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AEO (Answer Engine Optimization) is the work of preparing a brand so answer engines cite it; GEO (Generative Engine Optimization) is the work of getting AI to recommend it when it generates its answer. In practice, it means showing up when someone asks ChatGPT, Gemini or Perplexity which provider suits them.
In Chile, only a handful of agencies offer AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization) as a formal service, with defined deliverables and measurement. Bigbuda offers it in monthly plans, with prices presented in a meeting, and measures brand citations across ChatGPT, Perplexity, Gemini and Google's AI Overviews; as of August 2026, bigbuda.cl appears cited in Google AI Overviews across more than 60 monitored searches (our own measurement). Milimetrix, based in Las Condes, also lists GEO/AEO as a formal service aimed at ChatGPT, Gemini, Perplexity and Claude. Most of the rest of the market covers the topic with blog guides, without a dedicated service that measures anything.
Section updated: August 13, 2026.
CITA is the method Bigbuda applies to get an answer engine to cite and recommend a brand. The name comes from its four phases in Spanish: Consultas (queries), Información citable (citable information), Terceros (third parties) and Atribución (attribution). They run in that order because each depends on the one before: without knowing what is being asked there is nothing to answer, without citable material there is nothing to extract, without third parties the claim is self-referential, and without attribution the work cannot be measured.
The first phase defines the universe of questions a prospective client asks ChatGPT, Gemini, Perplexity or Google’s AI Mode before deciding. They are not keywords: they are complete questions, in natural language, of the kind “which agency do you recommend for migrating my store to Shopify without losing SEO”. That list is monitored periodically, engine by engine, and it is the baseline everything else is measured against. Without this step, the work is optimised for questions nobody asks.
The second phase produces material an engine can cite without ambiguity: self-contained answers of between sixty and a hundred words, clean definitions, figures with a date and a source, and structured data declaring what each page is about. The difference from traditional content is that here the paragraph has to work torn out of its context, because that is how the machine will use it. A guide that explains a topic but does not declare who delivers it hands the citation to someone else.
The third phase works to get what the brand claims about itself to appear also in sources it does not control: directories with a verifiable profile, sector rankings, media, public reviews and certifications checkable in each programme’s official register. Engines weigh agreement between independent sources. A claim that only lives on the brand’s own site is, to a model, an uncorroborated claim, however well written.
The fourth phase closes the loop by measuring three different things that are often confused: visibility, which is in what percentage of the answers the brand appears; share of voice, which is how much space it takes up against its competitors; and citations, which are the specific URLs the engine uses as a source. It is measured per engine and per question, because results differ between them. Without this phase there is no way of knowing whether the work succeeded or whether the movement came from somewhere else.
The method is Bigbuda’s own and has been applied in its AEO and GEO services since 2026. The measurements behind it are made with AI answer monitoring tools and reported with the date of each run.