What does the AI hallucination audit reveal?
The hallucination audit asks multiple AI engines direct questions about your business and checks their responses for accuracy. It catches four types of issues: facts AI invents about you, outdated cached info, competitor confusion where AI mixes you up with similar businesses, and missing information about key products or services AI should know but doesn't.
How does the live citation test work?
We submit real user-style queries to ChatGPT, Claude, and Perplexity, then analyze whether your domain appears in citations, which pages are referenced, whether quoted info is accurate, and how your citation rate compares to competitors for the same queries. This is real-world AI visibility — not a readiness checklist.
What is a content depth score?
Content depth score uses AI evaluation to judge whether your pages cover topics with enough breadth and depth to be considered authoritative. A shallow page that skims a topic scores low even with perfect technical markup — because AI engines compare your depth against competing sources in real time.
What are citation-ready content patterns?
Specific content structures AI engines prefer to extract: attributable claims with sources, self-contained factual statements, comparative assertions with evidence, definition-then-elaboration sequences. The intelligence report tests whether your content matches these patterns by running it through AI extraction algorithms.
How does topic authority clustering work?
Topic authority clustering maps your content into topic groups and evaluates whether you cover enough related subtopics to qualify as a real authority. A single page on a topic is weak. Multiple interconnected pages covering setup, comparison, pricing, and features — that's a cluster AI engines recognize as authoritative.
What is cross-engine consistency and why does a gap matter?
Cross-engine consistency measures the variance in your scores across ChatGPT, Claude, and other engines. A gap greater than 10 points — like Tidio's +14 Claude bonus or Crisp's +17 — signals your content is tuned for one engine but not another. The intelligence report uses this gap to trigger engine-specific recommendations.
How does the content uniqueness analysis work?
Content uniqueness analysis uses AI to identify what percentage of your content provides genuinely novel information versus restating widely available knowledge. Pages that primarily restate common knowledge score low — AI engines already have that info from dozens of sources. They prioritize citing pages that add something new.
What is author schema depth and why does it matter?
Author schema depth evaluates whether your Person markup includes enough detail for AI engines to verify the author as a real expert. Beyond just a name, deep schemas include sameAs links to LinkedIn, jobTitle, knowsAbout topics, and alumniOf institutions. Deeper schemas create stronger trust signals.
How does Wikidata presence affect AI visibility?
A verified Wikidata entry and Google Knowledge Panel mean your business entity exists in public knowledge databases that AI engines consult. Entities with Wikidata QIDs get higher trust scores because AI systems can cross-verify claims about your business against authoritative external sources — independent of your website.
What does social profile verification check?
It goes beyond checking that sameAs URLs are present — it confirms linked profiles actually exist, are active, and contain consistent business information. Dead social links or profiles with different business names damage trust rather than build it. AI engines follow these links to verify entity claims.