Docs
What to know before you start
These are reference standards, not blog posts. When people in the same meeting use GEO to mean different things, every decision drifts. Here we publish the definitions DATAPREPREP works with, citation reach by publishing channel, how we choose target queries, the conditions for a citation, and our scope of work, so you can judge for yourself before hiring anyone.
Website migration
Moving a site built page by page by hand to a structure where data generates the pages. The response crawlers receive includes body text, a sitemap and structured data.
Programmatic SEO
Listing the keywords customers actually search, then building pages at once from a single template with data attached. We publish one keyword cluster first and expand from there.
How to tell which queries still offer a chance to be cited
Which queries should we create documents for, and which should we skip?
Two ratios that show whether citation opportunities remain for each query type, and the four-step screening process we use to choose target queries.
Read the documentWhat our SEO work scope covers
Which parts of SEO fall within the scope of work?
13 topic clusters adapted for search in Korea, with the current status of all 95 items. Items we decided against are listed along with the reason why.
Read the documentCitable documents
Writing citable documents with one direct answer per question, then handling search engine submission and places where the documents can be verified elsewhere.
Where you publish decides which AI answers can cite you
Can a post on Naver Blog be cited in ChatGPT answers?
A table crossing publishing channels (your own site, Naver Blog and Cafe, Korean communities) with AI answer services. Unmeasured cells say so.
Read the documentThe path to a citation
What needs to be in place for our content to be cited in AI answers?
The four conditions for a citation, in order, with how to check each one yourself and what to fix first when a page doesn’t meet a condition.
Read the documentStandards for every stage
Standards that apply across all three stages: what terms mean, what can and can’t be counted, the scope of work, and the record of what changed.
How SEO, GEO, AEO and AIO relate
What are SEO, GEO, AEO and AIO, and how do they relate to each other?
SEO, GEO, AEO and AIO drawn as a hierarchy instead of four equal boxes, plus a glossary of our terms with definitions and common misconceptions.
Read the documentWhat official documentation confirmed in 2026
Which AI search changes were officially confirmed in 2026?
Each entry pairs the date and official source with what changes in practice. Forecasts and announced plans are left out; only published documents count.
Read the documentSummary
How the four fit together
Two axes, one execution layer, one outcome. Drawing them as four equal boxes is where the confusion starts.
1Only two axes
SEOCrawled, indexed and evaluated
Technical health and intent matching. A document that isn’t indexed can’t make it into any answer.
GEOCited by AI
Getting a brand recognized as a single entity, with original data, sourcing and outside evidence in place. It’s about eligibility, not phrasing.
This is what DATAPREPREP specializes in. The G stands for Generative, not Geographic.
Work done inside both axes
2Execution
AEOExcerpted into answer boxes
Question-style headings with a direct answer up front (100–160 characters on Korean pages). It’s where a document with SEO and GEO in place moves into answer placements.
It’s formatting work, so it costs almost nothing.
What follows once conditions are met
3Outcome, not directly buildable
AIOOutcome metric
The stage where a document that meets AEO requirements is cited as a source in generative AI answers such as ChatGPT search and AI Overviews.
An outcome that appears once the conditions are met. What DATAPREPREP builds is those conditions.
E-E-A-T Experience, Expertise, Authoritativeness and Trustworthiness isn’t an item in any one box; it runs through all four. SEO and GEO are the only axes, and documents reach AIO by way of AEO. DATAPREPREP specializes in GEO, and E-E-A-T runs through all four.
20 terms
Terms that get mixed up in meetings
Each term’s definition and a misconception we’ve actually run into are in the glossary table. Each link jumps to that term’s row.
- SEOSearch Engine Optimization
- SEO: definition and common misconception →
- GEOGenerative Engine Optimization
- GEO: definition and common misconception →
- AEOAnswer Engine Optimization
- AEO: definition and common misconception →
- AIOAI Overviews
- AIO: definition and common misconception →
- Indexing rate
- Indexing rate: definition and common misconception →
- Entity-based design & expansion
- Entity-based design & expansion: definition and common misconception →
- Topical authority
- Topical authority: definition and common misconception →
- UGCUser-generated content
- UGC: definition and common misconception →
- Structured dataSchema, JSON-LD
- Structured data: definition and common misconception →
- Uniqueness rate
- Uniqueness rate: definition and common misconception →
- Informational query
- Informational query: definition and common misconception →
- Programmatic SEOpSEO
- Programmatic SEO: definition and common misconception →