Generative Engine Optimisation (GEO) – The Complete Guide

The way people search is shifting fast. Traditional SEO still matters, but it’s no longer the full picture. Instead of clicking through blue links, users are getting answers directly from AI tools like ChatGPT, Bing Copilot, and Google’s new AI Overviews.

That’s where Generative Engine Optimisation (GEO) comes in. GEO is about shaping your content so it’s not just seen, but used by AI engines. If a language model is crafting an answer, your brand needs to be in the mix. Otherwise, you’re invisible.

This guide breaks down what GEO means (beyond the buzz), why it’s a growing priority in 2025, and how to start applying it to your strategy. You’ll learn how generative engines choose what to cite, how to signal credibility, and which tactics move the needle.

If you’ve noticed your brand missing from AI answers, or you’re wondering how to adapt SEO for this next era, this is the roadmap.

What Is Generative Engine Optimisation (GEO)?

Generative Engine Optimisation (GEO) is the practice of tailoring your digital presence so AI systems can accurately reference, summarise, and surface your brand in response to user queries.

It sits at the intersection of SEO, content strategy, and AI readiness. Where traditional SEO focuses on ranking in search engine results pages (SERPs),

GEO ensures your brand is “sourceable” by Large Language Models (LLMs), the same engines powering ChatGPT, Google SGE, Bing Copilot, and Perplexity.

The rise of AI search means that search engines are now part engine, part author. Your content isn’t just competing for clicks; it’s competing for inclusion in the AI’s actual response. GEO is how you increase those odds.

 

Why It Matters in 2025 and Beyond

AI-generated search results are no longer experimental, but are becoming the default experience for millions of users.

• Google’s AI Overviews now roll out by default in many queries.
• ChatGPT, Perplexity, and Bing Copilot are gaining serious traction, especially in high-consideration research.
• Over 25% of search queries are now resolved without a single click.

This is a profound shift. Being referenced by AI is fast becoming as important as ranking on page one. Brands that embrace GEO now will build early AI visibility.

 

Why GEO Is Critical for Modern Search Visibility

Generative engines aren’t just a trend; they’re the new front door to your brand. From Google’s SGE to ChatGPT, Bing Copilot, and tools like Perplexity, users now expect fast, synthesised responses that skip traditional results entirely.

And they trust them. Nearly 60% of users consider AI-generated answers just as reliable, if not more, than standard search listings.

What does that mean for your brand? If you’re not cited or included in those answers, your visibility drops to zero. GEO ensures you remain part of the conversation as AI becomes the first (and often only) stop in the buyer journey.

 

The Decline of the 10 Blue Links

It was once simple. Search results meant ten blue links stacked neatly on page one. Ranking there was the game.

But that’s not how search works anymore.

Search engine results pages (SERPs) have evolved into something far more fragmented and far less predictable.

Today, those traditional organic listings are often pushed below a mix of:

• AI-generated overviews
• Video carousels
• Knowledge panels
• Featured snippets
• People Also Ask boxes

These features dominate the visible space. They’re designed to answer questions directly on the page, without sending anyone to your site at all.

“Visibility is no longer just about position. It’s about format. It’s about being the answer.”

And the shift is not subtle. Zero-click searches are hitting record highs.

According to Similarweb, over 65% of Google searches in 2024 ended without a single click. That means most people never even visit a website after searching. They find what they need on Google itself, often powered by your content or your competitors’ content, but without attribution, traffic, or leads for you.

It’s a fundamental change in how discovery works.

For brands, this shift demands a new approach. It means:

• Optimising content not just to rank but to be summarised, cited, and trusted.
• Structuring pages so AI models can interpret them clearly.
• Invest in authority and clarity so your brand is the source search engines choose to display.

“Because in a world where fewer people click, being the source is everything.”

This is the challenge GEO is designed to address. It is not about chasing old-school rankings. It is about ensuring your content is the one that gets used, even when users never leave the results page.

 

Brand Discoverability and Sourceability

SEO today isn’t about tricking algorithms. It’s about making your brand findable, trustworthy, and quotable, especially in an environment where AI systems constantly summarise, rewrite, and recommend content.

