SEO Audit Checklist AEO Teams Can Use Together

An SEO audit checklist AEO teams can use together checks whether your site can be crawled, understood, ranked and cited by both search engines and AI answer tools. It brings technical SEO, content quality, brand authority and measurement into one workflow, so your team can prioritise shared fixes instead of maintaining separate workstreams. Start with the highest-impact checks below, then assign an owner and a pass condition to each one.

This checklist covers Google and Bing alongside ChatGPT Search, Perplexity, Claude, Gemini and Google AI Overviews. Some AI systems use live web search; others can also draw on model training or other sources. Their systems and policies differ, so treat AI visibility as something to test and monitor, not a result that a technical change can guarantee. If you need a repeatable way to track prompts and citations alongside your existing work, see SearchFIT’s AI search resources and pricing.

How to use this SEO audit checklist AEO teams share

Run the audit on a defined set of important pages, not just the homepage. Include service or product pages, high-value guides, category pages, comparison content and pages that already attract organic visits. For each check, record the URL or issue, evidence, priority, owner, due date and a pass condition. A finding without an owner is only an observation.

Use this simple priority order:

1. Eligibility: Can the right crawler fetch the page, and can the page be indexed?
2. Comprehension: Is the important information clear in the page source and structure?
3. Evidence: Are claims accurate, specific and supported by first-hand expertise or reliable sources?
4. Recognition: Do credible sources consistently describe the brand and its offering?
5. Measurement: Can you tell whether the changes improve search performance or AI visibility?

A combined audit does not mean every SEO and AEO check is identical. It means you share the crawl, content, authority and reporting work where the goals overlap, then add checks where answer engines behave differently. A comparison of SearchFIT and agency approaches may help teams decide how to organise ongoing tracking and implementation.

Stage 1: Technical access and crawling

Technical access is the first gate. A useful page cannot be selected as a source if a crawler cannot fetch it, or if important information is missing from the version the system reads. Check rules and rendering on real pages, including templates and subdomains.

• Check indexation and canonical tags on priority URLs. Confirm each page you want found returns the intended status code, has a self-referencing or otherwise correct canonical, and is not accidentally blocked by noindex; these are core SEO eligibility checks and help keep answer engines from encountering duplicate or contradictory versions.
• Review robots.txt for both search and AI search crawlers. Inspect the live file for rules that block important pages, assets or bots; allow the crawlers you want to access your content, and make the decision to block training crawlers separately from search crawlers.
• Know which OpenAI crawler does what before changing rules. OpenAI distinguishes OAI-SearchBot, used for search features, from GPTBot, associated with model training; review OpenAI’s bot documentation and check current guidance before editing directives.
• Check the equivalent policies for other platforms. Verify the current crawler names and rules for the services you care about rather than assuming one bot setting controls all AI products; policies can differ between live search, model training and other uses.
• Test a page with JavaScript disabled or inspect its raw HTML. Make sure the main answer, product details, links and headings are present in the fetched source, because content added only after client-side scripts run may be harder for some crawlers to retrieve reliably.
• Compare rendered and raw page content. Look for mismatches such as a different title, missing price, hidden text or incomplete schema; a page that looks complete in a browser can still present a thinner version to a crawler.
• Check response codes, redirects and internal links. Fix loops, chains, broken destinations and unnecessary redirects on important pages; clean paths help crawlers reach useful content and make it easier for people to navigate.
• Confirm the XML sitemap contains canonical, indexable URLs. Remove redirected, blocked or obsolete pages, keep the sitemap current, and submit it through the search engine tools your organisation uses; a sitemap supports discovery but does not guarantee indexing.
• Review mobile usability and page experience. Test the site on a phone and check layout, interaction and loading issues; a usable page supports visitors as well as search engines evaluating page experience.
• Measure performance rather than guessing at a speed target. Use field and lab data to find slow templates, oversized assets and unstable layouts, then prioritise fixes that affect real users; no single speed score guarantees an AI citation.
• Inspect access controls and consent behaviour. Check whether a bot or visitor is served a login wall, regional block, cookie overlay or age gate that hides the actual answer; make sure restrictions reflect business and privacy requirements, not accidental configuration.
• Treat /llms.txt as an optional experiment, not an indexation requirement. If you publish one, make it accurate, maintained and useful as a concise guide to key pages; the proposal is described by Answer.AI, but it should complement, not replace, standard site architecture, HTML content and sitemaps.

Stage 2: Page structure and entity clarity

Search systems need to understand what a page is about, who created it and how its subject relates to your brand. Clear headings, consistent names and structured data help express those relationships. Markup can clarify visible facts, but it cannot make unsupported claims true or guarantee a rich result.

