Everything we publish on getting cited by ChatGPT, Google AI Overviews, AI Mode, Perplexity, and Gemini — audits, trackers, schema work, and free visibility checkers.
Generative engine optimization is the practice of making a brand retrievable, quotable, and citable by AI answer engines. It shares an index with classic search but rewards a different set of signals: an unambiguous entity identity, structured data that machines can resolve without inference, atomic answers a model can lift verbatim, and third-party corroboration that raises confidence in the claim. This hub collects every GEO service, guide, and free checker we publish.
In AI search the shortlist is the SERP. Being on page one of an index nobody reads is not distribution.
— Arise GEO, GEO & AI Search
If an AI engine cannot state what your company is, who it serves, and what it sells in one sentence, it will cite a competitor that made that easy.
— Arise GEO, GEO & AI Search
GEO optimises for retrieval and citation inside a generated answer rather than for a ranked list of links. The unit of success changes from a position to an inclusion, and the unit of content changes from a page to a passage.
Across the engagements we have run, citation lift traces back to the same four levers in roughly this order of impact.
AI answers vary between runs, so a single snapshot proves nothing. We probe each query repeatedly per cycle and report citation frequency, first-citation share, and competitor share-of-voice as trended metrics.
Technical eligibility first, then entity identity, then answer surfaces, then off-site corroboration. Running this out of order produces beautiful schema on pages the engine never retrieves.
Engagements that move citation share.
Entity, schema, and citation-surface diagnosis with a 90-day fix plan.
Open →Probe five engines with real buying queries and score your share of the answer.
Open →Risk-score every keyword for AIO suppression and defend the ones worth defending.
Open →Scheduled probes across AI Overviews, ChatGPT, and Gemini with full response capture.
Open →The full methodology, from entity anchoring to citation measurement.
Open →The checks we run, in order, so you can audit yourself.
Open →How Google AI Mode retrieves differently from AI Overviews and what to change.
Open →Passage-level tactics that get a brand named inside the generated answer.
Open →Entity stacking, @id anchoring, sameAs, and knowsAbout done correctly.
Open →The new Google product properties and how to avoid misleading-markup penalties.
Open →What changes, what does not, and where to reallocate budget.
Open →See whether ChatGPT names your brand on your category's buying questions.
Open →Track how Perplexity describes and cites your brand over time.
Open →Check which of your queries trigger an AI Overview and who gets cited.
Open →Test whether Google AI Mode cites you on commercial queries.
Open →Score your site's structural readiness for AI citation in two minutes.
Open →Estimate the clicks AI Overviews are absorbing from your keyword set.
Open →Generate the llms.txt file that tells AI crawlers what your site is.
Open →Generative engine optimization is the practice of making a brand retrievable and citable inside AI-generated answers from engines like ChatGPT, Google AI Overviews, Google AI Mode, Perplexity, and Gemini. Where SEO optimises for a position in a list of links, GEO optimises for inclusion in a synthesised answer, which rewards entity clarity, structured data, and self-contained answer passages.
It extends SEO rather than replacing it. AI engines retrieve from the same crawled index, so crawlability, rendering, and indexation remain prerequisites. What is new is the emphasis on entity resolution, passage-level answers, and third-party corroboration, because the engine is choosing which sources to paraphrase rather than which links to list.
Long-tail and comparison queries typically show first citations within 30 to 60 days of implementation. Category-defining head terms take three to six months because they depend on off-site corroboration accumulating, which cannot be shipped in a sprint.
With a fixed probe set of 100 to 300 buying queries run repeatedly across each engine per cycle. Because model outputs vary between runs, we report citation frequency, position inside the answer, sentiment, and competitor share-of-voice as trends rather than reporting a single snapshot as fact.
Regularly, and it is usually fixable. Factual errors almost always trace to a stale third-party source, a missing entity anchor, or contradictory copy on your own site. Identify the source, correct it, and the correction propagates as the engines re-retrieve.
Yes, indirectly but materially. Structured data lets an engine resolve facts without inference, which raises its confidence in your page as a source. Schema alone will not earn a citation on a thin page, but a strong page without schema regularly loses the citation to a weaker page that made its facts machine-readable.
Audits scoped within 24 hours. Results within 90 days, or your money back.
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