The AJ Center - Knowledge Center

A Guide to Knowledge Graph Optimization

By Andrew Juma – Founder of The AJ Center, an award-winning end-to-end digital marketing firm. Follow Andrew on LinkedIn.

How to Optimize Knowledge Graphs

In the age of AI-powered search and zero-click SERPs, mastering Knowledge Graph Optimization (KGO) is no longer optional—it’s critical. As search evolves into answer engines rather than information directories, visibility hinges less on blue links and more on structured data that feeds machines. For brands, individuals, and institutions, this shift represents both an existential risk and a strategic opportunity.

The Rise of the Knowledge Graph: From Freebase to AI Search

Google first unveiled the Knowledge Graph in 2012, calling it “things, not strings.” It marked a turning point: instead of returning websites containing matching keywords, Google began understanding real-world entities—people, places, things—and how they relate. Behind this capability was the acquisition of Metaweb Technologies in 2010, whose Freebase project seeded Google’s structured knowledge infrastructure.

Early implementations were clunky but visionary. The infoboxes we now take for granted on the right-hand side of search results began appearing for queries like “Barack Obama” or “Leonardo da Vinci.” Over time, these panels evolved to reflect increasingly nuanced relationships, supported by schema markup, Wikidata, and user behavior signals.

Today, the Knowledge Graph is integrated not only into Google Search but also into Assistant, Discover, Bard, and Gemini—Google’s AI systems. With the rollout of Search Generative Experience (SGE), these entity databases are feeding not just static panels but real-time AI responses. This makes optimization of these profiles more critical than ever.

Entities Are the New Keywords

Traditional SEO was about ranking for strings—phrases like “best running shoes” or “Italian restaurants near me.” But Google’s BERT (2019) and MUM (2021) updates further cemented the shift toward understanding intent and context. Now, Google doesn’t just try to match keywords—it tries to understand what users want and which entities fulfill those needs.

An entity is a thing or concept that is singular, unique, well-defined, and distinguishable. It could be “Apple Inc.”, “Serena Williams”, or “photosynthesis.” When you optimize for an entity, you ensure Google understands the subject and connects it with relevant facts, mentions, and relationships across the web.

For example, an author seeking inclusion in the Knowledge Graph might ensure consistent use of their name, link all social and book profiles, claim their Google Knowledge Panel (if available), and include schema.org/Person markup with structured data fields like “jobTitle,” “sameAs,” and “knowsAbout.” The goal is to reinforce the entity’s identity and context wherever it appears.

Strategies for Inclusion in the Knowledge Graph

1. Establish Entity Identity and Authority

To appear in the Knowledge Graph, an entity must be notable, consistent, and verifiable. That means aligning:

Many SEOs overlook the importance of consistent “sameAs” references, which tie your site’s content to external sources that already exist in the Graph. For example, if a company is listed on Crunchbase, its schema markup should include a “sameAs” link to that Crunchbase URL.

Additionally, PR coverage on authoritative websites helps affirm notability. Sites like TechCrunch, Inc., and Forbes, when linked and referenced with structured data, signal that the entity is part of the knowledge ecosystem worth indexing.

2. Use Schema Markup Aggressively and Correctly

The most direct path to the Knowledge Graph is via schema markup, specifically properties under schema.org/Person, schema.org/Organization, or schema.org/Product. Essential fields include:

The inclusion of sameAs is particularly crucial, as it lets search engines connect multiple representations of the same entity across the web. Tools like Merkle’s Schema Markup Generator and Google’s Rich Results Test make it easier to validate and deploy this code.

3. Build Contextual Relevance Across Platforms

Your entity must be discussed, linked, and recognized across multiple contexts. This means:

Entities that are referred to consistently across these ecosystems build stronger semantic associations. This increases the likelihood of Google assigning a stable ID (MID) in its internal Knowledge Graph database.

Tools That Power Knowledge Graph SEO

Entity SEO in the Age of Generative AI

With the rise of Google’s Search Generative Experience (SGE), Bing Chat, and ChatGPT plugins, entities no longer just affect the right-hand panel—they now shape the answers themselves. AI models rely heavily on structured repositories like Wikidata, schema markup, and semantic link graphs to decide which brands, people, and facts to surface.

For instance, OpenAI’s GPT models integrate knowledge from Wikipedia and other high-authority sources during training. That means inclusion in the Knowledge Graph not only improves your visibility on Google but also affects how AI models interpret and present your brand.

Furthermore, Google's recent AI Overviews prioritize results from sources with entity-rich content. This means KGO now directly impacts your appearance in voice assistants, mobile previews, and AI-generated summaries. In many ways, entity optimization is AI SEO.

The Role of E-E-A-T in Entity Validation

As Google continues to emphasize Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T), Knowledge Graph optimization is a natural extension. Google’s Search Quality Rater Guidelines mention entities explicitly—associating reputation, authorship, and reviews as part of understanding the credibility of content.

For example, a nutritionist writing about “intermittent fasting” will have stronger rankings if their Knowledge Graph entity is associated with:

Case Studies: How Entities Changed SEO Outcomes

Shopify: When Shopify optimized its product pages and Help Center with structured data and “sameAs” schema linking back to their GitHub and developer profiles, their documentation began appearing directly in Google’s AI snippets. This reduced dependency on traditional keyword ranking while increasing top-of-funnel awareness.

Neil Patel: By ensuring all mentions of his name link to his personal website, YouTube, and Crunchbase, Neil Patel has solidified his position as a Knowledge Graph entity. His Knowledge Panel appears for many marketing terms, despite SERP volatility.

Museum of Modern Art (MoMA): By linking MoMA’s exhibitions to Wikidata items and using schema.org/Exhibition data types, MoMA increased its presence in AI summaries and Google Discover cards—extending its reach without additional paid distribution.

Risks of Not Optimizing for the Knowledge Graph

Invisibility is the new penalty. If your brand or identity is not represented as an entity, you’re not just missing traffic—you may be excluded from the conversation altogether.

This is especially risky in high-competition verticals like health, finance, and education, where SGE and AI overviews may consolidate answers from just 3–5 top sources, often based on entity authority. As Google moves toward federated answers and fewer links, lack of entity optimization equates to algorithmic irrelevance.

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