Methodology
A GEO/AEO score you can inspect. A system you can act on.
AI Authority is Auzork’s proprietary measurement framework for brand presence across answer engines — the discipline the industry calls GEO (Generative Engine Optimization) and AEO (Answer Engine Optimization). It’s built on 100+ SEO and AI-search research papers, and it closes the loop with a content engine that ships ranking pages and blogs in minutes.
100+
SEO, GEO and AI-search research papers analyzed to build the scoring and content algorithms.
6
Answer engines sampled per analysis — ChatGPT, Gemini, Perplexity, Claude, Grok and AI Overviews.
5
Weighted authority signals, not one vanity mention-count metric.
Minutes, not a day
Time for the Content Engine to turn a visibility gap into a publish-ready page or blog.
The research
We didn’t guess the algorithm. We reverse-engineered it.
Before we scored a single prompt, we analyzed 100+ SEO, GEO and AI-search research papers, ranking studies and algorithm-pattern write-ups to find the signals that actually hold up — in traditional search and in AI answers alike.
Search ranking research
Peer-reviewed and industry studies on what actually correlates with rank position — not recycled blog-post folklore.
AI citation & retrieval studies
Research on how LLMs select, weight and cite sources when they compose an answer, and why some domains get quoted and others don’t.
Algorithm & update pattern analysis
Patent filings, leaked ranking documents and years of search and AI model update patterns, reverse-engineered for the signals that persisted.
Content & entity structure studies
Research on topical authority, entity coverage and answer formatting — the difference between content that gets crawled and content that gets cited.
The signal model
Authority is multidimensional.
A mention alone can be misleading — and mention-counting is where most GEO tools stop. Our engine evaluates six connected signals to build diagnostic context you can actually act on.
Visibility
Does the brand appear at all for the questions that influence demand — across ChatGPT, Gemini, Perplexity, Claude and Grok?
Rank position
Where does it land in the response and recommendation order? Position one earns a fraction of the demand position four does.
Sentiment
How does the model characterize the brand — as a leader, an afterthought, or a caveat next to a competitor?
Platform breadth
Is authority durable across models, or is it a single-engine fluke that disappears the moment a user switches assistants?
Citation authority
Which sources support the answer, and does your domain earn the citation — or does a competitor’s?
Competitive context
Who wins when you do not, and which content, technical or authority pattern explains the gap?
How it works
Designed for direction, not false precision.
Six connected steps take you from raw AI answers to a shipped fix — the same loop, run on a schedule, for as long as you’re competing for the answer.
- 01Map
Your brand, category, competitors, markets and buyer-intent topics define the GEO/AEO prompt universe — the exact questions your market asks AI before it asks you.
- 02Sample
The Signal Engine runs representative prompts across every enabled model on a fixed cadence and preserves response-level evidence, not just a summary score.
- 03Interpret
We extract mentions, order, sentiment, cited sources and competitive entities from raw model output — the same evidence a human analyst would read, at machine scale.
- 04Score
Signals are normalized into an AI Authority Score with platform-level breakdowns, so you know exactly which engine is costing you demand.
- 05Recommend
Visibility gaps are connected to specific technical, content and competitive actions — then the Content Engine can draft the fix as a publish-ready page in minutes, not the day-per-page timeline of a manual SEO workflow.
- 06Repeat
Scheduled reanalysis builds a trend line, so your team judges durable progress against real history — not one noisy AI response.
The Content Engine
One pipeline. Ranking pages and blogs, both.
The same research base that powers your score powers what the Content Engine writes — for a new landing page or a full blog post, the pipeline is the same five stages.
Research
The engine pulls your AI Authority evidence, live SERP data and competitor pages for the target topic — grounded in the same 100+ studies behind the scoring model.
→Outline
Entity coverage, heading structure and answer format are planned against the patterns that actually earn rank position and AI citations.
→Draft
A full page or blog post is written — briefs, headings, on-page copy and FAQ blocks — in your brand voice, not generic filler.
→Optimize
Schema, internal links, readability and technical on-page checks run automatically before a human ever opens the draft.
→Publish
Push straight to your site or CMS. Total time: minutes — the same page a specialist would need a full day to research and write.
Why it holds up
Built to survive a board-level question.
Every score traces back to a stored prompt, a stored model response and a stored citation. Nothing is estimated after the fact — if a number moves, we can show you the exact answer that moved it.
Why it compounds
Measurement and execution share one engine.
Because the Content Engine reads the same evidence that produced your score, the fix it ships is grounded in the exact gap the score identified — no handoff, no reinterpretation, no day-long wait on a specialist’s queue.
Your next search channel is already here