Poor entity clarity
Your copy mentions products, claims, and stats but never maps them to canonical entities or `sameAs` sources.
AEO/GEO optimization toolkit
Be the cited answer in AI search.
Paste a single URL and we will show you exactly how to restructure that page so ChatGPT, Claude, Perplexity, and Google AI Overviews can ingest, trust, and cite it. You get the AI Mention Scorecard, schema patches, checklist, and prompts--no monitoring noise, just optimization instructions.
- Optimize content structure. Entities, schema, answerability, and verifiability diagnosed in one scan.
- Copy/paste implementation plan. JSON-LD, evidence links, and writing cues ready for dev + content teams.
- Research-backed methodology. Informed by the KDD 2024 GEO paper listed by Princeton University.
Why your content gets ignored
ChatGPT can only cite what it can parse.
Schema drift
Schema is missing, invalid, or detached from the content block the AI is reading.
Answerability gaps
Paragraphs ramble without providing cite-able, verifiable responses to the prompts buyers actually ask.
No ingestion trail
Broken sitemaps, weak headings, and missing evidence links keep answer engines from trusting the page.
How we fix it
The AI Mention Scorecard pinpoints every structural issue.
- Entity & schema map with copy/paste JSON-LD
- Answerability edits mapped to prompts
- Evidence & ingestion checklist
- Implementation sequencing for dev + content
Research Basis
This methodology is grounded in published GEO research.
Academic foundation
Based on GEO: Generative Engine Optimization
The framework behind this site is informed by the Princeton-listed KDD 2024 paper GEO: Generative Engine Optimization, which formalized GEO and evaluated which content changes actually improve visibility in generative engine responses.
Up to 40% visibility lift
The paper reports that GEO methods can improve visibility in generative engine responses by up to 40% across a diverse benchmark.
Evidence-centric tactics win
The paper specifically highlights citations, quotations, and statistics as high-performing ways to improve visibility in generative engine responses.
Visibility has to be measurable
The research formalizes GEO as a measurable visibility problem, which is why this site scores concrete page signals instead of offering vague "AI optimization" advice.
No one-size-fits-all playbook
The paper found that results vary by domain, so the report focuses on page-level and context-specific recommendations instead of generic SEO checklists.
AISearchLab uses this research as a methodological input. It is not affiliated with or endorsed by Princeton University.
Inside the sample
See the AI Mention Scorecard before you buy.
Scorecard & rubric
Overall GEO readiness score plus nine rubric categories with per-signal commentary.
Schema patch kit
Copy/paste JSON-LD with entity IDs, relationships, and validation notes.
Answerability checklist
Rewrite cues, prompt coverage, and evidence gaps prioritized by impact.
Prompt pack
5 queries your buyers ask AI today with recommendations to earn the citation.
Before & after
We don't track mentions--we fix your inputs.
Before Optimization
- Paragraphs without entities or IDs
- Images with no descriptive alt text
- Claims lacking citations
- Schema referencing generic placeholders
After Optimization
- Entity graph aligned to product taxonomy
- Answer-ready copy with cite-able blocks
- Evidence + sameAs links for each claim
- Structured data tied to actual copy
Process
From crawl to implementation in three steps.
01
Crawl
We fetch the exact HTML, schema, and feeds AI engines ingest.
02
Score
9-point GEO/AEO rubric grades entities, answerability, verifiability, and ingestion.
03
Ship
You receive the AI Mention Scorecard, implementation plan, and optional consulting path.
Proof points
Optimization beats guesswork.
FAQ
What buyers usually ask before they run a scan.
What is GEO/AEO, in plain English?
It is the practice of structuring a page so AI systems can parse it, trust it, and reuse it in generated answers. That means clearer entities, stronger evidence, better answer formatting, and cleaner schema, not just more keywords.
Is this just SEO with a new label?
Not exactly. SEO is still important, but GEO targets a different outcome: visibility inside generated answers. The paper formalizes separate visibility metrics for generative engines rather than traditional blue-link ranking.
Why does your report emphasize citations, statistics, and quotable claims?
Because those are exactly the kinds of changes the paper found to be high-performing. AI systems appear to reward content that is easier to trust, summarize, and attribute.
Will the same recommendations work for every industry?
No. The paper explicitly found domain-specific differences, which is why this site analyzes the actual page and gives targeted fixes instead of a universal checklist.
Can a smaller site benefit, or is this only for brands already ranking at the top?
Yes, potentially. The paper's core point is that content creators can influence visibility even in black-box generative engines, but the size of the gain depends on the query set, domain, and page quality.
Does this guarantee that ChatGPT or Google AI Overviews will cite me?
No. These systems are black-box and constantly changing. What you can do is improve the odds by making your page easier to retrieve, verify, summarize, and quote.
What do I get after I run a scan?
You get a live report with a scorecard, category-by-category findings, prioritized fixes, and implementation guidance. If you want a portable copy, you can also export the report as Markdown.
Need hands-on help?
We can implement every recommendation for you.
Our consulting team ships schema, rewrites content, and sets up ingestion governance so you own AI citations end-to-end.