You've done the audit. You opened ChatGPT, typed the questions your customers ask, and read the results. And there it was: either your brand doesn't show up at all, or it appears in third position with a description that doesn't quite sound like you.
The first instinct is usually to think you just need to "optimize for AI." But the reality is more nuanced than that. LLM visibility doesn't work like an SEO ranking. It's built layer by layer, through signals that accumulate over weeks.
There's no shortcut. But there is a logical order. Here are the 7 levers that actually move the needle, from the most foundational to the most refined.
AI visibility isn't won overnight. It's built like a reputation: slowly, honestly, and consistently across dozens of independent sources.
Before you start: understanding why LLMs ignore you
Large language models like GPT-4, Gemini, or Claude don't have rankings in the traditional sense. They have a probabilistic representation of the world, built from billions of texts. When someone asks a question about your category, the model synthesizes what it learned from hundreds of sources.
If your brand doesn't appear, it's not because you "optimized a page badly." It's because the model hasn't accumulated enough consistent signals to confidently associate you with your category. Each lever below works to strengthen those signals.
Lever 1: entity recognition
The foundation for everything else
Before the model can recommend you, it needs to know with certainty what you are. Technically speaking, you need to exist as an entity in its world model: a clearly defined company, with a category, a target audience, and a value proposition.
The problem with many SaaS sites: their homepage is full of marketing jargon ("the all-in-one platform", "revolutionize your workflow") but never clearly says what they do. An LLM reading your homepage can't confidently infer that you're an AI visibility tracking tool.
What to do concretely:
Write a factual description of your product in plain language: "Vizible AI is an AI visibility tracking tool that measures brand mentions in ChatGPT, Gemini, Claude, Perplexity, Mistral, and DeepSeek." Simple, precise, no metaphors.
Add the Organization JSON-LD schema to your homepage with name, description, url, and sameAs fields pointing to your LinkedIn, Crunchbase, Product Hunt, and GitHub.
Create or claim your profiles on the directories LLMs trust: G2, Capterra, Crunchbase, Product Hunt, Trustpilot. Every profile must use exactly the same product description.
Audit your positioning consistency: if you describe yourself differently on LinkedIn, on your site, and on G2, the model accumulates contradictory signals. Unify everything.
Expected impact: 4 to 8 weeks for RAG engines like Perplexity, longer for LLMs with periodic training cycles.
Lever 2: content depth
Owning a topic, not just mentioning it
LLMs don't remember a page that mentions a topic. They remember the source that explains it best. If your article on "how to track AI visibility" is the most complete, the most structured, and the most cited, the model will use your framing to answer that question.
This is called topical ownership. It's not about length for length's sake. It's about coverage: does your content answer every sub-question someone might have on that topic?
What to do concretely:
Identify the 3 to 5 core topics in your category (for Vizible AI: AI visibility tracking, GEO vs SEO, improving LLM visibility, GEO tools, AI share of voice).
For each topic, write the definitive guide: 1,500 to 3,000 words, with concrete examples, data, comparisons, and a clear H2/H3 structure. The goal is to be the resource that other articles cite.
Use the precise technical language of your domain: RAG, prompt alignment, share of voice, entity recognition. LLMs recognize expertise in vocabulary precision.
Answer questions directly in your headings: "What is AI share of voice?", "How does RAG search work?". This format is what real-time search engines will directly cite.
Expected impact: 1 to 3 weeks for Perplexity (RAG), 2 to 6 months for LLMs with fixed training.
Lever 3: independent citation frequency
Votes, not links
In SEO, a backlink from a high-DA domain is worth a lot. In GEO, it's different. What builds model confidence is the consistent repetition of the same information across independent sources. If 40 different sources describe Vizible AI as "an AI visibility tracking tool covering ChatGPT, Gemini, and Perplexity", the model ends up treating that description as a high-confidence fact.
This isn't spamming. It's organic presence on the channels where your audience naturally talks about your subject.
What to do concretely:
Guest posts in industry newsletters: a mention in an SEO newsletter read by 10,000 subscribers is worth far more than 5 articles on anonymous sites.
