The 34 AEO Scoring Factors: Complete Audit Methodology

How the 6 Categories Break Down

Every AEO audit score is composed of six weighted categories. Each category targets a distinct dimension of AI engine readability and citation potential. Here is how they contribute to your overall score:

Now let us examine each factor within every category. For each factor, you will learn what it measures, why it matters for AI visibility, and specific steps to improve it.

Content Structure & Extractability (30%)

Content structure is the most heavily weighted category in the AEO audit. AI engines do not just read your words — they parse your formatting to decide whether your content can be cleanly extracted into an answer. Well-structured content is the difference between being cited and being ignored.

A1 — Answer-First Format (Weight: 0.15)

What it measures: Whether your content leads with a direct answer before expanding into detail. AI engines prioritize content that provides the answer in the first paragraph or two, rather than burying it after a long preamble.

Why it matters: When an AI engine scans a page to answer a query, it often pulls from the opening content. Pages that start with background context or lengthy introductions get passed over in favor of pages that answer immediately. This mirrors how featured snippets work in traditional search, but it is even more critical for AI citations because AI models are trained to extract the most concise, relevant answer.

How to improve: Start every page and section with a direct answer to the question the reader likely asked. Use the inverted pyramid approach: lead with the conclusion, then provide supporting detail. Avoid introductions like "In this article, we will explore..." and instead jump straight to the answer.

A2 — Atomic Paragraphs (Weight: 0.10)

What it measures: Whether your paragraphs are focused on a single idea and kept to a reasonable length. AI engines extract better from short, self-contained paragraphs than from dense walls of text.

Why it matters: AI models parse content in chunks. When a paragraph covers multiple ideas, the model struggles to isolate the relevant piece. Atomic paragraphs — those that convey one clear idea each — are easier for AI to extract, quote, and attribute correctly.

How to improve: Keep paragraphs to 2-4 sentences. Each paragraph should address one concept. If you find yourself using transition phrases like "Additionally" or "On the other hand" within a paragraph, that is usually a signal to split it into two.

A3 — Question-Based Headings (Weight: 0.08)

What it measures: Whether your headings are phrased as questions that match how users query AI engines. Headings like "What is AEO?" or "How does schema markup affect AI visibility?" directly match conversational search patterns.

Why it matters: AI engines map user queries to headings to find relevant sections. A heading that exactly matches a common question creates a direct path from query to answer. This dramatically increases the likelihood that your content gets cited for that specific question.

How to improve: Audit your headings and rephrase them as questions where natural. Use tools like "People Also Ask" or AI chat logs to identify the exact questions your audience is asking, then use those as H2 or H3 headings.

A4 — Fact Density (Weight: 0.10)

What it measures: The ratio of concrete, verifiable facts to filler content. AI engines prefer content that packs specific data points, statistics, definitions, and actionable information into each section.

Why it matters: AI models are trained to surface factual, specific answers. Content that is heavy on opinions or generalities without supporting data is less likely to be cited. High fact density signals to AI that your content is a reliable source worth referencing.

How to improve: Include specific numbers, percentages, dates, and named entities wherever possible. Replace vague claims like "many businesses benefit" with specific data like "73% of businesses that implemented schema markup saw increased AI citations within 90 days."

A5 — List & Step Formatting (Weight: 0.08)

What it measures: Whether your content uses structured lists (bulleted, numbered) and step-by-step formatting where appropriate. AI engines extract list items and procedural steps particularly well.

Why it matters: When users ask "how to" questions, AI engines look for numbered steps. When they ask for comparisons or features, AI looks for bulleted lists. Content formatted this way maps directly to the structured answers AI models generate.

How to improve: Convert any procedural content into numbered steps. Turn feature lists, benefit lists, or comparison points into bulleted lists. Use HTML list elements (ul, ol) rather than manual dashes or asterisks so the structure is machine-readable.

A6 — Summary / TL;DR Blocks (Weight: 0.10)

What it measures: Whether your content includes summary sections, key takeaways, or TL;DR blocks that condense the main points into a compact format.

