How SignalFox evaluates the evidence behind AI visibility.

Every SignalFox audit covers four dimensions:

• Brand clarity: does the website state the category, offer, audience, and use cases clearly?
• Positioning clarity: do the title, description, H1, visible copy, and structured data tell a consistent story?
• Technical readiness: can crawlers access and interpret relevant metadata and machine-readable evidence?
• Competitive context: where does supplied competitor website evidence communicate the category or offer more clearly?

We combine crawl responses, visible page content, metadata, structured data, submitted business context, and available competitor website evidence.

We never train models on your data, and we never surface another customer's data inside your workspace.

The report may propose buyer-intent questions based on the available evidence. These are opportunities to investigate, not live provider tests. Purchased updates create saved report versions so teams can compare the evidence collected at different points in time.

The Visibility Score is a weighted baseline derived from inspectable website signals, including access, metadata, headings, canonical information, social previews, and structured data. Competitor scores, when available, use the same website-evidence framework and are not live AI rankings.

The methodology is reviewed as the product and evidence framework evolve. Material scoring changes should be documented transparently.

• If we don't have evidence, we say so. No placeholder scores.
• Material findings are tied to available page, metadata, structured-data, competitor, or supplied-context evidence.
• Recommendations are prioritized by effort vs. impact, not vendor preference.