Active presence on Reddit and Quora in relevant subreddits (r/SEO, r/marketing, r/SaaS). Answer real questions with value, mention your tool naturally when it's relevant. Perplexity crawls Reddit heavily.
Ask to be included in comparison articles: "Top 10 GEO tools" or "best alternatives to [competitor]" are exactly the types of content LLMs use to build their answers.
Encourage detailed customer reviews on G2 and Capterra: a review that precisely describes what your tool does is an independent source the model will learn from. Not just "great tool, 5 stars", but "I use Vizible AI to track my mentions in ChatGPT and Gemini daily".
Expected impact: 4 to 12 weeks depending on cadence and sources. Cumulative effect: each new mention reinforces the previous ones.
Lever 4: prompt alignment
Speaking the same language as your buyer
This is the most underestimated lever. In SEO, you target keywords. In GEO, you target prompts: the exact phrasings your customers type into ChatGPT when they have a problem you solve.
"AI visibility tool" and "how to know if ChatGPT recommends me" are two phrasings of the same need, but they trigger different responses in LLMs. Your content needs to use both.
What to do concretely:
Build your prompt universe: list the 20 to 30 questions your customers ask AI before buying. Ask your existing customers directly, or use ChatGPT to generate them.
Create a page or article that directly answers each prompt cluster: not just an article that mentions the topic, but one that answers the question in its title, introduction, and sections.
Study the language LLMs use in their responses on your topics. If ChatGPT uses "GEO score" and "brand visibility in AI", integrate those expressions into your content. Those are the terms the model uses naturally.
Add a FAQ to each key product page: "Does Vizible AI monitor ChatGPT in real time?", "What's the difference between a mention and a citation?". This format is natively citable by LLMs.
Expected impact: 1 to 4 weeks for Perplexity, effect on other LLMs at their next training cycle.
Lever 5: sentiment and online reputation
What the model says about you, not just whether it cites you
You can be mentioned in 80% of AI responses and still lose customers if the description is bad. "Vizible AI can be useful for small teams on a tight budget" is a description you don't want. "Vizible AI is the reference for B2B teams who want complete AI visibility" is a description that converts.
The sentiment LLMs associate with your brand comes from how you're described across all the sources they've consulted: customer reviews, blog articles, Reddit discussions, comparison pieces.
What to do concretely:
Audit how you're currently described: open ChatGPT, Gemini, and Perplexity and read exactly how they present you. Note the adjectives, the nuances, any limitations mentioned.
Identify the source of the problem: if your description is neutral or limiting, find which sources are feeding it. A forum where someone complained? A comparison that positions you as a "budget alternative"? Address the source.
Respond carefully to negative reviews on G2 and Capterra. LLMs read company responses to reviews too. A response that clarifies a misunderstanding or shows a product improvement is a positive signal.
Build your narrative on LinkedIn and Twitter/X: publish regularly on your area of expertise. Viral posts in your niche often end up in training data. Every post where you're cited as an expert reinforces the association.
Expected impact: 6 to 16 weeks. This is the slowest lever, but the most durable. Online reputation changes over the long term.
Lever 6: crawlability for AI bots
If you're not accessible, you don't exist
This is the most technical lever, and often the most neglected. Perplexity, ChatGPT in browsing mode, and other RAG engines actively crawl the web to enrich their responses. If your site blocks their bots, your content is invisible to these engines, even if it's excellent.
What to do concretely:
Check your robots.txt: make sure GPTBot (OpenAI), PerplexityBot, ClaudeBot (Anthropic), Googlebot, and CCBot are not blocked. If you have a global Disallow: /, your pages are invisible.
Optimize page load speed: bots have timeouts. A page taking more than 3 seconds to load may be skipped. Aim for an LCP (Largest Contentful Paint) under 2.5 seconds.
Avoid critical content rendered purely in JavaScript: not all bots render JavaScript the same way. Your key text content (product descriptions, blog articles) should be in the initial HTML, not loaded dynamically.
Submit your sitemap to Google Search Console and make sure all your important pages are included. What Google can index, Perplexity can generally crawl.
Optimal robots.txt example for AI visibility:
User-agent: GPTBot Disallow: User-agent: PerplexityBot Disallow: User-agent: ClaudeBot Disallow: User-agent: * Allow: /
Expected impact: immediate to 2 weeks once fixes are deployed. This is often the fastest win.
