Skip to main contentWhat Sentiment Analysis Is
Sentiment Analysis automatically extracts and classifies how AI platforms talk about your brand. When AI engines like ChatGPT, Perplexity, or Google AI Overview mention your brand, Slate analyzes whether the mention is positive, neutral, or negative.
Every mention is categorized by theme (like pricing, support, or performance) and tagged with specific keywords. This gives you a detailed view of your brand perception across AI-generated responses.
Why It Matters
AI platforms shape how users perceive brands. A single negative mention in a ChatGPT response can influence purchasing decisions. Sentiment Analysis helps you:
- Monitor brand perception across AI platforms in real-time
- Identify strengths and weaknesses by analyzing which themes get positive vs. negative mentions
- Track competitor sentiment to understand how you compare
- Spot emerging issues before they become widespread
- Measure improvement as you address negative perceptions through content updates
Key Metrics
Sentiment Labels
Every mention is classified into one of three categories:
- Positive: The AI platform describes your brand favorably (recommendations, praise, benefits)
- Neutral: The AI platform mentions your brand without clear positive or negative framing
- Negative: The AI platform highlights drawbacks, limitations, or criticisms
Sentiment Score
Each mention receives a score from -1.0 to 1.0:
- -1.0: Strongly negative
- 0.0: Neutral
- 1.0: Strongly positive
The score provides more granularity than labels alone. A mention labeled “positive” with a score of 0.6 is less enthusiastic than one with a score of 0.95.
Confidence
Every classification includes a confidence score (0.0 to 1.0) indicating how certain the analysis is. Higher confidence scores mean more reliable classifications.
Delta Tracking
Sentiment metrics include period-over-period comparisons. If you’re viewing the last 7 days, you’ll see how each metric changed compared to the previous 7 days.
Sentiment Themes
Mentions are automatically categorized into themes that reflect different aspects of your brand:
Product Quality
- Core Functionality & Features: How well your product delivers on its main purpose
- Performance & Reliability: Speed, uptime, and consistency
- Scalability & Capacity: Ability to handle growth
Pricing
- Price Competitiveness: How your pricing compares to alternatives
- Cost Effectiveness & ROI: Value for money
- Promotions & Incentives: Deals, discounts, and offers
- Pricing Transparency: Clarity of pricing structure
User Experience & Support
- Ease of Use & Accessibility: How simple your product is to use
- Design & Aesthetics: Visual appeal and interface quality
- Customer Support Responsiveness: Speed and quality of support
- Onboarding & Learning Support: How easy it is to get started
- Resolution Quality & Self-Help: Effectiveness of support resources
Trust & Security
- Safety, Security & Compliance: Data protection and regulatory adherence
- Brand Perception: Overall reputation and trustworthiness
- Customer Feedback & Reputation: Reviews and testimonials
- Transparency & Communication: Openness and clarity
Integration & Compatibility
- Compatibility & Interoperability: Works with other tools
- Ecosystem Fit & Partnerships: Integration ecosystem
Business & Growth
- Customization & Flexibility: Ability to adapt to specific needs
- Innovation & Differentiation: Unique features and forward-thinking
- Roadmap & Evolution: Product development direction
- Market Competitiveness: Position relative to alternatives
- Growth & Traction: Business momentum
How to Use Sentiment Analysis
Filter Your Data
Use the filters at the top to narrow your analysis:
Platform: Select which AI platforms to analyze (ChatGPT, Google Overview, Google AI Mode, Perplexity, Claude, Gemini).
Topic: Focus on specific topics or query categories.
Date Range: Choose your time period (Last 7 days, Last 30 days, Last 3 months, Last 6 months, Last year).
Sentiment: Filter to show only positive, neutral, or negative mentions.
Overall Sentiment View
The summary cards show total counts for positive, neutral, and negative mentions with delta indicators showing change from the previous period.
Use this to get a quick pulse on overall brand perception.
Sentiment by Brand
Compare sentiment distribution across your brand and competitors. See which brands receive more positive or negative mentions.
For each brand, you’ll see:
- Positive, neutral, and negative mention counts
- Top positive keyword (what they’re praised for)
- Top negative keyword (what they’re criticized for)
Sentiment by Theme
View sentiment breakdown by theme to understand where your brand excels or struggles. Each theme shows:
- Sentiment breakdown (positive, neutral, negative)
- Delta compared to previous period
Best Practices
1. Monitor Weekly Trends
Review sentiment changes weekly. Sudden shifts in negative mentions often indicate emerging issues.
2. Focus on High-Volume Themes
Prioritize themes with the most mentions. A theme with 100 negative mentions matters more than one with 5.
3. Compare Against Competitors
Don’t just track your own sentiment. Compare against competitors to understand relative perception.
4. Investigate Negative Themes
When you see a theme with high negative sentiment, analyze what’s driving it. Understanding the specific criticism helps you prioritize improvements.
5. Track Improvement Over Time
After addressing an issue (updating content, improving a feature), monitor whether sentiment improves in subsequent periods.
6. Cross-Reference with Citations
Use Sentiment Analysis alongside Citation Analysis. If negative mentions cite specific URLs, you know which content to update.
What’s Next
Now that you understand Sentiment Analysis, explore:
