What Is GEO (Generative Engine Optimisation) and Why Your SEO Strategy Is Already Obsolete

The Question Nobody Is Asking

Here is an experiment worth running right now.

Open ChatGPT, Perplexity or Google's AI Mode. Type in a question your ideal customer would ask about a problem your business solves. Not your company name — the actual question they would ask before they know you exist.

Read the answer. Read it carefully.

Is your brand mentioned? Is your content cited? Is your name, your product, your expertise anywhere in that response?

If the answer is no — and for the majority of Australian businesses it will be no — then your potential customer just got a complete, synthesised answer to their buying question, and your brand did not exist in that conversation.

This is the problem that Generative Engine Optimisation (GEO) exists to solve. And it is a fundamentally different problem from the one traditional SEO was designed for.

The Terminology Mess, Cleared Up

Before going further, it is worth settling the terminology. The industry has not agreed on a single term, and the inconsistency causes genuine confusion.

SEO (Search Engine Optimisation) — the practice of optimising content to rank in traditional search engine results. Google, Bing, lists of blue links. Still critical. Still the foundation. Not going away.

AEO (Answer Engine Optimisation) — originally designed for voice search, now refers to structuring content so it gets extracted and surfaced as a direct answer in AI-driven interfaces. Featured snippets, People Also Ask, and Google AI Overviews are all AEO surfaces. AEO makes your content extractable.

GEO (Generative Engine Optimisation) — the newer layer, specifically about getting your brand cited in AI-generated responses across large language model platforms: ChatGPT, Perplexity, Claude, Google Gemini, Microsoft Copilot. GEO makes your content citable.

LLMO, GSO, AIO — other terms for essentially the same set of practices. The industry has not settled on which acronym wins.

The practical model is a stack:

• SEO makes your content discoverable
• AEO makes your content extractable
• GEO makes your content citable

In 2026, doing one without the others leaves significant visibility on the table.

Why This Matters Right Now — The Numbers

The scale of AI search is no longer speculative. It is measurable and accelerating.

ChatGPT now has more than 900 million weekly users as of April 2026. It processes 2.5 billion prompts daily, 65% of which qualify as search queries. AI-driven referrals to websites surged more than tenfold in the United States between July 2024 and February 2025. Thirty-six percent of generative AI users have replaced traditional search with AI assistants, and 18% use generative AI for tailored product recommendations. By October 2025, McKinsey reported that 50% of consumers were already using AI-powered search intentionally — not experimentally, but as their primary discovery method. Semrush predicts that LLM traffic will overtake traditional Google search by the end of 2027.

And here is the statistic that should change how you think about your SEO investment immediately: research from GEO firm Brandlight suggests that the overlap between top Google links and AI-cited sources has dropped from 70% to below 20%.

Read that again. You can rank number one on Google for a query and still not appear in the AI answer your customer receives. The ranking and the citation are increasingly disconnected signals.

Only 16% of brands systematically track their AI search performance. The competitive window is open. The majority of businesses in most industries have not started yet.

How AI Search Actually Works — What Most Guides Get Wrong

Most GEO guides treat AI search as if it were just a different kind of Google — better at answering questions, same basic mechanics. It is not. The underlying process is fundamentally different, and understanding it changes what you optimise for.

Query fan-out: the step nobody explains

When a user asks an AI platform a complex question, the AI does not process the full question as a single search query. It breaks the question into multiple smaller sub-queries and runs them independently.

If someone asks ChatGPT "What is the best marketing automation platform for an Australian training company with 5,000 contacts?", the AI might generate sub-queries like "marketing automation platforms B2B", "Dynamics 365 CI-J vs HubSpot", "email marketing for training companies", and "marketing automation Australia pricing" — and retrieve content for each separately before synthesising a response.

This means you need content that ranks for the fragments of the question, not just the full query. Comprehensive coverage of a topic area matters more than optimising a single page for a single keyword.

Information retrieval and synthesis

After running fan-out queries, the AI evaluates sources for relevance and credibility, extracts passages, and synthesises them into a single composed response. Your brand can appear in that synthesis as a citation, a mention, or a recommendation. The AI is not returning your page — it is pulling from your page as one of multiple reference sources.

This changes the content format that works. A paragraph that is clearly self-contained, directly answers a specific question, and includes verifiable data or a unique claim is more extractable than a well-structured narrative that requires context to understand.

LLM training data vs real-time retrieval

Different AI platforms work differently. Perplexity and Google AI Overviews retrieve content in real time — your current page quality and recency matter directly. ChatGPT's base model uses training data with a knowledge cutoff, but ChatGPT with search enabled retrieves in real time. Claude similarly has real-time search capability.

For models that use training data, your visibility depends on whether your brand has been cited, published, and referenced widely enough to be part of the corpus. This is why brand mentions, third-party citations, LinkedIn content, community forum participation, and digital PR all feed into GEO — they build the web of references that AI systems learn from, not just the pages they retrieve.

The Three Surfaces You Need to Win

Surface 1: Google AI Overviews

Present on 48% of all Google searches. The most immediately measurable surface. Being cited inside an AI Overview delivers 35% more organic clicks and 91% more paid clicks compared to non-cited brands on the same queries. Google retrieves content in real time, so page quality, schema markup, recency and authority are the primary inputs.

Surface 2: ChatGPT and Perplexity

ChatGPT's 900 million weekly users are asking questions that include your target customers. Perplexity is increasingly used for B2B research. Both platforms heavily reference Reddit, LinkedIn, Wikipedia and authoritative long-form content. Reddit and LinkedIn are the two most cited domains across ChatGPT, Perplexity and Google AI Mode as of January 2026. Your brand presence on these platforms directly affects AI citation.

