The On-Page AEO Checklist

Perplexity, ChatGPT, Claude, and Google's AI Overviews are reshaping how users find information, and the brands that earn visibility in AI-generated answers look very different from the ones that dominated the traditional blue-link era.

The good news for AEOs and SEOs? The fundamentals of on-page optimization still matter; you just need to evolve them.

On-page AEO is how you make that evolution. It's the practice of structuring, formatting, and optimizing individual webpages so that LLMs and answer engines can easily extract, trust, and cite your content. And because you have complete control over your own pages, it's the most direct lever you have to influence how AI engines see your brand.

This guide walks through exactly what that actually looks like: how to structure content for AI extraction, implement the schema that matters most, optimize for AI crawlersCrawlers
A crawler is a program used by search engines to collect data from the internet.
Learn More, and build a unified strategy that drives visibility across both traditional and AI-powered search. Put these tactics into practice with our bonus downloadable on-page AEO checklist that breaks down exactly what to do and when.

What is on-page AEO?

On-page AEO is the strategic process of formatting, structuring, and optimizing webpage content so that LLMs and answer engines can easily crawl, extract, understand, and cite your brand in their generated responses.

Think of it as the natural evolution of on-page SEO. While traditional on-page optimization focuses on ranking URLs in a list of blue links through keyword densityKeyword Density
Keyword density tells you how often a search term appears in a text in relation to the total number of words it contains.
Learn More and backlinksBacklinks
Backlinks are links from outside domains that point to pages on your domain; essentially linking back from their domain to yours.
Learn More, on-page AEO focuses on providing clear, concise, and highly structured answers that AI models trust enough to use as primary sources.

So, congratulations, if you have a strong foundation in SEO, you’re already on the right track. A lot of the groundwork for AEO overlaps with the traditional optimization tactics you’ve been using. That said, this downloadable on-page optimization checklist focuses specifically on the signals and formatting requirements that dictate whether an AI model chooses your content over a competitor's. For a deeper look at on-page SEO and how it lays the foundation for on-page AEO, take a look at our comprehensive on-page SEO guide.

On-page optimization vs. off-page optimization: What’s the difference?

To fully grasp on-page AEO strategies, you need to understand the relationship between on-page and off-page optimization in the context of AI search. Both are critical, but they serve different functions in the AI discovery ecosystem.

On-page optimization refers to all the changes and improvements you make directly to your website to improve visibility. This includes your content structure, entityEntity
An entity is a thing/concept that search engines and AI models can identify and relate to other entities, forming the foundation of semantic search.
Learn More clarity, technical health, internal linking, schema markupSchema Markup
Schema markup is structured data added to web pages that tells search engines what content means, enabling rich results and enhanced search features.
Learn More, and page speed. It is the layer of search visibility that you have complete control over.

Off-page optimization refers to the actions taken outside of your website to impact your authority and trust signals. In traditional SEO, this largely meant earning backlinks. In the world of AEO, off-page optimization is much more complex. AI answer engines weigh earned media links along with unlinked brand mentions, third-party citations, and your presence on forums like Reddit, Quora, or G2 much more heavily than traditional search algorithms did.

While this checklist focuses exclusively on on-page AEO, off-page AEO is critical for maximizing your AI visibility. A well-optimized page won’t be cited by an AI engine if the brand itself doesn’t have a strong reputation for off-page authority and trust. Here’s a quick breakdown of how those priorities differ in the AI era.

On-page AEO priorities:

• Content chunking and structure
• Entity definition and consistency
• Schema implementation and structured data
• Direct answerability of user queries
• AI crawler accessibility and rendering

Off-page AEO priorities:

• Unlinked brand mentions across authoritative publications
• Positive sentiment in third-party reviews
• Presence in user-generated content communities and forums
• Digital PR and expert quotes in industry roundups
• Traditional high-quality backlinks

You need both to succeed. But if you get the on-page piece right, it’s a lot easier for AI engines to connect the dots between your off-page authority and your on-page answers.

Why is on-page optimization important for AI search?

On-page optimization is the only layer of AI search where brands have complete control over the conversation. You can’t force a third-party publisher to mention your brand, but you can control how your technical architecture and content structure present information to an AI crawler.

AI engines read and chunk pages differently from traditional crawlers. Traditional search bots scan for target keywords, assess the backlink profile, and rank the page based on relevance and authority. AI models break down your content into semantic chunks, mapping entities and relationships to answer complex, multi-part questions.

