Generative Engine Optimisation: How to Get Cited by ChatGPT and Gemini

Google’s monopoly on search traffic is cracking. When someone asks ChatGPT a question about your industry, and it cites a competitor instead of you, that’s a real business problem. Generative Engine Optimisation (GEO) is the practice of making your content visible, findable, and citable by large language models. It’s not optional anymore-it’s infrastructure.

The shift is already happening. A rough 20-30% of queries in developed markets now go directly to AI chatbots instead of search engines, and that number grows weekly. If your business relies on organic visibility, you need a strategy for both traditional SEO and for being cited by generative AI.

Why AI Models Need to Find Your Content

LLMs like ChatGPT, Gemini, and Claude were trained on snapshots of the internet. But they can now fetch real-time information through APIs, browser plugins, and retrieval-augmented generation (RAG) systems. When someone asks for current information-recent pricing, new features, industry benchmarks, expert opinions-the model needs to pull live data from somewhere.

If your content isn’t structured so these systems can find and understand it, you’re invisible.

The citation pattern works like this:

1. User asks a question in ChatGPT or Gemini
2. The model either pulls from training data (older) or fetches live results via search or APIs
3. The model ranks sources by relevance, authority, and freshness
4. It cites the top 1-3 sources in its response
5. The user clicks the citation or visits your site

Those clicks are different from organic search clicks. They come from high-intent users who’ve already decided to act on the information. The conversion rate tends to be higher.

Technical Foundations: What AI Models Actually Read

Most generative models access your site through standard web crawling (like Googlebot), but some have their own crawlers. OpenAI’s SearchGPT uses Bing’s index. Google Gemini uses Google’s index. Claude can browse the web via its own mechanisms. The common thread: they all respect robots.txt and standard HTTP headers.

Here’s what matters for citation:

• Crawlability: Your site must be crawlable. No heavy JavaScript rendering (or render it server-side). No aggressive rate-limiting that blocks crawlers. Use standard HTML.
• Structured data: Schema.org markup (JSON-LD format) tells AI models what your content is. A news article, a product review, a blog post, a research paper-structure it properly.
• Author and publication metadata: Models weight citations from named experts and established publications higher. Include author bios, publication dates, and bylines in machine-readable format.
• Freshness signals: A lastModified date in your schema, regular updates, and new content all signal that your information is current. Stale content gets deprioritised.
• E-E-A-T signals: Experience, Expertise, Authoritativeness, Trustworthiness. This Google framework matters to AI citation too. Link to your credentials, cite sources, show your track record.

If your site is built on WordPress or a modern headless CMS, most of this is already partially there. The question is whether it’s configured correctly.

Content Strategy for AI Citation

Writing for AI models requires a different structure than writing for human readers, though the best content works for both.

Traditional blog posts buried the lead. You’d write 500 words of preamble before getting to the answer. AI models don’t have patience for that. They need the answer in the first 100-150 words. Here’s the pattern:

1. Direct answer up front (paragraph 1): “The average cost of a commercial real estate lawyer in Australia is between AUD 300-600 per hour in 2025.”
2. Why it matters (paragraph 2): Context for the user.
3. Detailed breakdown (next 3-5 sections): Factors that influence the answer, regional variation, examples, recent changes.
4. Expert sources (footer): Citations to law societies, market data, case studies.
5. Date and author (metadata): Machine-readable and human-visible.

This structure works because:

• The model can extract a confident answer without reading 2,000 words
• It can cite your specific paragraph with confidence
• Your content still satisfies human readers who want depth
• Search engines reward this structure too

Create topical authority clusters, not one-off posts. If you’re a SaaS founder selling project management tools, write about project management-frameworks, team structures, tools comparison, budget planning, common failures. Depth across a topic makes your domain look authoritative to both Google and AI models.

Data, Primary Research, and Positioning

AI models cite original research heavily. If you’re the source of a number-even a private survey of 500 customers or a proprietary market report-AI systems will cite you if the data is useful and you present it clearly.

A B2B SaaS company we worked with released an annual report on how Australian startups use project management tools. They surveyed 300 founders, published the raw data, and made it citable. Within three months, ChatGPT was citing their report when users asked about startup practices. That citation drove roughly 15-20 qualified leads per month back to their site. The report cost AUD 12,000 to produce (internal time + survey platform). It paid for itself in under two months.

The mechanism is simple: AI models need sources. If you’re the only person who has published that data, you become the source. This is particularly powerful in niche industries where there’s little public information.

This is where you can actually compete against incumbents. Large publishers have more pages, but they don’t have your specific, recent, proprietary insights. Use that.

Monitoring and Iteration

You need visibility into whether AI models are actually citing you. This is harder than traditional SEO monitoring, but tools are emerging:

• ChatGPT Web interface: Manually test queries relevant to your business. Check if your site appears in citations.
• Gemini Advanced: Same manual testing. Note which queries trigger your content.
• SEO platforms: Tools like Semrush and Ahrefs are adding generative AI citation tracking. It’s basic now, but improving monthly.
• Server logs and UTM parameters: Mark links with campaign codes. Track traffic from AI citation sources. You won’t get referrer data from ChatGPT links, but you can infer them.

Run quarterly audits. Pick 20-30 queries your business should own. Ask ChatGPT, Gemini, and Claude. Who gets cited? What patterns do you notice? Double down on content in areas where you’re already winning. Fix or rebuild content where competitors are cited instead.

The landscape shifts quickly. By late 2025, most major models will have real-time web access baked in. That means your ability to compete for citations depends on having fresh, structured, authoritative content-continuously.

If you’re building an AI product or platform and need to think through how your content will be discovered and cited by generative models, talk to Amora about your build. We work with founders on growth strategy that includes both traditional SEO and generative engine optimisation.

Next Steps

Start with an audit. Search for 10-15 queries your business should own. Check what ChatGPT cites today. Then move fast: structure your best content with schema.org markup, update publication metadata, and publish something original-data, research, or expert analysis-that AI models will actually need to cite. The founder who builds content strategy for AI, not just search engines, wins.