Search once revolved around pages stuffed with the right terms. Type “apple iphone”, receive a list of documents where that string appeared. That model served us for years, yet it was always a shortcut for meaning. The arrival of AI Overviews and similar features shows the shortcut has expired. Google and other engines now respond to concepts, not strings, and they draw facts from knowledge graphs, not raw text. Generative Engine Optimisation (GEO) is the practice of giving those systems reliable data about your business so that it appears inside the answer, not only beneath it.
From Strings to Things
Traditional optimisation rewarded repetition. Writers sprinkled target phrases through headings, alt tags and backlinks. Trouble came whenever one word pointed to several ideas—does “jaguar” mean a car, a cat or a football team? Engine updates such as Hummingbird, RankBrain and BERT taught the algorithm to solve that puzzle by treating every object—whether product, suburb or person—as a distinct entity. Once an engine recognises an entity, it can study how often it appears with other entities and decide relevance on context rather than counts.
Knowledge Graphs: The Engine Room
A knowledge graph stores entities and the relationships between them. It consists of three-part statements: subject, predicate, object. “Parramatta Eels — play in — National Rugby League” is one. Link thousands of statements and the graph becomes a map of reality that software can query. Google maintains an enormous private graph, yet it draws on public sources such as Wikipedia, government registers and, importantly, the structured data that site owners publish. When your Company node connects to trustworthy nodes—accreditations, partners, locations—the authority of the whole cluster rises.
Stages of a Graph-First Strategy
- List core entities—products, services, people, locations, specialist topics.
- Mark them up with Schema.org JSON-LD. Use specific classes and include properties such as legalName, address, geo, offers and sameAs.
- Back the markup with consistent off-site data. Claim the Google Business Profile, align social bios, land reputable directory entries and, where possible, a Wikidata item.
- Show relationships. Nest schema, link pages with plain-language anchors and make the mini-graph inside the domain reflect the broader web.
GEO Meets Local Search
Local results illustrate entity thinking in action. A query like “best coffee near Circular Quay” produces a panel of cafés with ratings, opening hours and directions—answers, not links. The panel is filled from LocalBusiness schema, the café’s Google profile and the language of customer reviews. A shop that keeps those signals tidy enjoys visibility even when its website never receives a click. GEO, then, is inseparable from local optimisation: accurate location data grounds the model, while fresh reviews supply the text that proves relevance.
Quality Signals in the Entity Era
Google’s E-E-A-T guidelines—Experience, Expertise, Authoritativeness, Trustworthiness—apply more to entities than to pages. An expert profile with a clear bio, professional memberships and citations sends stronger signals than a nameless by-line. Customer feedback that names specific menu items or staff members enriches the graph with extra nodes. Thoughtful internal linking that guides readers from a broad hub page to supporting articles shows topical depth. These practices help the engine confirm facts and cut the risk of hallucination in generated snippets.
Tracking Progress
Keyword ranks still matter, yet they no longer tell the whole story. Instead, watch how often the brand appears in AI Overviews, the accuracy of its Knowledge Panel, the breadth of rich results triggered by structured data and the click-through rate of those enhanced listings. Traffic from branded searches may plateau while discovery traffic rises; that shift signals the entity is being surfaced for broader queries.
Common Hurdles
The biggest headaches are data hygiene and resourcing. Mismatched phone numbers or stale opening hours create uncertainty that machines seldom resolve in your favour. Building and maintaining the graph demands cooperation between marketers, developers and subject matter experts; a one-off schema generator will not suffice. Establish governance early and schedule audits alongside other site maintenance.
Why the Investment Pays
A well-formed knowledge graph is hard to copy. A competitor can rewrite an article overnight, but replicating thousands of validated triples that link a brand to suppliers, patents, charities and local landmarks takes both time and trust. That barrier creates a durable edge in a market where AI tools compress content-creation costs.
Final Thoughts
Search is shifting from lists of pages to structured answers. By treating a website as a data source and a brand as an entity, organisations position themselves inside those answers. The process involves clear identification of entities, disciplined use of schema, consistent off-site citations and regular upkeep. Completed well, it keeps a business visible even as the way people search keeps changing.
