Once upon a time, cracking Google's algorithm was the holy grail of digital marketing. You'd sprinkle the right keywords, build some backlinks, and boom - top of the SERPs. But the search game has changed, and it's not just SEO anymore.
Now we've got GEO, AEO, LLMO - a growing acronym soup that sounds more like a law firm than a digital strategy. But behind some of the buzzwords, the future rules of modern visibility are being formed.
As search engines get smarter - and AI assistants become our go-to guides - businesses need to not just optimise for traditional SEO but for answers, conversations, and even generative experiences. That means learning the differences between:
Many marketing articles suggest that AEO, GEO, LLMO (and even AIO) largely overlap and describe the same strategic goal - improving visibility in AI-mediated search - and differ more in framing than in underlying tactics, which includes understanding AI crawlers.
This guide tries to make sense of what each of these strategies means, how they work, where they overlap, and why they all matter right now.
Because here's the thing: the businesses that adapt early to these changes? They won't just be found - they'll lead the conversation.
GEO stands for Generative Engine Optimisation - a new approach to content marketing that focuses on how brands show up in generative AI tools like ChatGPT, Google's Search Generative Experience (SGE), Perplexity, Claude, and many others.
Unlike traditional search engines, these generative engines don't just list links; they create answers. GEO is about influencing those answers.
Think of it this way: while SEO helps you rank on Google and other search engines, GEO helps you appear in AI-generated conversations that provide concise and relevant answers. And with more users turning to AI for information, product suggestions, and even purchasing decisions, GEO is quickly becoming a must-have part of the digital marketing mix.
It's not just about keywords anymore. It's about credibility, context, structure, and LLM-friendly formatting - ensuring your content is not just searchable, but usable by AI.
The term “Generative Engine Optimisation” was introduced in 2023 in academic literature and includes metrics like GEO-bench, which showed content visibility could improve by up to 40% in generative engine outputs.
Generative Engine Optimisation works by aligning your content with the way Large Language Models (LLMs) ingest, understand, and generate information. These AI models don't just 'crawl' the web like search engines - they learn from large-scale datasets and retrieve relevant answers based on patterns, structure, and credibility.
It's all about being included in the narrative - not just snipped - but woven into answers or summaries.
Here's what that means:
Generative engines prefer content they can trust. That means:
Well-structured content helps LLMs understand and pull relevant snippets. Think:
LLMs are designed to replicate natural human conversation through natural language processing, enabling them to better understand and respond to the way people speak. GEO content anticipates user intent and speaks to it in a helpful, conversational tone – not keyword-stuffed jargon.
Generative engines often rely on embedding vectors - mathematical representations of meaning. The clearer your content's intent and language, the more likely it is to be included in these AI 'memory banks'.
In short? GEO works by making your content more useful, understandable, and retrievable - not just by humans, but by the machines humans are increasingly turning to.
AEO is all about a strategy to format content so AI-powered answer engines - think Microsoft Copilot, and Google's AI overviews - can surface content as a direct answer to a user's question - especially in search environments where results are increasing zero-click.
It concentrates on Q&A-style formatting, structured data (like schema markup), and trust signals to increase inclusion in zero-click AI responses.
You've probably seen it in action:
In essence, AEO asks: "How can I become the answer?"
It's about creating content that search engines and AI tools can quickly trust and parse. The goal is for your content to be displayed instantly when needed.
AEO's scope is becoming broader, targeting AI-generated answer platforms, not just traditional search results.
As more users lean into AEO, AI assistance, instant answers, and optimising for voice search results is becoming essential. Ignoring it is no longer viable.
AEO works by aligning your content with the way search engines and AI assistants extract and deliver precise answers - not pages, not posts, but answers.
It's less about ranking and more about relevance, clarity, and authority.
Here's how it works in practice:
AEO content is built to answer questions directly, offering valuable insights and clear takeaways for the reader. - ideally in the first 2-3 sentences.
Structured data (like FAQs, how-tos, and article schema) helps answer engines understand the context of your content and surface it in rich results.
Answer engines rely heavily on entities (people, places, brands, products) to match content to user queries. AEO content names and defines those entities, making connections easier to parse.
AEO works best when you speak like your audience. That means:
Author bios, dates, external links, and clear citations build authority - and help search engines select your answer over someone else's.
