Cross-platform GEO comes down to one discipline: build a single, consistent, well-structured brand entity that every major AI answer engine can retrieve and trust, then tune a handful of platform-specific signals on top of it. You do not write five versions of your site for five models. You make your brand so clearly defined — same name, same claims, same proof, everywhere — that ChatGPT, Gemini, Perplexity, Copilot, Grok, and Google's AI surfaces all reach the same conclusion when a buyer asks for a recommendation. The platform tactics that matter — Bing indexing for ChatGPT, fresh citations for Perplexity, video and Google's index for Gemini — are refinements, not separate campaigns.
Key takeaways
- The AI discovery layer is fragmented across at least seven answer surfaces; optimizing for one leaves you invisible on the rest.
- Roughly 80-90% of the work is a shared core entity — consistent naming, Schema.org structure, and authoritative citations that every engine reads the same way.
- llms.txt is now best understood as a map for agents and in-product assistants, not a search-ranking lever — Google has confirmed it ignores the file for rankings and AI Overviews.
- Platform tactics differ at the margins: ChatGPT leans on Bing's index, Perplexity rewards freshness and primary sources, Gemini pulls from Google and YouTube, Grok summarizes recent X activity.
- You cannot eyeball this across engines; measure Share of Model and citation rate per platform with a tool like GEOly.
Why one engine is no longer enough
In the Google era, "optimization" quietly meant "optimize for Google," which held 90%-plus of search. Ignoring Bing was a rounding error.
That arithmetic is gone. A single buyer might brainstorm with ChatGPT, verify claims in Perplexity, compare products through Gemini or Google's AI Overviews, and ask Grok what people are saying this week. Each engine draws on different indexes, citation logic, and "personality." Rank in one and you can still be absent from the four where your customer actually decides.
The useful mental model is an oligopoly of intelligent agents, not a monopoly you can game with a single playbook. Your job is to be un-ignorable to all of them. What GEO is at its core is exactly this: engineering how generative engines describe and recommend you.
Build the core entity first
You cannot maintain five bespoke websites. You can build one brand entity robust enough that every model understands it identically. Three signals do most of the work.
Consistency
AI models cross-reference. When your positioning, product names, and basic facts — founding, category, flagship SKUs — match across your site, LinkedIn, Crunchbase, review platforms, and social profiles, the models resolve you to one confident entity. Contradictions, like a different tagline here or an old product name there, dilute that confidence and get you dropped from shortlists.
