Question 1

What is AEO (AI Engine Optimization)?

Accepted Answer

AEO (AI Engine Optimization), also called Answer Engine Optimization, is the practice of optimizing your brand and products to appear in AI-generated answers from engines like ChatGPT, Claude, Gemini, and Perplexity. Unlike SEO which focuses on search result rankings, AEO focuses on structured data, content quality, and citable information that AI models reference when generating recommendations. AEKO provides tools to monitor and optimize AEO for global commerce.

Question 2

How is AEO different from SEO?

Accepted Answer

SEO optimizes for search engine rankings (Google, Bing). AEO optimizes for AI engine recommendations (ChatGPT, Claude, Gemini, Perplexity). SEO targets keywords and backlinks; AEO targets structured data, conversational content, and citation sources that AI models use to generate answers. As more consumers ask AI directly instead of searching, AEO becomes critical for brand visibility.

Question 3

How do AI engines decide which products to recommend?

Accepted Answer

AI engines recommend products based on training data, real-time web citations, structured data quality, brand authority, and content relevance. Key factors include JSON-LD product schemas, llms.txt files, review aggregations, and how well product information matches the user's purchase intent. Different AI engines weigh these factors differently, and recommendations vary significantly by market and language.

Question 4

What is Agentic Commerce?

Accepted Answer

Agentic Commerce is the next evolution of e-commerce where AI agents autonomously discover, evaluate, and purchase products on behalf of consumers. As AI assistants handle more shopping decisions, brands need to be visible and accurately represented to these AI agents. AEO (AI Engine Optimization) is the foundation for Agentic Commerce readiness.

Question 5

How can cross-border sellers optimize for AI recommendations?

Accepted Answer

Cross-border sellers should implement structured data (JSON-LD product schemas), maintain an llms.txt file, optimize content for conversational queries, ensure accurate multilingual product information, and monitor how AI engines recommend their products across different markets. The same product often gets completely different AI recommendations depending on the country and language.

Question 6

What are AEKO Agents?

Accepted Answer

AEKO Agents connect AEO optimization tools directly to Claude Desktop and Claude Code via MCP (Model Context Protocol). They provide 25+ tools including llms.txt generation, robots.txt analysis, JSON-LD creation, product schema optimization, and AI visibility audits, enabling AI-assisted AEO optimization workflows.

Question 7

AEO(AI Engine Optimization)란 무엇인가요?

Accepted Answer

AEO(AI Engine Optimization, AI 엔진 최적화)는 ChatGPT, Claude, Gemini, Perplexity 같은 AI 엔진이 생성하는 답변에 브랜드와 상품이 노출되도록 최적화하는 방법입니다. 검색 엔진 순위에 집중하는 SEO와 달리, AEO는 AI 모델이 답변 생성 시 참조하는 구조화 데이터, 컨텐츠 품질, 인용 가능한 정보에 초점을 맞춥니다.

Question 8

AEO와 SEO는 어떻게 다른가요?

Accepted Answer

SEO는 구글, 네이버 등 검색 엔진의 순위를 최적화하고, AEO는 ChatGPT, Claude 같은 AI 엔진의 추천을 최적화합니다. SEO가 키워드와 백링크에 집중한다면, AEO는 구조화 데이터, 대화형 컨텐츠, AI 모델이 답변 생성 시 인용하는 소스에 집중합니다. 소비자가 검색 대신 AI에 직접 물어보는 시대에 AEO는 필수 전략입니다.

Question 9

Which brands do AI engines actually cite?

Accepted Answer

AI engines disproportionately cite brands whose product pages provide structured data (JSON-LD, schema.org/Product) and whose content explicitly expresses brand, product, and review relationships. Brands relying only on social posts or image-only product pages are rarely cited, because AI bots cannot reliably parse them. Structured, schema-rich content earns the citation.

Question 10

AI는 어떤 브랜드를 추천하나요?

Accepted Answer

AEKO 모니터링 데이터에 따르면, AI 엔진은 JSON-LD와 스키마가 잘 갖춰진 상품 페이지, 그리고 브랜드 ↔ 상품 ↔ 리뷰 관계가 명시적으로 표현된 콘텐츠를 가진 브랜드를 더 자주 인용하는 경향이 있습니다. 소셜 게시물 위주로 운영하거나 이미지로만 된 상품 페이지는 봇이 정확히 읽지 못해 답변에 등장하는 빈도가 낮습니다. 구조화된 스키마 기반 콘텐츠가 AI 인용 가능성을 높입니다.

Question 11

Why do AI engines tend to cite social posts less?

Accepted Answer

In AEKO's monitoring data across thousands of buyer-intent prompts, AI engines tend to favor citable, attributable sources with structured metadata. Social posts typically lack stable URLs, structured data, and trust signals that AI models prefer when quoting and linking to a source. Brand owners optimizing for AI visibility tend to see better results from structured website content (PDPs with JSON-LD, articles with FAQ/Article schema) than from social-only strategies.

Question 12

AI 엔진이 상품을 추천하는 기준은 무엇인가요?

Accepted Answer

AI 엔진은 학습 데이터, 실시간 웹 인용, 구조화 데이터 품질, 브랜드 권위, 컨텐츠 관련성 등을 기반으로 상품을 추천합니다. JSON-LD 상품 스키마, llms.txt 파일, 리뷰 데이터, 구매 의도와의 정보 일치도가 주요 요인이며, 각 AI 엔진마다 가중치가 다르고 시장과 언어에 따라 추천 결과가 크게 달라집니다.

Question 13

에이전틱 커머스(Agentic Commerce)란 무엇인가요?

Accepted Answer

에이전틱 커머스는 AI 에이전트가 소비자를 대신하여 자율적으로 상품을 발견, 평가, 구매하는 이커머스의 다음 단계입니다. AI 어시스턴트가 더 많은 쇼핑 결정을 내리게 되면서, 브랜드는 이러한 AI 에이전트에게 정확하게 노출되어야 합니다. AEO(AI Engine Optimization)는 에이전틱 커머스를 대비하는 핵심 전략입니다.

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Loss of Reach

Loss of Conversion

Collapse of Trust

How AI engines actually pick the brands they recommend.

Structured product pages get cited

Social content rarely makes it in

Schema-rich content earns the citations

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