The AI Search Entity Audit: How to Verify AI Answer Engines Actually Know Who You Are
A step-by-step method for checking whether ChatGPT, Perplexity, and Google know your brand as its own entity — not a competitor or generic term.
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#schema markup
14 published storiesCanonical archive
Stories tagged Schema markup
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A Structured Data Validation Workflow Content Teams Can Actually Run
Schema markup breaks silently — a renamed field, a missing required property, a template change — and nobody notices until rich results disappear. Here's a repeatable validation workflow, the tools that actually check different things, and why passing every test still doesn't guarantee AI citation.
Finding Schema Conflicts Across Templates: A Technical Audit for Large Sites
Large sites accumulate contradictory structured data — two Organization schemas, mismatched Product prices — as templates, plugins, and migrations pile up. Here's how to find it, why it confuses both Google and AI search systems, and how to fix it at the template level instead of page by page.
AEO Myths vs. Facts: What the Research Actually Shows
A myth-busting guide to AEO's most-repeated claims — what Google, Ahrefs, and Bing have actually confirmed, and how to vet visibility stats yourself.
Structured Data for AI Search: What Schema Markup Actually Does (and Doesn't)
Google says schema isn't a ranking or AI-citation lever. Here's the real evidence on what structured data does — and doesn't — do for AI search visibility.
sameAs Link Audit to Anchor Brand Entity for AI Search
sameAs doesn't rank pages — it tells Google and AI systems which Wikipedia page, Wikidata item, and social profiles all describe the same entity. Here's how to audit it correctly, and what it can't do for you.
Pricing Pages for AI Search: Structuring Plans So Answer Engines Quote Them Right
Why AI search engines misquote SaaS pricing, and the structural fixes — from Offer markup to per-seat basis — that make plans unambiguous.
Content Freshness and Schema to Signal Trust Without Gaming
Visible dates, dateModified schema, and actual content changes are three separate signals that both Google and AI answer engines check independently — and faking any one of them is a well-documented pattern Google has publicly pushed back on.
Organization Schema Audit for Brand Consistency: A Step-by-Step Guide
Fragmented Organization and LocalBusiness markup — a different logo on the pricing page, a stale address in the footer schema, a sameAs link to a dead Twitter handle — quietly breaks the entity signal AI search systems use to recognize a brand. Here's how to audit it and fix it.
Multimodal Content for AI Search: Images, Video, and Audio
How to prepare images, video, and audio so AI search systems can actually use them as evidence — verified schema.org guidance, no invented stats.
Research Asset Landing Pages That Support Retrieval: A Practical Build Guide
A standalone page hosting one study, dataset, or report gets extracted and cited by AI answer engines differently than a blog post does — here's what the actual research says about structure, schema, and what still isn't proven.
Review Content for AI Search: Making Customer Evidence Real, Useful, and Compliant
How to publish genuine review content AI answer engines can trust and cite, without crossing into the FTC's newly-enforced fake review rules.
Author Entity Pages: How to Build Bios Google and AI Search Can Actually Verify
A generic "About the Author" blurb doesn't establish expertise to anyone — human or machine. Here's what a verifiable author entity page requires, backed by Google's own documentation and schema.org's Person type.
Schema Markup and AI Citations: What the Evidence Shows
A data-backed look at schema.org markup and AI search: what's proven, what's marketing, and when structured data is still worth your engineering time.
