Get your brand named in the answers ChatGPT, Perplexity, Gemini and Google AI Overviews write for your buyers, and see it as a number: your share of citations on a fixed prompt set, re-run on the same engines every two weeks.
Generative engine optimization (GEO) services are the work of getting your brand named inside the paragraph an AI engine writes when a buyer asks about your category, in ChatGPT, Perplexity, Gemini and Google AI Overviews. Where classic SEO earns a ranked link, GEO earns a mention in the answer itself. The work is entity clarity, original data engines can quote, pages that cover the sub-questions a prompt fans out into, and earned third-party mentions, measured as your share of citations on a fixed prompt set. It is one facet of answer engine optimization.
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Read the top-3 column as how hard it is to break in: in fintech three brands already hold 58% of citations, so a new name needs evidence engines cannot get elsewhere. The last column is where the answers come from: when most answers cite a review site or forum, those threads are part of the GEO plan, not an afterthought.
| Vertical | Brands named per answer | Top 3 brands' share of citations | Median brand's share | Answers citing a review site or forum |
|---|---|---|---|---|
| B2B SaaS | 5.8 | 47% | 3.1% | 62% |
| AI and developer tools | 6.4 | 41% | 2.6% | 71% |
| Fintech | 4.9 | 58% | 3.8% | 44% |
| Web3 and crypto | 5.2 | 52% | 2.9% | 68% |
| Cybersecurity | 5.5 | 55% | 3.4% | 49% |
| Consumer apps | 7.1 | 38% | 2.2% | 74% |
40 buyer-intent prompts per vertical, one run per engine on ChatGPT, Perplexity, Gemini, Google AI Overviews, September 2026. Share is a brand's mentions divided by all brand mentions in that vertical. Per-engine cite rates for a single domain are in the FORKOFF AI Citation Index.
Want to know your own share, and which three brands hold the rest? The sandbox audit runs your category's 40 buyer prompts on all 4 engines and names the sources each engine leans on for you.
GEO works the generated paragraph, AEO works the cited answer, classic SEO works the ranked link. All three still depend on pages Google and Bing can crawl and rank.
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| Feature | GEOGenerative engine optimization · this page | AEOAnswer engine optimization | Classic SEOBlue-link ranking |
|---|---|---|---|
| What the engine returns | A written paragraph that names a few brands and cites a few sources | A short cited answer or a list of 4 to 8 recommended brands | Ten blue links ordered by rank |
| Unit of success | Citation share: how often your brand is named across a fixed prompt set | Citation count and position (recommended vs alternative) | Rank and clicks |
| Main levers | Entity clarity, original data, third-party mentions, pages that rank for the fan-out sub-queries | Answer-first capsules, question headings, schema hygiene, llms.txt for non-Google crawlers | Relevance, links, technical health |
| Engines covered | ChatGPT, Perplexity, Gemini, Google AI Overviews | ChatGPT, Perplexity, Claude, Bing Copilot, Google AI Overviews | Google, Bing |
| How it is measured | Same prompts, same engines, every run; share per vertical and per engine | Weekly citation scan on a 20 to 40 query bench | Rank tracker and Search Console |
| First measurable signal | 2 to 6 weeks after the first evidence pages ship | About 30 days | Weeks to months |
| Still depends on classic SEO |
The longer side-by-side, with examples for each engine, is in the AEO vs GEO guide. If you want the plain definition first, start with what answer engine optimization is.
Six pieces of work, each tied to a reason engines name one brand over another.
01
40 buyer-intent prompts for your category, run on 4 engines, with your share of citations and the brands that beat you logged per prompt.
02
One consistent description of what you are, used on your site, your Organization schema, Wikidata where you qualify, and the directories engines read.
03
Pages built around a number only you have: a benchmark, an index, a teardown. Engines quote sources that carry original data, and so do the people they quote.
04
Answers to the sub-questions an engine expands your buyer's prompt into, so your pages rank for the queries the paragraph is assembled from.
05
Genuine placements on the review sites, forums and publications that appear in your category's answers. Earned, never bought.
06
The same prompts re-run on a fixed cadence, reported as share per engine and per competitor, so you can see movement instead of anecdotes.
Your citation share, per engine, against the brands that win.
Deliverables (5)
Engines describe you the same way everywhere.
Deliverables (5)
Pages with numbers engines can quote.
Deliverables (5)
Share per engine, per competitor, re-run on the same prompts.
Deliverables (5)
Google's own guide to its generative AI features says it does not use llms.txt files, needs no special schema.org markup, does not require content to be chunked into small pieces, and gains little from inauthentic mentions. We agree, and we do not sell any of those as a Google lever.
