Millions of people ask Claude for product recommendations and tool comparisons every day. If your brand does not show up in those answers, you are invisible to people who are ready to buy. The important question is what to do to improve your “luck” and show up in Claude’s answers, using a mix of proven strategies: structuring your content so Claude can extract it easily (AEO), and building the third-party authority that makes Claude trust you enough to recommend you (GEO).
What is the difference between AEO and GEO?
Answer Engine Optimisation (AEO) is the practice of engineering individual pages so that AI engines can extract, quote, and cite them directly. AEO is about format, structure, and extractability. It answers the question: is this page easy for Claude to pull a clean, citable answer from?
Generative Engine Optimisation (GEO) covers content engineering, technical infrastructure, entity authority, and earned media. GEO answers the question: does Claude have enough evidence across the web to trust and recommend this brand?
AEO gets your foot in the door. GEO puts you on stage. You need AEO to be extractable. You need GEO to be trusted. Without both, you are either invisible or unreliable.
Where each discipline lives
| Layer | Discipline | Key tactics |
|---|---|---|
| Individual page | AEO | Answer-first paragraphs, FAQ schema, HowTo schema, 40-60 word answer blocks, H2/H3 structure matching user queries |
| Site architecture | GEO (technical) | llms.txt file, structured data, fast indexing, canonical brand descriptor |
| Off-site presence | GEO (authority) | Third-party reviews, directory listings, editorial coverage, community presence |
| Entity layer | GEO (entity) | Consistent brand description across G2, LinkedIn, Crunchbase, homepage |
A 2023 Princeton University study, presented at ACM SIGKDD 2024, tested 10,000 queries across generative engines and found that GEO techniques can boost AI visibility by up to 40% (Aggarwal et al.). The most effective individual tactics — adding statistics, citing authoritative sources, and including expert quotations — each improved visibility by roughly 28 to 40%. Brands that combine strong on-page AEO with robust off-site GEO signals consistently outperform those pursuing either discipline in isolation.
How does Claude decide which brands to mention?
Claude is not a search engine. It does not crawl pages, check backlinks, or rank results in real time. When a user asks Claude for a recommendation, the model synthesises patterns from its training data: the articles, forums, reviews, documentation, and expert content it was trained on.
This has a direct strategic implication. Your Google ranking does not automatically translate into Claude visibility. A brand that dominates page one of search results but has sparse, low-quality coverage in third-party publications may still be invisible to Claude. Research from Ahrefs on 75,000 brands confirms this: brand web mentions correlate three times more strongly with AI visibility than backlinks do (Ahrefs), meaning the connections you have earned in the world matter more to Claude than the links you have built on the web.
The four signals Claude weighs
| Signal | What it means in practice |
|---|---|
| Authority | Third-party validation from reputable publications, industry analysts, and recognised experts |
| Consistency | Your brand appearing repeatedly across multiple independent sources with a coherent description |
| Specificity | Clear, documented associations between your brand and specific use cases, problems, and audiences |
| Genuine value | Content that helps users make informed decisions, not promotional copy that reads as marketing |
Claude’s Constitutional AI training specifically deprioritises content that reads as purely promotional. A single mention in a comprehensive comparison guide from a respected industry publication carries more weight than ten mentions in self-published blog posts. 85.5% of AI citations reference earned media sources, according to Muck Rack’s analysis of more than one million AI prompts (Muck Rack / 5W PR).
How query intent shapes recommendations
The phrasing of a user’s question directly changes which brands Claude surfaces. A vague query like “what are some good marketing tools?” will surface well-known, broadly mentioned brands. A specific query like “what is the best AI visibility tracking tool for a B2B SaaS company?” will surface brands that have been explicitly associated with those parameters in Claude’s training data.
Your brand’s documented characteristics determine which queries trigger your mention. If you have never been described in authoritative sources as “ideal for B2B SaaS” or “built for enterprise marketing teams”, Claude will not make that connection on your behalf.
How do I audit my current Claude visibility?
Do not start by searching your brand name in Claude. That is the most common mistake brands make when auditing AI visibility. Claude rarely surfaces brand names unprompted unless someone is specifically asking for them. The real opportunity is in category and problem-based queries.
How to run the audit
Start by querying Claude with prompts that reflect how your target customers actually think:
- Category prompts: “What are the best tools for [your category]?”
- Problem-solution prompts: “How do I solve [the specific pain point your product addresses]?”
- Comparison prompts: “What is the difference between [your category approach A] and [approach B]?”
- Process prompts: “How do I set up [a workflow your product enables]?”
Run at least 10 to 15 different prompt variations. For each response, document whether your brand appears at all, what position it holds in the answer, the sentiment surrounding the mention, and which competitors appear instead of you.