This creates a completely new traffic and visibility pattern. Users aren’t clicking through multiple search results to synthesize their own answers. The AI does the synthesis for them. If your on-page content isn’t formatted in a way that the AI can easily extract and cite, you won’t appear in the generated response, and that content will essentially be invisible.

How on-page AEO relates to on-page SEO

Before we dive into the specific on-page AEO strategies, we need to address the overlap. On-page AEO isn’t replacing on-page SEO. It’s building on it. The foundational practices of keywordKeyword
A keyword is what users write into a search engine when they want to find something specific.
Learn More optimization, header structure, internal linking, content depth, and author signals are still the bedrock of digital visibility.

When you optimize a page for specific target keywords or topic areas, you’re making it easier for Google to parse and understand your content, and you’re also teaching the AI model which topics and entities your page covers.

The core difference lies in intent and extraction. On-page SEO often focuses on keeping a user on the page through long-form narratives and extensive context. On-page AEO focuses on delivering immediate, direct answers because the goal of an answer engine is to provide the answer a user needs quickly, not endless context to introduce their target topic.

On-page AEO strategies for content

Content is the fuel for AI answer engines. But not all content is created equal in the eyes of an LLM. To earn citations, your content must be structured specifically for machine comprehension.

1. Write for answerability

If your content doesn’t directly answer the questions your target audience is asking, it won’t be cited. Plain and simple. Writing for answerability means front-loading your most valuable information.

For example, if you work for a healthcare provider and you’re creating content explaining the differences between an FSA and an HSA, you shouldn’t bury the table breaking down their differences in the last paragraph. You should frontload that information and ensure it’s immediately following the relevant header copy. You want to provide a tight, definitive answer that an AI model can lift and cite without needing to parse through hundreds of words of conversational filler.

Another key to answerability is to use question-based headings that mirror the queries users type into AI prompts. If you’re writing a guide about website migrations, use an H2 like How long does a website migration take? and immediately follow it with a bolded, direct answer.

Finally, formatting makes a big difference in making it easier for LLMs to parse your content. Definition blocks, key takeaway boxes, and bulleted summaries, and similar formats in your articles signal that you synthesized the complex information into a digestible format, which is exactly what the AI is trying to do for the end user. Ultimately, it makes it easier for LLMs to take your content word-for-word and include it in their reply.

2. Structure and chunk content for AI extraction

Content chunking is the practice of breaking down information into small, distinct, and logically organized sections that can be understood independently of the surrounding text.

While traditional SEO values comprehensive, long-form content, AI models process information in chunks. If your page is a massive wall of text without clear structural breaks, the AI will struggle to identify the most relevant facts.

To optimize for chunking brands should:

• Rely heavily on HTML formatting
• Use bulleted lists to break down processes or features
• Use numbered lists for step-by-step instructions
• Use HTML tables to present data, comparisons, and specifications—AI models excel at reading and extracting data from properly formatted tables

A good way to ensure you’re chunking your content is to strive to make every section stand on its own. If an AI engine extracts a single paragraph from your page to use in an AI Overview, that paragraph needs to make sense without the preceding context.

That’s why it’s important to always specify the exact entity or topic you’re referring to and avoid using ambiguous pronouns like this process or these tools at the beginning of a section.

3. Prioritize originality, proprietary data, and primary sources

Generic listicles and rehashed industry advice don’t get cited or mentioned by AI answer engines. LLMs are already trained on tons of generic information; the last thing they need is another generic definition of digital marketing. They need your website for what they can’t generate themselves: original data and human experience.

Creating unique content based on proprietary data is the most effective way to establish authority and force AI models to cite you. If you conduct an original survey, analyze internal customer data, or publish a proprietary benchmark report, you become the primary source for that information. When a user asks an AI engine for statistics related to your industry, the AI has no choice but to pull your original data and cite your brand.

Lean into expert quotes, detailed case studies, and proprietary research. If your web team solved a complex technical issue, document the exact process with real data points. This level of specificity and originality is something AI can’t replicate.

4. Focus on entity clarity and consistency

AI models don’t think in keywords in the same way traditional search algorithms do. They think in entities. An entity is a distinct, well-defined concept, person, organization, or thing that can be uniquely identified and linked to other entities.

To optimize for AEO, you need to shift your focus to entity clarity. That means naming things consistently across all your webpages. If you refer to your product as enterprise marketing software on the homepageHomepage
A homepage is a collection of HTML documents that can be called up as individual webpages via one URL on the web with a client such as a browser.
Learn More, do not call it a digital optimization tool on the pricing page. Pick a primary entity and stick to it.

