Generative Engine Optimisation: GEO vs Traditional SEO

Generative engine optimisation (GEO) is the practice of shaping your content so AI answer engines cite you. Think ChatGPT, Perplexity, Google AI Overviews and Gemini. Instead of chasing blue links, you earn a mention inside the generated answer itself. GEO makes your brand the source those systems quote, not the one they skip.

So why does this matter now, and how is it different from the SEO you already know?

Why GEO showed up

Search changed fast. Google rolled out AI Overviews across Australia and the United States in 2024, and answer engines like Perplexity and ChatGPT now field billions of questions. Users read the answer. They often skip the links entirely. That shift is what created generative engine optimisation as a discipline. Honestly, it caught a lot of marketers off guard.

Here is the uncomfortable part. If an AI answer summarises your topic without naming you, you lose the click and the credit. The visit simply does not happen. So the goal moves from ranking a page to being the source a model quotes. Different game, same customer.

GEO vs traditional SEO

Both want visibility. They chase it in different places. Traditional SEO optimises for a ranked list of ten blue links. GEO optimises for a single synthesised answer that may cite two or three sources. Here is the honest split.

Notice the overlap. Good SEO still helps, because most AI engines pull from the same web index they read before. GEO adds a layer on top. You still write the page. You just write it to be lifted cleanly.

How AI engines decide who to cite

Few people outside Google and OpenAI have the full recipe. Still, the pattern is visible if you read enough answers. These systems favour pages that state a fact cleanly, back it with something verifiable, and match the entity the user asked about. A model reading your page is not skimming for keywords. It hunts for a sentence it can quote without embarrassment.

Three signals show up again and again. First, extractability: can a single sentence stand alone as an answer? Second, corroboration: does the claim hold up across your site and other places on the web? Third, entity match: is it obvious who you are and what you do? Perplexity, in particular, leans on citations it can link back to. Google AI Overviews tends to blend several sources into one paragraph. Gemini and ChatGPT reward recency and plain phrasing. Different engines, overlapping tastes.

We test this the dull way. We ask each engine a set of real buyer questions, then note which brands get named. Do that every week and a pattern surfaces. You find out fast whether your last edit helped or hurt, which beats guessing.

How GEO relates to AEO

People mix these two up, so let me be plain. AEO, answer engine optimisation, is the older sibling. It aimed at featured snippets, voice assistants such as Siri and Alexa, and short direct answers. GEO is the version built for generative models that write a fresh answer rather than reading one snippet aloud. AEO asks whether a machine will read your answer. GEO asks whether a model will weave your claim into its own words and credit you.

They rhyme. In practice we treat GEO and AEO as one workflow, and we cover the mechanics in our answer engine optimisation service and our broader AI SEO work. Same customer, same intent, wider set of surfaces. Microsoft Copilot and Google AI Mode reward the same habits, so the effort compounds.

How to get cited by ChatGPT, Perplexity and Google AI Overviews

There is no magic switch, and anyone selling one is fibbing. What we see working is boring, repeatable and grounded in how these systems read the web. Luckily, the fix is not complicated. A few things move the needle.

• Make one claim per paragraph, stated up front. Models lift clean, self-contained sentences, so bury nothing.
• Add structured data. Schema.org markup such as FAQPage and Article helps engines parse your meaning, and according to Google’s documentation this improves how a page is understood.
• Show first-party evidence. Original numbers, dated tests and named case studies give a model something no competitor page has.
• Strengthen your entity. A consistent name, address and about page helps Gemini, ChatGPT and Claude recognise who you are.
• Answer the real question, then expand. Lead with the direct answer in 40 to 60 words, the way this article opens.
• Keep it fresh. Update and re-date pages, because stale content quietly drops out of AI answers.

Want the tooling side? We keep a running list in ChatGPT SEO tools and a full walkthrough in how to appear in ChatGPT. Start with structure and evidence. The rest follows.

According to Google Search Central, there is no special markup that forces you into AI Overviews, and the same content best practices apply. Their AI features documentation says this plainly. The structured data guide then shows how Schema.org markup helps Google understand a page. Dull advice, but it holds.

Where most sites go wrong

The common mistake is writing for a crawler from 2015. Long, hedged paragraphs that circle a point without stating it. A model cannot lift a claim you did not make. If your page says there are many factors to consider, it hands the answer to a rival who wrote the three factors are speed, proof and clarity. Be the one who states it.

