GEO & AEO: how to get cited by ChatGPT, Gemini, and YandexGPT — full guide

How GEO shapes traffic: three channels standard analytics miss

Most GEO impact never shows up as a direct referral. The model recommends a brand—the user remembers and arrives later via search, direct, or another channel.

How we got here: a short history of GEO

GEO isn’t a 2024 marketing fad—it’s the next stage of search. Understanding the timeline shows where things are heading.

Why SEO alone is no longer enough

Picture this: top 3 in Google on 80% of target queries, technical SEO at 95%, weekly publishing—and organic traffic still drops ~30% in six months.

This isn’t hypothetical—many B2B SaaS teams saw it in 2025. The driver wasn’t a random Google update. Users stopped clicking links the same way.

Now someone asks ChatGPT “which analytics tool should marketers pick?” and gets a ranked list with rationale—no ten-tab research. If you aren’t named, the buyer may be gone before they ever load your site.

Search isn’t dead—it evolves. Seer (1.8M sites, 2025): 74% of brands in Google’s top 10 also appear in ChatGPT; correlation ~0.65. SEO is the foundation; GEO is the layer on top.

SEO, AEO, and GEO: three different jobs

Each acronym is a different surface where your brand can show up. Knowing the split tells you where to invest.

SEO — Search Engine Optimization

Classic optimization for Google, Yandex, Bing: earn a spot in the link list and win the click—titles, H1s, links, speed, CWV. Still essential, but alone it’s incomplete without GEO/AEO.

AEO — Answer Engine Optimization

Optimization for direct answers: featured snippets, Yandex Alice blocks, Siri, Assistant. One source is quoted verbatim or close. You need crisp, structured answers to explicit questions.

GEO — Generative Engine Optimization

Optimization for generative models—ChatGPT, Gemini, Claude, Perplexity, YandexGPT, GigaChat, DeepSeek. Unlike AEO, the model synthesizes across sources, paraphrases, and cites links. Your job is to be one of those sources with a clear brand mention.

How a model chooses whom to cite: the RAG architecture

To act with intent, understand the mechanics. Modern AI search (ChatGPT Search, Perplexity, YandexGPT) is mostly RAG—retrieval first, then generation.

It looks like “the model found the best sources,” but each document is scored on multiple signals at once:

Signal 1: technical access

If robots.txt blocks AI crawlers, the site is invisible regardless of content quality. ~35% of RU-language sites still block GPTBot—often a 2023 “just in case” rule never revisited.

Second barrier: JS-only rendering without SSR/SSG—many crawlers see an empty shell.

Signal 2: answer-first structure

Models extract answers to explicit questions. Content that leads with the answer gets cited far more often.

Signal 3: E-E-A-T

Concrete E-E-A-T signals:

• Named author + role + Schema Person
• Clear published and updated dates
• Outbound links to sources and studies
• Third-party authoritative mentions of your brand

Signal 4: semantic density

Models read via semantic triples. Every claim should carry specifics.

Signal 5: Schema.org markup

Markup is a direct vocabulary for LLMs—without it, a FAQ looks like a plain paragraph.

Four prompt types people actually ask models

Prompt types map to content priorities. ~70% of LLM prompts are phrased in ways classic keyword tools never captured.

How to write content models actually cite

Rule 1: answer in the first two sentences

Rule 2: headings as questions

Models cite sections whose H2 mirrors the user’s question—a direct hint that an answer lives here.

Rule 3: specifics instead of abstractions

Models favor verifiable facts—numbers, dates, names, outcomes. If you can prove it, say it outright.

Rule 4: FAQ block on key pages

Question → ≤80-word answer is the most citable pattern. Add 5–7 real customer questions and mark them up as FAQPage.

Rule 5: tables over prose

Structured data beats long prose—comparisons, specs, and checklists belong in tables or lists.

Analyzer: score your copy for GEO readiness

Paste any paragraph from your site—seven checks mirror how models shortlist sources.

Three visibility scenarios: sample AI answers

Prompt Win Rate: before and after GEO

Prompt Win Rate = share of prompts where the model mentions your brand.

Test yourself: GEO quiz

LLM-Score simulator: gauge your potential

Step plan: 30 days to LLM visibility

Copy-ready snippets: robots.txt & Schema.org

robots.txt — allow AI crawlers

# One group for * and AI bots — Disallow applies to all (REP groups are not merged).
User-agent: *
User-agent: GPTBot
User-agent: OAI-SearchBot
User-agent: anthropic-ai
User-agent: ClaudeBot
Allow: /

Disallow: /admin/
Disallow: /api/

Schema.org FAQPage — JSON-LD

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is GEO optimization?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "GEO (Generative Engine Optimization) is optimizing content for generative AI: ChatGPT, Gemini, Perplexity, YandexGPT. The goal is to become a source the model cites in its answer—not just a link in a search list."
      }
    },
    {
      "@type": "Question",
      "name": "How is GEO different from SEO?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "SEO targets Google/Yandex crawlers (rankings in link lists). GEO targets language models (brand citations in AI answers). Key GEO signals: E-E-A-T, answer-first structure, Schema.org markup, semantic density."
      }
    }
  ]
}
</script>

llms.txt — navigation for LLM crawlers

# Getllmspy — LLM brand monitoring

## Description
Getllmspy measures brand visibility in AI model responses.
Checks ChatGPT, Gemini, YandexGPT, GigaChat, Perplexity.
Returns LLM-Score (0–100), Share of Voice, competitor analysis.

## Key pages
- /en/check — Free brand check (start here)
- /en/pricing — Pricing plans
- /en/faq — Frequently asked questions
- /en/blog/geo-aeo-optimization — GEO/AEO guide

## Target audience
Marketing managers, SEO specialists, brand managers,
digital agencies managing multiple clients.

Nine mistakes that kill LLM visibility

Five GEO myths that slow you down

GEO services are in a noisy hype phase—vendors promise “secret” plays. Here are the common myths and the reality behind them.

GEO by niche: where AI visibility matters most

Not every niche depends on GEO the same way—potential and competition differ. Pick a vertical to see typical prompts and difficulty.

Real patterns: what works in practice

Glossary: GEO/AEO terms in one place

FAQ: GEO & AEO