LLMO focuses on structuring content in ways that make it better understood and retrievable by LLMs' internal mechanisms - vector embeddings, semantic clarity, and being presented in high-authority sources that LLMs learn from.
LLMO is about more than rankings - it's about representation:
That's the game LLMO plays. It may be a newer field than SEO or AEO - but it's fast becoming the first stop for research, discovery, and decision-making.
LLMs, or Large Language Models, are powerful AI systems that thrive on vast amounts of optimised text data to understand and generate human-like language. Think of them as digital brains that can read, write, summarise, translate, code - and most important for marketers: answer.
You're already interacting with LLMs every day, whether you realise it or not:
These models aren't search engines in the traditional sense. Instead of crawling the web in real time, they rely on what they've been optimised for - semantically rich, vector-friendly content, and strategic presence in high-authority sources that LLMs already reference.
That's why getting your content recognised by LLMs has become a critical piece of visibility - and where GEO and LLMO come in.
LLMO works by ensuring your content is seen, understood, and retrieved by Large Language Models during user interactions - even if there's no traditional search engine involved.
Since LLMs don't crawl the web in real time, LLMO is less about real-time indexing and more about embedding yourself in the AI's training data, knowledge graphs, or retrieval plugins.
Here's how LLMO works:
LLMs love content that's well-organised, factual, and easy to semantically 'digest'. That means:
LLMs often pull from high-authority databases and sources (like Wikipedia, GitHub, government sites, industry publications). Being referenced in these places boosts your presence in their output - even if your site isn't directly crawled.
When you write clearly and contextually, your context forms a unique meaning fingerprint called a vector. These vectors are stored in databases LLMs use to retrieve relevant content. The more semantically rich your content, the more findable you are.
LLMs thrive on content that mimics human conversation and Q&A:
Some LLMs (like Perplexity or You.com) cite sources. Optimising for these platforms by making your metadata, headlines, and claims easy to quote increases your chance of being surfaced as a cited source.
LLMO isn't about having search algorithms - it's about aligning with how AI understands and selects language. The more useful and trustworthy your content is to the model, the more visible you'll become within it.
Getting seen by Large Language Models (LLMs) is about making your content useful, trustworthy, and retrievable in AI-powered environments.
Let's explore how to boost your LLM visibility step by step:
LLMs often use Retrieval-Augmented Generation (RAG) - meaning they fetch supporting documents or web pages to help answer a prompt. If your high-quality content is clear, structured, and contextually rich, it's more likely to be pulled into those responses.
Being mentioned on well-known, trusted sites - such as industry publications or educational domains - increases your exposure in training sets and retrieval databases.
If you can't be the source, be on the sources.
LLMS pull from structured signals like:
LLMs are trained on how people talk, not how marketers write. Use the same tone your audience would use when asking a question.
Instead of:
"Leveraging enterprise-grade CRM solutions for scalable outcomes."
Try:
"What's the best CRM for growing a small business?"
But...
While optimising for AI visibility includes citing sources and authoritative presentation, there are ethical risks to consider - like manipulating generative AI with strategic text sequences - which could undermine trust in AI-delivered answers
LLMs don't always learn from a single page; they learn from patterns across multiple sources.
Publish regularly. Repeat your core themes and expertise. Be findable across formats: blogs, podcasts, PDFs, social media, video transcripts.
Think of LLM visibility like digital osmosis - the more helpful. Human, and widely distributed your content is, the more likely it is to be absorbed into the model's world.
SEO is the long-established approach of optimising your website to rank highly, especially on platforms like Google, Bing, and Yahoo, using keywords, backlinks, technical improvements, and user experience.
It's the classic formula:
Better visibility = more clicks = more traffic = more leads/sales.
SEO focuses on helping search engines understand:
Done right, SEO helps you capture intent-driven traffic - people who are actively searching for something you offer.
It includes both on-page and off-page strategies, such as:
While SEO has been the cornerstone of digital strategy for decades, it's changing - and is now intersecting with newer models like GEO, AEO, and LLMO.
At its core, SEO works by making your website more discoverable, understandable, and valuable in the eyes of search engines - especially Google, which processes over 8.5 billion searches per day.
