Why an AEO Audit
An AEO audit evaluates whether your digital presence is structured for AI citation across ChatGPT, Perplexity, Google AI Overviews, and Claude. Most businesses have robust SEO monitoring but no visibility into whether they are being cited, mentioned, or ignored by AI-generated answers. An AEO audit closes that gap.
The audit serves two purposes. First, it establishes a baseline — documenting your current AI citation status, identifying gaps in schema, content structure, entity consistency, and trust signals. Second, it creates a prioritized action plan that maps directly to measurable AI visibility improvements.
Without an audit, businesses operate blind to a growing share of how customers find them. An SEO dashboard shows rankings and organic traffic but says nothing about whether your business appears when someone asks ChatGPT for a recommendation in your category. That blindness is the problem the AEO audit solves.
The Five Audit Categories
A comprehensive AEO audit covers five categories: content (accuracy and extractability), technical (crawlability and performance), schema and entity (structured data and consistency), trust and review (reputation signals and E-E-A-T), and measurement (AI visibility tracking and baselines). Each category addresses a different stage of the AI retrieval pipeline.
| Category | What It Evaluates | AI Pipeline Stage |
|---|---|---|
| Content | Accuracy, answer-first structure, Q&A coverage, non-promotional tone | Extraction — can AI pull a clean answer from your content? |
| Technical | Crawlability, Core Web Vitals, indexation, AI crawler access | Discovery — can AI find and access your content? |
| Schema and Entity | Markup completeness, entity naming consistency, sameAs links, knowsAbout | Understanding — can AI identify your entity and its expertise? |
| Trust and Review | Review volume, rating, recency, E-E-A-T signals, citation consistency | Ranking — does AI trust your entity enough to cite it? |
| Measurement | AI visibility tracking, citation frequency baseline, share-of-voice | Monitoring — can you see whether you are being cited? |
Category 1: Content Audit
The content audit evaluates whether your pages are structured for AI extraction. It checks for answer-first formatting, Q&A coverage of target queries, non-promotional tone, factual accuracy, data table usage, and visible update dates. Content that cannot be cleanly extracted by AI systems cannot be cited, regardless of how well it ranks.
| Check | What to Look For | Pass Criteria |
|---|---|---|
| Answer blocks | 40-60 word self-contained answer under every H2 | Every primary service and resource page has answer blocks |
| FAQ sections | Question-and-answer sections matching real customer queries | FAQs present on all service pages and key resource pages |
| Data tables | HTML tables for comparisons, specifications, and structured data | All comparisons use tables, not prose lists |
| Tone | Factual, non-promotional language throughout | No superlatives, no marketing claims without evidence, honest limitations |
| Update dates | Visible "last updated" dates on content pages | Every content page shows a recent, accurate update date |
| Query coverage | Content exists for "best X," "X vs Y," "how to X," and "emergency X" queries relevant to your business | Core customer queries are covered with dedicated, structured content |
| Heading structure | Logical H1 to H2 to H3 hierarchy with descriptive headings | Every page uses semantic heading hierarchy. No skipped levels. |
Category 2: Technical Audit
The technical audit ensures AI systems can discover and access your content. It evaluates indexability, Core Web Vitals performance, AI crawler access in robots.txt, JavaScript rendering issues, and canonicalization. If a page is not indexed or is blocked from AI crawlers, it cannot be cited regardless of content quality.