Brand discoverability means ensuring your content appears in search results, AI overviews, and conversational answers. Sourceability is about making it easy for machines (and people) to cite you confidently.

This isn’t just a technical exercise. It’s about ensuring your expertise is visible and verifiable wherever your buyers look for answers.

Here’s what that involves in practice:

Writing in ways LLMs can parse and infer credibility

• Use clear, direct language with well-defined claims.
• Avoid vague assertions that AI models can’t confidently summarise.
• Break complex ideas into digestible parts that can be excerpted cleanly.
• Support key points with data, examples, and clear reasoning that signal authority.

Using structured formats, citations, and schema markup

• Apply consistent headings to signal content hierarchy.
• Include numbered or bulleted lists for steps, benefits, or frameworks.
• Use schema markup (like Article, FAQ, or HowTo) to help search engines interpret your page.
• Cite reputable sources for important claims, such as that LLMs favour content with explicit attribution.

Aligning your content with known entities and topical clusters

• Reference well-known concepts, brands, or industry standards that LLMs can connect semantically.
• Cluster content around related topics on your site to build authority.
• Link internally to other pages covering subtopics in depth to create a meaningful structure.
• Make your brand consistently associated with the topics you want to own.

Beyond Technical Optimisation: Building Machine Trust

• Write like an expert aiming to be understood, not like you’re gaming a system.
• Provide clear, specific, actionable advice without ambiguity.
• Keep content updated so it remains accurate and credible.
• Include author bios, credentials, and company details to reinforce trust.

Trust Equals Presence in Conversational Search

AI-generated answers often summarise content without sending users to your site. To appear in those summaries, your content must be credible enough to quote directly.

That requires investing in clarity, evidence, structure, and authority across your entire site. If an AI system can confidently rephrase your explanation, you’ve succeeded in being sourceable.

Because in the age of conversational search, trust isn’t a bonus, it’s the price of admission.

 

How Generative Engines Source Information

Generative engines aren’t browsing like a human. They’re parsing, weighing, and stitching together content based on structure and trust.
That means your content can’t just be good. It needs to be recognisable, at least to a machine, as authoritative.

Clear headings. Tight formatting. Logical flow. These aren’t just UX best practices anymore, but are AI visibility factors. Add in elements like author bios, publication dates, third-party coverage, and E-E-A-T-aligned context, and you’re signalling to engines: this can be trusted.

Overlook those basics, and your content might still be useful to people, but invisible to LLMs.

 

Entity Recognition and Citation Logic

When an AI tool answers a query, it doesn’t pull from thin air. It leans heavily on entity relationships, such as names, places, companies, topics, and the connections between them.

Content that clearly references recognised entities (backed by knowledge graphs or consistent schema markup) is more likely to get cited. Why? Because LLMs seek consistency. They cross-reference internal models, training data, and real-time context to decide who’s credible.

Vague writing, unclear attribution, or buried expertise? That’s how you get skipped.

We cover these techniques and real-world examples in our webinar about the shift in AI, which explores how AI engines evaluate and cite content.

 

Example Prompts and Responses

Let’s see how this plays out in practice.

Prompt example:

“What’s the difference between Generative Engine Optimisation and SEO?”

When someone enters this query in an AI-powered search tool like Perplexity, here’s what happens:

• Brand A appears as a cited, linked source in the answer.
• Brand B does not, even though they have a well-written blog post on the same topic.

Why the difference?

Brand A structured its content to be machine-readable and sourceable. They used clear, descriptive subheadings that matched search intent and made the content easy to parse. The article was published under a real author profile with credentials that signalled trust. It also included topical entities and related terms like “semantic SEO,” “LLMs,” and “conversational search” that tied it to recognised concepts in the AI’s training data.

This combination of factors provided strong signals of credibility and relevance. When the AI model generated its answer, Brand A’s content was easy to summarise and safe to cite because it was clear, authoritative, and semantically rich.