Why it matters: Summary blocks are citation gold for AI engines. When an AI needs to provide a concise answer, a pre-written summary is far easier to cite than a long article that the AI would need to synthesize on its own. Pages with explicit summaries are cited more frequently and more accurately.

How to improve: Add a "Key Takeaways" or "TL;DR" section near the top of long-form content. Summarize your main points in 3-5 bullet points. Each bullet should be a standalone, quotable statement.

A7 — Concise Definitions (Weight: 0.08)

What it measures: Whether your content provides clear, quotable definitions for key terms and concepts. AI engines frequently need to define terms in their responses and prefer sourcing from pages that offer clean definitions.

Why it matters: "What is [term]?" is one of the most common query patterns in AI search. If your page defines a term clearly in 1-2 sentences, AI can quote you directly. Vague or overly complex definitions get skipped in favor of more concise sources.

How to improve: For every key term on your page, provide a clear one-to-two-sentence definition. Use the pattern: "[Term] is [definition]." Place definitions near the beginning of the relevant section so AI can find them quickly.

A8 — Comparison Content (Weight: 0.06)

What it measures: Whether your content includes structured comparisons, such as tables, side-by-side lists, or explicit "X vs Y" sections. AI engines frequently need to compare options when answering user queries.

Why it matters: Comparison queries like "AEO vs SEO" or "best tools for X" are among the most common AI search patterns. Pages with pre-structured comparison content provide ready-made answers that AI can cite directly rather than attempting to synthesize comparisons from multiple sources.

How to improve: Add comparison tables or structured "pros vs cons" sections where relevant. Use HTML table elements for data comparisons. Include explicit "X vs Y" headings that match common comparison queries in your niche.

A9 — Natural Language Tone (Weight: 0.08)

What it measures: Whether your content is written in a natural, conversational tone that matches how people ask questions and how AI engines formulate responses.

Why it matters: AI-generated answers sound conversational. Content written in stilted, overly formal, or keyword-stuffed language is harder for AI to weave into a natural response. Content that already sounds like how AI "speaks" is more likely to be quoted verbatim.

How to improve: Write as if you are explaining the topic to a knowledgeable colleague. Avoid jargon without explanation. Read your content aloud — if it sounds unnatural when spoken, revise it. Use contractions and direct address where appropriate.

A10 — Content Depth (Weight: 0.17)

What it measures: Whether your content provides comprehensive coverage of the topic, addressing the full scope of what a user might need to know. This is the highest-weighted factor within the Content category.

Why it matters: AI engines prefer authoritative, comprehensive sources over thin content. A page that thoroughly covers a topic is more likely to be cited for multiple related queries. Depth signals expertise, and expertise signals trustworthiness — both of which increase citation probability.

How to improve: Cover all subtopics that a user might search for within your main topic. Use semantic analysis tools to identify related questions and concepts you may have missed. Aim for at least 1,500 words for informational content, with deeper pages reaching 3,000 or more when the topic warrants it.

Schema & Structured Data (20%)

Schema markup is the most direct way to communicate with AI engines in their own language. JSON-LD structured data tells AI exactly what your page is about, who wrote it, and how to categorize it. Sites without schema markup force AI to guess — and guessing leads to omission.

B1 — Organization Schema (Weight: 0.15)

What it measures: Whether your site includes valid Organization schema markup that identifies your business, including name, logo, contact information, and social profiles.

Why it matters: Organization schema is the foundation of entity recognition for AI. When AI engines encounter your business name, they need schema to disambiguate you from other entities with similar names. Without it, AI may confuse your business with competitors or simply fail to identify you as a distinct entity.

How to improve: Add JSON-LD Organization schema to your homepage with your business name, legal name, logo URL, founding date, social media links (sameAs), and contact information. Ensure the information matches your Google Business Profile and other directory listings exactly.

B2 — FAQ Schema (Weight: 0.15)

What it measures: Whether your pages include valid FAQPage schema markup for question-and-answer content.

