10 - FAQFrequently asked questions.
Answers to the most common questions about entity SEO, building a Knowledge Graph presence, Wikidata, Schema and visibility in LLMs. Anything else we clarify in the scope call.
What is entity SEO?
Entity SEO shifts optimization from the keyword to the node in the Knowledge Graph. An entity is a clearly identifiable person, organization, product, place or idea with attributes, relationships and references. The work covers identifiability (QID, @id), consistency (sameAs, contact data) and corroboration (authoritative third-party mentions).
How is it different from classic SEO?
Classic SEO optimizes documents for keywords. Entity SEO optimizes nodes in the Knowledge Graph. In LLM-driven search, entity work is the primary lever, because generative systems resolve the entities in a query before they generate an answer.
Do I need Wikipedia for entity SEO?
No. Wikidata is the primary lever. Its notability policy differs from Wikipedia's but still requires serious, public references, so we check eligibility first. Wikipedia adds corroboration once its own criteria are met. In our projects, around 80 percent do not need it.
How long does the build take?
The 90-day protocol lays the foundation. Measurable effects on LLM resolution and Knowledge Graph visibility typically show after three to nine months. If a Knowledge Panel appears, it usually does so after six to twelve months; whether it appears is Google's decision.
What is a Knowledge Panel and how does it come about?
It is Google's visible representation of an entity, in the desktop sidebar or as a mobile card. You cannot apply for one. It appears as a by-product of a stable entity: a referenced Wikidata item, a coherent Schema graph, a consistent sameAs cluster and at least three authoritative secondary sources.
How does entity disambiguation work when names are shared?
Distinct signals decide: a consistent image, a distinct profession property, distinct sameAs profiles and distinct co-occurrence (affiliation, geography). The name-collision matrix in the audit lists every namesake and defines a set of distinguishing attributes that is kept consistent everywhere.
What does a sameAs cluster include?
Links from the entity home to profiles with identical name, photo, role and affiliation: LinkedIn, Wikidata, Crunchbase, GitHub, YouTube, industry directories, conference and author profiles. A wider footprint may span 15 to 25 profiles; only the 7–10 strongest belong in sameAs. Press coverage goes into subjectOf.
How do I measure whether my entity work is working?
Six metrics: referenced Wikidata statements, sameAs coherence, Schema graph validity, Knowledge Panel appearance for brand queries, LLM entity resolution rate (GPT, Claude, Gemini, Perplexity) and citation rate in AI Overviews. We measure quarterly.
How are entity SEO and AI search connected?
AI Overviews, ChatGPT, Perplexity, Gemini and Claude first identify the entities a question refers to, then generate the answer. A brand that cannot be resolved unambiguously is often missing or confused with others, even with flawless classic SEO.
Which industries benefit most?
Sectors with high trust needs and real risk of name confusion: healthcare and pharma, financial services, B2B SaaS with several products, multi-brand groups, and personal brands in consulting and public speaking.
How does entity SEO differ from classic brand SEO?
Brand SEO targets brand queries and brand SERP real estate (sitelinks, reviews, brand box). Entity SEO works one level deeper, on the machine-readable identity node. Brand SEO is the visible result, entity SEO the foundation, and without it brand SEO breaks down when names are shared.