| Check | What to Look For | Pass Criteria |
|---|---|---|
| Indexation | Key pages indexed in Google Search Console | All primary pages indexed. No unintended noindex tags. |
| AI crawler access | robots.txt allows GPTBot, Google-Extended, ClaudeBot, PerplexityBot | No blanket blocks on AI user agents |
| Core Web Vitals | LCP, INP, CLS meeting Google thresholds | LCP under 2.5s, INP under 200ms, CLS under 0.1 |
| Mobile performance | Mobile-friendly rendering and performance | PageSpeed Insights mobile score 80+ |
| JavaScript rendering | Content visible without client-side JavaScript execution | Primary content renders in static HTML or is server-side rendered |
| Canonicalization | Correct canonical tags, no duplicate content issues | Every page has a self-referencing canonical. No conflicting canonicals. |
| XML sitemap | Complete, accurate sitemap submitted to GSC | Sitemap includes all primary pages with accurate lastmod dates |
Category 3: Schema and Entity Audit
The schema and entity audit evaluates whether AI systems can identify your business as a defined entity with verifiable expertise. It checks for Organization, Person, LocalBusiness, FAQPage, Article, and Review schema, sameAs links to authority profiles, knowsAbout properties, and consistent entity naming across all schema blocks and platforms.
| Check | What to Look For | Pass Criteria |
|---|---|---|
| Organization schema | Present on every page with identical entity naming | Consistent name, description, and knowsAbout properties on all pages |
| Person schema | Present on about/author pages with credentials and sameAs links | Links to LinkedIn, professional profiles. Matches author bios on-page. |
| LocalBusiness schema (if applicable) | Specific subtype with PostalAddress, GeoCoordinates, OpeningHours, AreaServed | All location data matches GBP and directory listings exactly |
| FAQPage schema | Present on service and resource pages with FAQ sections | Schema questions match on-page FAQ content exactly |
| Article + Speakable schema | Present on all content pages with Speakable targeting answer blocks | Every blog and resource page has Article schema with Speakable selectors |
| sameAs links | Organization and Person schema include sameAs to active authority profiles | All linked profiles are active, accurate, and consistent with on-site claims |
| Entity naming consistency | Business name identical across all schema blocks, pages, and platforms | Zero variations. Same name everywhere — no abbreviations, no alternate forms. |
Category 4: Trust and Review Audit
The trust and review audit evaluates the reputation signals that AI systems use to determine whether your entity is credible enough to cite. It covers review volume, rating, and recency across platforms, E-E-A-T signals including author bios and original research, and NAP consistency across directories, social profiles, and listing sites.
| Check | What to Look For | Pass Criteria |
|---|---|---|
| Google Reviews | Volume, rating, recency, response rate | Active review profile with 4.5+ rating, recent reviews (within 30 days), all reviews responded to |
| Multi-platform reviews | Presence on Yelp, industry directories, and relevant platforms | Consistent positive presence across at least 2-3 review platforms |
| Author attribution | Clear author bios on content pages with credentials and linked profiles | Every content page has a named author with verifiable credentials |
| Original research/case studies | Published original data, methodology, or documented results | At least one original case study or data-backed experiment published |
| NAP consistency | Name, address, phone identical across all directories and platforms | Zero discrepancies. Master NAP record matches every listing. |
| Expertise alignment | Service descriptions and specialties consistent across website, LinkedIn, GBP, directories | Identical terminology used everywhere. No conflicting expertise claims. |
Category 5: Measurement Audit
The measurement audit evaluates whether you have the tools and processes to track your AI visibility over time. Without measurement, you cannot know whether your AEO efforts are working, whether competitors are gaining ground, or whether AI system updates have changed your citation status. Most SEO-mature businesses have no AI-specific monitoring in place.
| Check | What to Look For | Pass Criteria |
|---|---|---|
| AI citation tracking | Tool or process monitoring brand citations across ChatGPT, Perplexity, Google AI Overviews, Claude | Active monitoring with at least monthly citation testing across 2+ platforms |
| Baseline established | Documented baseline citation frequency and AI share-of-voice | Baseline data recorded for core topic queries before optimization begins |
| Branded search monitoring | Google Search Console tracking for branded query trends | GSC monitoring active with branded query data reviewed monthly |
| AI crawler log analysis | Server logs checked for GPTBot, Google-Extended, and other AI crawlers | Crawl activity confirmed. Blocked crawlers identified and resolved. |
| Competitor tracking | Regular testing of competitor citation appearances in AI answers | Quarterly competitor AI visibility comparison documented |
The Five Most Common Gaps
Agency and consultant audit data consistently reveals five gaps that appear in the majority of AEO assessments: incomplete schema implementation, weak E-E-A-T signals, inconsistent entity and NAP data, content not structured for AI extraction, and no AI-specific monitoring layer. Fixing these five gaps addresses the highest-leverage opportunities for most businesses.