Think of it as trying to make your content as understandable and consistent as possible. Define industry jargon and acronyms upon first use instead of assuming an AI will automatically understand and translate them. Especially in quickly evolving industries like AI search, the AI might not be completely familiar with which acronym is most popular.

Finally, it’s critical to treat your internal linking strategy as a way to reinforce how entities relate to one another. For instance, when you link from a blog post to a product page, use exact-match anchor textAnchor Text
An anchor text is the text displayed on a website for a given link.
Learn More that clearly defines the entity you are linking to. This helps the AI build a semantic map of your website and understand how your different topics relate to one another.

On-page AEO strategies for technical health

You can write the most brilliant, answer-ready content in the world, but if the AI bots can’t access or render it, you won’t get cited, and at worst, LLMs might begin to see your site and brand as unreliable. Technical AEO, again, is very similar to technical SEO, but the focus shifts heavily toward ensuring machine readability. Here are the technical AEO strategies we recommend.

1. Implement structured data and schema for AI engines

Schema markup is the universal language of search and answer engines. It translates your content into a highly organized data format that machines can instantly process.

For AEO, implementing JSON-LD schema is non-negotiable. While traditional search engines use schema to generate rich snippetsRich Snippets
Special result snippets in Google search results are described as rich snippets.
Learn More, AI models use schema to confidently extract facts and understand the context of your content. You’re essentially handing the AI a structured database of your webpage.

Prioritize the schema types that matter most for AEO extraction:

• Article Schema: Establishes the author, publication date, and core topic.
• FAQPage Schema: Directly maps questions to answers, perfectly aligning with AI prompt behavior.
• HowTo Schema: Breaks down processes into logical steps for easy extraction.
• Product Schema: Feeds AI engines exact pricing, availability, and specification data.
• Organization Schema: Reinforces your brand entity and connects your social profiles.
• Person Schema: Establishes the authority and credentials of your authors.
• Breadcrumb Schema: Helps AI models understand site architecture and content hierarchy.

Once you implement it, you also need to audit your schema regularly to ensure it accurately reflects the content on the page. Misaligned schema will lead bots to misunderstand your content, which is a fast way to lose trust with both search and answer engines.

2. Optimize rendering for AI crawlers

The way AI bots crawl and render the web is different from how a user’s browser loads a page. This presents a massive technical challenge for modern websites built on complex JavaScript frameworks.

Many AI crawlers, including the bots used by major LLMs, don’t execute JavaScript efficiently, and some aren’t able to execute it at all, looking strictly at the raw HTML source code. If your content, navigation, or internal linksInternal links
Hyperlinks that link to subpages within a domain are described as "internal links". With internal links the linking power of the homepage can be better distributed across directories. Also, search engines and users can find content more easily.
Learn More rely on client-side JavaScript to render, that content is literally invisible to these AI bots.

If an AI crawler can’t see your content, it can’t cite it. You need to ensure that your most important content is served via server-side rendering (SSR) or dynamic rendering. When a bot requests your page, the server should deliver a fully populated HTML document containing all the text, links, and structured dataStructured Data
Structured data is the term used to describe schema markup on websites. With the help of this code, search engines can understand the content of URLs more easily, resulting in enhanced results in the search engine results page known as rich results. Typical examples of this are ratings, events and much more. The Conductor glossary below contains everything you need to know about structured data.
Learn More.

If they are hitting pages but failing to extract the content, you likely have a rendering issue that needs immediate attention from your IT or web development team.

3. Optimize site speed, mobile, and Core Web Vitals

Site speed and mobile-friendliness remain critical factors for on-page AEO, just like they did for SEO. While AI bots are focused on data extraction, the platforms powering these bots still value UX. Google’s AI Overviews, for example, are deeply integrated into the core search algorithm, meaning Core Web Vitals still dictate overall visibility.

Ensure your pages load quickly, avoid render-blocking resources, and provide a seamless mobile experience. AI crawlers operate on crawl budgets just like traditional search bots. If your server takes too long to respond, the bot will abandon the crawl, leaving your newest content undiscovered.

On-page AEO strategies for crawlability

Technical health ensures your site works; crawlability ensures AI bots are actually allowed through the front door. You need an intentional and proactive strategy for managing bot access and guiding them to your most important content. Here’s how to do it.

1. Ensure AI bot accessibility

The explosion of generative AIGenerative AI
Generative AI is a class of AI that creates content like text, images, and code rather than analyzing existing data, powering tools like AI search.
Learn More has introduced countless new web crawlers. Managing your robots.txt file isn’t just about Googlebot and Bingbot anymore. Now, brands need to actively manage access for LLM data collection bots.

