Executive Summary
- GEO is composed of : .
Pillar — full guide
A technical handbook that comprehensively explains the tactics you should implement for GEO, including llms.txt, Schema.org, FAQs, and AI crawler accommodation.
llms.txt deployment in particular showed a +20-30pp gap in implementation rate between the top and bottom AI citation groups, suggesting that implementing fundamental tactics directly drives citation acquisition.The five main tactics to work on for GEO are:
| # | Tactic | Implementation cost | Impact (GEO Meter observations) |
|---|---|---|---|
| 1 | Deploy llms.txt | Low (1-2h) | +20-30pp gap in smoke analysis (top 40% vs bottom 10%) |
| 2 | Schema.org / JSON-LD structured data | Medium (1-2 days) | Foundational, improves AI body comprehension |
| 3 | FAQ page design | Medium (1-3 days) | Advantageous for AI citation as a direct answer source |
| 4 | AI crawler accommodation (robots.txt) | Low (30 min) | Required (no accommodation = dropped from AI citation candidates) |
| 5 | Internal link strategy | Medium-high (ongoing) | Drives topical authority (hard to quantify) |
→ In cost-performance order: "llms.txt → crawler → Schema → FAQ → internal links."
Placing each tactic by "impact" and "implementation difficulty" makes priorities visible at a glance:
| Tactic | Impact | Implementation difficulty | Recommended priority |
|---|---|---|---|
| Deploy llms.txt | High | Low | ★★★ Tackle first |
| AI crawler accommodation | Medium-high | Low | ★★★ Tackle first |
| Schema.org implementation | High | Medium | ★★ Tackle early |
| FAQ page design | High | Medium-high | ★★ Tackle early |
| Internal link strategy | Medium | Medium | ★ Tackle in sequence |
We'll explain each tactic in order.
llms.txt is a file that uses Markdown to explicitly indicate your site's main content for AI crawlers.
Place /llms.txt at the site root. Minimal structure:
# Site name
> One- to two-line description of the site
## Main pages
- [Page name](URL): brief description
| Group | Deployment rate |
|---|---|
| AI citation top group | 40% |
| AI citation bottom group | 10% |
| Difference | +30pp |
A different topic (fat reduction) also showed a +20pp gap, confirming a consistent tendency across multiple topics.
lastmod-style date is recommended)Implement Schema.org in JSON-LD format. Think of it as "a vocabulary that tells AI what's on the web page."
| Schema | Where | Role |
|---|---|---|
| Organization | Once on the top page | Company info ID card |
| Article | Each article page | Author, publish date, update date |
| FAQPage | FAQ pages | Explicit Q&A format |
| BreadcrumbList | All pages | Breadcrumb navigation |
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Article",
"headline": "What is GEO?",
"datePublished": "2026-05-24",
"dateModified": "2026-05-24",
"author": {
"@type": "Organization",
"name": "XX Editorial Team"
},
"publisher": {
"@type": "Organization",
"name": "XX Inc."
}
}
</script>
Implementing Schema.org is the most important foundational measure for AI to understand "what this page represents" in a machine-readable form. It tends to raise priority as an AI citation candidate and also has a secondary impact on SEO rich results.
Q&A-format pages with FAQPage Schema are the structure most likely to be cited in AI search.
AI search engines (Perplexity / SearchGPT / Gemini / Claude) generate "direct answers" to user questions. The FAQ format is already structured as "question → answer," making it the easiest format for AI to handle.
FAQ pages perfectly match the structure of "direct answers to questions" that AI search wants, making them one of the structures most likely to be cited. Combining with FAQPage Schema maximizes impact.
| Aspect | Good example | Bad example |
|---|---|---|
| Question specificity | "What's the difference between the Pro and Lite plans?" | "About pricing" |
| Answer length | Concise in 1-3 sentences | Long paragraphs |
| Aligned with search intent | Natural questions users would actually ask | Questions written in internal jargon |
| Schema implementation | Structured with FAQPage | Plain HTML |
Explicitly Allow AI crawlers (GPTBot / Claude-Web / Google-Extended / PerplexityBot) in your robots.txt.
# GPTBot (ChatGPT / SearchGPT)
User-agent: GPTBot
Allow: /
# Claude-Web (Claude)
User-agent: Claude-Web
Allow: /
# Google-Extended (Gemini / AI Overview)
User-agent: Google-Extended
Allow: /
# PerplexityBot (Perplexity)
User-agent: PerplexityBot
Allow: /
# Make the sitemap explicit too
Sitemap: https://example.com/sitemap.xml
robots.txt templates may block AI crawlers (needs review)curl https://your-site.com/robots.txt
Check that Disallow: / is not set against AI crawlers.
Systematize internal links to build topical authority across your entire site.
Instead of vague links like "here" or "click here for details," use keywords that represent the linked content as the anchor text.
<!-- Bad example -->
For details, <a href="/llms-txt-guide">click here</a>
<!-- Good example -->
See <a href="/llms-txt-guide">how to write llms.txt correctly</a>
The recommended order of attack:
| Step | If done in-house | If outsourced |
|---|---|---|
| 1. Observe | 3 minutes (free diagnostic) | - |
| 2. llms.txt | 1-2 hours | 20,000-30,000 yen |
| 3. Schema.org | 1-2 days | 100,000-200,000 yen |
| 4. FAQ pages | 1-3 days | 50,000-100,000 yen |
| 5. Crawler accommodation | 30 minutes | 5,000 yen |
| 6. Internal links | Ongoing | 50,000-100,000 yen / month |
Week 1: Deploy llms.txt (1-2 hours) + verify AI crawler Allow in robots.txt
# robots.txt example
User-agent: GPTBot
User-agent: Claude-Web
User-agent: Google-Extended
User-agent: PerplexityBot
Allow: /
Sitemap: https://example.com/sitemap.xml
Weeks 2-3: Implement Schema.org (Organization + Article)
Week 4 onward: Start with 5 FAQ entries, add 2-3 per month
llms.txt" (market price 20,000-30,000 yen)<head>→ Initial cost including all outsourcing comes out to around 100,000-300,000 yen.
robots.txt (they're surprisingly often Disallowed)llms.txt→ Layer GEO-specific tactics on top while maximizing the use of SEO assets.
llms.txtPartially yes (Schema.org / internal links and the like work for both). However, llms.txt deployment and AI crawler accommodation are often not in the standard menu of SEO agencies. You need to explicitly request "GEO measures."
Yes. Schema.org JSON-LD can be implemented via plugins (such as Yoast SEO or RankMath). For llms.txt, you can edit the theme or place it directly on the server. FAQ pages are the same.
Some AI crawlers don't execute JavaScript (GPTBot has limited support). HTML delivery via SSR / SSG is essential for GEO measures. SSR configurations with Next.js / Nuxt and similar are recommended.
It varies by tactic:
llms.txt + robots.txt: 1-2 weeks until AI crawler access changesOnce you have read the article, check your own status. GEO Meter observes how Claude / ChatGPT / Gemini cite you in one pass.