| Gap | How It Manifests | Impact on AI Citation |
|---|---|---|
| Incomplete schema | Missing Organization, FAQPage, Person, or LocalBusiness schema. Partial implementation that covers some pages but not others. | AI cannot identify your entity or extract structured answers. Fundamental blocker. |
| Weak E-E-A-T | No author bios, no cited data, no original research, no case studies, no methodology documentation. | AI systems cannot verify expertise. Deprioritized in favor of sources with clear authority signals. |
| Entity/NAP inconsistency | Different business names, outdated addresses, conflicting phone numbers across directories and platforms. | AI confidence drops. Entity fragments into multiple unlinked mentions. Citation signal diluted. |
| Unstructured content | Long-form prose without answer blocks, no FAQ sections, no data tables, no clear heading hierarchy. | AI cannot extract clean answers. Pages skipped in favor of competitors with extractable structure. |
| No AI monitoring | Robust SEO dashboards but zero tracking of AI citations, mentions, or share-of-voice. | Business is blind to AI visibility. Cannot measure impact, cannot detect decline, cannot benchmark against competitors. |
AI Visibility Tools
Several tools specialize in tracking whether a brand is cited or mentioned by AI platforms. Established options include Conductor, Omnia, Visible by SE Ranking, and Averi. These tools track citation frequency, AI share-of-voice, brand mentions, and sentiment across ChatGPT, Perplexity, Claude, and Google AI Overviews. Pricing ranges from approximately $100 per month to enterprise-level plans.
| Tool | What It Tracks | Platforms Covered | Pricing Level |
|---|---|---|---|
| Conductor | Brand mentions (text) and website citations (linked URLs) in AI answers | ChatGPT, Perplexity, similar platforms | Enterprise-level (pricing not public) |
| Omnia | Brand description analysis, source reliance, citation context | ChatGPT, Claude, Perplexity, Google AI Overviews | Not publicly listed |
| Visible (SE Ranking) | AI Overview appearance, LLM answer presence | ChatGPT, Claude, Gemini, Perplexity, Bing Chat | Tiered, starting ~$100+/month |
| Averi | Citation frequency, AI share-of-voice, brand visibility score, sentiment | Multiple AI platforms | Vendor-specific pricing |
For businesses not ready to invest in dedicated tools, manual citation testing provides a viable starting point. Query ChatGPT, Perplexity, and Google with your core topic queries monthly and document whether your business appears. Track branded search volume in Google Search Console for spikes that correlate with AI citation (users who see your business in an AI answer often search for you directly afterward). Check server logs for AI crawler activity to confirm your content is being accessed.
Benchmark Metrics for AEO
Core AEO performance metrics include citation frequency, AI share-of-voice, brand visibility score, and query coverage breadth. Vendor benchmarks suggest targeting 30% or more mention rate in category-relevant prompts, with top brands reaching 50% or higher. These benchmarks are vendor-recommended targets, not independently validated standards, and should be treated as directional.
| Metric | Definition | Benchmark Target | Evidence Level |
|---|---|---|---|
| Citation Frequency | How often your brand is explicitly cited in AI answers for target queries | 30%+ mention rate in category-relevant prompts. Top brands: 50%+. | Vendor benchmark (Averi) |
| AI Share-of-Voice | Your brand's share of total mentions versus competitors in AI answers | Higher is better. AI answers cite 2-7 domains, making SOV winner-takes-most. | Vendor benchmark (Conductor, Averi) |
| Brand Visibility Score | When your brand is named in AI text, even without a linked citation | Track alongside linked citations for a composite visibility picture. | Vendor metric (Averi, Conductor) |
| Query Coverage Breadth | How many of your core topic prompts your brand appears in | Coverage across 70%+ of core queries indicates strong AEO positioning. | Practitioner recommendation |
| Branded Search Trend | Change in branded search queries in Google Search Console | Upward trend correlating with AEO implementation indicates AI-driven awareness. | Confirmed indirect signal |
| AI Crawler Activity | Frequency of GPTBot, Google-Extended, and similar crawlers in server logs | Active, regular crawling confirmed. Increasing crawl frequency is positive. | Confirmed technical signal |
How to Prioritize Findings
AEO audit findings are prioritized in three tiers based on leverage and dependency. High priority items are foundational — everything else depends on them. Medium priority items strengthen signals. Lower priority items refine and expand. Fix what keeps you out of AI answers first, then optimize what determines how often you appear.
