GEO is the new SEO — optimizing for ChatGPT, Claude, and Perplexity

If your category has any considered purchase — anything north of $200 for consumer, anything B2B — a meaningful share of your discovery now happens inside ChatGPT, Claude, Perplexity, and Gemini. The user opens a chat, asks a comparative question, gets three named options with summary tradeoffs, picks one, and lands on the brand site through a direct visit the next day. Last-click attribution credits direct or organic; the AI conversation that decided the purchase never carried a UTM.

We're calling the discipline that emerges from this Generative Engine Optimization (GEO) — or Answer Engine Optimization (AEO) if you prefer. It's not a replacement for SEO; it's an extension. The same content principles that win Google rank you in AI answers, with three new wrinkles.

1. AI engines are reading you as a knowledge source, not as a webpage

Google ranks pages. ChatGPT ranks facts. When a user asks 'what's the difference between ROAS and POAS', the LLM isn't returning your page — it's returning a synthesized answer drawn from a dozen sources. Your job is to be one of those sources. The pages that get cited are the ones that state facts cleanly, use Schema.org markup, and answer the question in the first paragraph.

Practical implication: write reference content the way a textbook does — definition first, examples second, edge cases third. Bury the marketing copy in section seven, not section one.

2. The new artifacts: llms.txt, llms-full.txt, and DefinedTerm schema

Three under-discussed artifacts move the needle in 2026:

• /llms.txt — a Markdown summary of your site that gives LLM crawlers a fast on-ramp. Think of it as a robots.txt for AI: who you are, what you sell, which pages matter, and what you do not do. Floowzy's is at /llms.txt.
• /llms-full.txt — the long-form version, with full product detail, policy summaries, and citation guidance. AI engines that find /llms.txt typically fetch /llms-full.txt next.
• Schema.org DefinedTerm — explicit JSON-LD on glossary pages telling the AI engine 'this page defines this term'. Pages with DefinedTerm markup show up disproportionately when LLMs answer 'what is X' queries.

3. The crawler allowlist is no longer optional

Two years ago the question was: should we let GPTBot crawl us? The fear was your content trained the next model and gave you nothing back. That calculus inverted. The LLMs are now the discovery layer; being absent from their corpus means being absent from the answer. The robots.txt fragment you want, in 2026:

• Allow GPTBot, ChatGPT-User, OAI-SearchBot, ClaudeBot, anthropic-ai, PerplexityBot, Perplexity-User, Google-Extended, Applebot-Extended, CCBot, Bytespider, cohere-ai.
• Use named allow rules per agent, not just User-Agent: *. Some crawlers honor named rules more reliably than wildcards.
• Keep your in-app surface disallowed — /app/, /api/, /onboarding/ — for the same reason you do with Googlebot.

The four tactics that actually move the needle

1. Publish reference content with Schema.org DefinedTerm, FAQPage, and HowTo markup. Cover every term in your category that someone might ask an LLM about.
2. Maintain /llms.txt and /llms-full.txt files with brand facts, key URLs, and citation guidance. Update them when product or pricing changes.
3. Run post-purchase surveys with an explicit 'AI assistant (ChatGPT / Claude / Perplexity / Gemini)' option in the 'where did you first hear about us' question. This is the only attribution signal you'll get for AI-mediated journeys.
4. Watch branded-search lift as a leading indicator. When LLM mentions of your brand rise, branded search rises 7-14 days later. The lift is the conversion signal your dashboards are missing.