TL;DR — AI may not describe your brand the way you intend, and the gap between perception and positioning is one of the highest-leverage signals to act on. Go to Strategy > Brand Perception to compare AI-assigned attributes against your actual positioning pillars, then verify with Visibility > Responses to read the exact framing AI uses. Check the attribute strength scores to see which pillars AI has absorbed and which are missing entirely. Pro tip: create a Tag for each positioning pillar so you can measure alignment per claim, not just in aggregate.
The Question
“Is the AI perception of my brand aligned with our actual positioning?”Your positioning is deliberate: your website, messaging, and sales collateral have been crafted to communicate specific attributes — innovation, reliability, enterprise readiness, or category leadership. AI models, however, form their own picture of your brand from training data, indexed content, community discussions, and third-party sources. That picture may not match yours. The alignment gap is one of the highest-leverage signals in AI brand management. A large gap means your content strategy is not reaching AI models effectively, or that older, off-brand content is dominating what AI has learned about you. You might also be wondering:
- “Which of my intended positioning attributes is AI actually picking up on?”
- “Are AI models describing my competitors with attributes I want to own?”
- “What content should I create to shift AI perception toward my intended positioning?”
Where to Go in Qwairy
Start here: Strategy > Brand Perception
Navigate to Strategy > Brand Perception — this is your primary alignment analysis view.
Focus on the attribute mapping panel, which shows both the attributes AI associates with your brand and how strongly. Compare this list against your defined positioning pillars. Any pillar missing from the AI-generated attribute list is a gap.
Verify claims: Visibility > Responses
Cross-reference with Visibility > Responses to read the actual text behind each detected attribute.
Use the Topic filter to find responses that should contain your intended positioning — if a response about “enterprise security” never mentions your brand, you know where the gap lies.
Check tone: Insights > Sentiment Analysis
Open Insights > Sentiment Analysis to understand whether aligned attributes are being discussed positively or with caveats.
An attribute can appear in AI responses but in a hedged framing (“claims to be enterprise-ready”) versus a confident one (“trusted by enterprise teams”) — sentiment distinguishes the two.
What to Look For
Brand Perception — Alignment Analysis
The Brand Perception view provides the clearest window into the gap between intended and actual AI narrative. The attribute strength scores show how confidently AI associates each theme with your brand, measured from 0 (not mentioned) to 100 (consistently prominent).| Element | What it tells you |
|---|---|
| Attribute strength scores | How firmly each attribute is embedded in AI’s understanding of your brand |
| Missing attributes | Positioning pillars you claim but AI does not reproduce |
| Off-brand attributes | Themes AI associates with you that you do not intend to own |
| Narrative summary | The synthesized sentence AI would use to describe your brand |
| Competitor comparison | Whether your competitors are capturing attributes you intend to own |
Responses — Claim Verification
Brand Perception gives you the aggregated signal; Responses let you verify it with source text. For each intended positioning attribute, search for responses that should reference it and check whether your brand appears and how it is framed.| Element | What it tells you |
|---|---|
| On-topic responses | Answers to prompts directly related to your positioning territory |
| Framing language | Whether your brand is described as a leader, a contender, or an alternative |
| Absent mentions | Prompts where competitors appear but you do not, even though the topic is relevant |
Pro Tip: Create a Tag in Qwairy for each of your core positioning pillars (e.g., “Enterprise”, “Security”, “ROI”). Assign that tag to relevant prompts. Then use the Tag filter in Brand Perception to see your alignment score per pillar, not just in aggregate.
Filters That Help
| Filter | How to use it for this question |
|---|---|
| Provider | Some AI models are trained on different corpora — your alignment may be better on Perplexity (which uses live web retrieval) than on GPT-4 (which relies on training cutoffs) |
| Period | Compare alignment before and after a content push to measure whether new material shifted the narrative |
| Topic / Tag | Isolate a specific positioning pillar to get a focused alignment score for that claim |
How to Interpret the Results
Good result
Your top 3–4 intended positioning attributes appear in the Brand Perception theme list with strength scores above 60. The narrative summary generated by Qwairy closely mirrors your elevator pitch. When you read responses in the relevant topic area, your brand is consistently framed using the language you intend. Competitors are not capturing attributes you want to own.Needs attention
One or more of your core positioning pillars scores below 30 in Brand Perception, meaning AI rarely or never connects that attribute to your brand. Off-brand attributes (e.g., “affordable” when you are repositioning upmarket, or “legacy” when you are a modern platform) appear with high strength scores. Responses show competitors owning your intended positioning territory while your brand is absent or described in generic terms.Example
Scenario: A telecom company has repositioned from “budget mobile carrier” to “5G-first network for business and IoT”. Their brand campaigns, enterprise landing pages, and partner program have been live for 8 months. They want to know whether AI models reflect the new positioning.
- Open Strategy > Brand Perception and review the attribute strength scores. Note that “cheap plans” and “prepaid” still score above 75, while “5G enterprise” scores 14 and “IoT connectivity” scores 9.
- Create tags in Workspace > Tags for “5G Enterprise” and “IoT”. Assign them to the relevant monitoring prompts covering business connectivity and smart infrastructure topics.
- Return to Brand Perception and filter by Tag = “5G Enterprise”. The filtered attribute map confirms that in enterprise 5G prompts, their brand does not appear in AI-generated descriptions — competitors with dedicated enterprise divisions dominate.
- Open Visibility > Responses, filter by Tag = “IoT”, and read the answers. Competitors appear consistently with IoT platform framing; this carrier appears only in 1 of 12 responses, described as “exploring IoT services alongside its consumer plans”.
- Bring the gap data to the marketing team: the enterprise repositioning content is not reaching AI models. The action item is to publish technical white papers on 5G network slicing for business use cases, secure citations in telecom analyst reports, and pursue coverage in enterprise technology publications that AI models heavily index.
Go Further
Brand Perception feature guide
Read the Brand Perception documentation to understand how Qwairy measures the gap between AI perception and your positioning
Perception gap tracker
Track the perception-positioning gap over time in Looker Studio using the answer-details data source
Run perception audits via Claude
Connect the Qwairy MCP server to Claude to run automated brand perception audits across all AI providers
Related Questions
What does AI actually say about my brand?
Read the verbatim AI responses before analyzing alignment scores.
What content should I create to improve AI visibility?
Turn the positioning gap into a concrete content roadmap.
What are the strengths and weaknesses AI associates with my brand?
Understand which attributes AI has firmly assigned to you — wanted or not.
Is AI generating negative sentiment about my brand on specific topics?
Check whether misaligned attributes carry negative framing.