GEO

Which AI Engines Should You Optimize For First?

Which AI engines to optimize for first; prioritizing ChatGPT, Google AI Overviews, Perplexity, Gemini, Grok, and Claude based on audience and effort.

ai enginesgeoai search prioritizationanswer engineschatgptperplexity

You should optimize for the two or three AI engines your buyers actually use, because the content structure that earns citations is nearly identical across engines and depth in a few surfaces beats thin coverage of many. ChatGPT and Google AI Overviews are the default anchors for most startups, Perplexity dominates research-heavy audiences, and Gemini, Grok, and Claude matter where your niche hangs out. The Conductor AEO/GEO benchmarks report shows the same citation mechanics win across engines, and DemandSage's Perplexity statistics show the research-heavy engine growing quickly for technical audiences, so prioritization is about audience, not technique.

Why Can't You Just Optimize for All Engines at Once?

You can, but you should not try to tailor content per engine. The retrieval weights differ slightly, but the citation requirement is the same: a direct, extractable, trustworthy answer. Spreading thin effort across ten engines produces ten mediocre surfaces, while going deep on three produces pages that win everywhere.

The difference between SEO, AEO, and GEO is the lens, not the page. Write one definition-first, question-form, stat-backed page and most engines will pick it up. Prioritization simply tells you where to measure and iterate first.

How Do You Choose Which Engines Matter for Your Audience?

Map your buyers to their default assistant. A B2B buyer evaluating tools asks ChatGPT or checks Google AI Overviews. A developer or analyst asks Perplexity, which leans on research and citations. A consumer in an X-native community gets answers from Grok. A Google-first consumer sees Gemini and AI Mode. Pick the three that match where your ICP asks questions.

If you are unsure, measure. Run brand-mention monitoring across LLMs for a month, then look at which engines already mention you or cite competitors. The engines where your competitors appear and you do not are the ones to fix first.

What Does a Realistic GEO Workload Look Like?

Optimize deeply for two engines, track the rest. Deep optimization means: build the citable page, earn a citation, measure the referral impact, and iterate on structure. Tracking the rest means monitoring whether your brand enters their citation sets without dedicated work. That is a sustainable workload for a lean team.

The best geo tools for b2b startups help here, because they collapse multi-engine monitoring into one dashboard. You see which engines cite you, which pages, and which queries, then spend effort where the gap is.

What Is the Order of Operations?

Start with ChatGPT because it is the largest answer surface for most startups, and the page structure that wins there wins elsewhere. Then add Google AI Overviews and Perplexity, since together those three cover most B2B intent. Add Gemini, Grok, or Claude only when your buyer research says your niche lives there.

Within each engine, the loop is the same: publish or fix the page, wait one to three weeks, check citations, and refresh. The geo content refresh workflow keeps pages in the rotation once they start earning citations.

How Do You Know When to Add Another Engine?

Add an engine when it starts appearing in your brand-mention reports or when competitive tracking shows your competitors cited there while you are not. Otherwise, leave it on the monitoring list. Engines that never surface your category cost nothing to ignore until they do.

We keep our own citation monitoring running across ChatGPT, Perplexity, Google AI Overviews, Gemini, Grok, Claude, and DeepSeek, but our clients actively optimize for the two or three where their buyers are. The monitoring catches shifts; the optimization follows the audience.

How Conbersa Prioritizes AI Engines for Clients

Conbersa helps clients pick their top engines by audience, then builds the single citable structure that wins across all of them, tracked in one managed AEO/SEO service. We monitor mentions across every major engine, so when a new engine starts surfacing a category, clients see it immediately and can respond.

We built this because the engine count keeps growing while the winning content stays the same. Pick where your buyers ask questions, optimize deeply there, track everywhere else, and let the structure do the rest.

Neil Ruaro
Founder, Conbersa

We run agentic distribution on a fleet of real phones — and write up what we learn helping founders escape the cold start. Got a topic you want covered? Tell us.

FAQ

Frequently asked questions

Start with the engines your buyers actually use: ChatGPT and Google AI Overviews for most B2B audiences, Perplexity for technical and research buyers, and Gemini, Grok, or Claude where your niche hangs out. The content structure that wins is nearly identical across engines, so prioritizing a few covers the rest.
No. Writing one clean, citable page wins citations across engines because the mechanics are shared. The value of prioritizing is focus: optimize deeply for the two or three engines your ICP uses, track the rest, and only invest more where gaps appear.
For most B2B and consumer startups, yes, because ChatGPT has the largest answer-surface audience. But an engine's importance is audience-specific: Perplexity dominates for research-heavy buyers, Grok for X-centric communities, and Gemini for Google-first consumers. Pick the engine your buyers use, measure there first, and let the shared structure cover the rest.
Very little. Definition-first openings, question-form sections, linked stats, and freshness win across ChatGPT, Perplexity, Gemini, Claude, and Grok. The main difference is retrieval weight, not the final citation requirement, so one structured page covers most engines. Build one strong page rather than a tailored page per engine.
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