AI Search & GEO FAQ

GEO is the practice of optimizing your brand's digital presence to be cited by AI-powered search engines (ChatGPT, Perplexity, Gemini, Claude). Unlike SEO which targets ranked lists, GEO targets AI-generated answers and recommendations. The key signals are entity authority, co-citation frequency, structured data density, and direct-answer content formatting.

AEO is a broader term encompassing optimization for any engine that answers questions —” including traditional featured snippets, Google AI Overviews, and conversational AI engines. GEO is a subset of AEO specifically focused on generative AI systems. Many practitioners use the terms interchangeably.

Share of Model measures what % of AI recommendations in your category include your brand. If ChatGPT mentions you in 30 out of 100 category queries, your SoM is 30%. It's the AI-era equivalent of Share of Voice —” the primary KPI for AI search visibility.

Google ranks individual pages based on keyword match, PageRank, and on-page signals. AI engines rank entities (brands, products) based on their knowledge graph presence, structured data quality, co-citation frequency, and content format. You're optimizing a brand identity, not a page.

Priority order by commercial query volume in 2026: ChatGPT Search (38% of AI searches), Perplexity (22%), Google Gemini (18%), Bing Copilot (10%), Claude (6%). B2B SaaS should prioritize ChatGPT + Perplexity. Consumer brands: ChatGPT + Gemini. Start with ChatGPT Search —” it has the highest volume and best public documentation.

Add these exact lines to your robots.txt: User-agent: GPTBot Allow: / User-agent: OAI-SearchBot Allow: / If you use Cloudflare, you also need a WAF bypass rule —” robots.txt alone won't prevent Cloudflare Bot Fight Mode from blocking these crawlers.

Cloudflare's Bot Fight Mode uses behavioral fingerprinting that ignores robots.txt. Fix: Go to Security > WAF > Custom Rules. Create a rule with expression: (http.user_agent contains 'PerplexityBot') or (http.user_agent contains 'GPTBot') or (http.user_agent contains 'OAI-SearchBot'). Set Action: Skip all remaining custom rules.

llms.txt is a Markdown file at yourdomain.com/llms.txt that gives AI crawlers a curated site overview. Format: H1 = company name, brief paragraph description, then H2 sections for Products, Pricing, Docs, and Key Pages —” each as Markdown links. It guides AI understanding rather than controlling access (that's robots.txt's job).

llms.txt is a concise index (what AI crawlers discover first). llms-full.txt is an optional expanded version with full documentation. Start with llms.txt —” it has the most implementation support. Add llms-full.txt only if your product requires detailed technical documentation for AI understanding.

Three methods: (1) Check Cloudflare Firewall Events for blocked requests from AI crawler IPs, (2) Use Optymia's Crawler Intelligence audit —” it simulates GPTBot, OAI-SearchBot, and PerplexityBot against your URLs, (3) Test manually: curl -A 'GPTBot/1.2' https://yourdomain.com —” you should get HTTP 200, not 403 or a redirect.

Entity grounding is the process of establishing your brand as a verified, unambiguous entity in AI knowledge graphs. Without grounding, AI engines can't confidently identify your brand —” leading to 0 citations even if your content is excellent. The primary grounding assets are: Wikidata Q-item, JSON-LD Organization schema with sameAs links, and Google Knowledge Panel.

Go to wikidata.org and click 'Create a new item'. Add: label (company name), description (one-line description), and properties including: instance of (Q4830453 = business), official website (P856), LinkedIn ID (P4264), founded (P571), and sameAs links to Crunchbase/G2. Optionally add industry (P452). This typically takes 20-30 minutes but has the highest ROI of any GEO action.

Priority order: (1) Organization (homepage) —” establishes brand entity with sameAs links, (2) SoftwareApplication (product page) —” enables product recommendation queries, (3) FAQPage (any Q&A content) —” directly extracted for AI answers, (4) AggregateRating (from G2 reviews) —” signals social proof to AI engines. All four together put you in the top 10% of schema density.

Wikidata entity creation: 2-4 weeks for initial citation lift. Organization schema: 1-2 weeks if AI crawlers already have access to your site. Full entity grounding (Wikidata + schema + 20 G2 reviews): 6-10 weeks for measurable SoM lift. ChatGPT Search responds faster (2-4 weeks) than base model training (can take months).

Perplexity's RAG layer strongly prefers: direct-answer paragraphs (answer in first 2-3 sentences, no preamble), FAQPage schema Q&A pairs, original data points with source attribution, and comparison tables for 'best X' queries. Long introductions, promotional language, and content without clear authorship are frequently skipped.

Google AI Overviews perceive Reddit as unbiased third-party opinion (higher trust) vs. branded content (promotional). Reddit's direct conversational format also matches AI Overview extraction preferences better than formal blog posts. Fix: create query-matched content pages (H1 = the exact question), add FAQPage schema, and build authentic Reddit mentions.

Research threshold: 10+ reviews with keyword-rich descriptions begin to influence Perplexity citations for your category. Meaningful SoM impact: 25+ reviews. Competitive parity with established players: 50+ reviews. Reviews must contain your category keywords naturally —” not just 'great product' style feedback.

Write for humans, structured for machines. The best AI-citation content reads naturally but is architecturally optimized: direct answer first (for AI extraction), supporting context second (for human value), FAQPage schema (for structured extraction), and specific data points (preferred by AI citation engines). Never sacrifice human readability for AI optimization.

Co-citations are instances where your brand name appears alongside your target category keywords in third-party, authoritative content —” Reddit threads, G2 reviews, Quora answers, industry publications. AI engines use co-citation frequency as a key signal of category relevance and brand legitimacy. Building co-citation velocity (rate of new co-citation instances) is one of the fastest paths to SoM improvement.

Manual method: Define 20 target queries, run them through ChatGPT/Perplexity/Gemini monthly, record how often your brand is mentioned. Automated method: Optymia tracks SoM daily across all AI engines, showing your citation rate, position, and trend vs. competitors. Most brands need 8-12 weeks of baseline data before SoM trends become meaningful.

Optymia's Prompt Research Lab shows which queries trigger competitor citations but not yours —” the exact 'citation gap' queries. For manual research: run your 20 target queries and note every instance where a competitor appears but you don't. Those are your highest-priority content and entity grounding targets.

2026 benchmark across 500 brands: Top quartile = >25% SoM. Median = 8-12%. Bottom quartile = <3%. For competitive categories (10+ established players), achieving >15% SoM is strong. In newer categories (fewer than 5 players), leaders often reach 40-60%. Focus on your percentile rank vs. competitors rather than an absolute SoM number.