What is GEO (Generative Engine Optimisation)?

An AI answer draws on two sources of knowledge.

What the model already knows. Large language models learn from huge amounts of web text during training. If your brand was described often and consistently in that text, the model may know who you are without searching. If it was barely mentioned, it will not.

What it retrieves at the moment of asking. For many questions, especially current, local or commercial ones, ChatGPT, Perplexity, Copilot and Google's AI features run web searches, read the top results, and write an answer from them, often with citations. Google's AI Mode goes further, splitting one question into several related searches and combining the results.

GEO works on both. Retrieval rewards pages that are indexed, rank reasonably and contain a clean, quotable answer. Model knowledge rewards a brand that appears consistently across credible sources over time.

SEO competes for positions in a list of links. GEO competes to be included in a single written answer. That changes three things:

• The unit is the passage, not the page. Engines quote a paragraph, a definition or a list. A section that needs the previous three to make sense is hard to lift.
• Your brand's reputation off-site matters more. When someone asks "which agencies in Dubai do X?", the engine names businesses it has seen described as doing X by sources other than themselves.
• There is no fixed rank. Answers vary between engines and between runs. You measure how often you appear across many prompts, not one position.

GEO does not replace SEO. Most retrieval still runs on search indexes, so a page that cannot be crawled, indexed or ranked rarely gets cited.

• A direct answer in the first two to four sentences of the page and of each section.
• Specifics instead of adjectives: prices or price ranges, timelines, named locations, steps, criteria.
• Headings that mirror real questions your buyers ask.
• One idea per section, so each section stands on its own.
• A clear author or organisation, with an about page and consistent business details.
• Structured data that matches the page, such as Organization, Article and Product schema.
• Corroboration elsewhere: the same facts about you appearing on directories, reviews, press and sector publications.

1. Write your prompt set. List 20 to 50 questions real buyers would ask an AI assistant: "best X in Dubai", "how much does X cost in the UAE", "X vs Y", plus questions about your brand by name.
2. Run a baseline. Ask each question in ChatGPT, Perplexity, Gemini, Copilot and Google (to trigger AI Overviews or AI Mode). Record who is named, which sources are cited and how you are described.
3. Check access. Make sure robots.txt and your CDN or firewall do not block search crawlers such as Googlebot, Bingbot, OAI-SearchBot and PerplexityBot.
4. Fix the entity. Same name, category, location and one-line description on your site, schema, Google Business Profile, LinkedIn and directories.
5. Restructure priority pages. Answer-first, question-led headings, specifics, one idea per section.
6. Fill gaps. If the engines cite a type of page you do not have, such as a comparison, a pricing guide or a local guide, build it.
7. Earn third-party mentions on the sources the engines already cite for your topics, through PR, contributed articles and reviews.
8. Re-run the prompt set monthly and compare against the baseline.

• Starting with tactics before measuring. Without a baseline you cannot tell whether anything worked.
• Only rewriting your own site. If no one else describes you, engines have little reason to name you.
• Inconsistent positioning. Calling yourself a "consultancy" on one platform and a "software company" on another makes the entity harder to resolve.
• Expecting llms.txt to do the job. It is an unproven convention. Fundamentals come first.

Here is a hypothetical. Say you run a 15-person cybersecurity consultancy in Dubai. Your baseline shows that ChatGPT and Perplexity name four competitors for "cybersecurity consultancy Dubai" and never mention you, while Google's AI Overview cites a competitor's blog post on UAE data protection rules.

The plan: tidy your listings so every platform calls you a cybersecurity consultancy in Dubai; rewrite your services page so the first paragraph says exactly who you serve and what you do; publish a clear, well-sourced guide to the regulation the AI Overview is answering questions about; and pitch expert comment to the regional tech publications Perplexity keeps citing. Re-run the prompts monthly, and expect the retrieval-led engines to move before the model-knowledge ones.

Every GEO engagement starts with an AI visibility check: a prompt set built from your buyers' questions, run across ChatGPT, Perplexity, Gemini, Copilot and Google's AI features, with every named brand, cited source and description logged. That baseline tells us whether your gap is access, content, entity consistency or third-party mentions.

The work then follows the gap. Site and structure fixes, sometimes a rebuild through Web Design when the CMS or templates are the problem. Page restructuring for extraction. Listings cleanup. PR distribution and contributed articles aimed at the publications the engines already cite. We automate the monthly prompt runs and reporting with the same tooling we use in AI Automation, so trend lines arrive without manual copy and paste.

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