Why it matters: FAQ schema directly maps your content to the question-answer format that AI engines use to generate responses. When an AI engine encounters a question that matches your FAQ schema, it has a structured, pre-formatted answer ready to cite. This is one of the most impactful schema types for AI visibility.

How to improve: Identify the top 5-10 questions your customers ask and add them as FAQ schema on the most relevant page. Ensure the schema answers match the visible content on the page. Use concise, factual answers in the schema.

B3 — Article Schema (Weight: 0.15)

What it measures: Whether blog posts, guides, and informational content include Article (or NewsArticle, BlogPosting) schema with headline, author, publication date, and description.

Why it matters: Article schema helps AI engines understand the context and credibility of your content. It connects content to a specific author and publication date, which feeds into freshness and authority evaluations. AI engines use article metadata to decide recency and relevance.

How to improve: Add Article schema to every blog post and informational page. Include headline, author (linked to a Person or Organization schema), datePublished, dateModified, and publisher fields. Keep dateModified accurate when you update content.

B4 — Product Schema (Weight: 0.10)

What it measures: Whether product or service pages include Product schema with name, description, price, availability, and review information.

Why it matters: When users ask AI engines for product recommendations, the AI relies heavily on Product schema to compare options. Pages with complete Product schema are far more likely to be included in AI-generated product comparisons and recommendation lists.

How to improve: Add Product schema to every product and service page. Include name, description, price (with currency), availability, brand, and aggregate rating if available. For SaaS products, use the offers property to describe pricing tiers.

B5 — Author / Person Schema (Weight: 0.10)

What it measures: Whether content includes Person schema for authors, linking to their credentials, social profiles, and other published works.

Why it matters: Author attribution is a key trust signal for AI engines, particularly in YMYL (Your Money, Your Life) topics. Person schema helps AI verify that content was created by a qualified individual, which increases the content's authority score and citation likelihood.

How to improve: Create author pages with Person schema for every content creator. Include name, job title, employer, sameAs links to social profiles, and a description of credentials. Link from Article schema to the author's Person schema.

B6 — HowTo Schema (Weight: 0.10)

What it measures: Whether instructional or tutorial content includes HowTo schema with defined steps, tools, supplies, and estimated time.

Why it matters: "How to" queries are among the most common AI search patterns. HowTo schema provides AI with a pre-structured set of steps it can cite directly. Without this schema, AI must parse your content to extract steps, which introduces ambiguity and reduces citation accuracy.

How to improve: For any content that explains a process, add HowTo schema with individual step elements. Each step should have a name and description. Include totalTime if the process has a defined duration, and list any required tools or supplies.

B7 — Review Schema (Weight: 0.10)

What it measures: Whether your site includes Review or AggregateRating schema for products, services, or content.

Why it matters: AI engines use review data to assess quality and to include ratings in their recommendations. When AI suggests products or services, it often cites star ratings and review counts. Sites with Review schema provide this data in a structured format that AI can directly include in responses.

How to improve: Add Review or AggregateRating schema to pages that feature customer testimonials, product reviews, or service ratings. Ensure the schema matches visible review content on the page. Include reviewCount and ratingValue for aggregate ratings.

B8 — Schema-Content Alignment (Weight: 0.15)

What it measures: Whether your schema markup accurately reflects the visible content on the page. Mismatches between schema data and actual page content are penalized.

Why it matters: AI engines cross-reference schema with visible content to verify accuracy. If your schema says one thing but your page says another, AI models flag this as untrustworthy. Schema-content alignment is both a quality signal and a trust signal that affects how confidently AI will cite your content.

How to improve: Audit your schema markup against your visible page content. Ensure FAQ schema questions and answers match word-for-word with content on the page. Verify that Article headlines in schema match your actual H1. Update schema whenever you update page content.

Authority & Trustworthiness (20%)

AI engines do not just look at what you say — they evaluate whether you are a credible source. Authority signals help AI decide whether to cite your content or skip it in favor of a more established source. Building authority is a long-term investment that pays compounding returns in AI visibility.