• Give every important page one clear purpose. State the audience, need and subject in the title, main heading and opening; a page trying to serve several unrelated intents is harder to navigate and summarise.
• Use descriptive titles and headings. Make the title and H1 specific to the page, then use H2s and H3s to break the topic into logical questions or steps; avoid repeating keywords where a plain description is clearer.
• Check heading hierarchy and page landmarks. Ensure headings represent the actual content order and that navigation, main content and footer are distinguishable; this improves accessibility and makes the page’s structure easier to interpret.
• Describe the organisation consistently. Align the company name, product names, category, location and key facts across the website and official profiles; inconsistent naming can make it harder to distinguish your brand from similarly named entities.
• Make author and reviewer information verifiable. Where expertise matters, identify the author and explain relevant experience or review responsibility, with links to genuine profile pages; visible accountability builds reader trust and gives context to the content.
• Add structured data that matches visible page content. Use the appropriate Schema.org type for the page and validate the markup; structured data can help machines interpret facts but is not a shortcut to rankings or citations.
• Connect the right entities in JSON-LD. Where accurate, use Organization, Person, Product or other relevant properties to identify the organisation, authors and products; only include sameAs links to official profiles that genuinely represent the same entity.
• For products, keep commercial facts aligned. Check that visible product name, SKU, availability, price, currency and return information match the structured data and current catalogue; conflicting versions confuse shoppers and systems.
• Validate markup after template or catalogue changes. Run representative URLs through relevant validators and inspect rendered output; a template update can silently remove or duplicate schema across many pages.
• Avoid marking up content that users cannot see. Hidden or misleading structured data can undermine trust and may violate search engine guidelines; markup should describe the page, not invent a better one.

Stage 3: Content that answers and can be cited

A page should satisfy the reader before it tries to impress a crawler. Put the central answer where a reader can find it quickly, then support it with explanation, evidence and useful detail. This structure can serve featured snippets, organic results and AI retrieval without reducing a complex subject to a simplistic answer.

• Answer the main question near the beginning. In the opening paragraph or first relevant section, give a direct response in plain language; readers and answer engines should not have to work through a long preamble to discover the point.
• Make the opening answer stand on its own. Define the subject, state the key qualification and give the practical takeaway without relying on a previous paragraph; a self-contained passage is easier to quote accurately.
• Match the format to the search intent. Use a guide for a process, a comparison for a choice, a product page for a purchase and a clear definition for a basic question; format mismatch leaves the user’s real need unresolved.
• Cover the subquestions that help complete the task. Use customer interviews, sales questions, support tickets and search query data to identify follow-ups; include relevant answers rather than adding sections solely to increase word count.
• Use question-led headings when they improve navigation. A heading such as “How do I compare these options?” tells readers what follows, but do not force every heading into a question or repeat the same wording unnaturally.
• Break long explanations into meaningful sections. Keep each section focused on one idea, and use numbered steps for sequences or bullets for grouped points; modular writing helps users scan and helps systems locate relevant passages.
• Use tables for genuine comparisons. Compare like with like, label columns clearly and ensure the information is available as text rather than only inside an image; tables are useful when they make a decision easier, not as decoration.
• Support important claims with evidence. Link to primary research, official documentation or clearly identified first-hand data, and explain what the evidence does and does not establish; precise sourcing makes claims easier to verify.
• Attribute every statistic and quote. Name the source and link to it where possible, include dates or context when they affect interpretation, and do not turn one benchmark into a universal promise.
• Include original expertise where you have it. Add a documented process, a real example, a tested observation or a clearly explained dataset; distinctive first-hand material gives the page something more useful than a paraphrase of competing guides.
• Use claims that can be checked. Replace broad statements such as “the best platform” with the criteria, evidence and limits behind the comparison; unsupported superlatives are difficult for readers to trust and systems to verify.
• Cite external sources in context. A Princeton GEO benchmark reported that certain content changes, including adding relevant citations and statistics, improved visibility in its tested generative settings; read the study discussion and critique at this overview of the Princeton GEO study before treating its findings as a forecast for your site.
• Front-load the most useful information without hiding nuance. CXL’s analysis of AI Overview citations found many cited passages in the early part of source pages; review its analysis of AI Overview citation sources for context, then test whether your own key material is easy to find.
• Define terms and abbreviations on first use. Explain AEO as Answer Engine Optimization or spell out a technical term before relying on its abbreviation; clear language helps readers outside the specialist team.
• Make comparisons fair and transparent. State the evaluation criteria, date and relevant limitations, and give competitors a factual description; fair comparisons are more useful than pages built only to declare a winner.
• Keep essential information in crawlable text. Do not put crucial specifications, instructions or claims only in a screenshot, video or downloadable file; provide a readable text version and use media as a supplement.
• Add useful internal links at the point of need. Link to the next step, related explanation or relevant product page with descriptive anchor text; a helpful site path supports visitors and helps crawlers discover related pages.

A large-scale study reported by Conductor on AI Overviews and organic rankings found that many cited URLs were outside the organic top ten. That does not mean rankings are irrelevant, or that every page can earn a citation regardless of quality. It is a reminder to audit both ranking performance and the clarity, relevance and evidence of pages that answer important queries.

Stage 4: Freshness, trust and brand authority

AI answers can draw from your site and from other sources. Your own page is only one part of how a brand is understood. Build a consistent, credible footprint, and make sure important facts remain current. Do not manufacture mentions or treat a presence on any one platform as a guaranteed ranking signal.

