Most articles about AEO (Answer Engine Optimization) describe principles in theory. We're doing something different: running a real experiment on yositeup.com and documenting every step - methodology, data, what works and what doesn't.
This is Part 1 of an ongoing series. Over the coming months, we'll publish updates with intermediate data, strategy adjustments, and actual results - good and bad.
Why this matters: very few sites publicly document a real AEO experiment with actual data, especially for a small site with DR 26. We're creating this record openly.
What Is AEO and Why It Matters in 2026
AEO (Answer Engine Optimization) is the practice of optimizing content to earn citations in AI-powered search engines: ChatGPT, Perplexity, Google AI Overviews, Gemini. Unlike traditional SEO - where the goal is a position in search results - AEO's goal is to become the source that AI uses when answering user questions.
Why this is critical in 2026:
- Google AI Mode grew from 1,600 to 38.2 million monthly visits - a 12x increase in one year
- AI-driven traffic grew 527% year-over-year (Semrush data)
- AI Overviews appear in 60%+ of informational search results
- ChatGPT Search and Perplexity together have 100+ million active users
A site cited in AI answers gains a new type of traffic and builds a reputation as an authoritative source in its niche - separate from its traditional organic rankings.
Why We're Running This Experiment
To verify real-world AEO effectiveness for a small multilingual site with DR 26. Most AEO success stories involve large EN-language publishers. We want data from the small-site perspective.
To create irreplicable content. A live documented experiment is one of the few content formats competitors can't copy. The data and process are inherently unique - genuine E-E-A-T.
To contribute to the community. SEO practitioners across multiple markets lack access to real AEO experiment data for multilingual sites. We're creating this resource publicly.
Methodology
Measurement Tools
- Google Search Console - traffic, positions, impressions
- Google Analytics 4 - traffic sources, engagement
- Perplexity AI - manual citation checks for 20 target queries
- ChatGPT Search - mention verification
- Google AI Overviews - screenshots of presence
Fan-Out Testing
To verify AEO visibility, we use the fan-out technique: take one topic and test 5-10 query variants that AI might "expand" from a base question.
Example for Google Preferred Sources:
- «what is Google Preferred Sources»
- «how to add a site to Google Preferred Sources»
- «Google Preferred Sources CTR impact»
- «why Google Preferred Sources matters for publishers»
Experiment Timeline: May - August 2026
Baseline Data (Before Active AEO Optimization)
AI visibility of yositeup.com (May 2026):
| Tool | Citations from 20 Queries |
|---|---|
| Google AI Overviews (EN) | 0 of 20 |
| Google AI Overviews (non-EN) | 0 of 20 |
| Perplexity | 0 of 20 |
| ChatGPT Search | 0 of 20 |
Expected - baseline for a new site. Organic traffic: +18% growth in April 2026 (GSC). Traditional SEO is working; now we test AEO.
What We're Optimizing and How
1. Quick-Answer Block in the First 150 Words
AI search engines prefer sources where the answer to the question is clearly stated early. We add a "quick answer block" in the first 2-3 paragraphs of every article: a direct, concise response to the article's main question.
2. FAQ Blocks with Exact Query Formulations
For each article: 4-5 FAQ questions matching exact real-world search query phrasing + FAQ Schema markup (JSON-LD) on every page.
3. Definitions in "X is Y that Z" Format
AI models prefer sources with clear, encyclopedic definitions when generating citations. Every key term gets an explicit definition.
4. Authoritative Data and Source Citations
Citing primary research (Semrush, Ahrefs, Google Search Central) strengthens E-E-A-T signals that both Google's algorithm and AI citation models value.
5. Structured Data (Schema)
FAQ Schema, Article Schema, BreadcrumbList - deployed across all blog articles.
What We're Testing as Hypotheses
H1: Concise quick-answer blocks (1-2 sentences) vs. expanded ones (5-7 sentences) - which gets cited more often in AI Overviews?
H2: Internal cluster linking - does connecting articles within the same topical cluster improve AI citation frequency?
H3: Recency signals - does updating the "last modified" date increase appearance frequency in AI Overviews?
H4: Non-English AEO timing - do RU/UK/PL versions earn first citations faster than EN versions due to lower competition?
First Observations (Weeks 1-2)
After publishing the first AEO-optimized articles (#4 Google Preferred Sources, #18 Google UCP Agentic Commerce):
Indexation: both articles indexed by Google within 48 hours across all 10 language versions.
AI citations: 0 so far for all queried variants. Expected - standard lag is 4-8 weeks for new publications.
Organic impressions: trending-topic articles (#4, #18) show GSC impressions appearing 5-7 days after publication.
FAQ
What is AEO (Answer Engine Optimization)?
AEO is the practice of optimizing content to earn citations in AI-powered search engines: ChatGPT, Perplexity, Google AI Mode, Gemini. The goal is to become the source AI uses when answering user questions - distinct from ranking in traditional search results.
Does AEO work for small sites with low Domain Rating?
That's exactly what we're testing. Preliminary evidence suggests AEO is less DR-dependent than traditional SEO - AI models select sources based on answer relevance and structure, not purely on domain authority. We expect first data in 4-6 weeks.
How is AEO different from SEO?
SEO targets position in traditional search results. AEO targets citation in AI answers. The principles partially overlap (E-E-A-T, structured data, topical authority) but AEO puts additional emphasis on direct answers at the top of content, FAQ structure, and precise definitions.
How long does AEO take to show results?
For already-indexed pages: 4-8 weeks. For new publications: 6-12 weeks. This is the standard lag for AI search citation pickup. We'll publish data as it comes in.
How do you track AEO performance?
Manual query testing in Perplexity, ChatGPT Search, and Google (with AI Overviews enabled). Tracking referral traffic from AI sources in GA4. Monitoring impression changes in GSC for queries where AI Overviews appear. We document each check with screenshots.
Schema FAQ (JSON-LD)
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "What is AEO - Answer Engine Optimization?",
"acceptedAnswer": {
"@type": "Answer",
"text": "AEO (Answer Engine Optimization) is the practice of optimizing content to earn citations in AI-powered search engines: ChatGPT, Perplexity, Google AI Mode, Gemini. The goal is to become the source that AI uses when answering user questions."
}
},
{
"@type": "Question",
"name": "Does AEO work for small sites?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Preliminary data suggests AEO is less dependent on Domain Rating than traditional SEO. AI models select sources based on answer relevance and structure. We're testing this on a DR 26 site and publishing results publicly."
}
},
{
"@type": "Question",
"name": "How is AEO different from SEO?",
"acceptedAnswer": {
"@type": "Answer",
"text": "SEO targets rankings in traditional search results. AEO targets citation in AI-generated answers. AEO requires direct answers early in the content, FAQ schema markup, precise definitions, and authoritative data citations."
}
},
{
"@type": "Question",
"name": "How long does AEO optimization take to show results?",
"acceptedAnswer": {
"@type": "Answer",
"text": "For already-indexed pages: 4-8 weeks. For new publications: 6-12 weeks. This is the standard lag for AI search engines to incorporate new sources into citation pools."
}
}
]
}Conclusion
This is one of the few publicly documented live AEO experiments for a small multilingual site. We don't know the outcome in advance - and that's precisely what makes it valuable. Theory is being tested with data.
What's next:
- June 2026: Interim report with AI citation data and organic traffic changes
- Testing: quick-answer length, cluster internal linking, update frequency signals
- Publishing results - positive and negative
Follow yositeup.com blog for updates.
Related: Agentic AI vs Generative AI: Complete SEO Guide 2026