Brand B, on the other hand, may have written an excellent, insightful piece. But it lacked the structural and semantic cues that AI systems rely on to evaluate and select sources. The article used vague or generic headings, didn’t reference related entities, and offered no author attribution.

As a result, the AI had no reason to pick it over better-structured alternatives.

Same effort in writing. Very different outcomes in visibility.

The lesson here is simple: creating strong content isn’t enough anymore. You also need to make it easy for search engines and AI systems to recognise, interpret, and trust your content enough to recommend or quote it directly.

That’s the core of Generative Engine Optimisation: designing content not just for human readers but for the AI models that increasingly mediate how people find information.

 

GEO Strategy: How to Optimise for Generative Engines

Getting cited by AI isn’t about guesswork. It takes a layered approach that is technical, strategic, and editorial. Each piece plays a role in making your brand the obvious choice for AI systems to reference when generating answers.

Here’s how to build that foundation.

 

First Step: Audit Your Brand’s AI Footprint

If someone asked ChatGPT about your company, what would it say?

That’s not a rhetorical question. Type it in. Try different variations: your brand name, your service category, comparisons with competitors. Do the same in Perplexity, Bing Copilot, and even Google’s AI Overviews. You might find your brand mentioned. Or misrepresented. Or missing altogether.

What you uncover here is your AI visibility baseline, or a snapshot of how machines interpret your digital presence today. It won’t come from Search Console or GA4. This is a different layer. Keep track of what’s accurate and where gaps exist. Look for competitors that are showing up too, and dig into why. What content of theirs is being cited? What patterns can you reverse engineer?

This step isn’t flashy, but it’s foundational. It tells you whether AI sees you, and what story it’s telling.

 

Create Sourceable, Authoritative Content

Want your content to show up in AI answers? Then it has to pull its weight.

That doesn’t mean louder headlines or more keywords. It means clarity, structure, and a trail of credibility that an algorithm can follow.

Be direct.

Avoid hand-wavy language. Don’t say you “drive results.” Say what you did, who it helped, and how. Something like:

“We helped a UK SaaS brand increase lead quality by 47% by reorganising its content around entity clusters and applying schema.”

That line didn’t need to be flashy. It just needed to be verifiable.

Shape your content for machines and people.

Use clear headings, logical formatting, and a structure that helps LLMs figure out what’s important. Short paragraphs, clean bullet points, and natural transitions make all the difference.

Add substance.

Original insights. Data with a source. A quote from someone with real authority. The goal isn’t to impress but to be the most trustworthy source.

Make connections obvious.

Reference known topics or frameworks. For example, if you’re explaining topical authority, tie it to E-E-A-T or Google’s quality rater guidelines. This helps engines “anchor” your content to broader concepts.

 

Build Domain-Level Trust Signals

Great content needs backup. Specifically, a domain that looks reliable from the outside in.

That means showing up in the right places. If industry publications, relevant blogs, or third-party directories mention your brand, it builds the kind of external credibility AI engines notice. You don’t need a PR agency. You need consistency.

Update your business details across every platform you control. Make sure bios are aligned, links are live, and brand voice doesn’t swing wildly between LinkedIn, your website, and your About page.

As for authorship, names matter. Articles tied to a real person with a digital footprint carry more weight than anonymous content. Use author markup, and keep bios connected across properties.

 

Schema and Site Structure

AI systems don’t read a page like people do. No scanning for design cues or admiring clever copy. It’s more mechanical, patterns, structure, the bones of the page. What’s this about? Is it trustworthy? Machines have to figure that out without human intuition.

That’s where schema matters. Not as an afterthought, but as the basic translation layer. It tells search engines exactly what they’re looking at. Without it, there’s guesswork. An FAQ might not be recognised as one. Product details can get lost. Reviews might not even register.

It’s not about stuffing in every possible tag. Just clarity. What’s essential? Article? FAQ? Product info? Make it unambiguous.

Of course, plenty of sites rely on plugins. They’re fine to a point. But they miss things. They can even break things. A quick test, just to see what search engines pick up, can reveal gaps that hurt visibility.