• Check dates and facts on pages where recency matters. Review prices, product capabilities, policies, regulations, integrations and dated claims; stale details can mislead customers even when the page continues to rank.
• Update a page when the information changes, not just the timestamp. Record what changed and revise the relevant explanation, examples and sources; changing a visible date without meaningful edits can misrepresent the page’s freshness.
• Keep published and modified dates consistent. Where you display dates or use structured data, make sure they reflect the real editorial history; accurate dates help readers understand whether guidance is current.
• Give every important claim an accountable owner. Assign a subject expert or editor to review content that could affect a buying, financial, health or compliance decision; clear responsibility makes maintenance sustainable.
• Check your official brand profiles. Verify names, descriptions, links, product details and leadership information across key directories and social profiles; consistent public facts make it easier to identify the real organisation.
• Look for independent evidence of your work. Review legitimate customer feedback, trade coverage, partner pages, community discussions and expert references; address inaccurate information professionally rather than attempting to seed artificial praise.
• Track brand mentions as well as backlinks. Record where your brand is discussed, what products it is associated with and whether the context is positive, neutral or critical; mentions can reveal reputation and positioning gaps that link reports miss.
• Use buyer questions to check how AI systems describe you. Ask consistent questions about your category, product and competitors across the answer engines you monitor, then save the prompt, date, response and cited sources; this gives you a repeatable baseline rather than an anecdote.
• Investigate incorrect or missing descriptions at the source. If an AI answer repeats an outdated feature or confuses your brand with another, locate the underlying pages and profiles that may contribute to the error; improve authoritative information instead of trying to game a response.
• Earn references by publishing material worth referencing. Original research, transparent methodology, useful tools and expert commentary can give others a reason to cite your work; outreach should be relevant and honest, not a request for unsupported endorsements.

Stage 5: Measurement and reporting

Organic rankings, clicks and conversions remain important, but they do not show every way people encounter a brand. Add AI visibility measures that match your goals, keep their limitations visible, and connect observations to actions. Search systems do not always expose a complete or stable record of what influenced an answer.

• Set a baseline before making changes. Record organic impressions, clicks, ranking groups, conversions, important landing pages and current AI answer visibility; a baseline gives the team a fair comparison later.
• Group tracking prompts by customer task. Separate discovery, problem definition, comparison, product evaluation and support questions; this reveals which parts of the journey are covered and where a brand is absent.
• Track presence, citation and accuracy separately. Note whether the brand appears, whether a source URL is cited, and whether the description is correct; a mention without a link is different from a cited page, and neither necessarily reflects traffic.
• Keep the prompt set stable enough to compare. Use a documented set of representative queries and record when you change it; otherwise, a shift in results may reflect different questions rather than a change in visibility.
• Check several engines, not one favourite. Results can differ between ChatGPT Search, Perplexity, Claude, Gemini and Google AI Overviews; note the platform, date, query and available sources for each observation.
• Use Search Console and analytics for the questions they can answer. Review organic impressions, clicks and landing-page behaviour alongside conversions; do not label all direct or unassigned traffic as AI referrals without evidence.
• Create an AI referral segment in GA4. Define a channel or report using known referral domains, maintain the list as services change, and test that visits are classified correctly; referral traffic captures measurable visits, not every AI-assisted discovery.
• Separate visibility metrics from business outcomes. Track citations and share of voice as diagnostic indicators, then compare them with qualified visits, leads, sales or assisted conversions; more mentions do not automatically mean more revenue.
• Annotate site and content changes. Record technical releases, content revisions, campaign launches and major platform changes alongside reporting; annotations help explain movements and avoid attributing every fluctuation to one edit.
• Review results on a regular cadence. Bring SEO and content owners together to review issues, assign actions and close the loop; a shared review prevents duplicate tickets and helps resolve conflicts between teams.
• Use a monitoring tool when manual checks stop being practical. Compare platforms, prompt coverage, citation reporting and audit needs before choosing a service; SearchFIT’s pricing page outlines its plans, while the SearchFIT blog has further guidance on AI visibility measurement.

Audit summary: what to check and what a pass looks like

Turn audit findings into one shared work plan

A checklist only helps when findings become fixes. Start with blocked or broken high-value pages, then prioritise issues that affect several URLs or important customer journeys. For each action, write the problem, evidence, impact, owner and a clear test for completion. A change such as “improve AEO” is not a useful ticket; “put the current product eligibility criteria in crawlable text on the comparison page and verify the source and rendered versions” is.

Keep a single backlog with labels for technical access, content, structure, authority and measurement. Some work will benefit both traditional search and AI answers, while other actions will be specific to one channel. Review outcomes against the original baseline and avoid claiming that one edit caused a change unless the evidence supports that conclusion.

The core principle is straightforward: make valuable information accessible, clear, accurate and easy to verify, then measure whether the right people and systems find it. Use this SEO audit checklist AEO framework as a shared starting point, and adapt the checks to your site, category and risk level.