Surface 3: LLM training and knowledge bases

For base LLM responses (without real-time search), visibility comes from your historical content footprint — how often your brand, your content, and your expertise have been cited, shared, and referenced across the web. This is the slowest surface to influence and the most durable once built. Think of it as domain authority for the AI era: it compounds over time and is genuinely difficult for competitors to replicate quickly.

SEO vs AEO vs GEO: What Actually Differs

Eight Things to Do Right Now

1. Check whether AI crawlers can access your site

Many websites are accidentally blocking AI bots. If you use Cloudflare, check your configuration — Cloudflare recently changed its default settings to block AI crawlers. Check your robots.txt file for directives that exclude GPTBot (OpenAI), PerplexityBot, or ClaudeBot. If AI systems cannot crawl your site, they cannot cite it.

2. Add an llms.txt file

An llms.txt file sits at yoursite.com/llms.txt and gives AI crawlers a structured summary of your business, your services, your expertise and your key content. ChatGPT, Perplexity and Claude all read these files when available. It is the clearest signal you can send an AI engine about who you are and what you know. We built an llms.txt Generator specifically for this.

3. Implement and audit your schema markup

JSON-LD schema tells AI systems what your content is about — FAQ schema, HowTo schema, Article schema, Organisation schema, Person schema. Every important page on your site should have relevant, correctly implemented schema. Run each page through Google's Rich Results Test to confirm your schema is valid. Invalid schema is invisible to AI systems.

4. Write for extraction, not just engagement

Every section of your content should be able to stand alone as an answer to a specific question. AI systems extract paragraphs — not articles. Write each section so that if the heading and that section's first two sentences were extracted without context, they would still make complete sense as a self-contained answer. Lead with the answer. Then explain it.

5. Cover the fan-out queries, not just the primary keyword

Map out the sub-questions an AI would generate when breaking down your target query. Write dedicated content sections (or separate pages) for each sub-query. A comprehensive topic cluster that covers every meaningful question in a subject area performs significantly better in AI retrieval than a single highly-optimised page.

6. Publish original data, case studies and proprietary findings

AI systems actively prefer sources that contain information that cannot be synthesised from other sources. Your real metrics, your genuine client outcomes, your specific practitioner experience — these are your most valuable GEO assets. Generic content, even well-structured generic content, is increasingly invisible to AI citation systems. The posts on this blog with specific numbers (508% YoY growth, +26.73% email revenue) are far more citeable than posts that paraphrase what everyone else has already published.

7. Build your brand presence on AI-referenced platforms

Reddit and LinkedIn are the two most cited domains across major AI platforms. Contributing genuinely useful answers on Reddit threads relevant to your industry, maintaining an active and substantive LinkedIn presence, and earning coverage on authoritative third-party sites all feed into the web of references AI systems draw from. It is not about gaming a platform — it is about building the kind of distributed brand presence that AI systems interpret as authority.

8. Start measuring AI visibility now

Only 16% of brands track AI search performance systematically. Set a baseline today. Start by manually searching your target queries in ChatGPT, Perplexity and Google AI Mode and auditing whether your brand appears. Track AI-referred traffic in GA4 (it shows up as a separate referral source). Use a tool like Semrush Enterprise AIO if you want systematic monitoring. You cannot improve what you are not measuring.

How to Check Your Current AI Search Visibility

A manual audit takes about 20 minutes and gives you a useful baseline.

Step 1. Write down your 10 most important informational queries — the questions your ideal customers ask before they are ready to buy.

Step 2. Search each one in ChatGPT (with browsing enabled), Perplexity and Google AI Mode. Record whether your brand is mentioned, cited or referenced in each response.

Step 3. Check GA4. Go to Traffic Acquisition → Session source/medium. Look for referral traffic from chatgpt.com, perplexity.ai, claude.ai, gemini.google.com, or bing.com/chat. This is your current AI referral baseline.

Step 4. Run your site's most important pages through Google's AI Overview test. Search the primary query for each page in Google and note whether an AI Overview appears, and whether your page is cited within it.

Step 5. Check your robots.txt file at yoursite.com/robots.txt. Look for any User-agent rules that might be restricting GPTBot, ClaudeBot, PerplexityBot or Anthropic's crawlers.

This audit tells you where you are. The eight actions above tell you how to move.

What Changes About How You Measure Success

Traditional SEO reporting — ranking positions, organic click volume, page impressions — does not capture GEO performance. You need additional metrics.

Track:

• Citation frequency: how often your brand appears in AI-generated responses for target queries
• AI referral traffic: sessions from ChatGPT, Perplexity, Claude and Gemini in GA4
• AI Overview appearance rate: the percentage of your target queries where you appear in a Google AI Overview
• Share of voice in AI responses: compared to your primary competitors
• Conversion rate from AI-referred traffic: AI-referred visitors convert at significantly higher rates than average organic (14.2% vs 2.8% in some studies) — track this separately

The goal shifts from "ranking first" to "being cited". Both matter. They are not the same objective and they require different strategies.

Your Audit Starts Here

GEO is not a complete rebuild of your marketing. It is a set of specific additions to what you are already doing — technical changes to how AI systems read your site, structural changes to how your content is written, and strategic expansion of where your brand maintains a presence.

The competitive window is real. The 16% of brands tracking AI visibility today are building citation authority that their competitors are not. That gap compounds.

We built an AI Readiness Scorer to quickly audit how well your website is currently structured for AI visibility — it flags the specific gaps you need to address. We also built an llms.txt Generator to create a properly formatted file for your site in minutes.

If you want a full GEO audit of your website and content, or help implementing the technical and content changes, that is the work we do.

Get in touch here →