Here's how it breaks down:
To match searcher intent, your content needs to intent, your content needs to include the right keywords, structured under clear headings, and written in a way that will enhance user experience and further engagement.
Google wants to serve the best possible result for relevant search queries, providing an answer to user queries that demonstrates expertise and authority - so your job is to prove it's you.
Backlinks from other websites act as votes of confidence. The more trustworthy and relevant the sources linking to your content, the better your site will perform in organic rankings.
Domain authority, brand visibility, and even social signals all play a part.
Search engines measure how people interact with your site:
Google interprets these behaviours as quality signals - and ranks accordingly.
The behind-the-scenes structure of your website - like XML sitemaps, canonical tags, internal linking, HTTPS security, and structured data - helps search engines index your pages correctly and efficiently.
In short: SEO works by making sure your site ticks all the right boxes - for both bots and humans.
While GEO, AEO, and SEO may sound like the members of the same digital marketing boy band, they each play a very different role in how content gets found - and by whom.
Let's break it down:
Goal: Rank higher in search engine results pages (SERPs).
Audience: People using traditional search engines (e.g. Google and Bing).
Optimised For: Algorithms that prioritise links, keywords, content depth, UX, and site authority.
Format: Full pages, blogs, and landing pages.
Goal: Be selected as the direct answer to a specific query.
Audience: People using voice search, smart assistants, or featured snippets.
Optimised For: Short, structured answers, entity clarity, and schema markup.
Format: Q&AS, FAQs, definitions, how-tos, and featured snippets.
Goal: Be surface in AI-generated responses (like ChatGPT or Google SGE).
Audience: People using a generative engine to research, decide, or explore.
Optimised For: LLM-friendly formatting, semantic clarity, and credibility signals.
Format: Conversational, citation-read, and chunked content that's easy to summarise.
Think of it like this:
And together? They form a modern visibility strategy across both search and AI.
Despite their differences, these four optimisation strategies all aim for the same end goal:
Here's what unites GEO, AEO, LLMO, and SEO at their core:
Whether you're targeting Google's algorithm or ChatGPT's next-generation brain, the focus is the same:
Be helpful. Be relevant. Be clear.
All four strategies reward content that:
Search engines and LLMs both prioritise trustworthy sources. That means:
If people trust you, algorithms and AI are more likely to as well.
Structured content isn't just for technical SEO anymore. It helps LLMs understand context, improves scanning, and enables features like:
Think: headers, lists, definitions, and schema.
The way people discover information is changing at lightning speed. SEO once dominated that space, but now, AI-powered tools are front and centre.
All four methods aim to answer the same question:
"When someone's looking for what we do - will we shop up?"
These strategies shouldn't be seen as rivals, but teammates - each covering a different channel across the digital ecosystem.
Because the way people search is changing - and if your brand isn't adapting, it's disappearing.
Generative engines are becoming the first stop for research, recommendations, and decision-making. These tools don't serve up a list of links; they serve up answers. That means if your content isn't optimised for these platforms, you might become completely invisible.
We’re moving from searching to asking. From “Googling it” to “Asking ChatGPT” or checking Google’s AI Overviews.
If your content isn't part of that answer, you're not in the game.
AI-generated responses often satisfy a user's intent without sending them to a website at all. That means you can't rely solely on clicks anymore - you need to be part of the output itself.
GEO is still new territory, meaning:
Early adopters are already shaping the knowledge that future AI responses will draw from. Why not be one of them?
From product comparisons to 'best of' lists, AI tools are already recommending services, tools, and brands. GEO ensures your offering gets considered - even before a user hits your website.
By no means are we saying that GEO is a replacement for SEO - it's the next layer on top to enhance online visibility and future-proof your content strategy.
Search is no longer just about being found - it's about being chosen by humans and machines.
Whether it's traditional SEO, answer-led AEO, AI-savvy GEO, or cutting-edge LLMO, your brand needs to show up where decisions are being made - not just where searches begin.
At Blue Train Marketing we help businesses not only rank higher - but show up in the answers AI is already gathering. From SEO fundamentals to LLM-ready content strategies, we'll make sure your brand leads the digital conversation.
Find out about LLM-optimsation and other search strategies to take your search strategy into the future.