By Vlad Radu · Founder, Wolfdesk
We crawl your URL, parse the schema, and run it through a GEO scoring model to predict your citation probability across answer engines.
A short primer for content and marketing teams on what Answer Engine Optimization is, why it matters right now as search shifts toward AI-generated answers,[1] and how it differs from the SEO playbook — including the E-E-A-T signals search platforms already reward.[2]
Answer Engine Optimization — the discipline of making your content structured, extractable, and trustworthy enough that AI systems quote it directly in their answers, not just link to it.
Generative Engine Optimization — the same discipline applied to generative surfaces like ChatGPT, Perplexity, and Gemini, where the model synthesises an answer from cited sources.
Search is shifting from ten blue links to synthesized answers in ChatGPT, Perplexity, Gemini, and Google AI Overviews. If your brand is not cited inside those answers, you become invisible to the users who never click through.
These common blockers stop LLMs from confidently quoting a page:
Lead with a direct 40–60 word answer, add topical depth underneath, mark up entities with schema, cite primary sources, and keep author, publisher, and dateModified metadata clean and current.
References
Real audit results on aeo-audit.app — before and after optimization.
We simulate how large language models (LLMs) read your website to ensure you are visible in AI-driven search.
Paste your URL and our engine crawls the page, parsing JSON-LD, headings, canonical tags, and rendering mode exactly the way ChatGPT and Perplexity see it.
We probe schema completeness, headless rendering gaps, llms.txt presence, and the semantic blocks answer engines rely on when picking citations.
Get a score-based audit across Technical, Content, and Authority pillars with step-by-step instructions to fix what's blocking AI citation.
Scores are derived from real-world LLM behaviour, not keyword heuristics or PageRank proxies.[1] Feature weights are grounded in the same signals search platforms document publicly for structured content and E-E-A-T.[2]
thousands of queries logged across verticals to identify which URLs get cited and how often.
each cited page decomposed into ~40 technical, content, and authority features including structured data, prose density, crawlability, heading hierarchy, and source age.
feature importance calibrated against citation frequency to produce the Technical, Content, and Authority sub-scores.
weights are updated on a rolling basis as LLM retrieval patterns shift, so scores always reflect current citation behaviour.
References
Methodology questions → hello@aeo-audit.app
A practical, tool-agnostic playbook you can apply to any site — regardless of stack, CMS, or vertical.
Start by discovering the exact phrasing real users bring to answer engines. Pull queries from Google's People Also Ask, Reddit threads in your niche, support-ticket subject lines, and sales-call transcripts. Cluster them by intent, then map each cluster to one target page so every URL owns a distinct answerable question.
Open every page with a 40–60 word lead answer that resolves the query in a single readable block, then expand into depth below. Wrap the page in the correct JSON-LD type — FAQPage, Article, HowTo, or Product — so LLMs can parse entities and quote the answer verbatim.
Prove the page was written by a real, qualified human. Attach a byline, link to an author bio page marked up with Person schema, list credentials and prior publications, cite primary sources inline, and keep dateModified current so answer engines treat the page as an authoritative source.
Ship the critical content in server-rendered HTML with exactly one h1, a clean h2/h3 hierarchy, and semantic elements like article, section, and nav. Do not hide the answer behind client-side JavaScript, tabs, or accordions — AI crawlers frequently skip content that requires hydration to appear.
Earn inbound mentions from domains that LLMs already trust in your vertical — trade publications, university pages, government sources — and interlink your own pages inside a tight entity cluster. Answer engines preferentially cite sources that are corroborated across multiple independent domains on the open web.
Most tools grade your site against a checklist. We grade it against the behaviour of the answer engines themselves.
Optimize for a ranked list of ten blue links using keyword volume, backlink counts, and SERP position. They tell you nothing about whether an LLM will actually cite the page in a synthesized answer.
Run the same generic pass-fail checks on every URL — 'add schema', 'shorten title' — with no model of how retrieval actually works or which signals push a page into an answer citation.
We render the page the way an LLM does — headless-parity HTML, extracted entities, weighted against real citation frequency across SearchGPT and Perplexity — so the scorecard reflects behaviour, not a checklist.
Everything you need to make your site readable, quotable, and citable by modern answer engines.
Beyond any single tool, AEO is a strategic bet on where discovery is heading. The compounding advantages accrue to teams that start early.
Every AI answer that cites you seeds the next one. Being the default source in your vertical creates a citation flywheel competitors struggle to break.
Users who click through from an AI answer arrive pre-qualified — the model has already screened them for fit and framed the context of the visit.
Early movers in AEO become the trusted, corroborated source LLMs return to. That position is hard to dislodge once retrieval patterns settle.
As zero-click AI answers grow, being cited inside those answers protects your brand reach even as classic organic click-through-rates compress.
Answer Engine Optimization (AEO) is the process of optimizing your website so that AI chatbots and answer engines like ChatGPT, Perplexity, and Gemini can easily read, understand, and cite your content as a source in their answers.
GEO (Generative Engine Optimization) is the practice of structuring content so generative AI systems quote, summarize, and link to your page inside their generated responses. GEO overlaps heavily with AEO — both target machine-readable structure, direct answers, and verifiable authority signals.
Traditional SEO focuses on ranking links on Google by targeting keywords and backlinks. AEO focuses on structuring data, providing direct factual answers, and optimizing for machine-readability so AI models feature your brand directly in conversational responses.
The Wolfdesk AEO audit checks your site against the technical requirements and crawling behaviors of major AI systems, primarily focusing on ChatGPT (SearchGPT), Perplexity, and Gemini.
Many modern websites use complex JavaScript that AI crawlers struggle to read. A low score usually means your site lacks server-side rendering, clear semantic HTML headings, or proper structured data (Schema markup). Our audit tells you exactly how to fix this.
The most common pitfalls are over-optimizing for a single engine, keyword-stuffing answer blocks, publishing generic AI-written filler with no source authority, omitting dateModified timestamps, and writing walls of prose with no extractable summary an LLM can quote.
Monthly for high-velocity content (blog, docs, product pages) and quarterly for evergreen pages. Re-audit whenever a major LLM ships a new retrieval model, because citation behaviour shifts and yesterday's optimizations may no longer trigger inclusion.
No — when done correctly, AEO reinforces classic ranking factors. Structured answers, schema markup, and E-E-A-T signals all improve traditional SEO. Risk only appears if you strip prose depth in favour of bare Q&A snippets, which can hurt topical authority and dwell time.