Most major AI providers operate multiple distinct bots, each with a different purpose. OpenAI alone operates three:

• GPTBot crawls the web to gather data for training future models.
• OAI-SearchBot crawls to surface content in ChatGPT search results.
• ChatGPT-User fetches specific URLs in real time when a user or agent retrieves a page during a conversation.

For example, you might block GPTBot to keep your content out of training data, while allowing OAI-SearchBot and ChatGPT-User so your brand still appears in ChatGPT answers and can be retrieved on demand. This same training-vs-search-vs-user pattern applies across providers.

The major AI bots you need to account for include:

• OpenAI: GPTBot (training), OAI-SearchBot (search), ChatGPT-User (user/agent retrieval)
• Anthropic: ClaudeBot (training), Claude-SearchBot (search), Claude-User (user/agent retrieval)
• Google: Google-Extended (AI training; separate from Googlebot, which handles search)
• Perplexity: PerplexityBot (indexing), Perplexity-User (user retrieval)
• Apple: Applebot-Extended (AI training; separate from Applebot)
• Meta: Meta-ExternalAgent
• Common Crawl: CCBot (training data used by many LLM providers)

You face a strategic decision at the bot-type level, not just the provider level: do you allow these bots to crawl your site, or do you block them? Blocking them protects your intellectual property from being used to train future models without compensation. But blocking them also guarantees that you won’t appear as a cited source in their answer engines.

For most enterprise marketing teams focused on digital growth and visibility, the right play is usually: block training bots if IP protection is a priority, allow search and user-facing bots so you remain visible and citable. If you block PerplexityBot, you’re forfeiting all the potential brand visibility within the Perplexity platform. Work with your IT and legal teams to establish a governance policy, but understand that visibility in the AI era requires crawler access.

2. Maintain sitemaps for AI discoverability

XML sitemaps are just as critical for AEO as they are for SEO, but their strategic application is shifting. An XML sitemap serves as a blueprint for all crawlers, telling them exactly where to find your content and when it was last updated.

Unlike traditional SEO sitemaps, which often focus on comprehensive URL discovery and indexing every possible page, AEO sitemaps should be highly curated. You want to direct AI crawlers to your most authoritative, structured, and high-quality answers.

For most enterprise sites, the cleanest approach is a sitemap index that references multiple segmented sitemaps by content type—separate files for original research, pillar content, FAQ sections, and product pages. This structure makes it easier to see which content types of AI bots are crawling, but it can only be done by making server logs accessible.

If your site is on the smaller side or if your content is essentially one type, a single well-maintained XML sitemap is ideal. No matter which structure you choose, it’s important to keep sitemaps dynamically updated, free of dead links and redirect chains, and referencing only canonical URLs. Every wasted crawler request is one that’s not getting spent on the content you really want cited.

3. Reinforce entity and topic authority with internal linking

Internal linking is how you teach AI models about the relationships between your content. LLM bots navigate between pages using internal links to build a comprehensive understanding of your domain's expertise.

A strong topic cluster strategy makes it incredibly easy for LLMs to parse and summarize your content. Build comprehensive pillar pages that cover a broad topic, and use descriptive anchor text to link out to highly specific subtopic pages.

This clustered approach proves to the AI that you’re not just answering a single question, but that you have a deep, systemic knowledge of the subject as a whole. When the AI model needs to generate a complex response, it’ll look for domains that demonstrate this interconnected topic authority.

On-page AEO strategies for authority

In traditional search, authority was heavily reliant on inbound links. In AI search, authority requires a multidimensional approach to trust signals. You need to prove to LLMs that your content is credible, accurate, and created by recognized experts.

1. Prioritize author and entity signals

AI models evaluate the credibility of the person and organization behind the content. Google’s E-E-A-T (experience, expertise, authoritativeness, trustworthiness) framework matters more now than ever.

An AI-friendly author bio should do more than share a fun fact about the writer. It needs to clearly state their professional credentials, years of experience, and specific areas of expertise. Link the author bio to their external entity profiles, such as their LinkedIn page or industry association profiles, to help the AI verify their identity.

Implement Person and Organization Schema to solidify these relationships in the code. Your About Us page should be heavily optimized to define your corporate entity, linking out to your official social channels, third-party review sites, and major parent companies or subsidiaries. Entity consistency across the entire web is the foundation of AEO trust.

2. Focus on outbound linking to build trust

It might feel counterintuitive, but linking out to other websites is a powerful on-page AEO strategy. Answer engines are built on the concept of citation networks. When you link out to highly authoritative external sources, primary research, and official documentation, you signal to the AI that your content is well-researched and integrated into the broader knowledge graph.

