The 12-Pillar AVS Framework is the structured scoring model that measures AI visibility across twelve pillars, which roll up into three weighted dimensions.
The 12-Pillar AVS Framework is the scoring model behind the AI Visibility Score. It measures a business across twelve distinct pillars, each capturing a different signal of how AI engines name and recommend it. The pillars roll up into three weighted dimensions: AI Visibility at 40%, Source Quality at 30%, and Narrative Fit at 30%, producing a single score from 0 to 100.
AI visibility is not one thing. Being named is different from being recommended, which is different again from being framed accurately or cited from authoritative sources. A single headline number would hide all of that. The framework breaks the picture into twelve measurable pillars so a business can see exactly where it is strong and where it is absent.
The pillars are: Direct Mentions, Recommendation Rate, Sentiment and Framing, Source Authority, Narrative Consistency, Competitor Gap, Query Coverage, Multi-LLM Consistency, Feature and Service Attribution, Geographic Relevance, Temporal Freshness, and Category Leadership. Each one is scored on its own evidence, then weighted into the three dimensions.
This structure turns a vague worry, are we visible in AI, into a precise plan. If your Recommendation Rate is low but your Direct Mentions are healthy, you are known but not yet trusted enough to be the answer. If your Source Authority lags, the citations that do exist are weak. The framework tells you which lever to pull first.
The framework is the engine of our methodology. We score each of the twelve pillars from real engine answers, then combine them into the three dimensions. AI Visibility (40%) covers whether and how often you are named and recommended. Source Quality (30%) covers the authority and freshness of the sources engines draw on. Narrative Fit (30%) covers whether the story engines tell about you is accurate, consistent and aligned to your category.
Those three dimensions produce your AI Visibility Score and its band. Because the pillars are separated, every recommendation we make traces back to a specific weakness rather than a hunch. We measure across all three engines we track, ChatGPT, Google AI Overviews and Perplexity, so the score reflects the real landscape, not a single tool.
The framework is also what makes change measurable. When we reassess, we can show movement pillar by pillar, so a business sees not just that the score rose but which work moved it. You can see this in practice on our see it in action page.
Book an AVS Exec Brief: a real, one-off measurement of how ChatGPT, Google AI Overviews and Perplexity talk about your business right now. Same methodology as the full AI Visibility Strategy, delivered manually, free of charge. Annual, Bi-Annual and Quarterly cadences are bespoke priced.
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