How to Do Generative Engine Optimization: Best Practices for Agencies and Brands for AI Visibility

Traditional SEO optimizes content to rank in a list of blue links. Generative engine optimization structures content so AI systems retrieve and quote it inside a generated answer. SEO earns a position on a results page. GEO earns inclusion in the answer itself — the text that appears before the user ever sees a link.

Answer Engine Optimization (AEO) focuses on featured snippets and zero-click answers within traditional SERPs. GEO goes further — targeting the full generative AI layer, including ChatGPT Search, Perplexity AI, and Bing Copilot, which operate outside the traditional SERP entirely. AEO is the foundation. GEO is the next layer built on top of it.

According to Ahrefs, only 11% of citations overlap between ChatGPT and Google AI Overviews. That means optimising for one platform does not guarantee visibility on another. Businesses that implement GEO correctly build citation presence across all platforms simultaneously — compounding visibility that no paid search budget can replicate.

Their content gets crawled, processed, and passed over in favour of competitors with better passage structure. It’s not that their content disappears — it’s that another business’s answer appears first, every time. The compounding effect runs in both directions: early citation share grows, and businesses that start late face a growing gap.

What HubSpot does that most businesses don’t: every blog section opens with a direct answer in the first two sentences. Every technical term is defined at first use. Every comparison question has a table. The content is built for retrieval — not just for ranking.

The lesson is not “be HubSpot.” The lesson is that their content structure is replicable. Any agency or business that applies the same passage architecture to their existing content can close the citation gap within 60–90 days.

The three structural differences between cited and invisible businesses: first, cited businesses write for passage retrieval — not page ranking. Second, they maintain consistent entity architecture across every platform where their brand appears. Third, they give AI crawlers clear permission and clear structure to work with. Remove any one of those three and citation share drops regardless of content quality.

According to Google’s published guidance and Ahrefs citation analysis, the content formats AI Overviews cite most frequently are: numbered how-to lists, definition blocks with a term followed by a plain-English explanation, comparison tables, and FAQ-structured content where the question appears as a heading and the answer follows immediately. Long introductory paragraphs, vague conclusions, and content without structured hierarchy are consistently passed over.

Five signals make content citable by AI systems: a direct answer in the opening passage, self-contained explanation that works without the surrounding page context, specific statistics with named sources, clear entity attribution linking the content to a trusted organisation or author, and structured data that confirms the content’s topic, author, and publication date to the crawler.

Google AI Overviews retrieve passages — not pages. The single most effective tactic is ensuring every H2 section on your key pages opens with a direct, standalone answer to its implied question within the first 40 words. Pair this with FAQPage schema mapping each H3 question to its answer, and Article schema with accurate author and publication date. According to Ahrefs research, only 11% of AI Overview citations overlap with ChatGPT citations — so Google-specific optimization is worth doing independently.

ChatGPT Search uses a combination of Bing’s index and OpenAI’s own crawl (via GPTBot and OAI-SearchBot). The primary signal is entity confidence — does ChatGPT recognise your brand as a consistent, trusted entity? Implement Organization schema with sameAs links to your LinkedIn, Wikipedia (if applicable), Crunchbase, and social profiles. Ensure your brand name appears identically across every external platform. Then confirm GPTBot is explicitly allowed in your robots.txt.

Perplexity weights community validation more than any other major AI search platform. Businesses with active Reddit presence, cited in technical communities, and referenced in documentation-heavy content consistently outperform businesses relying on website content alone. Perplexity’s own crawler (PerplexityBot) must be explicitly allowed. Technical documentation depth — not just marketing copy — is what Perplexity retrieves and cites.

Yes — significantly. Schema markup is the machine-readable translation of your content. It tells AI crawlers not just what your page says, but what type of content it is, who wrote it, when it was published, and what questions it answers. Without a schema, AI systems must infer all of this from unstructured text — and they frequently infer incorrectly or skip the page entirely. The FAQ Page schema in particular maps directly to the question-answer retrieval pattern that AI Overviews use.

llms.txt is a plain-text file placed at your domain root (yourdomain.com/llms.txt) that provides AI systems with a structured overview of your website, brand entity, key pages, and content scope. It functions like a robots.txt for LLMs — not blocking access, but actively guiding it.

A well-implemented llms.txt includes your brand description, key service pages with descriptions, team member entities, and brand authority signals. It’s one of the fastest implementations, highest-impact technical GEO actions available in 2026.

The most effective agency GEO workflow runs in five phases: audit, structure, schema, monitor, report. Each phase produces a client-facing deliverable that demonstrates progress without requiring the client to understand the technical detail behind it.

Foundation fixes — crawler access, passage restructuring, schema basics — produce measurable results within 30–60 days. Full Authority GEO, including entity architecture, external mentions, and citation compounding, takes 4–6 months. The same timeline any serious organic visibility investment requires. What’s different about GEO is that results are visible much earlier, and the compounding curve is steeper.

• We audit before we recommend.
  Every GEO engagement starts with a scored readiness report — crawler access, passage extractability, schema coverage, entity consistency, external signals. You see exactly where you stand before a single dollar of execution budget is spent.
• We cover all four platforms, not just Google.
  Most SEO agencies optimize for Google AI Overviews and call it GEO. Only 12% of AI citations overlap between Google and ChatGPT. That means Google-only optimisation leaves the majority of AI citation opportunity untouched. The team tracks and optimizes across Google AI Overviews, ChatGPT Search, Perplexity AI, and Bing Copilot simultaneously.
• We operate invisibly for agency partners.
  If you’re an agency, your client never sees us. We run the full GEO workflow — audit, content restructuring, schema implementation, monthly reporting — under your brand. Your client sees your name on every deliverable.
• We report on citation share, not just effort.
  Activity reports tell you what was done. Monthly GEO scorecard tells you whether citation frequency moved — by platform, by query, by page. The metric that matters is whether your content is being quoted by AI systems. That’s what we track.