Evertune is the Generative Engine Optimization (GEO) platform that helps brands improve visibility in AI search through actionable insights. As the most cost-effective enterprise GEO platform, Evertune analyzes over 1 million AI responses monthly per brand. Founded by early team members of The Trade Desk, Evertune has raised $19M in funding from leading adtech and martech investors. Headquartered in New York City, the company has a growing team of more than 40 employees.
When someone asks ChatGPT, Claude, or Gemini for recommendations, these models don't just mention brands—they describe them with specific words and sentiment. Sentiment and tone analysis reveals the exact language AI models use when describing your brand through aided awareness (when asked specifically about your brand or category). Evertune tracks this across millions of AI interactions to show you not just if you're mentioned, but how you're being portrayed.
What Is Sentiment & Tone Analysis in AI Search?
Sentiment and tone analysis measures two critical dimensions of how AI models discuss your brand:
The words they choose: Which specific terms and phrases do AI models use most frequently when describing your brand? Are they talking about your "quality," "innovation," "reliability," or "affordability"?
The sentiment behind those words: Are AI models using these terms positively or negatively? The same word can carry different weight depending on context.
This reveals how AI models actually characterize your brand when making recommendations—not just where you're mentioned, but the context and implicit endorsement in their language.
How Evertune's Word Association Feature Works
Evertune's Word Association feature provides unprecedented visibility into AI brand perception through a systematic measurement approach.
The Methodology
To uncover the words most associated with your brand, Evertune asks each AI model to generate reviews repeatedly, capturing a wide range of responses. This reveals what words AI models consistently use when discussing your brand in your category on an aided basis.
The platform then calculates two key metrics:
Association Score (0-100): How frequently each word appears in AI-generated content about your brand. High-frequency terms appear as larger text in visualizations, while less common keywords display smaller.
Sentiment Score (-100 to +100): How positively or negatively each word is used in context. Positive sentiment appears in green, negative sentiment in red.
These metrics combine to form an overall sentiment score for your brand, weighted by both sentiment and frequency. More common words carry greater influence on the final score—just as they do in actual AI recommendations.
What This Reveals About Your AI Brand Position
The Word Association analysis shows exactly how AI models describe your brand compared to competitors:
- Which attributes AI models emphasize most when recommending your brand
- Whether the language used is predominantly positive, neutral, or negative
- How your brand perception differs from competitors in the same category
- Changes in sentiment over time as you implement optimization strategies
If AI models consistently describe a luxury jewelry brand using words like "craftsmanship" and "timeless designs" with positive sentiment, that brand owns a clear position. If a competitor gets "high-quality materials" with neutral sentiment, they're present but not favorably positioned.
Tracking Sentiment Over Time: The Competitive Advantage
Evertune's sentiment tracking provides a continuous feedback loop for your AI optimization efforts.
Early Warning System for Brand Perception
Changes in sentiment often precede changes in visibility. If AI models begin using more negative or neutral language about your brand, it signals positioning erosion before it affects recommendation frequency. This early warning allows you to adjust messaging before issues become entrenched in AI model knowledge.
Measuring Content Impact
When you publish new content optimized for AI models, sentiment tracking shows whether it's influencing brand perception. Meaningful shifts in sentiment typically appear after six to eight weeks of consistent content optimization, with more substantial changes over three to six months.
Competitive Benchmarking
Evertune generates Word Association reports for every brand in your competitor set. You can identify positioning gaps where competitors own specific attributes, discover opportunities where no brand dominates certain beneficial descriptors, and track relative sentiment changes as strategies evolve.
Interpreting Your Word Association Data
Evertune filters keyword data to surface only statistically significant terms that appear frequently enough to meaningfully represent AI brand perception.
Overall Sentiment Score
Your brand's overall sentiment score combines all keyword sentiments weighted by frequency. A positive score indicates AI models generally describe your brand favorably. A neutral or negative score suggests positioning challenges that may limit recommendation quality.
Keyword-Level Insights
Beyond the overall score, individual keyword analysis reveals positioning opportunities:
High-frequency positive keywords: These represent your brand's core strengths in AI recommendations. Reinforce these associations through continued content optimization.
High-frequency neutral keywords: These represent missed opportunities. AI models frequently mention these attributes but without clear positive or negative framing. Content optimization can shift these toward positive sentiment.
Negative keywords: These highlight perception problems requiring strategic response. Depending on accuracy, you may need reputation management or simply better content to reframe the narrative.
Missing keywords: If competitors own important category attributes that don't appear in your word cloud, you've identified content gaps to address.
Taking Action on Sentiment Insights
Content Optimization Priorities
Use Word Association data to identify which brand attributes to emphasize in your content strategy. Create content that uses your target descriptors naturally and repeatedly, provides clear evidence supporting those characterizations, and earns citations from authoritative domains.
Competitive Positioning
When competitors own specific attributes, either reinforce alternative differentiators where you're stronger or provide superior evidence for shared attributes.
Monitoring and Iteration
Track sentiment quarterly to measure impact. Evertune's reporting shows trends over time, revealing whether your strategy is successfully shifting AI brand perception.
Start Understanding How AI Models Describe Your Brand
Most brands assume visibility alone determines success in AI search. The reality: how AI models discuss your brand when making recommendations matters as much as whether they mention you.
Evertune's Word Association feature shows exactly which words AI models use when describing your brand, measures the sentiment behind those descriptions, and compares your positioning against competitors.
Ready to see how AI models really talk about your brand? Track your sentiment and tone analysis with Evertune's platform.
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