The second mistake is thin proof. A page full of adjectives and no numbers reads as marketing, and models discount it. For instance, we watched one Sydney client double their citation rate after we swapped vague promises for two dated results and a named example. Same topic, same length, far more quotable. That surprised the client, and it is the sort of change you can copy this week.

The third mistake is drift. Your name shows up three ways across your site, your Google Business Profile lists an old address, and the model cannot tell which entity is real. Tidy that up. Consistency is unglamorous, yet it is what lets Gemini and ChatGPT trust that the RevivalMD on your homepage is the RevivalMD in the answer.

What we actually measured

Here is where it gets real, because “trust me” is not evidence. We ran our GEO pipeline for RevivalMD, a single physician-led clinic, not a hospital chain with a marketing army. Within 30 days of the pipeline going live, we tracked their citations across the major engines. The result surprised even us.

In our RevivalMD case study, that one clinic was cited in 10 of 10 tracked queries in Google AI Mode, and 10 of 10 in Perplexity, with ChatGPT at 9 of 10. One clinic. Ten out of ten. “We didn’t expect to outrank the big directories,” the founder told us, and frankly neither did we. That is the payoff when structure, evidence and entity clarity line up together.

Does this transfer to your business in Sydney or Chicago? Probably, with caveats. RevivalMD works in a focused niche, and a broad consumer brand faces stiffer competition for each citation. Take the numbers as a signal, not a promise. Australian service businesses, in our experience, often have a real edge here, because their niche is tight and their local authority is genuine.

A quick word on measurement

Rankings told you where you sat on a page of links. Citation share tells you how often an engine names you when it answers a real question. Those are different measures, and most legacy tools track only the first. So we built a simple tracker instead. It is a list of buyer questions, a weekly run across ChatGPT, Perplexity and Google AI Mode, and a tally of who got cited.

Nothing about that is fancy. It is honest, and it shows movement within a few weeks rather than months. When we changed RevivalMD’s pages, the tracker caught the lift almost straight away. If you cannot measure the citation, you are back to guessing, and guessing is expensive. Watch the answer, not just the ranking.

FAQ

What is generative engine optimisation?

It is the practice of shaping content so AI answer engines cite you. ChatGPT, Perplexity, Gemini and Google AI Overviews read the web, then write an answer. GEO helps make your page the source they quote, not the one they skip.

How is GEO different from SEO?

Traditional SEO chases a ranking position in a list of links. GEO chases a citation inside a single generated answer. The skills overlap, since AI engines still read the web index, but GEO leans harder on clear claims, structured data and first-party evidence.

Is GEO the same as AEO?

They are close cousins. AEO, answer engine optimisation, grew up around snippets and voice assistants. GEO targets generative models that write fresh answers. We run them as one workflow, because the customer and the intent are the same.

How long does GEO take to work?

It varies with your niche and starting authority. For RevivalMD, a focused clinic, we tracked strong citation share within 30 days. A crowded consumer category can take longer, so treat any timeline as an estimate, not a guarantee.

Can small Australian businesses compete with big brands here?

Yes, more than you might think. A tight niche and genuine first-party data can beat a generic page from a larger rival. Being quotable matters more than being enormous, which is good news for smaller firms.

Key takeaways

Generative engine optimisation is how you get cited inside AI answers, not just ranked in a list of links. It shares roots with traditional SEO and with AEO, then adds structured data, clear extractable claims and first-party evidence aimed at ChatGPT, Perplexity, Gemini and Google AI Overviews. The Australian and US search results now show AI answers by default, so the citation, not the click, is the new front door. Our RevivalMD work suggests a focused business can win that citation quickly, though your mileage depends on the niche. Start with one clear claim per section, add Schema.org markup, and show real evidence.

Want your brand quoted by the answer engines? That is the work we do in AI SEO, grounded in structure and evidence rather than hope.

Sources

• Google Search Central, AI features and your website: https://developers.google.com/search/docs/appearance/ai-features
• Google Search Central, Intro to structured data markup: https://developers.google.com/search/docs/appearance/structured-data/intro-structured-data

Updated August 2026. Written by Sheetal Dhadial, founder of SIAGB, an AI-native consultancy in Sydney.