Citations are part of this clarity, too. Vague mentions don’t help anyone. Being precise matters. Link directly. Use full names. Provide context so there’s no confusion about the source. It’s not about sounding formal or academic for its own sake. It’s about being clear enough that even a machine can follow along.

Then there’s the experience itself. A slow site, confusing navigation, broken links, all of that signals neglect. Search systems notice. They treat it as a sign of reliability, or the lack of it.

None of this is just box-ticking. It’s about being understood, without ambiguity, whether it’s a human reader or a machine deciding what gets shown.

 

Tools and Tactics to Support GEO

Generative Engine Optimisation is more than a theory. It’s a working system. And like any system, it runs better when backed by the right set of tools.

Some tools will help you structure content for AI readability. Others let you check how and where your brand is showing up. A few are early indicators of where the GEO landscape is heading.

Here’s how to support your strategy in practice.

 

Content Formatting and Markup

A lot of brands still think good content alone will do the job. That a strong message will somehow shine through, no matter how it’s laid out. That’s rarely true these days. Especially when AI models decide what gets surfaced or summarised.

AI isn’t reading your page like a person with patience and curiosity. It’s scanning for structure. Patterns. Cues about what’s important and how it all hangs together. If that structure is sloppy or overcomplicated, good luck getting cited.

Headings matter here. Not in a token way. Real, logical headings that make sense of the argument. Imagine someone in Birmingham or Edinburgh looking for an answer on their phone; are they going to fight through a wall of text? No. Neither will a search engine.

Short paragraphs help too. Readers and crawlers both get lost in big grey blocks. Clean bullet lists? They’re easier to scan, but they also help AI models lift key points for summaries.

Consider an agency service page.

• Strategy and planning
• Content production
• Technical SEO
• Link building

That is easier to parse at a glance than burying all of it in a dense sentence.

And then there’s the semantic side. Tags like “<article>”, “<section>”, proper heading levels, they’re quiet signals that say “this is structured, reliable, ready to be understood.”

But here’s where it goes wrong for a lot of UK brands: heavy design. Fancy tabs, sliders, and accordions. They look slick in a desktop demo, but if the content is hidden or loaded in weird ways, crawlers may not see it. AI can’t cite what it can’t read.

Schema is part of this clarity story. It’s less about trickery and more about clear labelling. Saying: “This is an article.” “This is an FAQ.” “This is the business behind it.”

Yes, plugins help, but they’re blunt tools. They don’t always cover every field, and sometimes they break. It pays to test it. A lot of brands don’t.

Because at the end of the day, clear, well-structured content isn’t just good UX. It’s a signal to anyone, and anything, trying to understand you that you’re worth paying attention to.

Monitoring AI Response Presence

Here’s the truth: most SEO tools won’t tell you a thing about whether your brand is showing up in AI-generated answers. You might own the top organic spot, but that doesn’t mean you’ll be cited when someone asks Bing Chat or Perplexity for a recommendation.

That’s a gap. And it’s one you have to fill in manually right now.

The only real way is to test it yourself. Put in the kind of prompts an actual prospect might use. Not just generic ones. Think about what people here in the UK type.

Examples?

• Best B2B SEO agencies in the UK
• What does generative engine optimisation involve?
• GEO services for UK SaaS companies

Try it in ChatGPT,  Bing Copilot, or Perplexity. Watch what comes up.

And don’t just do it once and call it research. You’ll want to track it over time. Competitors change. AI models get updated. The responses can shift dramatically in a matter of weeks.

How do you even track it?

Keep a simple log. Date. Prompt. Who showed up? Was your brand there? What link did it use? Who else was mentioned? Even noting the wording can help, because sometimes it’s a subtle change that tells you why one brand got picked over another.

Example log fields:

• Date
• Prompt used
• Brand appearance
• Content cited
• Competitors shown
• Notes

This is not the kind of thing that scales easily right now. It’s a bit of a manual slog. But that’s the cost of understanding where you stand.
Browser extensions can help a bit. AIPRM for managing your ChatGPT prompts. The SGE SERP Overlay to see what Google’s AI answer shows. Detailed

SEO Extension for checking what’s on-page and what schema you’ve got.

