Methodology
How SurfaceGX measures whether AI engines can find, read, and accurately represent your brand — and how those measurements turn into prioritized repair work.
What we measure
SurfaceGX evaluates your brand the way an AI answer engine experiences it. Rather than tracking link rankings, we ask the same kinds of questions a real buyer would ask AI assistants, capture how your brand is represented, and inspect whether your site gives those engines the signals they need to cite you accurately.
Every audit combines two perspectives: what AI engines currently say about your brand, and whether your published pages are technically structured for AI systems to read and trust.
The four audit dimensions
Each audit reports on four independent dimensions, then combines them into a single visibility score so you can track progress over time.
Whether and how prominently your brand appears when AI engines answer category and recommendation questions. This captures mention rate, position, and how richly your brand is described.
Whether AI engines state things about your brand that are factually wrong. Findings are graded by severity, from minor inaccuracies to critical errors such as wrong pricing or nonexistent products, each paired with the verified fact it contradicts.
How closely the language AI uses to describe your brand matches your official positioning, tone, and competitive framing. This measures conceptual alignment, not keyword matching.
Whether your website is technically structured for AI crawlers to extract — covering content density, structure, authorship signals, crawl accessibility, canonical consistency, and freshness.
Page readiness and Fix Cards
Beyond the brand-level score, SurfaceGX evaluates individual pages and assigns each a readiness tier — AI-Visible, Partially Visible, or Not Visible. Pages that fall short generate a Fix Card: a specific, actionable description of what is blocking the page, which team should own the fix, and the estimated effort. This is what turns a diagnosis into deployable work for content, SEO, and engineering teams.
Source mapping
SurfaceGX identifies the sources AI engines draw from when they describe your brand and maps them against the PESO model — Paid, Earned, Shared, and Owned media. Comparing your current authority profile against what strong coverage looks like in your industry highlights where to invest to earn more trustworthy citations.
How often to measure
AI engine behavior shifts as training data and retrieval systems update. Most brands re-run audits monthly so they can track improvement, confirm that shipped fixes worked, and catch regressions before they compound.