With the widespread adoption of AI chat tools like ChatGPT and Gemini, the way we use search is undergoing a significant transformation. When users look for information, they are increasingly asking AI directly for answers, rather than just opening search engine results pages. When these AIs generate responses, they compile information by referencing content from the internet. This state of being 'referenced' is what is known as citation by AI.
Quoted content is treated as a source in AI responses. This not only enhances brand recognition but also signals that your content is considered reliable. Just as traditional SEO aims for high rankings in Google search, incorporating structures that AI is likely to quote is essential for future content strategy.
AI models like ChatGPT and Gemini prefer clear, concise, and reliable information. Content with specific data and clear explanations is more likely to be quoted than ambiguous statements or unsubstantiated claims. In other words, content written clearly for readers is also easy for AI to understand.
When AI models quote specific content, there are several common characteristics. First, it's important whether the content directly answers the question. Content that clearly answers specific queries like 'What is X?' or 'How do I do X?' at the beginning is useful material for AI when generating responses.
Next, consider whether the structure of the text is organized. If headings are clear and each section has independent meaning, AI is more likely to quote entire sections. Conversely, writing that doesn't make sense without the preceding or succeeding context is less likely to be picked up by AI.
Including reliable sources and data is also a major factor. AI tends to prioritize content with high E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness). By including statistical data, research results, and real-world examples, the content becomes more likely to be treated as "reliable information" by AI.
The basic principle for content that AI is likely to cite is to write the answer first. This is similar to the "inverted pyramid structure" that journalists use when writing articles. It's effective to put the most important information at the beginning, followed by details and background. This is because AI often prioritizes the beginning of the text when generating answers.
For example, if answering the question 'What is GEO?', the ideal approach is to clearly answer in the first sentence: 'GEO (Generative Engine Optimization) is a method of optimizing your company's content to make it more likely to be cited in responses generated by AI such as ChatGPT and Gemini.' Following this with specific measures and case studies would be the ideal flow.
The content under each heading should be written so that it makes sense even when only the heading is read. This is called chunk optimization. This is because AI often extracts and uses relevant "chunks" of a webpage rather than reading the entire page.
Each section should have one theme, with the conclusion at the beginning, followed by an explanation. Checking with the criterion "Does this section make sense on its own?" allows you to confirm whether chunk optimization has been done.
AI tends to trust content that includes numbers and specific facts. Instead of vague statements like 'Many companies are using it,' expressions using numbers, such as 'In a 2026 survey, 68% of companies listed adapting to AI search as a priority for their SEO strategy,' are more likely to be quoted.
When citing data, also indicate the source of the information. AI will treat content with data from government agencies, research institutions, or reliable industry media as more trustworthy. If it's your company's data or original research, briefly describing the survey method and subjects will increase its credibility.
FAQ sections and Q&A style content are prime examples of structures that are easily cited by AI. The style of using questions that users actually search for as headings, followed immediately by clear answers, is effective.
Use tools like "People Also Ask" and "AlsoAsked" to research related questions that users are actually searching for and incorporate them into your content. This approach also helps cover question patterns that AI is likely to answer.
To create content that AI can easily read, not only the content but also the format is important. Use appropriate heading hierarchies (H1, H2, H3) and clarify the role of each section. Keep paragraphs to about 4-5 sentences and aim to convey one idea per paragraph.
Bullet points and numbered lists are effective for explaining steps or listing multiple items, but overuse can make the entire content appear fragmented. It's important to strike a balance, valuing the flow of the text and using lists only when necessary.
Table format is useful when comparing multiple items on the same criteria. AI can easily recognize the structure of tables and may quote comparative information in a summarized manner. For example, comparing content performance with and without GEO measures is more effective when organized in a table.
If you only publish content in Japanese, you will only have opportunities for quotation by users who ask questions in Japanese. However, by developing content in multiple languages such as English, Chinese, and Spanish, you can expand the chances of being quoted by AI users worldwide.
What's important to note here is that simple translation isn't enough. Unless content is optimized with an understanding of the actual expressions, search patterns, and cultural backgrounds used by users in each language region, it won't achieve the level of credibility needed to be cited by AI. Platforms like VERBARANK, which offer GEO-enabled multilingual capabilities, use neural translation that understands user context to achieve a structure that is easily cited in each language.
By 2026, it's projected that approximately 40% of search queries to AI assistants will be in languages other than English. Multilingual support is becoming an indispensable element of future GEO strategies. VERBARANK supports over 120 languages and optimizes for citation by the seven major AI models, including ChatGPT, Gemini, Claude, and Perplexity.
While SEO (Search Engine Optimization) and GEO (Generative AI Optimization) have different goals, they overlap significantly. This is because both seek "reliable, easy-to-read content that answers user questions."
SEO emphasizes technical elements like keyword placement, internal linking structure, and page speed. GEO, in addition, prioritizes chunk optimization, Q&A structure, and clear information sources. By designing with both in mind, you can aim for both high rankings in Google search and AI citations.
| Elements | Role in SEO | Role in GEO |
|---|---|---|
| Clear heading structure | Easy for crawlers to understand the structure | Easily Excerpted by AI Sections |
| Question format headings | Supports long-tail keywords | AI recognizes it as an answer pattern |
| Reliable data | Contributes to E-E-A-T evaluation | AI judges it as information worthy of citation |
| Internal links | Improve overall site evaluation | Complement the reliability of related content |
| FAQ section | Acquire featured snippets | Easy for AI to cite in Q&A format |
What is the most important factor for getting cited by ChatGPT?
The most important thing is to place the direct answer to a clear question at the beginning of the content. When generating an answer, ChatGPT prioritizes referring to text that immediately answers the question. The basic structure is to write the answer first, followed by the reasons and background.
Do GEO and SEO need to be optimized separately?
GEO and SEO are different, but many measures are common. The basic policy of providing reliable information in a structured way is the same. It is efficient to first establish the SEO foundation and then add GEO-specific measures such as chunk optimization and Q&A format.
Are Japanese content less likely to be cited by AI?
Japanese content is also quoted sufficiently. However, opportunities for quotation are limited to users who ask questions in Japanese. If you want to increase global citation opportunities, multilingual support is effective. By preparing content optimized for each language, you can expand your reach to AI users worldwide.
What is the appropriate amount of FAQ sections?
Ideally, aim for about 5 to 8 questions per article. Choose realistic questions that users are actually searching for, and provide clear answers of about 100 to 150 characters for each. Overly long answers can become unfocused and less likely to be excerpted and used by AI.
Does updating content change its citation rate by AI?
Yes, it does. AI models tend to prioritize the latest information. Content that is regularly updated is more likely to be cited than content containing old or outdated information. We recommend reviewing statistical data and examples at least once every six months.
Is structured data (schema markup) effective for GEO?
It is effective. By implementing FAQ schema, Article schema, etc., AI can understand the structure of the content more accurately. FAQ schema, in particular, is effective in organizing Q&A content in a format that AI can easily recognize.
To create content that is likely to be quoted by ChatGPT and Gemini, it's important to focus on four basics: write the answer first, make sections independent, use specific data, and adopt a Q&A format. These don't require special techniques; they stem from a reader-centric approach to content design.
A strategy that combines SEO and GEO is the fastest way to achieve both high search rankings on Google and citation by AI. Especially if you're considering multilingual expansion, GEO optimization in each language significantly broadens citation opportunities. VERBARANK, as a platform supporting over 120 languages and major AI models, assists in executing these content strategies.
There are many things you can start working on today. First, choose an existing piece of content and check if the answer is at the beginning, if each section is independent, and if it includes FAQs.
