Brand Perception
Your report shows how AI models perceive and describe your brand across key attributes, and what associations they link to your brand.
The Perception Radar
The perception radar visualizes how AI models rate your brand across key attributes compared to competitors. Each axis represents a perception dimension relevant to your specific industry and market.
The attributes shown are tailored to your brand - they reflect the dimensions that matter in your space, not a generic template. Your score on each attribute reflects how positively AI describes you on that dimension relative to how it describes competitors.
The radar makes it easy to spot your strongest and weakest attributes at a glance. Peaks show your competitive advantages; valleys reveal positioning opportunities.
Understanding Attributes
We calculate attribute scores by analyzing how AI models describe your brand:
- Frequency of positive mentions for each attribute
- Strength of language used (e.g., “good” vs “excellent” vs “industry-leading”)
- Context of mentions (direct praise vs passing reference)
- Comparison to how competitors are described on the same attribute
Your “weakest attribute” is where you score lowest compared to competitors. This doesn’t necessarily mean AI perceives you negatively - it means competitors are perceived more strongly on that dimension.
Brand Associations
Brand associations are keywords and phrases that AI most commonly links to your brand. We display these as a word cloud where:
- Larger text: More frequently associated with your brand
- Green associations: Positive perceptions that strengthen your brand
- Red associations: Negative perceptions that may limit opportunities
- Neutral associations: Descriptive but neither positive nor negative
LLMs tend to avoid surfacing negative information unprompted. If you see red (negative) associations, they’re likely significant - AI doesn’t casually mention negatives, so when it does, that perception is strong enough to override its default positivity bias.
Pay attention to associations that surprise you. If AI strongly associates you with something you don’t emphasize, it may indicate how the market actually perceives you versus how you position yourself.
Improving Perception
Perception shifts require consistent effort across content, sources, and positioning. The Action Center generates specific recommendations based on your weakest attributes and negative associations - from content creation to source optimization.
Perception changes take time. Unlike visibility gaps that can improve quickly, shifting how AI describes you requires building a body of evidence across multiple sources.
Common Questions
How do you measure perception attributes?
We analyze how AI models describe your brand across key dimensions. Scores are based on the frequency and context of positive versus negative mentions for each attribute, normalized against how competitors are described.
Why might my Innovation score be low?
Low innovation scores usually mean AI models don’t associate your brand with cutting-edge technology, R&D breakthroughs, or industry firsts. This could be accurate (you compete on reliability, not innovation) or a gap in how you communicate your innovations.
Can negative associations be removed?
Associations can shift over time as you publish new content and AI models update. You can’t directly remove associations, but you can dilute them by creating stronger content around the perception you want. Addressing the underlying issue (if valid) also helps.
Why do font sizes vary in the association cloud?
Larger text indicates more frequent associations. The most prominent associations have the biggest impact on how AI positions your brand in responses. Focus your perception efforts on the largest associations you want to change.