Answer Engine Optimisation (AEO) makes your brand the authoritative source that ChatGPT, Perplexity, Gemini, and Google AI Overviews cite. Stop hoping AI mentions you — make it inevitable.
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Answer Engine Optimisation (AEO) is the practice of making your brand, content, and entity the source that AI systems choose to cite when answering user queries. Unlike traditional SEO — which focuses on ranking in a list of blue links — AEO optimises for retrieval-augmented generation (RAG), training data influence, and entity authority so AI engines confidently reference your brand.
AI engines like ChatGPT, Perplexity, and Google Gemini pull answers from trusted, well-structured, entity-verified sources. If your brand lacks schema markup, a verified Knowledge Graph presence, and original E-E-A-T signals, you are invisible to the AI layer — even if you rank on page one of Google.
AI engines don't just pull from search rankings. They cite sources they consider authoritative, well-structured, and entity-verified — regardless of where they rank on Google.
AI systems understand the world through entities — named people, companies, places, and concepts. If your brand entity isn't established, you don't exist to AI.
Structured data (JSON-LD schema) is the language AI engines read to understand your content. Without it, even great content is difficult for AI to parse and cite confidently.
Experience, Expertise, Authoritativeness, and Trustworthiness signals tell AI systems your content is reliable. Author entities, credentials, and citations are the proof they need.
AI engines preferentially cite unique data, studies, and original insights they can't find elsewhere. Being the primary source is the highest-value AEO strategy available.
AEO doesn't replace SEO — it builds on it. Strong domain authority, quality backlinks, and solid technical foundations amplify your AI citation signals.
Our AEO frameworks are purpose-built for how AI engines retrieve, evaluate, and cite sources — not retrofitted SEO tactics.
We establish and verify your brand entity across Knowledge Graph, Wikidata, and structured data sources AI engines trust.
We deploy 20+ JSON-LD schema types with surgical accuracy — Organisation, FAQ, HowTo, Article, Person, and more.
We create proprietary studies and data reports designed to become the primary cited source in AI-generated answers.
We track your brand's citation rate across ChatGPT, Perplexity, Gemini, Copilot, and Google AI Overviews simultaneously.
Monthly reports showing exactly which AI engines cite you, for which queries, and how citation share is trending.
Every layer of AI citation optimisation covered — from technical schema to entity authority to original research.
Monitor your brand's citation frequency and sentiment across ChatGPT, Perplexity, Gemini, Copilot, and AI Overviews.
Monthly benchmarking of your AI citation share vs. competitors for your core query clusters.
Identify which queries your brand is cited for — and the high-value gaps where competitors appear instead.
Systematic prompting across AI engines to evaluate how your brand is described, compared, and recommended.
Benchmark your current citation rate across 5 AI engines, map competitor presence, and identify the highest-value query gaps.
Establish your brand entity in Google's Knowledge Graph, deploy site-wide schema markup, and create your llms.txt file.
Produce FAQ clusters, HowTo guides, and original research designed to be pulled into AI-generated answers for your key queries.
Build authoritative citations through digital PR, Wikipedia presence, Wikidata entries, and structured data alignment.
Track AI citation share monthly, test prompt responses, identify new citation opportunities, and expand content coverage.
Answer Engine Optimisation (AEO) is the practice of structuring your brand, content, and entity signals so that AI engines — ChatGPT, Perplexity, Gemini, and Google AI Overviews — select your brand as a cited source when generating answers. Traditional SEO optimises for ranking positions in search result lists; AEO optimises for citation in AI-generated responses. The two disciplines are complementary: strong SEO foundations (domain authority, quality backlinks, technical health) amplify AEO signals, but AEO requires additional layers — schema markup, entity verification, Knowledge Graph presence, and answer-formatted content — that standard SEO doesn't address.
Most clients see meaningful movement in AI citation rates within 60–90 days of completing the entity and schema foundation work. The fastest gains come from fixing technical barriers (missing schema, unverified entities, blocked AI bots) and creating answer-optimised FAQ content. Deeper strategies like Wikipedia entity building, original research amplification, and Knowledge Graph verification compound over 3–6 months. We measure progress through monthly AI citation share reports that track how often and accurately each AI engine references your brand.
We optimise for the five major AI engines that generate commercially relevant answers: ChatGPT (OpenAI), Perplexity AI, Google Gemini, Google AI Overviews (Search Generative Experience), and Microsoft Copilot. Each engine uses different retrieval mechanisms — some rely heavily on real-time web retrieval, others on training data, others on structured data signals — so our strategy is tailored to each engine's specific citation behaviour. We monitor citation performance across all five and report on each individually.
No — AEO builds on top of traditional SEO, it doesn't replace it. Strong domain authority, quality backlinks, technical site health, and keyword-optimised content remain important foundations. In fact, AI engines like Perplexity actively retrieve from the live web and preferentially cite pages that already rank well organically. The difference is that AEO adds a second optimisation layer — schema markup, entity signals, answer-formatted content, and Knowledge Graph presence — that traditional SEO doesn't cover but that AI citation algorithms depend on.
Schema markup (JSON-LD structured data) is the machine-readable language that AI engines use to understand what your content is about, who created it, and whether it's trustworthy. Without it, AI systems must infer meaning from unstructured text — a process prone to errors and uncertainty that reduces citation confidence. With comprehensive schema markup (Organization, Person, Article, FAQ, HowTo, LocalBusiness, and others), AI engines can parse your content with high confidence and are significantly more likely to cite it in generated responses. We deploy 20+ schema types as part of every AI SEO engagement.
llms.txt is an emerging standard (similar to robots.txt) that provides AI language models with structured guidance on how to interpret and use your website's content. It typically includes a plain-language description of your brand, key pages, and how you want AI systems to represent you. While not yet universally adopted by all AI engines, major LLM providers including OpenAI and Anthropic have acknowledged its value, and early movers who implement it benefit from cleaner AI content parsing. We create and configure your llms.txt as part of our technical AEO setup.
A B2B SaaS company had strong Google rankings but zero presence in AI-generated answers. Competitors were being cited by ChatGPT and Perplexity in response to their highest-value queries. We ran a full AEO engagement: entity verification, 20+ schema types, llms.txt setup, 40 FAQ clusters, and original industry research amplified through digital PR in authoritative publications.
Get a free AI visibility audit and discover where your brand appears — and where it doesn't — across ChatGPT, Perplexity, and Google AI Overviews. We'll map the gaps and build the strategy to close them.
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