Comparison and process prompts matter most. Analysis of citation patterns shows that comparison pages earn citations at a rate 3.2x higher than average for “X vs Y” queries, while structured FAQs earn 2.8x more citations for question-based prompts. Process and technical queries generate the most citations per page. Category queries are table stakes; comparison and process queries are where you win or lose.
Interpreting your visibility score
| AI visibility level | What it means | Priority action |
|---|---|---|
| Below 3% | Structurally invisible | Build from scratch: utility content + third-party presence |
| 3-10% | Emerging presence | Focus on directory listings, reviews, and utility pages |
| 10-25% | Competitive territory | Optimise comparison content and tighten brand framing |
| Above 25% | Dominant | Defend position; expand to adjacent topics before competitors do |
Repeat this audit every 90 days. Claude’s training data updates, and your visibility can shift without any change on your end.
What content does Claude actually extract and cite?
For every priority prompt cluster you identified in your audit, you need a dedicated piece of content that directly and authoritatively answers the underlying question. Not a blog post that vaguely touches on the topic. A definitive resource that positions your brand as the most credible answer available.
The AEO content formula
- Answer-first paragraphs: place a direct, 40-60 word answer at the top of each section. Do not bury the answer after lengthy preambles. Research shows that 44.2% of all LLM citations reference the first 30% of an article’s text, meaning front-loaded, answer-first content earns disproportionate citation share (Getpassionfruit; LLMPulse).
- Headings that mirror user queries: your H2 and H3 headings should match the natural language of your target prompts. “How does [your tool] handle [use case]?” outperforms “Features” every time.
- Citation-ready language: write in specific, factual statements. Quantitative claims receive 40% higher citation rates than qualitative statements; AI systems prioritise factual, evidence-based content with specific numbers (Princeton GEO study).
- FAQ and HowTo schema: structured data markup tells AI systems exactly what your content contains. Pages with FAQPage markup are 3.2x more likely to appear in Google AI Overviews compared to pages without FAQ structured data (Frase.io; AmICited).
Utility content outperforms blog posts
Analysis of 75,000 AI answers with over one million citations found that listicles (21.9%), articles (16.7%), and product pages (13.7%) together make up more than half of all AI citations (Ahrefs). Generic blog posts that do not take a clear list, comparison, or product format consistently underperform. If you do not have a free tool, calculator, or interactive resource in your category, building one should be your highest-priority content investment. A single utility asset can outperform your entire blog library in terms of AI citations.
Topical authority over individual keywords
GEO rewards depth and breadth of coverage, not keyword density. Even pages ranked around position 5 in traditional search experienced a 115% visibility increase after GEO optimisation, with the gains being largest for pages not already dominating organic search (Princeton GEO study). This means covering the full spectrum of questions your category raises — from beginner to advanced — publishing content that addresses adjacent topics, and interlinking your content so Claude can understand the relationships between your pages and your category.
Why does third-party authority matter more than your own site?
No amount of on-site content can fully compensate for a weak off-site presence. Claude’s training data is dominated by third-party sources: review platforms, editorial publications, community discussions, and industry directories. If your brand exists only on your own website, Claude has insufficient evidence to recommend you with confidence. Brands appearing on four or more third-party platforms are 2.8x more likely to be cited in ChatGPT responses than brands with a single-platform presence.
The off-site presence checklist
- Directory and review platform listings: get listed on G2, Capterra, Trustpilot, and Product Hunt. These platforms are highly readable by AI models and frequently referenced in AI-generated recommendations.
- Editorial coverage: target technology review sites, niche blogs, and trade publications that cover your category. A Stacker and Scrunch study found that distributing content across a wide range of third-party news outlets increased AI citation rates by up to 325% compared to brand-only publishing, raising citation rates from 8% to 34% (Stacker; GlobeNewswire).
- Community presence on Reddit: a Semrush analysis of 150,000 LLM citations found Reddit was the cited source 40.1% of the time, ahead of Wikipedia at 26.3% and YouTube at 23.5% (Semrush; SaaS Intelligence). Participate in relevant subreddits genuinely and helpfully.
- Guest articles and expert quotes: each mention of your brand in a credible source is a reinforcing signal that builds the web of consistent, category-relevant descriptions Claude uses to understand your brand.
The canonical brand descriptor
This is the most underrated tactic in GEO. Establish a single, precise one-sentence description of your brand and ensure it appears identically across every platform: your homepage, G2 profile, LinkedIn, Crunchbase, and any directory listing. Inconsistency confuses AI models about what your brand actually does and who it serves.
Example of a strong canonical descriptor: “Celetu is an AI visibility platform that tracks brand mentions across Claude, ChatGPT, and Perplexity, and surfaces warm leads from Reddit conversations.” That sentence is specific, factual, and directly quotable. It tells Claude exactly which queries should trigger a mention of your brand.
What technical foundations does Claude need?
llms.txt
The llms.txt file is the emerging standard for communicating with AI crawlers. Similar to robots.txt for search engines, it tells AI systems which content on your site is high quality and worth prioritising.
