Answer engines we track
ChatGPT and Google AI Overviews build their answers in genuinely different ways. Here's how each one works, what OptimizeCamp captures every time we ask a question on your behalf, and why you need both.
Quick recap: what’s an answer engine?
If you haven’t read AEO, GEO & AI search explained yet, the short version is this: an answer engine is any system that responds to a question with a written answer instead of a list of links to click through. ChatGPT and Google’s AI Overviews are both answer engines. This page is about the mechanics of those two specifically — how each one actually produces the words a user reads, and what OptimizeCamp pulls out of that process every time it runs.
The two tracks we track today
OptimizeCamp measures your brand’s presence on two answer engines right now: ChatGPT and Google AI Overviews. They’re built on similar underlying technology (large language models), but they answer questions through very different paths — which is exactly why tracking only one of them would leave you flying blind on the other.
How ChatGPT builds an answer
For every tracked prompt, OptimizeCamp sends your question straight to a ChatGPT-family model — the same words a real user would type, with no extra instructions layered on top, so the answer approximates what a person would actually see.
The question is sent as-is
Web search is switched on — every time
It answers quickly, like a normal chat
Citations come from the model’s own source list
How Google AI Overviews differ
A Google AI Overview is the AI-generated summary box that can appear above the normal blue-link results on a Google search. The mechanics are different from ChatGPT in one important way: Google decides, per search, whether a query deserves an AI Overview at all. Plenty of searches still return a plain list of links with no overview whatsoever.
No AI Overview shown is still a result
When a tracked prompt doesn’t trigger an AI Overview, OptimizeCamp doesn’t treat that as an error or a blank spot — it records it as a real, meaningful outcome: nothing was shown to the searcher for that question. That tells you something true about your visibility on that surface, so it’s counted rather than skipped. Contrast that with ChatGPT, which — because it’s a direct conversation — essentially always produces some answer.
When an AI Overview does appear, OptimizeCamp captures the overview’s text and the list of source links it references — the same shape of data as a ChatGPT answer: text plus an ordered citation list.
Note
OptimizeCamp is upfront about data quality: if a platform’s results for your project aren’t coming from a live call yet, the app labels that plainly next to the number — you’ll never see simulated data presented as a real answer.
What we capture from every run
Whichever platform answers, OptimizeCamp stores the same four things for every run:
| Field | What it is |
|---|---|
| Answer present | Whether the platform actually returned an answer for this question — false for a Google search where no AI Overview appeared. |
| Answer text | The full text of what the AI said, exactly as returned — this is what gets scanned for your brand and your competitors’ names. |
| Citations | The ordered list of source links the answer points to: URL, title (when given), and position — 1 meaning the first link listed. |
| Brand detections | Which tracked brands — yours and every competitor you track — were actually named in the text, plus the tone each was mentioned with. See Mentions, citations & share of voice for exactly how this works. |
Why you need both
ChatGPT and Google AI Overviews are different mechanisms answering different audiences in different moments — a forced web search inside a chat conversation versus a summary Google chooses to show, or not, above its normal results. A brand can be strong on one and nearly invisible on the other; nothing about your ChatGPT presence predicts your Google AI Overview presence, or vice versa. That’s why OptimizeCamp scores each platform separately, side by side, rather than blending them into one number you can’t act on.
More platforms are coming
OptimizeCamp is built so that answer engines are pluggable — each one is a self-contained adapter that knows how to ask its platform a question and hand back an answer in the same shape (text plus citations). That means adding a new answer engine later — Perplexity, Microsoft Copilot, Google’s Gemini — doesn’t require rebuilding anything upstream: the scoring, the dashboard, and the alerts all already know what to do with a new platform’s answers once it’s plugged in.
Key takeaways
- OptimizeCamp tracks two answer engines today: ChatGPT (a chat model with web search forced on) and Google AI Overviews (a summary Google may or may not show above search results).
- A missing Google AI Overview isn't an error — it's recorded as a real, meaningful result, because 'nothing was shown' is itself a visibility outcome.
- Every run captures the same four things: whether an answer came back, its full text, an ordered citation list, and which tracked brands were detected in it.
- The two platforms behave independently, so OptimizeCamp scores them separately — track both to see the full picture.
Next step
Now that you know how an answer is produced, see exactly how OptimizeCamp reads one: Mentions, citations & share of voice breaks down the difference between being named and being linked.