Be the Source AI Answers Cite

Traditional SEO optimises for the 10 blue links in Google Search. GEO optimises for the AI-generated answer that now appears above those links — the Google AI Overview, or the ChatGPT and Perplexity response to a question. The signals are different: traditional SEO rewards high domain authority and keyword density; GEO rewards direct, factual answers, structured content, cited statistics, and genuine expertise. A page can rank #1 in traditional SEO but never be cited by an AI engine if it does not contain a clear, self-contained answer to the user's question.

Traditional search optimisation earned you a position in a list of blue links. A user clicked, visited your site, and you had the opportunity to convert them. AI search changes this dynamic fundamentally. When Google shows an AI Overview above organic results, a significant percentage of users read the answer and never click through. When someone asks ChatGPT about the best approach to a problem, the answer draws from a set of source documents — and the businesses whose content is cited are the ones that influence the response, get the brand mention, and earn the small percentage of users who click the source links. Being a source AI systems trust is the new version of ranking on page one.

Google AI Overviews (formerly SGE) appear above organic results for a significant and growing percentage of queries — particularly informational, how-to, and comparison searches. They pull content from pages Google already ranks highly in organic search, which means strong SEO performance is the primary prerequisite for AI Overview inclusion. Beyond ranking, content that appears in AI Overviews tends to have clear, direct answers to the query in the first paragraph, properly formatted headings that match the question structure, and FAQPage or HowTo schema markup that makes the answer structure machine-readable.

Perplexity AI is particularly valuable for GEO because it explicitly shows source citations for every answer — users see exactly which websites contributed to the response. Being a cited source in Perplexity is a direct brand impression. ChatGPT with web browsing operates similarly for queries where it chooses to retrieve current information. For these platforms, content that gets cited tends to be: structured around specific factual claims that can be extracted cleanly, written at a high readability level that reduces ambiguity, from domains with clear topical authority in the subject area, and accessible to web crawlers (no login walls, minimal JavaScript rendering requirements).

AI systems prefer to cite content that makes specific, extractable factual claims — statements that can be quoted accurately without requiring the full context of the surrounding article. Generic language ("there are many ways to approach this") is never cited. Specific language ("studies show X% of businesses experience Y within Z months, according to [source]") is frequently cited. We restructure content to include: definition-first opening sections that directly answer what a term or concept means, step-by-step instructional sections with numbered lists that AI can quote sequentially, statistics with named sources that AI can verify and attribute, and summary statements that encapsulate the key claim of each section in a single quotable sentence.

Original research, surveys, and proprietary data are among the most frequently cited content types across all AI platforms. When your content contains a statistic or finding that no one else has — survey data from your customer base, case study results from your work, analysis of industry trends using your own methodology — AI systems cannot get that claim from anywhere else and are more likely to cite you. We help clients identify what original data they already have (even informal survey results or client data aggregates) and how to structure it for maximum citation probability. A single well-cited original statistic can earn hundreds of brand mentions in AI-generated answers over its useful life.

FAQPage schema marks up question-and-answer pairs, making each question and answer independently extractable — ideal for AI Overviews and voice search. HowTo schema marks up step-by-step instructions, which AI systems frequently cite for procedural queries. Article schema with author markup (linking to a Person entity with credentials) supports E-E-A-T signals that influence citation probability. Speakable schema marks sections of content as appropriate for text-to-speech, which correlates with content Google considers clear and direct enough for AI response use. We implement the full schema set as part of GEO work, not just for SEO purposes.

AI systems build knowledge graphs of entities — companies, people, products, concepts — and their relationships. When your brand appears as a clear, consistent entity across its website, social profiles, Google Business Profile, and third-party mentions, AI systems are more likely to correctly identify and cite it. Entity optimisation involves: consistent NAP (name, address, phone) data across all platforms, Organisation schema on every page with correct identifiers, sameAs markup linking to verified social profiles, Wikidata presence for larger brands, and structured content that explicitly states what your brand does and who it serves in machine-readable format.

Voice assistants and direct answer boxes return a single answer, not a list. The source of that answer earns the brand mention without the user necessarily clicking through to the website. AEO optimises for: Featured Snippets (the content block above organic results that Google selects as the best answer to a specific query), People Also Ask (the expandable question boxes that draw direct answers from web content), voice search responses from Google Assistant, Siri, and Alexa, and the increasingly prominent direct answer boxes in mobile search. All of these draw from well-structured content that answers specific questions directly in the first 40 to 60 words.

AEO-optimised content follows a specific structure: H2 or H3 heading that is the exact question, followed immediately by a direct 40 to 60 word answer, followed by more detailed explanation for users who want depth. This inverted pyramid structure gives the AI or voice assistant the answer it needs at the top, while still satisfying the intent of a human reader who wants the full context. We audit existing content for AEO opportunities — identifying questions your pages almost answer correctly but structure poorly — and update headings and opening paragraphs to match the format that earns featured positions.

Currently measurable: AI Overview appearance rate for a defined set of target queries (tracked via SERP monitoring tools that record whether an AI Overview is present and whether our client content appears in it); Featured Snippet and PAA inclusion rates (measurable through Google Search Console and third-party rank tracking); Perplexity and Bing Copilot referral traffic visible in GA4 under the referral source; and manual citation testing of target queries in ChatGPT, Perplexity, and Gemini. Currently not reliably measurable: ChatGPT non-browsing responses (these use training data, not live web retrieval, and cite no sources), voice assistant responses at scale, and the exact frequency of non-attributed brand mentions in AI summaries.

Monthly GEO reports cover: AI Overview appearance frequency for the target query set (sample of 20 to 50 queries tracked consistently each month), Featured Snippet and PAA wins and losses, AI search platform referral traffic trend, manual citation test results for key brand and category queries, and the GEO content updates published during the period with rationale. As measurement tooling matures, we update our methodology and expand what we can track. We are always transparent about the difference between what we know and what we are inferring.