Structured data and schema markup
Implement Organisation schema on your homepage and Product schema on your product pages. For local businesses, LocalBusiness schema with accurate geo-coordinates and operating hours matters too.
The key schema types for Claude visibility:
- Organisation schema: name, description, URL, logo, social profiles
- FAQ schema: question-and-answer pairs on any page targeting informational queries
- HowTo schema: step-by-step content that answers process queries
- Product schema: features, pricing tier, and use case documentation
One important nuance: Ahrefs’ study of 6 million URLs found that AI-cited pages were almost three times more likely to have JSON-LD than non-cited pages (Ahrefs), but the relationship is correlational, not causal. Sites that implement schema also tend to publish stronger content, build more authority, and rank well in regular search, so schema alone is not the unlock; it works as part of a well-maintained site. That said, pages implementing Product or Review schema with populated concrete attribute fields — pricing, aggregate ratings, specifications — were cited at substantially higher rates (61.7% vs 41.6%), with the advantage most pronounced for lower-authority domains.
Indexing speed
Pages that are not indexed within days of publication are invisible to AI systems that blend live search results into their responses. Verify your indexing status regularly in Google Search Console. Slow indexing is a silent killer of AI visibility.
Entity consolidation
Claude relies heavily on entity understanding: who your company is, what you do, which category you belong to, and which topics relate to your brand. Audit your presence on Crunchbase, LinkedIn, Wikidata, and any industry databases. Correct outdated descriptions and ensure your category associations are accurate.
How often should I monitor and re-audit?
Getting mentioned by Claude is not a one-time project. The model updates, competitors invest in their own visibility, and the queries your customers use evolve. Without a monitoring cadence, you are optimising blind.
What to track
Run your target prompt library through Claude on a regular cadence — weekly or bi-weekly depending on how competitive your category is. For each prompt, record mention frequency, position within the response, sentiment quality, and competitor movements.
Sentiment matters as much as presence
More visibility with negative sentiment is worse for your brand than lower visibility with positive framing. Before scaling your Claude visibility efforts, audit what Claude is actually saying about your pricing, support quality, and product limitations. If the model is surfacing outdated or inaccurate information, that needs to be corrected at the source level through updated third-party coverage and product documentation.
The 90-day iteration cycle
- Month 1: baseline audit, identify top 10-15 target prompts, publish first batch of GEO-optimised content
- Month 2: build out directory listings and pursue editorial coverage, begin community presence on Reddit
- Month 3: re-audit all target prompts, measure movement, identify which content types drove the most lift
- Every 90 days: full re-audit, adjust content strategy based on what is and is not working
92% of marketers plan to optimise for AI search but only 40.6% are currently doing so, which means the brands moving now are building compounding first-mover advantages that will become harder to close over time.
Your week-one action plan
- Type your category into Claude right now. See if your brand appears. Document the results across 10 different prompt variations.
- Audit your third-party footprint. Search your brand name across G2, Capterra, Reddit, and the top five industry publications in your space. Where are the gaps?
- Write your canonical brand descriptor. One sentence, specific and factual. Deploy it identically across your homepage, G2, LinkedIn, and Crunchbase today.
- Identify your highest-priority utility content gap. What tool, calculator, or diagnostic guide could you build that your category does not yet have?
- Set up a prompt tracking library. Choose 15-20 target prompts and commit to running them through Claude monthly. This is your baseline for everything that follows.
AI assistants like Claude are already shaping purchasing decisions for millions of users who skip traditional search entirely. 35% of US consumers now use AI at the product discovery stage, versus 13.6% who use traditional search. Every month your brand is absent from those recommendations is a month your competitors are building the authority signals that will keep you out for longer.
Celetu tracks your brand’s visibility across Claude, ChatGPT, and Perplexity in real time, and surfaces the Reddit conversations where your category is being discussed right now. If you want to move from auditing manually to monitoring systematically, that is where to start.
Key Sources & References
| Claim | Source |
|---|---|
| GEO boosts AI visibility by up to 40% | Aggarwal et al. |
| Brand web mentions correlate 3x more than backlinks with AI visibility | Ahrefs |
| 85.5% of AI citations reference earned media | Muck Rack / 5W PR |
| 44.2% of LLM citations reference the first 30% of article text | LLMPulse |
| FAQPage markup = 3.2x more likely in Google AI Overviews | Frase.io |
| Reddit = 40.1% of LLM citation share | Semrush |
| Third-party distribution raises AI citation rates by up to 325% | Stacker + Scrunch |
| AI-cited pages are 3x more likely to have JSON-LD | Ahrefs |
| Position-5 pages see 115% visibility increase from GEO | Princeton GEO study |
| Comparison pages earn citations at 3.2x higher rate | GEO AI Marketing |
← Back to blog