Understanding the engines
BD GEO Tracker runs every prompt against four engines: ChatGPT, Claude, Gemini, and Perplexity. They answer the same question differently, and those differences matter when you're deciding what to optimize.
This guide covers how each engine answers, why they diverge, what we ask them, and where Google AI Overviews fit into the picture.
Why four engines
These four cover the bulk of consumer and prosumer AI search traffic. Other engines exist — DuckDuckGo's AI assistant, You.com, Brave's Leo, Kagi's Assistant — but their traffic share is small enough that tracking them adds cost without proportional signal.
If a fifth engine reaches meaningful share, we'll add it. Customers on Growth and Agency get new engines included at no extra cost.
How we query each engine
We send your prompt as a single-shot user message. No system prompt biasing, no follow-ups, no chain-of-thought instructions. We want the engine's default behavior — the same answer a real user would get if they typed your prompt cold.
For each engine, we use the public API where available, otherwise a stable browser-automation path. We rotate model versions to match each provider's current default (whatever a logged-in free-tier user gets is what we ask). When a provider updates their default model, we update within 72 hours.
We don't enable web-browsing tools for engines that have them as a toggle. The exception is Perplexity, where retrieval is the entire product — there's no non-retrieval mode worth tracking.
ChatGPT
The most-used AI engine, and the one that produces the most consistent answers across runs. ChatGPT tends to:
- Lead with the largest, most established brand in a category
- Name 3-5 alternatives with brief descriptions
- Cite few sources unless retrieval is triggered
- Maintain a fairly stable list of named brands week-over-week
What this means for your data: ChatGPT is the slowest engine to move. If you're new in a category, expect to wait 8-12 weeks before you appear in ChatGPT for most prompts. Once you appear, you tend to stay.
How to improve ChatGPT presence: ChatGPT's training data leans heavily on well-indexed, widely-linked content. Earning mentions on major industry publications, getting included in roundup posts, and being part of "X vs Y" comparison content all help. Direct technical SEO is a weaker lever here.
Claude
Conservative in its answers. Claude tends to:
- Hedge more than the other engines ("depending on your needs, options include…")
- Name fewer brands per answer, often just 2-4
- Default heavily to the market leader
- Refuse more prompts on content-policy grounds
- Cite sources rarely, even when grounded retrieval is available
What this means for your data: Claude is the hardest engine to move. The bias toward the market leader is strong, and the smaller named-brand surface means there's less room to land. If you're a challenger brand, expect lower share-of-voice on Claude than on the other three.
How to improve Claude presence: Claude has fewer obvious levers. The strategies that help most are the slowest: long-running PR, getting into the comparison-content ecosystem (Capterra, G2, industry "vs" pages), and time. Don't chase Claude share at the expense of the other three engines.
Gemini
Google's engine, and the one most likely to surface answers grounded in current web content. Gemini tends to:
- Cite real URLs more often than ChatGPT or Claude
- Favor brands with strong organic search rankings (unsurprising — same parent)
- Mix in conversational hedging with concrete recommendations
- Update its named-brand list faster than ChatGPT when a new player gains traction
What this means for your data: Gemini moves with your SEO. If your Google rankings for category-level queries improve, your Gemini share-of-voice tends to follow within a few weeks. The two metrics aren't identical — but they're correlated more tightly than any other engine pair.
How to improve Gemini presence: Traditional SEO is the lever. Schema markup, content depth on category-level pages, earned links from sites with high domain authority. If you have a strong SEO program already, you'll see Gemini results sooner than the other engines.
Perplexity
The outlier — Perplexity is a retrieval-first engine. It answers questions by searching the web in real time and citing every source. Perplexity tends to:
- Cite 4-10 URLs per answer
- Surface smaller, newer brands more often (because it's reading current pages, not training data)
- Vary answers more between runs (because the underlying search results change)
- Be the fastest engine to reflect new content
What this means for your data: Perplexity is the most volatile and the most actionable. If you publish a high-quality piece on your category today, you can see Perplexity mention rate move within a week.
How to improve Perplexity presence: Be cited. Perplexity's answer is built from the pages it retrieves, so the question becomes: which pages does Perplexity find when it searches your category? The cited URLs panel in your dashboard answers exactly that. Get mentioned on those pages — guest posts, sponsored mentions, earned roundups, partner content — and Perplexity will start citing you alongside them.
Why the engines disagree
Three reasons:
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Different training data cutoffs. ChatGPT and Claude have static training data with quarterly-ish refreshes. Gemini and Perplexity supplement with live retrieval. A brand that launched last month doesn't exist in ChatGPT's worldview yet, but Perplexity sees it.
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Different default behaviors on listing. Claude is comfortable naming two options and stopping. ChatGPT will name five. Perplexity will name everything it found in the top retrieval results. The surface area to land in is different per engine.
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Different incentives. Each engine optimizes for different things — ChatGPT for plausibility, Claude for caution, Gemini for grounding in Google's index, Perplexity for citable retrieval. Those incentives produce different answers to the same question.
What "coverage" means
A brand has "coverage" on an engine when it shows up consistently in answers to its target prompts. Coverage isn't binary — it's a spectrum from "never mentioned" to "leading the answer most of the time."
Strong coverage on one engine doesn't guarantee coverage on another. We see customers with 60% mention rate on Perplexity and 5% on Claude all the time. The work to fix the Claude gap is different from the work that earned the Perplexity coverage.
Trying to be evenly covered across all four engines is usually the wrong goal. Some engines will always lag (Claude for challengers, ChatGPT in fast-moving categories). Focus on the engines where movement is possible and your customers actually use.
Where Google AI Overviews fit in
Google AI Overviews — the AI-generated summary that appears above some Google search results — is increasingly visible. We don't query it directly because Google doesn't expose an API for it, and the overviews are inconsistent (they appear for some queries, not others; they vary by user, region, and signed-in state).
What we do for Agency-tier customers: we run a SerpAPI-mediated check against a subset of your prompts to detect whether an AI Overview shows up at all, and if so, whether your brand is named in it. This is reported as a separate metric in the dashboard, labeled "AI Overview presence." It's directional, not quantitative — treat it as a yes-no signal per prompt, not a continuous metric.
For Starter and Growth tiers, AI Overview tracking isn't included. The reason is cost: SerpAPI charges per query, and at Starter prices the math doesn't work. If AI Overview tracking is critical to your work, Agency is the tier.
Engine failures and partial snapshots
Engines fail. Rate limits, timeouts, content-policy refusals, occasional outages on the provider side. When an engine fails:
- The snapshot still finalizes with the engines that succeeded.
- The failed engine is marked on the snapshot timeline.
- Trend calculations exclude failed engines for that point in time so your rolling averages don't get distorted.
If one engine is consistently failing your prompts (more than 20% of runs), the dashboard surfaces a banner. Common cause: the prompt is triggering content-policy refusals on one engine but not others. Rephrase the prompt or drop it.
Choosing where to invest
If you have limited GEO budget, the rough order of leverage is:
- Perplexity — fastest to move, most actionable, citation-driven.
- Gemini — moves with your SEO, so any SEO investment compounds here.
- ChatGPT — slower to move, but the largest audience by far, and stable once you're in.
- Claude — hardest to move directly; usually moves as a lagging indicator of broader category presence.
Most teams should focus on the first two for the first six months. ChatGPT and Claude will follow as your category visibility grows.
What to read next
- Writing good prompts — if you haven't read it yet, this is the highest-leverage place to spend an hour
- Reports and exports — turn cross-engine data into something you can share