Of course, it’s important to remember not to link to competitors, but instead link to academic institutions, government databases, and recognized industry standards. This outbound linking builds a web of trust that elevates the authority of your own content and brand.

3. Develop authority through original content

We touched on this in the content section, but it bears repeating from an authority perspective: your unique point of view is your most defensible AEO asset.

Proprietary data, primary research, and strong editorial stances can’t be faked. When you publish a perspective that challenges industry norms, backed by your own data, you’re forcing AI engines to recognize your brand as a primary source. This is how you transition from being a website that simply repeats information to a brand that shapes the AI's understanding of the market.

How to monitor your on-page AEO

You can’t set and forget your on-page AEO strategy. The algorithms powering AI answer engines update constantly, and a seemingly minor technical change to your website can instantly crush your visibility. You need a centralized command center to track performance.

Keep an eye on your AEO success with the following metrics:

• AI citations: How often is your brand linked as a source in an AI response?
• Brand mentions: How often is your brand discussed in the text of the AI response, even without a link?
• Share of voice in AI responses: Are you appearing more frequently than your top competitors for critical industry queries?
• Brand sentiment: Is the AI model framing your brand positively, neutrally, or negatively?
• Traditional rankings: Don’t abandon Google. Traditional search still drives billions of clicks and feeds the AI models.

It is crucial to understand that AI referral traffic is not the ultimate metric for AEO, and it’s not a stand-in for organic traffic in SEO. AI search is a visibility play. The goal of an answer engine is to provide the answer without requiring a click. If your brand is cited as the definitive source directly in the chat interface, you won the interaction, even if it doesn’t register as a session in your analytics dashboard.

To effectively track your visibility, you need enterprise-grade tools. Look for enterprise AEO platforms that provide features like citation trackers, log file analyzers, and schema validators to keep an eye on everything in one place. The right platform will help you diagnose exactly why you are not being cited and surface underperforming pages that need structure optimizations.

Conductor provides unified insights across AEO, SEO, and technical performance in one platform. You can even leverage LLM apps for AEO to prompt AI tools directly for on-page analysis, provided you have the enterprise data quality to ensure you are acting on accurate information.

Where on-page AEO strategies fail

The most common pitfall is limiting your measurement to a single AI engine. According to our research into how AI engines choose and cite sources, ChatGPT, Perplexity, Google AI Overviews, Google AI ModeAI Mode
AI mode is a search feature using AI to provide comprehensive answers by synthesizing information from multiple sources into direct responses.
Learn More, and Gemini have meaningfully different citation source preferences, even when answering the same question with the same intent. That means measuring your visibility on one engine tells you almost nothing about how you're performing on the others, and your audience isn't using just one. They're likely split across several of them.

Another pain point for on-page AEO comes from deploying schema markup without quality content underneath. Schema isn’t a magic trick. If you wrap a generic, unhelpful paragraph in FAQ Schema, the AI will still recognize the content as poor quality and ignore it.

Just like in traditional search, the goal of LLMs is to provide users with the best, most complete, and easily digestible answer possible. That’s why creating bulleted lists and FAQ sections can be so impactful. But creating a list of 50 disconnected, keyword-heavy questions at the bottom of a page is an outdated SEO tactic that harms AEO. AI models favor natural language and logical flow. It’s much better for long-term visibility and authority to answer the questions naturally within the context of the page structure.

Ensuring that natural language and flow are why it’s so critical not to over-rely on generic AI to scale your content production and leverage a human-in-the-loop approach to AI content creation.

Using basic prompts to churn out hundreds of generic blog posts is a fast track to irrelevance. Content quantity and velocity mean absolutely nothing when the underlying content lacks original insight. AI engines will not cite AI-generated fluff; they are looking for human expertise and unique, original insights that generic AI just can’t replicate.

Finally, don’t treat AEO as a replacement for SEO. Billions of searches still happen on traditional search engines every day. If you completely pivot to AEO and neglect your organic search presence, you risk abandoning a massive portion of your core audience. Success is about integrating SEO and AEO into a unified strategy, not choosing one over the other.

On-page AEO in review

The transition to AI-driven discovery requires a fundamental shift in how marketers and digital teams structure and optimize web content. On-page AEO is about translating your brand's expertise into a format that machines can instantly process, trust, and cite.

By focusing on content chunking, direct answerability, entity consistency, and robust technical health through schema and rendering optimization, you give your website the best possible chance to dominate the new era of search. Don’t neglect your traditional SEO foundations. Ensure every new page you publish is built to satisfy both the human reader and the AI crawler.