They’re not magic bullets. They won’t think for you. But they can make the work less painful. Because until someone invents a true GEO analytics dashboard, this is the best you’ve got.

 

Emerging GEO Tools and AI Visibility Trackers

This whole space is moving fast. If you’re expecting some polished, all-in-one GEO analytics platform. It’s something that just tells you “Here’s where you’re cited in AI answers”. This doesn’t exist yet, at least, not in any mature way.

But that doesn’t mean there’s nothing you can do.

There are already tools and tactics that make a real difference, even if they weren’t built with GEO in mind from day one.

Prompt discovery is a big one. Generative engines tend to lean on familiar question structures. Knowing what those are gives you an edge.
Tools like AlsoAsked can be surprisingly useful.

1. You type in something like “Best UK B2B agencies”
2. It shows you all the follow-up questions people ask
3. Things like “Top B2B marketing firms London” or “Affordable SEO services UK”

That’s not just good for SEO planning. It tells you exactly the kind of phrasing people use when these AI models are picking up prompts to answer.

The same goes for People Also Ask scrapers. They help you see the real questions that show up in Google’s results. These often end up feeding the AI’s training data or influencing what it thinks is a “natural” question.

Audience research tools aren’t GEO-specific either, but they’re underrated for this.

SparkToro is a great example.

• Want to know which UK marketing podcasts your audience listens to?
• Which local blogs do they trust?
• Where do they hang out online?

Those are the sources that build your authority, because when AI tries to decide if you’re credible, those signals count.
It’s the same logic as old-school link-building, just with an eye to how these engines choose what to summarise.

Direct testing is another piece of the puzzle.

If you’ve got Perplexity Pro or ChatGPT with web access, you can see what they pull in for answers.

Example prompts worth testing:

• Best HR software providers for UK SMEs
• Who offers generative engine optimisation in London?

You’ll see what shows up. Sometimes it’s your content. Sometimes it’s a competitor’s blog post you didn’t realise was winning those queries.

And you’ll probably notice differences between tools. Perplexity might prefer highly structured guides. Bing Copilot could lean on well-known brands. Google’s SGE might be pulling in schema-marked FAQs.

No one said it would be consistent.

Finally, let’s be honest: at the moment, manual audits are still the best way to understand your presence in these AI-generated answers.

But that’s going to change.

You can bet that the next wave of SEO tools will include features to track brand mentions in AI summaries. To measure inclusion rates. To flag opportunities in real time.

The brands paying attention now will be ready to take advantage of that shift the moment those tools arrive.

 

GEO vs AIO vs AEO: What’s the Difference?

As AI reshapes search, a new wave of terminology has emerged. GEO is just one acronym in the mix. You’ll also hear AIO and AEO, often used interchangeably or without much clarity.

Let’s clear that up.

 

Terminology Overview

GEO stands for Generative Engine Optimisation. It focuses on increasing a brand’s visibility within AI-generated responses, particularly from tools like ChatGPT, Bing Copilot, and Google’s AI Overviews.

AIO typically refers to AI Optimisation. This is a broader concept that might include everything from using AI to generate content to adjusting your marketing stack with artificial intelligence in mind. It’s more about how marketers adapt their processes to work with AI, not how they become visible in AI results.

AEO means Answer Engine Optimisation. It’s been around longer than GEO and refers to optimising content to appear in direct answer boxes or featured snippets, especially on Google. Think of it as early groundwork for what GEO is becoming.

In short:

• GEO is about being included in the response
• AEO is about ranking in quick answers
• AIO is about using AI tools and tactics in your workflow

Each term touches the search experience from a different angle.

 

Industry Consensus (or Lack Thereof)

At the moment, there’s no universal agreement on which acronym will stick.

Some agencies have adopted AIO as a catch-all. Others prefer AEO because of its ties to structured data and featured snippets. GEO, however, is gaining traction because it directly addresses what most marketers are now seeing in search: fewer clicks, more AI answers, and new rules of visibility.

Common Ground uses GEO intentionally. It’s a practical framework that bridges SEO, content, and brand strategy in the age of generative search.

