AEO Audit Checklist:
27 Points to Maximize LLM Visibility in 2026

Place a plain-text file at yourdomain.com/llms.txt describing your brand, products, authority claims, and preferred citation format. Include: company name and one-sentence description, product list with brief descriptions, 3–5 verifiable authority claims (customer count, founding year, geographic reach), and a "Preferred citation" line. Keep it under 60 lines. Validate that it is publicly accessible with no authentication.

Place a structured JSON file at yourdomain.com/agents.json describing your brand's capabilities, API endpoints (if relevant), and how AI agents should interact with your site. This is increasingly read by agentic AI systems (AutoGPT, Claude agents, OpenAI Assistants) that take actions on behalf of users and need to understand your site's structure and capabilities.

Add FAQPage JSON-LD to any page with question-and-answer content: product pages, pricing pages, how-to guides, comparison pages. Each FAQ entry is a pre-written citation you are offering LLMs. Write questions that match real user queries ("What is the pricing for [Product]?", "How does [Product] compare to [Competitor]?"). Keep answers 2–4 sentences, factual, and specific. Validate with Google's Rich Results Test.

Add HowTo JSON-LD to step-by-step guides, tutorials, and setup documentation. The schema requires: name, description, and an array of HowToStep objects each with position, name, and text. Well-structured HowTo schema significantly increases the probability that Perplexity and ChatGPT Browse will extract and cite your instructional content when users ask procedural questions in your category.

Implement Article JSON-LD on every piece of editorial content. At minimum include: headline, description, author (use Organization if no individual author), publisher, datePublished, dateModified, and mainEntityOfPage. The dateModified field is particularly important for retrieval models — they weight recently updated content more heavily for queries where currency matters.

Every key page should have a self-referencing <link rel="canonical"> tag with the full URL including HTTPS and trailing slash convention. For LLMs, canonical URLs matter because retrieval systems that encounter your content via multiple paths need to consolidate attribution to a single URL. Missing or incorrect canonicals can split your citation footprint across URL variants.

Publish a page that presents original or curated statistics in your industry. Structure each stat as an H2 or H3 heading containing the statistic itself ("63% of B2B buyers now use AI assistants in the research phase — [Year]"), followed by a brief explanation and source attribution. Run a survey, analyze your user data, or compile public data with a clear methodology. A well-maintained statistics page becomes one of the most-cited pages in your domain because LLMs routinely need specific data points to answer user queries.

Build structured comparison pages for the top 3–5 "[Your Brand] vs [Competitor]" query pairs that represent real user consideration sets. Each page should include an HTML comparison table with clear feature columns, factual claims backed by evidence, and a balanced structure that does not read as pure marketing copy. LLMs reproduce comparison tables frequently — a user asking "what's the difference between X and Y" will often get a direct table reproduction. Be the authoritative source for that comparison.

Write one how-to guide for each major use case your product solves. Format: numbered steps with bold action verbs ("Step 1: Install the tracking script"), specific measurable outcomes ("reduces setup time from 4 hours to 20 minutes"), and HowTo JSON-LD schema. Target procedural queries like "how to set up [your category] for [use case]" — these are some of the most commonly asked and most consistently answered query types in LLM responses.

Conduct and publish original research in your category — a survey of N respondents, an analysis of anonymized platform data, or a benchmark report. Original research is the gold standard citation asset because it creates data that exists nowhere else. It also attracts links from industry publications and practitioners sharing the data, which compounds your SEO authority. Aim for a sample size of at least 100 for surveys (ideally 500+) to make claims statistically defensible.

Publish clear, authoritative definitions for the key terminology in your category. "What is [your category]?" and "What does [term] mean?" queries are extremely common in LLM usage and often cite definitional pages directly. Write definitions that are 100–200 words, factual, and attribute your source of definition if you are citing an established standard. Becoming the go-to definition source for 2–3 terms in your category creates a lasting citation anchor.

"Alternatives to [market leader]" is one of the highest-volume query patterns in B2B SaaS and many other categories. A well-structured alternatives page that lists your brand among 4–6 legitimate alternatives, with a fair comparison, gets cited heavily because LLMs need a source when answering these queries. The page should be factual, not purely promotional — a balanced breakdown of who each alternative is best for will rank better in both Google and LLM citation than pure marketing copy.

Before optimizing, measure. Run a free AIS scan at AISearchStackHub to get your AIS score (0–100) across ChatGPT, Claude, Perplexity, and Gemini, plus your top 3 citation gaps. Record this date and score — it is your AEO baseline. All progress will be measured against this number. Most brands score between 15 and 40 on their first scan; anything above 50 puts you in the top quartile for your category.

Schedule a monthly AIS scan to track score changes over time. LLM citation patterns shift with model updates (roughly quarterly), Perplexity index refreshes, and changes in the external discourse about your brand. A declining score often signals that competitors have published new citation assets or earned new authoritative citations. An improving score validates that your investment is working. Monthly scans catch these signals before they compound into a significant visibility gap.

Run an AIS scan within 30 days of: a major product launch, a press controversy, a significant pricing change, or a public incident affecting your brand. Sentiment shifts in LLM responses can lag real-world events by weeks as retrieval systems index new coverage. Catching a negative sentiment shift early — before it embeds in model weights through repeated training — gives you a window to respond with positive, authoritative content that can counter the narrative.

Scan 3–5 direct competitors quarterly and compare AIS scores. An AIS score of 45 is meaningless in isolation — but if your top competitor scores 68, you have a 23-point gap that represents a significant share of voice disadvantage in AI-generated responses. Competitive benchmarking tells you whether your AEO investment is keeping pace with the market or falling behind, and identifies which competitor's citation assets are outperforming yours so you can target the same query gaps.