C1 — Author Credentials (Weight: 0.15)

What it measures: Whether content is attributed to identifiable authors with demonstrated expertise in the subject matter. This includes author bios, credentials, links to other published work, and professional affiliations.

Why it matters: AI engines increasingly evaluate E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness). Content from a credentialed expert in the field carries more weight than anonymous or unattributed content. This is especially critical for YMYL topics where incorrect information could cause harm.

How to improve: Add detailed author bios to every piece of content. Include credentials, years of experience, and links to professional profiles. Create dedicated author pages that aggregate all content by each author. Link to external publications or speaking engagements where possible.

C2 — About / Contact Pages (Weight: 0.10)

What it measures: Whether your site has accessible, detailed About and Contact pages that establish your business identity and provide clear ways to reach you.

Why it matters: About and Contact pages signal legitimacy to AI engines. A business without these pages appears less trustworthy. AI uses the information on these pages to build its understanding of who you are, what you do, and whether you are a real, contactable entity.

How to improve: Create comprehensive About and Contact pages. Include your business story, team members, physical address (if applicable), email address, phone number, and social media links. Ensure this information is consistent across your site and external directories.

C3 — Outbound Citations (Weight: 0.10)

What it measures: Whether your content cites external authoritative sources to support claims, data, and statements.

Why it matters: Content that cites its sources signals academic rigor and factual reliability. AI engines view outbound citations as a quality indicator — the same way academic papers gain credibility through proper citations. Pages that make claims without sources are treated as less reliable.

How to improve: Link to authoritative sources for every statistical claim or factual statement. Cite industry reports, academic research, and official documentation. Use descriptive anchor text so AI can understand what the citation supports.

C4 — Content Originality (Weight: 0.15)

What it measures: Whether your content provides unique perspectives, original data, or insights not found elsewhere. Duplicate or heavily derivative content scores poorly.

Why it matters: AI engines have access to vast amounts of content and can detect when information is substantially duplicated. Original content that adds new value to a topic is far more likely to be cited than content that rehashes what is already widely available. AI engines seek out the most authoritative original source.

How to improve: Include proprietary data, original research, unique case studies, or first-hand expertise in your content. Share unique perspectives that cannot be found on competitor sites. If you must cover common topics, add original analysis or frameworks that differentiate your content.

C5 — Social Proof (Weight: 0.10)

What it measures: Whether your site includes verifiable social proof such as customer testimonials, case studies, client logos, review counts, and endorsements.

Why it matters: Social proof helps AI engines validate that your business is real, active, and trusted by others. Sites with strong social proof signals are more confidently cited in AI recommendations, particularly for product and service queries.

How to improve: Add customer testimonials with real names and companies. Include case studies with measurable results. Display client logos and partnership badges. Link to third-party review platforms where customers have left feedback.

C7 — Brand Consistency (Weight: 0.10)

What it measures: Whether your brand information (name, description, offerings) is consistent across your website, schema markup, social profiles, and external directories.

Why it matters: AI engines cross-reference your brand information across multiple sources. Inconsistencies — such as different business names on your website versus Google Business Profile — create confusion and reduce AI's confidence in citing you. Consistency equals clarity, and clarity equals citations.

How to improve: Audit your business name, description, address, and contact information across all platforms. Ensure your schema markup matches your visible site content and external directory listings. Use the exact same business name everywhere.

C8 — Legal Pages (Weight: 0.10)

What it measures: Whether your site includes standard legal pages such as Privacy Policy, Terms of Service, and Cookie Policy.

Why it matters: Legal pages are a basic trust signal. Their absence suggests an unprofessional or potentially fraudulent site. AI engines use the presence of legal pages as a baseline quality indicator when evaluating source credibility.

How to improve: Add Privacy Policy, Terms of Service, and Cookie Policy pages to your site. Link to them from your footer. Keep them up to date with current legal requirements including GDPR and CCPA compliance where applicable.

C9 — Brand Recognition (Weight: 0.30)

What it measures: The overall recognition and reputation of your brand across the web, including mentions on authoritative sites, backlink profile strength, and presence in knowledge bases. This is the highest-weighted factor in the Authority category.

