Which AI platforms should I optimize for?
Direct answer
The primary AI platforms to optimize for are ChatGPT, Google AI Overviews, Perplexity, Claude, and Gemini. Each platform retrieves and cites sources differently, but all reward clearly structured, authoritative content with direct answers. Start by optimizing for ChatGPT and Google AI Overviews, which have the largest user bases, then expand to other platforms as your LLMSEO strategy matures.
Key facts
- ChatGPT and Google AI Overviews together represent the largest share of AI-powered search traffic
- Perplexity explicitly provides source citations, making it an ideal platform to measure LLMSEO performance
- Claude and Gemini use different retrieval approaches but share a preference for well-structured, factual content
- SEORav's AI Citation Checker monitors your citation presence across all five major AI platforms simultaneously
The list that matters in 2026
Five platforms cover roughly 95% of category-relevant AI search traffic in 2026: Google AI Overviews, ChatGPT (with browsing or SearchGPT), Perplexity, Microsoft Copilot, and Claude. Gemini is relevant if your audience is on Android or uses Google Workspace. Apple Intelligence is relevant if iOS users are core; it currently runs queries through ChatGPT for most synthesis tasks. Voice assistants (Alexa, Siri, Google Assistant) read the same JSON-LD schema, so optimisation work covers them by extension.
How to prioritise the five
Two factors decide the order: your audience overlap with each platform's user base, and the cost of optimising for each. Google AI Overviews is highest priority for most B2C and most local-search businesses (audience reach is enormous, and optimising for it overlaps almost completely with classic SEO). ChatGPT and Perplexity are highest priority for B2B (the user base skews professional and technical, and citations on those platforms compound brand authority). Claude is a priority for technical and developer audiences. Copilot is a priority for enterprise audiences using Microsoft 365.
The shared signals that cover most of them
Four edits move the needle on every platform: direct-answer paragraphs in the first 40-60 words after each H2, FAQPage or QAPage JSON-LD schema, refreshed dates with a "last updated" line, and specific examples (named tools, dated stats, worked scenarios). Doing those four to a page tends to improve its citation rate across all five platforms simultaneously, because the same retrieval-quality signals matter to all of them.
The platform-specific gaps
Where the platforms diverge: Perplexity rewards original content and inline-citable claims more than the others (because its product depends on attribution). ChatGPT favours conversational, comprehensive content with context (because its training rewards depth). Claude weighs schema less heavily (its training data already encodes most of what schema would tell it). Google AI Overviews biases toward pages already ranking in Google's top ten. The implication: a page failing specifically on Perplexity often needs more original data; a page failing on Google AI Overviews often needs better classic SEO.
What to test, and how often
Pick five questions that matter most for your category. Run each question through all five platforms monthly. Record which platforms cite you, which cite competitors, and what the cited source looks like. A four-week cadence tends to surface platform-specific patterns fast enough to act on them. The brands that win LLMSEO are not the ones with the most platforms covered; they are the ones with the fastest measurement loop.