What GEO promotion is and why you need it
GEO (Generative Engine Optimization) means optimizing a website for generative engines: ChatGPT, Yandex Neuro, GigaChat, Perplexity and Copilot. These systems already answer millions of queries daily, and users increasingly never reach a classic SERP: they get one ready answer with 2–5 sources. If your site is not among the sources — to the AI audience you do not exist. GEO differs from SEO in selection logic: a search engine ranks pages, while a model synthesizes an answer and picks sources it trusts. It needs clear formulations, verifiable facts, dates, numbers and consistent entities — brand, services and regions described the same way across the site. That is why GEO starts not with link buying but with rebuilding content for the way language models read.
How AI engines pick answer sources
Generative systems work in a RAG scheme (Retrieval-Augmented Generation): first relevant fragments are retrieved, then the answer is assembled with citations. Several factors decide whether you get cited. First, clarity: a fragment that answers the question on its own gets cited more than polished marketing copy. Second, factoids: numbers, timelines, prices and definitions with update dates. Third, entity consistency: company name, services and advantages must repeat in title, H1, Schema.org, llms.txt and directories. Fourth, crawler access: robots.txt and llms.txt must explicitly allow GPTBot, YandexGPT and other agents. We check all four layers and strengthen them one by one — that is how a site becomes easy to cite.
What the ZXY GEO package includes
Work runs in 4-week cycles. Week 1 — audit: we test 20 niche queries in ChatGPT, Neuro and GigaChat, record who gets cited and for which formulations, and check robots.txt, llms.txt and server response for bots. Week 2 — framework: we prepare or update llms.txt and llms-full.txt, add answer blocks and FAQPage markup, and align entities. Weeks 3–4 — content: priority pages rewritten in the answer-first scheme, comparison tables and definitions added, topic LSI vocabulary distributed. Each cycle ends with a report: share of queries where you are cited, competitor positions, next-cycle plan. This rhythm gives measurable results without magic — you see the dynamics in numbers.
GEO vs SEO: the difference and why do both
SEO and GEO are not rivals but layers of one system. SEO ensures your fragments get into the search index that both search engines and RAG systems draw from; without technical health GEO does not work. GEO adds the upper layer: wording, structure and markup that make the model pick your fragment as a source. In practice 70% of the work overlaps: content quality, speed and semantics matter for both channels. The difference is in emphasis: GEO requires self-sufficient answers, dated facts and AI crawler access, while classic SEO relies on keywords, internal linking and behavioral signals. We build both layers coherently: tech foundation and semantics first, then answer optimization — one piece of content then works in SERPs and AI answers alike.
GEO cost and time to results
The GEO package costs from 60 000 RUB per month: audit and llms.txt setup, 2–4 rewritten pages monthly, markup, monitoring of 20 queries and a monthly report. A one-off GEO audit — from 18 000 RUB: it establishes the starting point and the work plan. First shifts appear within 4–8 weeks: engines re-index the site within weeks after answer-first content ships, then new formulations start appearing in answers. A sustainable share of citations in a niche takes 3–6 months of regular cycles. We are honest about limits: GEO is a young channel — in narrow niches you get cited faster, while in overheated topics the GEO + SEO + industry directories combo works best.
Why order GEO from ZXY
We have worked with GEO since AI answers appeared in Yandex and live in this paradigm ourselves: zxy.ru is optimized for generative engines, has llms.txt and an answer-first structure — you can test it in ChatGPT right now. The team includes SEO specialists with 12 years of experience and CRM analytics expertise, so we measure not "mentions in general" but the chain citation → traffic → leads. Fixed monthly package under a contract, reports as a clear table: query, engine, who was cited, what was done. After each cycle we refresh llms.txt and hand over content recommendations. 98% of clients extend cooperation — the best quality metric we have.
