
브랜드 데이터 연결
기존 분석 데이터를 연결하면 AI가 브랜드에 최적화된 콘텐츠를 생성합니다.
브랜드
톤앤매너, USP, 키메시지
진단(SCAN)
SEO/AEO/GEO 분석 결과
CDJ/전략
고객 여정 기반 콘텐츠 전략
영상 AI
슬라이드쇼, AI 아바타, 생성형 영상
공통 컨셉 설정
한 번 설정한 컨셉이 모든 채널 콘텐츠에 일관되게 적용됩니다.
주제
콘텐츠의 핵심 주제를 설정하면 AI가 채널별로 최적화합니다.
타겟 오디언스
CEP 클러스터나 페르소나를 연결하여 맞춤 콘텐츠를 생성합니다.
핵심 메시지
CDJ 분석의 광고 메시지를 활용하거나 직접 입력할 수 있습니다.
톤앤매너
전문적, 친근한, 유머러스 등 브랜드에 맞는 톤을 선택합니다.
CTA
Call to Action을 설정하여 전환을 유도하는 콘텐츠를 만듭니다.
AI 자동 생성
컨셉 위자드로 주제만 입력하면 AI가 나머지를 자동 완성합니다.
Content Studio FAQ
AI 콘텐츠 생성에 대해 자주 묻는 질문들
How is Content Reconstruction different from simple writing?
It's an engineering process that transforms content beyond human-readable text into data structures optimized for AI learning. Team HAI's AI Writing Assistant analyzes your content in real-time and guides you to apply two core strategies:
• Fill-in (Structuring): Suggests converting unstructured text into tables, ordered lists, and statistical figures that AI can easily extract.
• Extension (Context Expansion): Helps expand context by adding related questions (People Also Ask) and derivative topics instead of stopping at fragmented information.
What is a specific example of the Fill-in (Structuring) strategy?
It's a technique that converts unstructured text (prose) into structured data that AI prefers, filling information gaps.
• Before: 'Our product is lighter and cheaper than A.' (narrative form)
• After: Provide a comparison table using Table tags, organizing weight (kg) and price (₩) in rows/columns
This transformation makes it easier for AI (RAG models) to extract data, dramatically increasing the Retrieval Rate.
Why is Extension (Context Expansion) necessary?
To be recognized by AI as a knowledge authority in the field, beyond just providing fragmented information.
Instead of answering only specific questions, expanding content scope to related questions (People Also Ask) and derivative topics increases the Semantic Match score. This makes AI classify your brand as an expert rather than just an information source.
How does Entity Linking work?
It's the process of tagging brand names or product names so AI recognizes them as unique identifiers (Entities). The solution analyzes key keywords in your content and provides metadata guidance to link them to Wikipedia or knowledge graphs, establishing them as your brand's proper nouns rather than generic terms.
This ensures AI cites your brand accurately without confusing it with similarly named competitors.
What is the Structure-Data Fit score?
It's a score indicating how friendly your content is to AI answer generation models (RAG). It technically evaluates whether Schema Markup is properly applied and whether data tables are structured for machine readability.
The higher this score, the dramatically higher the probability of being cited by answer engines like ChatGPT or Perplexity.
Get Your Brand Recommended by AI Search
We optimize your brand to be mentioned first in AI search results from ChatGPT, Perplexity, Gemini, and more. Our AIGEO consultants will propose a customized strategy for your business.