or a reputation fix

The Sentiment dashboard brings these signals together in one place: the sentiment distribution, how share of sentiment shifts over time, an at-a-glance donut, and a Net Sentiment Score ranking that puts you next to your competitors.

The Overview tab below is where you read all of this at once.

What it does

• Classifies detected mentions as very positive, positive, neutral, negative, or very negative
• Shows how many detected mentions have a sentiment classification
• Calculates a Net Sentiment Score ranging from -100% (all negative) to +100% (all positive)
• Identifies sentiment topics: the themes AI discusses about your brand (shown as a treemap)
• Compares sentiment across your brand and all competitors
• Offers 4 analysis tabs: Overview (charts + rankings), Details (individual records), Topics (treemap), By Tag (per-tag breakdown)

How to use it

1. Navigate to Sentiment in the sidebar (under Reports)
2. Select a brand from the dropdown: "All Brands" for aggregated view, your brand, or a specific competitor
3. Use the Overview tab for charts showing sentiment trends over time
4. Switch to Topics to see a treemap of what AI says about the selected brand
5. Use By Tag to compare sentiment across different prompt groups
6. Use Details for individual sentiment records with comments and topic labels

Tips & notes

• Available on Growth plans and above
• Sentiment processing can take up to 24 hours after prompt execution (uses OpenAI Batch API)
• Matching names are used for sentiment analysis as well as mention detection
• Sentiment percentages and Net Sentiment Score use classified mentions only
• A detected mention can be absent from sentiment totals while analysis is processing or if no classification is available
• Net Sentiment Score = (positive + verypositive - negative - verynegative) / classified mentions
• Each sentiment record includes a comment explaining the AI's reasoning
• Sentiment analysis covers your brand AND all tracked competitors