| Priority | Category | Actions | Rationale |
|---|---|---|---|
| High (Fix First) | Technical | Ensure indexability, AI crawler access, Core Web Vitals | If AI cannot find your content, nothing else matters. |
| High (Fix First) | Schema/Entity | Implement Organization, FAQPage, Person, Article schema. Fix entity naming. | Highest-leverage AEO fix. Without schema, AI cannot identify your entity. |
| High (Fix First) | Content | Add answer blocks and FAQ sections to core pages | AI systems extract from these most readily. No extractable content = no citation. |
| Medium (Fix Second) | Trust | Fix NAP inconsistencies. Add author bios. Strengthen E-E-A-T. | Trust signals determine whether AI cites you over a competitor with similar content. |
| Medium (Fix Second) | Measurement | Set up AI visibility tracking. Establish baseline metrics. | Without measurement, you cannot track progress or detect regression. |
| Lower (Iterative) | Technical | Performance tuning beyond Core Web Vitals. Advanced rendering optimization. | Refinement layer. Only matters once foundation is solid. |
| Lower (Iterative) | Content | Competitor content gap analysis. Expanded query coverage. | Expansion layer. Broadens reach after core signals are strong. |
Frequently Asked Questions
What does an AEO audit cover?
A comprehensive AEO audit covers five categories: content audit (accuracy, answer-first structure, Q&A coverage), technical audit (crawlability, Core Web Vitals, AI crawler access), schema and entity audit (markup completeness, entity consistency, sameAs links), trust and review audit (review profile, E-E-A-T signals, citation consistency), and measurement audit (AI visibility tracking, citation frequency baseline, AI share-of-voice).
What tools track AI citation and visibility?
Established AI visibility tools include Conductor (tracks brand mentions and URL citations across ChatGPT, Perplexity, and similar platforms), Omnia (monitors brand descriptions and source reliance across ChatGPT, Claude, Perplexity, and Google AI Overviews), Visible by SE Ranking (tracks AI Overview appearance and LLM answer presence), and Averi (tracks citation frequency, AI share-of-voice, and brand visibility score). Pricing ranges from approximately $100 per month for standard plans to enterprise-level pricing.
What are the most common AEO audit gaps?
The five most common gaps are poor or incomplete schema implementation, weak E-E-A-T signals (missing author bios, no original research, no citations), inconsistent entity and NAP data across platforms, content not structured for AI extraction (no answer blocks, no FAQ sections, no data tables), and no AI-specific monitoring layer to track citation performance.
How do you prioritize AEO audit findings?
AEO audit findings are prioritized in three tiers. High priority (fix first): basic crawlability and indexability, core schema and entity signaling, and AI-readable content structure. Medium priority (fix second): entity and NAP consistency, E-E-A-T enhancement, and AI visibility tracking setup. Lower priority (iterative): performance tuning beyond Core Web Vitals and competitor-specific content expansion.
What metrics benchmark AEO performance?
Core AEO performance metrics include citation frequency (how often your brand is cited in AI answers, with a benchmark target of 30% or more mention rate in category-relevant prompts), AI share-of-voice (your brand's share of mentions versus competitors), brand visibility score (when your brand is named in AI text even without a link), and query coverage breadth (how many of your core topic prompts your brand appears in).