GEO Fundamentals Complete Guide — AI Search Optimization for Japanese Companies

• GEO (Generative Engine Optimization) is the practice of getting "cited" by generative AI search engines such as Claude, ChatGPT, and Gemini. It is more accurate to think of it as a different game rather than an extension of traditional SEO.
• The years 2025-2026 mark the dawn of the domestic market. Companies that take action early are more likely to dominate the top of industry rankings.
• According to GEO Meter's smoke analysis data (2 topics x roughly 20 domains), the companies cited by AI share three traits: (1) deployment of llms.txt, (2) implementation of structured data (Schema.org), and (3) FAQ-style body structure.
• This article organizes the definition of GEO, how it differs from SEO, the state of the market, and what your company should tackle first.

1. The Definition of GEO

GEO (Generative Engine Optimization) is the umbrella term for optimization practices aimed at getting your company's information cited and recommended by generative AI search engines such as ChatGPT, Claude, Gemini, and Perplexity.

A similar concept, AEO (Answer Engine Optimization), is often used as a near-synonym, but the industry is increasingly adopting GEO as the broader term.

The core of GEO comes down to these three points:

1. A structure AI can read easily (Schema.org JSON-LD, FAQs, clear heading hierarchy)
2. Optimization for AI crawlers (llms.txt, AI-bot accommodation in robots.txt)
3. Signals of authority (first-party data, explicit sources, regular updates)

2. How It Differs from SEO

GEO and SEO differ in goals, metrics, and tactics. The table below contrasts them.

3. Why GEO, Why Now

3.1 Rapid Market Growth

ChatGPT's user count surpassed 200 million in 2024, and Perplexity and SearchGPT are also growing rapidly. The shift from "searching on Google" to "asking an AI" is progressing, especially in the B2B space.

3.2 The Domestic Market Is at Dawn — First-Mover Advantage

2026 is likely "the last window for first movers to seize industry rankings." In 1-2 years, most companies will have implemented measures, making top positions hard to win.

3.3 SaaS / B2B Purchasing Behavior Has Changed

Surveys of B2B purchasing decision-makers show a growing share use AI chat as the first step in product research. If your company isn't cited for a query like "recommended XX service," it doesn't even reach the consideration set.

4. What Smoke Analysis (2 Topics x Roughly 20 Domains) Reveals About Companies Cited by AI

In GEO Meter's smoke analysis conducted in April-May 2026 (2 topics x roughly 20 domains), we compared the structural differences between the top citation group and the bottom citation group.

Differences actually observed in the smoke analysis:

Observational tendencies (quantification is future work):

• Schema.org JSON-LD implementation rate tends to be higher in the top group
• FAQ page possession is also notable in the top group
• sitemap.xml is a standard implementation deployed by virtually all companies

In particular, the gap in llms.txt deployment is vivid — the top group consistently exceeds the bottom group by 20-30pp. llms.txt itself has low implementation cost, making it the first measure you should tackle. Detailed analysis and per-industry numbers will continue to be updated as we expand the observation set.

5. Where to Start in Your Own Company

GEO tactics span many areas, but it's important to clarify priorities and work through them one at a time. The recommended order from GEO Meter:

5.1 Start with Observation (Free Diagnostic)

"Adding measures without knowing what the problem is" is the most inefficient approach. Grasp the current state, then improve from the weakest point is the standard play.

→ Check your current state in 3 minutes with GEO Meter's free diagnostic

5.2 Deploy llms.txt

Place /llms.txt at the root of your site, explicitly listing primary URLs and content overviews for AI crawlers. Implementation takes 1-2 hours.

→ llms.txt Complete Implementation Guide

5.3 Schema.org Structured Data

Implement Article / Organization / FAQPage / Product schemas as JSON-LD. This is the most important measure that directly affects LLM citation rates.

5.4 Publishing Primary Data

Regularly publish industry reports, in-house research, and original analysis to build the authority that makes AI decide "this is the source to cite."

6. Scenario by Scenario: How Should You Get Started?

The shortest-path startup steps by industry and situation:

If You Run a B2B SaaS

1. Use the free diagnostic to grasp your current Citation count / SOV
2. List your three main pages (product / pricing / case studies) in llms.txt
3. Implement Organization Schema (company info) + Product Schema (per product)
4. Create five "Differences between XX (product) and YY (competitor)" FAQs
5. Publish one note article per month with industry comparisons and empirical data

If You Run an EC Site

1. List "category pages" and "popular product pages" in llms.txt
2. Implement Product Schema on every product (price / stock / reviews)
3. Set up FAQPage Schema for shipping and returns
4. Cover SNS and store information in Organization Schema

If You're in a Professional Practice (Lawyer, Tax Accountant, Administrative Scrivener)

1. List "pricing," "consultation flow," and "office information" in llms.txt
2. LocalBusiness Schema (location) + LegalService / AccountingService schema
3. FAQPage Schema for typical consultations ("cost of XX," "procedure of XX")
4. Article Schema for resolved-case examples (with privacy-conscious abstraction)

If You Run a Media Site

1. Implement Article Schema on every article (author, publish date, update date)
2. Maintain Author Schema (author profiles)
3. List main series and tag pages in llms.txt
4. Compose content with an awareness of being a cited source (primary data, figures and tables)

If You're a Startup or Sole Proprietor with No Budget

1. Deploy llms.txt (free, 1 hour)
2. Start with 3-5 FAQPage Schema entries
3. One Organization Schema (company info)
4. Measure monthly impact with the free diagnostic

→ Common across all industries: first llms.txt, then Schema.org, then FAQs.

7. Summary

• GEO is a different game from SEO. Use "being cited" as the primary metric
• 2026 is the domestic dawn — first-mover advantage
• The common traits of top companies are llms.txt / Schema.org / FAQ
• Approach your own company in the order observe → llms.txt → Schema → FAQ → primary data
• The weighting of tactics varies by industry, but starting from llms.txt deployment is common

Related Resources

• llms.txt Complete Implementation Guide — Pillar 2
• AI Platform Optimization Complete Guide — Pillar 3
• Latest Articles (News) — Industry trends / regulation / proprietary observation data
• GEO Meter Free Diagnostic — Measure your current state