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Austin Heaton's technical AEO process
You can publish the best content in your category and still be invisible in ChatGPT, Perplexity, Claude, Gemini, and Google, because the technical foundation is quietly broken. Most AI invisibility is technical, not creative.
A Technical AEO Audit is Austin Heaton's deep diagnostic of whether AI engines can crawl, render, trust, and cite your site, from LLM crawlability and robots.txt to entity signals, content structure, NLP, and your CMS backend. You get a prioritized roadmap of exactly what to fix and why.
Every audit runs through the same rigorous checklist, the technical signals that decide whether AI engines and search can find, understand, and cite you.
Whether AI crawlers can actually reach, fetch, and render your pages, checked at the server, CDN, and firewall layers, not just the surface. This is where most "invisible" sites break.
Confirms the crawlers that drive citations, GPTBot, OAI-SearchBot, ChatGPT-User, ClaudeBot, PerplexityBot, and Google-Extended, are correctly handled, and that nothing important is blocked by accident.
Your XML sitemaps are complete, clean, and submitted, with no orphaned, blocked, or noindex URLs quietly keeping pages out of discovery and citation.
Render speed, JavaScript dependency, and server responses to bots, because many AI crawlers don't execute heavy JS, so content that relies on it can be invisible to them.
Consistent organization and author entity data, Organization and Person schema, and off-site consistency, the signals that tell AI systems who you are and why to trust you.
Heading hierarchy, definition-first answers, and chunkability, the structural patterns AI engines lift and cite, audited page by page across your key content.
How machines actually parse your language: entity coverage, semantic relevance, and topic depth measured against the exact queries you want to win.
The settings inside your CMS that quietly control everything: rendering mode (server vs client-side), canonicals, indexability rules, and how your schema is actually output.
Whether your markup is complete, valid, and aligned to your entities, one of the strongest technical levers for AI citation eligibility and rich-result visibility.
Plus more: internal linking and topical-cluster structure, llms.txt configuration, server log-file analysis, indexation coverage, and AI-citation tracking setup, so you can measure visibility going forward.
The data is clear: the most common reasons brands don't get cited are technical, and fixable.
Blocking the wrong bot makes you disappear. Per OpenAI's documentation, sites opted out of OAI-SearchBot won't appear in ChatGPT search answers, even if GPTBot has already crawled them. These mismatches are silent and common, and they're exactly what the audit catches.
Your CDN can override your robots.txt. A platform like Cloudflare can silently block AI crawlers regardless of what your file says. ZipTie research indicates roughly a quarter of B2B sites are blocking major LLM crawlers this way without realizing it.
Structure and schema decide citations. A Carnegie Mellon GEO study (KDD 2024) found schema among the top predictive features for LLM citation, and analysts find well-structured, self-contained content gets cited far more often. The audit scores your markup and structure against these signals.
These are Austin's own client engagements. In each, the technical groundwork, crawlability, schema, indexation, and structure, made the content visible and citable. Figures are from client analytics and AI citation tracking.
A technical SEO foundation paired with high-velocity content grew monthly organic sessions from 2,800 to 18,400+ and built AI citation presence across ChatGPT, Perplexity, and AI Overviews within 60 days.
In a DocuSign-dominated space, FAQ and entity schema plus clean indexation established Pactvera's terms as citation-ready entities, with homepage and comparison content indexed in week one.
With crawlability and structure dialed in, Lumanu became a consistently cited source across AI engines, and those AI visitors converted at materially higher rates than traditional organic traffic.
AI-visibility measurement and entity infrastructure was built from zero across ChatGPT, Perplexity, Claude, and Gemini, establishing authority for 50+ projects and making the publication LLM-referenced.
A clear, repeatable process, ending in a ranked list of fixes by impact, not a 90-page report you'll never read.
Crawlability, robots.txt, CDN, sitemaps, and LLM bot access.
Content structure, chunkability, and semantic coverage analysis.
Entity signals, schema, and off-site consistency review.
Rendering, canonicals, indexability, and platform settings.
Every issue ranked by impact, with fixes mapped to outcomes.
The technical audit is the diagnostic foundation. It finds what to fix, then Austin's content deliverables build the authority and coverage that earn AI citations and rankings.
The deep technical diagnostic of crawlability, trust signals, structure, NLP, and CMS settings, with a prioritized roadmap of fixes. Where every engagement starts.
This pageCitation-engineered pillar content that establishes your entity and topical authority, so AI engines and Google reach for you as the reference in your category.
Explore authority posts →Done-for-you blog content across five proven post types, written with a human + AI hybrid model and published at the velocity that compounds traffic into pipeline.
Explore blog posts →Get a senior operator's honest read on your technical AEO footprint, and the highest-impact fixes standing between you and AI-search visibility. No obligation.
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