Why it matters: AI engines are more likely to cite brands they "recognize" from their training data and retrieval sources. A brand with strong web presence, authoritative backlinks, and mentions on trusted sites has a higher baseline citation probability for any query in its domain.

How to improve: Build brand presence through consistent content publishing, guest contributions on authoritative sites, PR coverage, and active social media profiles. Earn mentions and backlinks from high-authority domains. Participate in industry directories and databases. This factor takes the longest to improve but has the highest long-term impact on AI visibility.

Technical Accessibility (15%)

Technical accessibility is the gatekeeper category. If AI crawlers cannot access, render, and parse your site, none of the other optimizations matter. These factors ensure the basic technical foundation is in place for AI visibility.

D1 — AI Crawler Access (Weight: 0.25)

What it measures: Whether your robots.txt, meta robots tags, and server configuration allow AI crawlers (such as GPTBot, ClaudeBot, PerplexityBot) to access your content. This is the highest-weighted factor in the Technical category.

Why it matters: If you block AI crawlers in robots.txt, your site is invisible to AI engines regardless of how well-optimized your content is. Many sites inadvertently block AI bots through overly restrictive robots.txt rules or through WAF (Web Application Firewall) configurations that treat AI crawlers as suspicious traffic.

How to improve: Check your robots.txt file and ensure it does not block GPTBot, ClaudeBot, PerplexityBot, or other AI crawlers. Review your firewall and CDN settings. Test accessibility by checking if your content appears in AI search results. Add explicit Allow directives for AI user agents if needed.

D2 — HTTPS (Weight: 0.10)

What it measures: Whether your site uses HTTPS encryption for all pages.

Why it matters: HTTPS is a baseline security and trust signal. AI engines deprioritize non-HTTPS sources because insecure connections indicate a site that has not maintained basic security standards. Most modern browsers also flag HTTP sites as insecure, reducing user trust.

How to improve: Install an SSL certificate and redirect all HTTP traffic to HTTPS. Most hosting providers offer free SSL through Let's Encrypt. Ensure all internal links and resources use HTTPS URLs.

D3 — Page Speed (Weight: 0.20)

What it measures: How quickly your pages load, including server response time, largest contentful paint (LCP), and overall page weight.

Why it matters: AI crawlers have time budgets. If your page takes too long to load, the crawler may abandon it before fully parsing the content. Additionally, slow sites often indicate poor technical maintenance, which is a negative quality signal. Fast-loading pages get crawled more completely and more frequently.

How to improve: Optimize images and use modern formats (WebP, AVIF). Minimize JavaScript and CSS. Use a CDN. Enable compression (gzip or Brotli). Implement lazy loading for below-the-fold content. Target a Largest Contentful Paint under 2.5 seconds.

D4 — Mobile Responsive (Weight: 0.10)

What it measures: Whether your site renders correctly and is usable on mobile devices.

Why it matters: AI crawlers often use mobile user-agent strings for crawling. A site that breaks on mobile may present incomplete or malformed content to AI crawlers. Mobile responsiveness also signals modern web development practices and overall site quality.

How to improve: Use responsive CSS frameworks or media queries. Test on multiple screen sizes. Ensure text is readable without zooming and touch targets are appropriately sized. Use the viewport meta tag correctly.

D5 — Sitemap (Weight: 0.10)

What it measures: Whether your site has an accessible XML sitemap that lists all important pages with their last-modified dates and priorities.

Why it matters: Sitemaps are roadmaps for crawlers. Without one, AI crawlers must discover your content through links, which may result in important pages being missed. A well-structured sitemap ensures that all your key content is discoverable and tells crawlers which pages are most important and most recently updated.

How to improve: Generate and maintain an XML sitemap at /sitemap.xml. Include all public-facing pages with accurate lastmod dates. Submit the sitemap to search engines. Update it automatically when content changes.

D6 — Clean URLs (Weight: 0.05)

What it measures: Whether your URLs are human-readable, descriptive, and free of unnecessary parameters, session IDs, or random strings.

