Everything about
AI visibility & GEO.

GEO stands for Generative Engine Optimization — the practice of structuring and optimizing digital content so that AI-powered search engines like ChatGPT, Perplexity, Claude, and Google AI Overviews recommend your brand in their generated answers. Unlike traditional SEO which targets ranking positions in Google's blue links, GEO targets inclusion in AI-generated responses.

Traditional SEO focuses on ranking for keywords in Google's search results page. GEO focuses on being cited and recommended by AI systems when users ask conversational questions. A website can rank #1 on Google and still be completely invisible to ChatGPT. The optimization techniques also differ: GEO requires structured content, third-party authority signals, and schema markup rather than keyword density and backlinks alone.

AI search traffic grew over 500% in 2025. ChatGPT now has over 800 million weekly active users. Perplexity processes 60-70 million queries per day. Google AI Overviews appears in over 50% of searches. If your brand isn't being recommended by these systems, you're missing a growing share of how customers discover products and services.

AI visibility refers to how often and how prominently your brand is mentioned or recommended when users ask AI assistants questions relevant to your product or service. A brand with high AI visibility appears frequently in AI-generated answers; a brand with low AI visibility is rarely or never mentioned.

An AI visibility score quantifies how often a brand appears in AI-generated responses across a set of relevant questions. Visora calculates this by sending 50 targeted questions to AI platforms and counting how many responses include your brand, weighted by prominence and sentiment.

AEO (Answer Engine Optimization) is an older term referring to optimization for featured snippets and voice search in traditional search engines. GEO is a newer term specifically targeting AI-generated responses in LLM-powered tools. While they share some techniques (structured content, FAQ format), GEO addresses a fundamentally different distribution channel.

Perplexity uses real-time web search combined with AI synthesis. It crawls relevant web pages, identifies authoritative sources, and generates an answer that cites those sources. Brands appear in Perplexity recommendations when they're mentioned in pages that Perplexity indexes as authoritative — including product review sites, comparison articles, and industry publications.

ChatGPT draws from its training data (periodically updated) and, in Search mode, from real-time Bing results. Brands appear in ChatGPT recommendations when they have a strong presence in training data sources and when they're mentioned frequently in authoritative web content that Bing indexes.

AI-friendly content has several characteristics: clear structure with headings and subheadings, direct answers to specific questions, factual claims supported by data or citations, FAQ format, schema markup (JSON-LD), short quotable passages (50-120 words), and comprehensive topic coverage. AI systems are trained to extract and cite content structured for easy comprehension.

A citation source is the third-party website that causes an AI system to mention your brand. For example, if Perplexity mentions your product in a response about project management tools, it might be because a G2 review, a TechCrunch article, or a Reddit discussion about your product influenced its search results.

Perplexity is designed as a transparent search engine — showing sources is core to its product. This makes Perplexity especially valuable for GEO tracking because you can trace exactly which websites led to a brand recommendation, making your optimization efforts actionable.

The fastest path is getting mentioned on high-authority third-party platforms AI systems frequently cite: submit to G2 and Capterra, get mentioned in "best tools" articles on high-authority sites, and seek coverage in industry newsletters. These actions can show results in 2-4 weeks.

Schema markup (structured data in JSON-LD format) helps AI systems understand your content accurately. Product schema, FAQ schema, and Organization schema tell AI crawlers exactly what your product does, who it's for, and how it works — without requiring them to interpret unstructured text. Pages with proper schema markup are significantly more likely to be cited accurately.

Yes. llms.txt is an emerging standard that provides AI systems with a curated, machine-readable summary of your website. While not yet universally adopted, it signals GEO awareness and helps AI systems accurately understand your brand. Place it at yourdomain.com/llms.txt.

Perplexity tends to cite content that: (1) directly answers a specific question, (2) includes citable statistics or data points, (3) comes from domains with high trust scores, (4) is structured with clear headings and bullet points, and (5) is recent — published or updated within the last 6-12 months.

GEO results typically appear faster than SEO results. New indexed content (publishing a comprehensive FAQ page, getting listed on G2) can show impact in 2-4 weeks. Schema markup improvements can show results within days. Consistent GEO efforts over 2-3 months typically produce significant, measurable improvements in AI visibility scores.

Not entirely. The underlying factors that drive GEO — authoritative third-party mentions, structured content, accurate schema markup — improve visibility across all AI platforms simultaneously. Each platform has nuances, but a solid GEO foundation lifts all of them.

Building in public means sharing your product development journey transparently on platforms like Twitter/X and Reddit. This generates organic mentions of your brand in places AI systems crawl — developer communities, product forums, social media. Each authentic mention contributes to your AI citation profile without paid placement.

robots.txt tells web crawlers which pages they're allowed to access. For GEO, ensure AI crawlers — GPTBot (OpenAI), PerplexityBot, ClaudeBot (Anthropic), and Googlebot — are allowed to access your key pages. Accidentally blocking these bots prevents your content from being indexed for AI citation.

Allow the following bots: GPTBot (OpenAI/ChatGPT), PerplexityBot (Perplexity AI), ClaudeBot (Anthropic/Claude), OAI-SearchBot (OpenAI Search), and Googlebot (Google AI Overviews). Most websites allow these by default, but aggressive bot-blocking configurations sometimes block them accidentally.

The most valuable schema types for GEO are: FAQPage (for FAQ content), SoftwareApplication or Product (for SaaS), Organization (for brand identity), Article (for blog posts and guides), and HowTo (for instructional content). Each type helps AI systems categorize and accurately describe your brand.

An FAQ page is critical for GEO because: (1) it directly provides AI systems with question-answer pairs they can cite, (2) with FAQPage schema markup it becomes machine-readable in a format AI systems prefer, and (3) it covers long-tail queries that might not be addressed elsewhere on your site.

Structure content with: a clear H1 title matching a common user query, H2 subheadings that are also questions, concise answers (50-150 words) immediately following each question, data points with sources, and a FAQ section at the bottom. Use plain HTML where possible — avoid JavaScript-heavy content that AI crawlers may not render.

Visora tracks AI visibility for your brand across AI search platforms, analyzes why your competitors appear in AI recommendations while you may not, and provides actionable content and technical recommendations to improve your GEO score. Think of it as Ahrefs, but for AI search.

Visora currently tracks Perplexity AI. ChatGPT tracking and Google AI Overviews tracking are coming in Q3 2026. Perplexity is the highest-value platform to track first because it shows real-time citation sources.

Visora sends 50 carefully crafted questions — designed to mirror what real users ask AI assistants about your product category — to AI platforms. It analyzes each response to detect brand mentions, citation frequency, sentiment, and the sources behind recommendations. This data is aggregated into an AI visibility score (0-100).

Visora offers three tiers: Starter (free) with monthly scans; Builder ($29/month) with weekly scans, 5 competitor tracking, citation analysis, and 10 content generations/month; Growth ($79/month) with daily scans, unlimited competitors, unlimited content generation, and API access.

Visora's primary differentiation is tracking + analysis + execution. Otterly and Rankscale focus on monitoring (showing you where you stand). Visora adds the analysis layer (why competitors beat you) and the execution layer (generating ready-to-use content to fix it). Visora is also priced significantly lower.

Visora is targeting a Q2 2026 launch. Join the early access waitlist to get first access, a discounted launch rate, and direct input into feature prioritization.