TL;DR: You don't need three AI SEO strategies. Roughly 80% of what gets a page cited by ChatGPT, Perplexity, and Gemini is the same writing discipline. What genuinely differs is configuration and measurement: crawler access, index dependency, refresh cadence, and attribution style. Splitting your content budget three ways on day one is how you turn one strong signal into three weak ones.
I am Akira. Across our GEO engagements, the pattern is consistent enough that I'll put a number on it — 80/20, shared versus per-engine. That's our characterization of where effort lands, not a lab measurement. But until the shared 80% is handled, per-engine tuning is effort spent in the wrong place.
The Universal 80%: What Gets Content Cited Everywhere
Five practices. Do them once, correctly, and they serve every engine — this is the shared SEO foundation under any GEO program:
- Self-contained paragraphs. Each one must survive being lifted out of context — because that's exactly what retrieval does to it.
- Qualified claims. "When resources are limited" beats absolutes. AI engines hedge; content that already hedges gets reused.
- Answer-first structure. Lead with the answer, phrase headings as questions, explain after.
- Stated relationships. Show how numbers compare; don't stack terms and hope the model infers context.
- Something worth citing. Original data, real test results, an observation nobody else published. This is the Answer Asset principle in our LLM-SEO methodology — citation is a reward for evidence, not formatting.
The Four Dials That Actually Differ Per Engine
Scope note: this is four surfaces, not three. Gemini apps and Google AI Overviews are both Google products but governed by different controls. Treat them separately or misconfigure both.
| Surface | Crawler to allow | Bound to Google index? | Recency weighting | Attribution style | |---|---|---|---|---| | ChatGPT | OAI-SearchBot (search); GPTBot is a separate training decision | Partially — retrieves via a third-party index (Bing, prominently) plus OpenAI's own | Moderate; higher on news-shaped queries | Inline links, few sources | | Perplexity | PerplexityBot | No — its own index, aggressive live fetching | High — visibly favors fresh pages | Dense numbered citations | | Gemini apps / AI Mode | Googlebot; Google-Extended governs training/grounding | Tightly — grounded in Google Search | Moderate | Source tray, fewer in-text attributions | | Google AI Overviews | Googlebot only — nosnippet / data-nosnippet / max-snippet / noindex are the controls | Tightly | Moderate | Link cards beside the answer |
Dial 1: Crawler Access Is the One Hard Gate
Every AI engine runs its own crawler, and you grant access to each one individually. Think of it as membership cards at different malls — a card at one gets you nothing at another. The industry's most expensive confusion: Google-Extended does not control AI Overviews. It governs training and grounding for Gemini-class products. AI Overviews is Google Search itself, running on Googlebot, governed by the nosnippet family. Every AI SEO and GEO audit we run checks these separately, because assuming one switch covers everything is how sites quietly vanish from a surface they paid to win. (The full diagnostic sequence is in our GEO Audit.)
Dial 2: Only Two of These Surfaces Care About Your Google Rankings
Gemini and AI Overviews assemble answers from Google's index, so conventional SEO rankings shape the pool they draw from. ChatGPT and Perplexity don't work this way — which is where GEO and SEO measurement genuinely diverge. Weak Google rankings give you a genuinely better relative shot on Perplexity and ChatGPT. But every engine retrieves from some index. A page indexed nowhere is retrievable nowhere. Loose coupling to Google is not independence from search.
Dial 3: Perplexity Rewards Freshness Enough to Change Your Calendar
Perplexity crawls near-real-time and visibly favors recently updated pages. Your dateModified must reflect reality — and a quarterly refresh cycle may simply not be frequent enough. This is the one engine where publishing cadence is a ranking input, not a vanity metric.
Dial 4: Attribution Style Changes What a Citation Is Worth
A Perplexity citation is traceable to clicks. A Gemini or AI Overviews mention behaves more like brand exposure. If your AI SEO reporting only counts sessions, you will systematically undervalue the Google side of the ledger. Measure per engine, with metrics that match each attribution style — that's the point of the LLM KPI framework.
What We Deliberately Don't Do
- Three drafts, one per engine. Splits one strong signal into three weak ones.
- Rewriting core content per engine. The five principles need doing once.
- Chasing which index ChatGPT uses this quarter. Index visibility is the entry ticket; the chase is a distraction.
- Assuming vendor documentation maps 1:1 to your site. Every site starts from a different baseline.
The Diagnostic Pattern Worth Naming
A site runs a crawler-access audit plus a genuine content refresh. Next quarter: Perplexity citations climb, AI Overview appearances stay flat. That asymmetry is almost never a content problem — the same passages are being cited elsewhere. It means Google's retrieval pool isn't reaching the site: a conventional index-visibility problem, fixed with conventional SEO work, not more passage editing. Different engines, different playbooks — and the first job is working out which playbook you actually need. If you're still framing the decision itself, start with Why GEO.
Does Query Language Change Which Engine Cites You?
Yes — mechanically, not translationally. Each language draws on different training corpora and retrieval pools, so blending them averages two unrelated systems. Our Hong Kong SERP sampling (June–August 2026) recorded AI Overviews on 29 of 36 Chinese-language queries (80.6%) versus 12 of 19 English queries (63.2%). Caveat stated alongside the number: the Chinese set skewed consumer-commercial, the English set B2B — language and topic are confounded. Treat it as an unresolved observation, not a law. The operational rule: set sampling region and query language deliberately, and report them separately. Prompts about a Hong Kong purchase sent from US infrastructure in English measure a market you don't sell in.
Where Per-Engine GEO Work Sits in the Loop
In Mercury Orbit terms — the customer loop the rest of the stack serves — citation is quarter one, not the whole product. The per-engine work concentrates in three places: baseline (each engine separately, before anything changes), access and schema (crawler permissions plus Google's snippet-level controls), and monitoring (per engine, feeding back into the shared content layer). The writing — most of the effort — is one job for all of them.
Which claims here are documented versus observed? Crawler names, Google-Extended behavior, and the nosnippet family: documented, verifiable. How strongly Perplexity favors freshness, and the exposure value of attribution styles: our tracked observation. No platform publishes full ranking logic — take the second category seriously, not as scripture.
Stop splitting content three ways. Start measuring four surfaces. One SEO foundation, four GEO dials — that's the whole strategy.
FAQ
If we can only resource one engine, which should we prioritize? It depends on your SEO baseline and audience behavior. Solid Google rankings make access controls the cheapest, fastest GEO win. If trackable click-through is the goal, Perplexity's attribution style delivers more measurable returns.
Does blocking AI crawlers protect our content without downside? No. Blocking one crawler only affects that engine — and surrenders whatever exposure and traffic it could have sent. It's a trade-off, not pure protection.
We're cited on Perplexity but absent from AI Overviews — what does that tell us? Rarely a content quality issue. More often a conventional SEO index-visibility problem on the Google side, which needs a different fix from more writing.
Not sure where your pages stand on each engine? The GEO Scorecard runs the free citability check; the GEO Audit turns it into a 48-hour per-engine baseline.
Mercury Technology Solutions: Accelerate Digitality.