Why it matters: Clean URLs help AI engines understand page hierarchy and content before even loading the page. A URL like /learn/aeo-vs-seo communicates topic clearly, while a URL like /page?id=12847&session=abc provides no context. Clean URLs also contribute to a cleaner crawl experience.

How to improve: Use descriptive, keyword-rich URL slugs. Remove unnecessary query parameters. Use hyphens to separate words. Keep URLs concise and hierarchical. Implement proper 301 redirects if you change URL structures.

D7 — Internal Links (Weight: 0.10)

What it measures: Whether your site has a healthy internal linking structure that connects related content and establishes topical relationships between pages.

Why it matters: Internal links help AI crawlers discover related content and understand how topics on your site connect. A well-linked site creates a knowledge graph that AI can traverse to find the most relevant answer to any query. Orphan pages with no internal links are less likely to be crawled and cited.

How to improve: Link related pages to each other using descriptive anchor text. Create hub pages that link to all content within a topic cluster. Ensure every page can be reached within 3 clicks from the homepage. Add "related content" sections at the bottom of articles.

D8 — Server-Side Rendering (Weight: 0.10)

What it measures: Whether your pages deliver fully rendered HTML from the server, rather than requiring client-side JavaScript execution to display content.

Why it matters: Many AI crawlers have limited or no JavaScript rendering capability. If your content is rendered entirely by client-side JavaScript, AI crawlers may see an empty page or incomplete content. Server-side rendering ensures that all your content is immediately available in the HTML response.

How to improve: Use server-side rendering (SSR) or static site generation (SSG) for all content pages. If using a JavaScript framework like React or Next.js, ensure content-heavy pages are server-rendered. Test by viewing your page source — if the content is not visible in the raw HTML, it needs SSR.

Freshness & Recency (10%)

AI engines prefer current information over outdated content. Freshness signals tell AI that your content is actively maintained and reflects the latest state of knowledge. Stale content gets deprioritized in AI citations, even if it was once authoritative.

E1 — Content Recency (Weight: 0.40)

What it measures: How recently your content was published or substantively updated. This is the highest-weighted individual factor within any category, reflecting the critical importance AI engines place on current information.

Why it matters: AI engines are trained to prefer recent information, especially for topics that evolve. A guide published three years ago will be deprioritized relative to a guide updated last month, even if the older content is more comprehensive. AI engines check publication and modification dates as primary freshness signals.

How to improve: Update your key content pages regularly — at minimum quarterly for evergreen content and monthly for fast-moving topics. Update the dateModified field in your Article schema when you make substantive changes. Add new data, examples, or sections to demonstrate that the content reflects current reality.

E2 — Visible Dates (Weight: 0.20)

What it measures: Whether your pages display visible publication and last-updated dates that users and AI crawlers can see.

Why it matters: Visible dates are a transparency signal. AI engines parse visible dates to confirm schema metadata and to evaluate recency when schema is absent. Pages without visible dates create uncertainty about when the content was created or last reviewed, which reduces AI's confidence in citing the content.

How to improve: Display "Published: [date]" and "Last updated: [date]" on every content page. Place these dates near the top of the page, ideally in the article header. Use a consistent date format and ensure visible dates match your schema markup dates.

E3 — Freshness Signals (Weight: 0.20)

What it measures: Whether your site shows broader indicators of active maintenance, such as recent blog posts, updated copyright years, active RSS feeds, and regular content publication cadence.

Why it matters: AI engines look beyond individual page dates to assess whether a site is actively maintained. A site with a blog that has not been updated in two years signals abandonment, which reduces trust in all content on the site, even pages that are individually current.

How to improve: Maintain a regular content publication schedule. Keep your blog or news section active. Update your homepage content periodically. Ensure dynamically generated content (like footer copyright years) reflects the current year.

E4 — Copyright Footer Date (Weight: 0.20)

What it measures: Whether your site's footer copyright date reflects the current year.