The same guide says its AI features are grounded in its core ranking systems and expand a query into related sub-queries before writing the answer. That is where GEO work pays: pages that rank for the sub-questions, a clear entity, and original data other sources want to quote. Other engines read the open web the same way, which is why earned mentions on review sites and forums show up so often in the index above. Read the guide yourself on Google Search Central.
Skip for Google
llms.txt as a ranking lever, special schema, chunked rewrites, bought mentions
Keep doing
Crawlable pages that rank for the fan-out, a clear entity, original numbers, earned mentions
Each figure links to the study that produced it.
Google users clicked a traditional result on 8% of visits when an AI summary appeared, against 15% when none did, and clicked a link inside the summary on 1% of visits. (Pew Research Center, 2025)
18% of Google searches in March 2025 produced an AI summary, rising to 53% for searches of ten words or more, and 88% of those summaries cited three or more sources. (Pew Research Center, 2025)
The paper that named generative engine optimization found that adding citations, quotations and statistics can lift a source's visibility in generative answers by up to 40%, with results that vary by domain. (Aggarwal et al., KDD, 2024)
On a fixed 50-prompt cluster across 5 engines, forkoff.xyz moved its average cite rate from 22% to 34% in four weeks, with Perplexity at 48% (measured 19 May 2026). (FORKOFF, 2026)
Each engagement below names the company, the window the work ran in, and the numbers it returned. They come from our proof registry, so the same figures appear wherever we quote them rather than being rewritten for each page. Read the duration alongside the result, because a fourteen-day number and a six-month number answer different questions about what a campaign can do.
6 months, 2026
AI answer citations
answer units live
engines covered
non-brand clicks
6 months, 2026
AI answer citations
answer units live
engines covered
non-brand clicks
6 months, 2026
AI answer citations
answer units live
engines covered
non-brand clicks
Walk through what numbers like these would look like for your business.
Your category's 40 buyer prompts run on 4 engines, your share of citations against the brands that win, the sources each engine leans on, and a ranked list of the pages and mentions that would move it. The retainer is quoted by application once the audit lands.
The free AEO checker checks whether AI crawlers can reach and read your site, which has to be true before any of the work above can show up in an answer, and in the same run scores a page's answer readiness and asks the engines whether they name you. No signup. To see how we compare with other agencies before you talk to anyone, read the best AEO and GEO agencies compared.
Generative engine optimization (GEO) services are the work of getting your brand named inside the paragraph an AI engine writes when a buyer asks about your category. The work covers a fixed prompt set and baseline, entity clarity, evidence pages built on original data, coverage of the sub-questions an engine fans a prompt into, earned third-party mentions, and a citation share report re-run on the same prompts.
They overlap. Answer engine optimization is the broader practice of being the source AI answer engines cite, and it leans on answer-first pages, question headings and schema hygiene. GEO focuses on the synthesized paragraph and on how often your brand is named across it, so its main levers are entity clarity, original data and third-party mentions. FORKOFF runs both inside one engagement; this page covers the GEO side.
SEO earns a ranked link. GEO earns a mention inside a generated answer. They are not rivals: Google says its generative features are grounded in its core ranking systems and expand a query into related sub-queries, so pages that rank for those sub-queries are the ones the answer is built from. GEO sits on top of SEO rather than replacing it.
With citation share. We run the same buyer-intent prompts on the same engines every time and count how often each brand is named. Our own September 2026 index read 960 answers across six verticals and found the three most-cited brands took 48.5% of all citations on average, which is why share, not a single mention, is the number that matters.
The baseline lands in the first two weeks. The first measurable movement usually shows 2 to 6 weeks after the first evidence pages ship and are indexed, and larger shifts in share take a quarter or more because third-party mentions and entity signals compound slowly. On our own domain the average cite rate moved from 22% to 34% in four weeks of work.
Engagements start with a sandbox audit that produces the baseline. The retainer is quoted by application after the audit, with a 90-day minimum, and we take a maximum of 5 engagements per quarter so each one gets senior attention. There is no per-page or per-mention fee.
Not for Google. Google's own guide to its generative AI features says it does not use llms.txt files, needs no special schema.org markup, and does not require content to be chunked. Other crawlers may read llms.txt, so we treat it as optional hygiene. The work that moves share is entity clarity, original data and genuine mentions.
No, and no one honest can. Answers change by prompt, model and date. What we commit to is a fixed prompt set, a measured baseline and a share number re-run on the same prompts, so you can see whether the work is moving and decide at each quarter end.
A 40-prompt baseline on 4 engines, the brands that beat you and the sources behind them, then the entity, evidence and mention work that changes the share. The wider program lives on our answer engine optimization service page.
The full AI search engagement GEO sits inside: answer-first pages, schema hygiene and a weekly citation scan across the answer engines.
The plain definition, how AEO differs from SEO and GEO, and how it is measured.
Check whether AI crawlers can reach and read your site, and whether AI engines name you, before any GEO work starts.
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