JSON-LD @graph
@graph is a JSON-LD container that lets a single <script type="application/ld+json"> block declare multiple, cross-referenced entities at once — for example, an Organization, a WebSite, a WebPage, and a BreadcrumbList that all reference each other via @id pointers. It is the recommended pattern for any site with more than one schema entity on a page. Why it matters: A consolidated @graph emits stronger entity signals than a stack of disconnected schema blocks, because the cross-references explicitly tell search and AI engines how the entities relate. It also reduces page weight and prevents the common bug where multiple Organization blocks contradict each other.
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→ AEO Pillar GuideRelated Terms
sameAs is a schema.org property that connects an entity on your site to its canonical representation elsewhere on the web — typically Wikidata, Wikipedia, official social profiles, Crunchbase, and authoritative directories. A single Organization JSON-LD block with a well-curated sameAs array is one of the highest-leverage entity-signal moves available. Why it matters: sameAs is how AI engines and search engines confirm that the "Smart Money Media" mentioned on this site is the same Smart Money Media in the Knowledge Graph, Wikidata, and across the social web. Strong sameAs arrays directly increase entity confidence, knowledge-panel eligibility, and AI citation likelihood.
ClaudeClaude is Anthropic's family of large language models, used in the Claude.ai consumer app, the Claude API, and embedded in major enterprise tools (Notion AI, Slack AI, Zoom, Quora's Poe). Claude is known for long-context reasoning, careful citation behavior, and lower hallucination rates on factual queries. Its web-browsing variants use the ClaudeBot crawler to fetch fresh information. Why it matters: Claude has become a primary research surface for executives, journalists, and analysts — exactly the audiences most valuable to a PR-driven brand. Earning Claude citations requires the same AEO fundamentals (schema, entity signals, third-party authority) plus an allowed ClaudeBot in robots.txt and a clean llms.txt file.
GrokGrok is xAI's large language model, integrated natively into X (formerly Twitter) and available standalone. Grok has unique real-time access to the X firehose, which makes it the dominant AI engine for breaking news, social sentiment, and live event queries. It also indexes the open web for grounded answers. Why it matters: For brands whose audiences live on X — crypto, AI, startup, finance, and political verticals — Grok visibility translates directly to in-platform discovery. Optimization combines standard AEO (schema, entity signals) with an active, on-brand X presence that produces the social signals Grok weights heavily.
Bing CopilotBing Copilot (formerly Bing Chat) is Microsoft's conversational AI search experience, powered by a combination of OpenAI GPT models and Microsoft's own retrieval stack. It surfaces in Bing.com, Microsoft Edge, Windows, and Microsoft 365, and shares its index with ChatGPT Search. Why it matters: Although Bing's market share is smaller than Google's, Copilot citations carry outsized weight: they appear inside enterprise workflows (Outlook, Word, Teams) where buying decisions happen. Optimization requires IndexNow submission, strong schema markup, and content that ranks for the underlying Bing query — because Copilot still draws heavily from the top organic results.
Entity SalienceEntity salience is a measure of how central a given entity (person, organization, product, concept) is to the meaning of a document — as opposed to merely being mentioned in passing. Google's Natural Language API exposes a salience score from 0 to 1, and the same concept drives how AI engines decide which brand to associate with a given topic. Why it matters: Mentioning your brand once at the bottom of a blog post produces near-zero salience. Building a page around the brand — with the brand in the title, repeated in H2s, anchored in schema markup, and cited as the source of insights — produces high salience, and high salience is what makes an AI engine name your brand when answering a topical query.
JSON-LDJSON-LD, or JavaScript Object Notation for Linked Data, is a lightweight and commonly used method of encoding structured data using JavaScript Object Notation. It's a specific format that allows website owners to embed structured data directly into their HTML, making it easier for search engines to understand the content and context of a webpage. Google explicitly recommends JSON-LD as its preferred format for implementing structured data markup. Why it matters: For SEO and reputation management, using JSON-LD is critical for enabling rich results (like star ratings, event details, or product prices) in search engine result pages. These rich results enhance visibility and click-through rates. More importantly, structured data helps search engines and AI models accurately interpret the entities and relationships on your site, which is essential for improving your chances of being featured in Knowledge Panels, AI Overviews, and for enhancing your overall entity recognition and E-E-A-T.