Three answer engines, three different citation behaviors. Here's what actually works for each one — not a generic "write good content" checklist.
Trained-knowledge answers rarely name a source. Browsing-mode answers do — and that's the version of ChatGPT most citation tracking actually measures.
It's built as a search-and-cite engine by default, so the fight isn't whether you get cited — it's which source out of five gets the reader's click.
Its grounding sits much closer to Google's own index than the other two, so classic technical SEO carries more weight here than anywhere else in GEO.
"GEO" gets talked about as if it's one target. It isn't. ChatGPT's default answers draw heavily on what was in its training data, and only reach for a live source when browsing is triggered or the question needs current information. Perplexity is the opposite: it's architected around live retrieval, so nearly every substantive answer comes with citations attached, and the real competition is over which sources make the cut. Gemini sits in between, but pulls disproportionately from Google's existing search index and knowledge graph — which means a page that's already ranking well organically has a real head start there that it doesn't automatically get in the other two. Treating all three as one undifferentiated "AI search" channel is why most GEO efforts plateau.
Before anything else, check your robots.txt. A surprising number of sites accidentally block OpenAI's crawler while chasing other GEO tactics. Once access is confirmed, structure the page so the direct answer sits in the first two sentences of a section — that's the part most likely to get lifted verbatim into a browsing-mode response.
Perplexity typically stitches together three to five sources per answer, favoring the ones with the most specific, dated, attributable claims. A page with "recent studies show" loses to a page with "a March 2026 analysis of 400 accounts found." Numbers with a named source beat confident-sounding generalities every time.
Because Gemini leans on Google's index, the fastest lever here isn't a new GEO tactic — it's the technical SEO fundamentals: valid structured data, fast load times, clean crawlability, and content that already earns a strong organic position for the query you want cited on.
Every engine does better at attributing a claim to you when your product names, statistics and terminology are phrased identically across every page that mentions them. Inconsistent phrasing for "freshness" reads as three different sources to a model, not one authoritative one.
The most common failure isn't bad content — it's infrastructure. Sites that block AI crawlers in robots.txt out of an old caution around scraping are invisible to all three engines by default, no matter how well the content is written. After that, the next biggest waste is publishing thin, near-duplicate pages targeting slightly different phrasings of the same question; it splits authority across pages instead of concentrating it in one page strong enough to be the obvious answer. And optimizing purely for one engine at the expense of the others is a real risk now that traffic increasingly arrives from all three.
“Most teams still ask 'how do we rank higher in ChatGPT' as if it's one search engine. It's three different retrieval systems wearing similar branding, and each one rewards a slightly different discipline.”