Why it matters: A footer that reads "© 2022" when the current year is 2026 is a red flag for AI engines. It suggests the site has not been maintained in years, casting doubt on the accuracy of all content. This is a simple signal with outsized impact because it applies site-wide.

How to improve: Use dynamic date generation in your footer so the copyright year updates automatically. In most frameworks, this is as simple as rendering the current year programmatically. Never hardcode the year in your footer.

Conversational Readiness (5%)

Conversational readiness measures how well your content matches the way people naturally interact with AI assistants. While this category carries the smallest weight, it often determines whether your content gets cited for the growing volume of natural-language queries that users type into AI tools.

F1 — Q&A Format (Weight: 0.40)

What it measures: Whether your content uses explicit question-and-answer formatting, with questions posed as headings or bold text and answers following immediately below.

Why it matters: The majority of AI interactions begin with a question. Content structured in Q&A format provides ready-made answers that AI can cite with minimal processing. When an AI engine encounters a question heading that matches a user's query, followed by a clear answer, the path to citation is direct and unambiguous.

How to improve: Add FAQ sections to key pages. Structure informational content with question headings. Use the actual questions your customers ask, discovered through support tickets, search console data, and AI chat analytics. Pair each question with a concise, direct answer in the first sentence below the heading.

F2 — Snippet Formatting (Weight: 0.30)

What it measures: Whether your content includes short, self-contained passages that can be extracted as standalone snippets by AI engines.

Why it matters: AI-generated answers are typically 2-4 sentences long. If your best content is buried in the middle of a long paragraph, AI has to do more work to extract it. Content formatted as standalone snippets — concise passages that make sense without surrounding context — is dramatically easier for AI to cite.

How to improve: Write key definitions and answers as self-contained passages of 1-3 sentences. Ensure these passages make sense if read in isolation. Front-load the most important information in each section. Use callout boxes, bold text, or dedicated summary blocks to highlight snippet-worthy content.

F3 — Long-Tail Keyword Targeting (Weight: 0.30)

What it measures: Whether your content targets specific, detailed queries (long-tail keywords) rather than only broad, competitive terms.

Why it matters: AI search queries tend to be longer and more specific than traditional search queries. Users ask AI things like "how do I add FAQ schema to a WordPress site for better AI visibility" rather than just "FAQ schema." Content that targets these specific, conversational queries is more likely to match and be cited in AI responses.

How to improve: Research long-tail queries in your niche using tools like Google Search Console, AnswerThePublic, or by analyzing AI chat transcripts. Create content that addresses these specific queries. Use long-tail phrases naturally in headings and opening sentences. Build out content depth around specific sub-questions within your broader topics.

Diagnostic Factors (Advisory Only)

In addition to the 34 scored factors above, the Vida AEO audit checks 7 diagnostic factors that carry zero weight in the score. These are best-practice checks that surface issues without penalizing your overall score. They appear as advisory warnings in your audit report.

While these diagnostic factors do not directly affect your AEO score, fixing the issues they surface is still worthwhile. Many of these factors overlap with traditional SEO best practices and contribute to overall site quality that AI engines evaluate holistically.

How to Use This Methodology

Understanding the 34 AEO factors gives you a strategic advantage. Here is how to put this knowledge into action:

1. Run a free AEO scan to see your current score across all 34 factors. The audit report breaks down your performance by category and highlights the specific factors where you can improve most.
2. Prioritize by weight. Focus on the highest-weighted factors first. Improving A10 Content Depth (0.17 weight, 30% category) will impact your score more than improving D6 Clean URLs (0.05 weight, 15% category).
3. Fix quick wins. Some factors like E4 Copyright Footer Date and D2 HTTPS can be fixed in minutes. Others like C9 Brand Recognition take months. Start with the fast improvements while building toward the bigger ones.
4. Re-scan regularly. AEO is not a one-time optimization. Re-scan your site after making changes to track progress, and scan periodically to catch regressions as your content evolves.
5. Read our related guides. For deeper guidance on specific improvements, explore our AEO fundamentals guide, our AEO vs SEO comparison, and the AEO glossary for definitions of key terms.