As the space matures, GEO is likely to become the dominant label simply because it captures what marketers are actually trying to do: show up in the answers, not just around them.

GEO is one of those terms that can feel abstract or even unnecessary if you drop it into a meeting cold. Most clients do not want another acronym. What they do want is to know what is changing and why it matters to them.

So don’t start with the technical details. Start with the impact.

“Why should they even care?”

Explain the shift in how search works.

It is not just about getting on page one anymore. AI tools are stepping in to answer questions directly. That means fewer clicks from Google’s organic listings. It means competitors can show up in tools like Bing Chat or Perplexity even if they are nowhere near outranking you in classic SEO terms.

Practical impacts worth highlighting:

• Fewer website visits from traditional search results
• Competitors are being recommended in AI-generated answers.
• Your brand is missing entirely from direct, cited responses.

That is the part they will understand straight away. It is tangible. It connects directly to goals they already have, like visibility and lead generation.

From there, move to what changes.

GEO isn’t a total replacement for SEO. It is an evolution. A shift in emphasis.

“Think of it as SEO growing up to handle the way people search now.”

It still needs the basics:

• Keyword research that aligns with real questions users ask
• Backlinks and mentions that signal authority.
• Technical SEO to ensure the site is accessible and fast

But now it also needs:

• Content that is clear and structured enough to be used by machines
• Schema markup to remove ambiguity about what a page is
• Consistent, domain-level authority that AI models can rely on for answers

You might frame it like this in a client meeting:

“We’re not just writing for people scanning Google anymore. We’re writing for the systems that decide what people see before they even click.”

For internal teams, the message can be even simpler.

GEO is not throwing out what you know about SEO. It is building on it. It is the next stage.

“If SEO is about ranking well in search results, GEO is about making sure your content is the answer when someone asks.”

This means close coordination between teams that might traditionally have worked in silos. Editorial teams need to understand schema and structured data. Technical SEO specialists need to care about content clarity and authoritativeness.

“You can’t bolt this on as an afterthought. It has to be part of the strategy from the start.”

Finally, always anchor the conversation to goals that matter to decision-makers.

They don’t want a lecture on schema types. They want to know how they will:

• Increase visibility where buying decisions start
• Build credibility as a source worth trusting.
• Expand their surface area across new platforms that matter.

Because that’s what leadership teams care about.

They do not want to be the brand that misses the shift while competitors get recommended by name. They want to be the one everyone cites.

“GEO isn’t jargon. It’s future-proofing.”

 

Final Thoughts and Next Steps

Generative Engine Optimisation isn’t a buzzword. It’s a strategic response to the evolution of search. As more queries are resolved without clicks, and more users turn to AI tools for answers, the old rules of visibility are breaking down.

This guide covered what GEO is, why it matters, and how to approach it practically. From auditing your brand’s AI footprint to creating content that machines can reference with confidence, every step helps close the gap between what you publish and what actually gets seen.

The shift isn’t just technical. It’s strategic. GEO forces brands to think beyond traffic and toward presence, specifically, how you appear, where you’re cited, and what role you play in the narratives AI engines are building in real time.

So, where should you start?

 

How to Get Started

Begin with a quick audit. Ask ChatGPT or Perplexity about your brand. Log what they say. Then review your most important content through a new lens. Is it factual, well-structured, and tied to a real author? Can a machine summarise it without missing the point?

From there, focus on:

• Building trust signals across your domain
• Tightening your schema implementation
• Creating new content with AI readability in mind

You don’t need to overhaul everything at once. Start with high-impact pages, then prioritise service pages, explainers, and long-form guides that speak to your core offer.

 

Explore Our GEO Services

If you want expert help, we’re here. Common Ground’s GEO service is built to help brands increase visibility in AI-generated answers across Google, ChatGPT, Bing Copilot, and beyond.

We’ll audit your current AI footprint, uncover gaps, and shape a strategy that aligns content, technical SEO, and brand positioning for the future of search.

If you’re looking to show up in AI-generated answers, but are not quite sure where to start, get in touch with us today for a chat.