Lever 7: publication cadence for RAG
Freshness as a competitive advantage
RAG engines like Perplexity, ChatGPT in browsing mode, and Bing AI don't rely solely on their training data. They actively look for the most recent content on the web. An article published yesterday can already be cited today in a Perplexity response.
This fundamentally changes content strategy. Publishing one article per quarter is no longer enough. Consistency becomes a direct competitive advantage.
What to do concretely:
Publish at least 2 articles per month on topics directly related to your category. Consistency signals that you're an active, up-to-date source.
Update existing articles with a last updated date: an article "updated March 2026" will be preferred over an identical article with no date or dated 2024.
React to news in your sector: a new AI model launches? Google introduces a GEO feature? Publish within 48 hours. These news articles are exactly what Perplexity looks for when answering fresh questions.
Share content on social media on publication day: links shared on LinkedIn and Twitter are often crawled quickly. It's an additional freshness signal.
Expected impact: 1 to 7 days for RAG engines. The effect is visible very quickly, making it the most measurable lever in the short term.
The 7 levers at a glance
Here's a summary to prioritize your actions based on your situation:
Lever 1: Entity recognition | Priority: Foundation (start here) | Timeline: 4 to 8 weeks | Effort: Medium | Impact: Permanent
Lever 2: Content depth | Priority: High | Timeline: 1 to 6 weeks | Effort: High | Impact: Major
Lever 3: Independent citations | Priority: High | Timeline: 4 to 12 weeks | Effort: Ongoing | Impact: Cumulative
Lever 4: Prompt alignment | Priority: High | Timeline: 1 to 4 weeks | Effort: Medium | Impact: Direct
Lever 5: Sentiment and reputation | Priority: Medium | Timeline: 6 to 16 weeks | Effort: Ongoing | Impact: Lasting
Lever 6: AI crawlability | Priority: Urgent if blocked | Timeline: Immediate | Effort: Low | Impact: Immediate
Lever 7: Publication cadence | Priority: Ongoing | Timeline: 1 to 7 days | Effort: Ongoing | Impact: Fast and measurable
The week-by-week action plan
Here's how to deploy these levers in a logical order, without spreading yourself too thin:
Weeks 1 and 2: the foundations
Check and fix your robots.txt (lever 6)
Write a clear factual description of your product and harmonize all your profiles (lever 1)
Add the Organization JSON-LD with sameAs to your homepage (lever 1)
Create or complete your G2, Capterra, Crunchbase profiles (lever 1)
Weeks 3 and 4: the reference content
Identify your 3 most strategic prompts (lever 4)
Write the definitive guide for your main topic (lever 2)
Add FAQs to your key product pages (lever 4)
Weeks 5 to 8: distribution and citations
Publish a guest post in an industry newsletter (lever 3)
Answer 10 Reddit or Quora questions in your category (lever 3)
Launch your publishing cadence (minimum 2 articles per month) (lever 7)
Start collecting detailed reviews on G2 (lever 5)
Month 3 and beyond: continuous optimization
Measure your progress with a monthly audit of key prompts
Identify prompts where you're still absent and target them with new content
Analyze descriptions of competitors ahead of you and work on improving your sentiment
The truth nobody wants to hear
These 7 levers don't work in isolation. Exceptional content nobody cites is pointless. Numerous citations on a non-crawlable site are invisible. A well-defined entity without topical depth stays in its competitors' shadow.
What actually works is stacking. Each lever activated reinforces the others. The month you launch your reference guide AND get three guest posts AND your robots.txt is clean AND you publish two additional articles, that's when the visibility curve really starts to climb.
The good news: the window is still open. Most of your competitors haven't systematically activated these levers yet. The brands that commit seriously now are building a lead that will be very hard to close in 12 months.
GEO isn't a sprint. It's a construction. Every action counts. Every week counts. Start today.
To know exactly where you stand on each of these 7 levers, Vizible AI analyzes your presence daily in ChatGPT, Gemini, Claude, Perplexity, Mistral, and DeepSeek. It measures your mentions, your position, your sentiment, and shows you the priority actions to move forward.