AI Search & AEO
What Google AI Overviews Cite vs ChatGPT and Perplexity
On 6 September 2026 we asked the same 21 B2B buying questions of ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews, in the United States, within a few minutes of each other. Four engines answered every question. Google showed an AI Overview on none of them. This post reports what each engine cited, what an Overview cites when it does appear, and why the first number to measure on Google is whether the surface shows up at all.
Key takeaways
- For 21 B2B buying questions asked on one day, Google AI Overviews appeared on 0 of 16 cleanly parsed searches. ChatGPT, Perplexity, Gemini and Claude answered every question. The comparison most posts promise cannot be made for this category because there was no Overview to cite anything.
- Across every search Answer Radar has run against Google AI Overviews to 6 September 2026, an Overview appeared on 2 of 20, both for the generic query 'best CRM for small business'. The niche buying questions triggered none.
- Perplexity attached exactly ten citations to every one of its 19 answers. ChatGPT answered 8 of 20 from memory with no sources at all, and cited 3.35 per answer across every measured answer.
- Where third-party samples compare surfaces on queries that do trigger an Overview, the overlap is small: Google leans on what ranks in Google plus YouTube and Reddit; ChatGPT on reference sites and vendors' own pages; Perplexity on the widest mix.
- An absent Overview is recorded as absence, graded absent, and excluded from presence and recommendation. It feeds the appearance rate, shown over shown plus absent, and that rate is the first thing to read on Google.
- The practical order for a B2B brand: measure appearance on your own questions, work the assistants where the recommendations are being made today, and treat the queries that do trigger an Overview as the Google list worth a page.
The question in the title is a common one, and a poster in r/digital_keda framed the test we ended up running: take the same set of prompts, run them through Google AI Overviews and ChatGPT, and compare which domains get cited and which brands get named. A reply set the expectation:
“They pull from very different signal sets, and the overlap is smaller than most people expect.”
We ran it on our own project and got a result nobody in that thread predicted: for our category, there was nothing to compare.
1What did we run, and what came back?
Answer Radar asked the 21 approved buying questions on our own project of all five engines, geography United States, language English, one sample per question, with no steering. 105 samples were requested; 99 returned before the run stalled with 6 outstanding, and the numbers below are over those 99. The run id is de56db16 and the full per-question detail is in our dataset file.
| Engine | Returned | Grounded (admissible) | Excluded by grade |
|---|---|---|---|
| ChatGPT | 20 answers, 1 error | 11 | 8 ungrounded, 1 thin |
| Claude | 20 answers | 17 | 2 ungrounded, 1 thin |
| Gemini | 21 answers | 20 | 1 thin |
| Perplexity | 19 answers | 8 | 11 thin |
| Google AI Overviews | 16 absent, 2 errors | 0 | 16 absent, 2 error |
Grounded means the engine searched and the answer carried enough to read a verdict from. Ungrounded means it answered from memory. Thin means it searched but named no product or attached nothing to verify. Absent means Google showed no AI Overview on a results page it parsed cleanly. Those grades are the reason every number in this post has a denominator beside it.
2What did Google do instead of citing?
It showed a normal results page. For 16 of our questions Answer Radar loaded a rendered desktop Google results page, found no AI Overview, and recorded the sample with status empty and reason not shown. Two searches failed at the provider and are counted on neither side. The appearance rate for this run is zero over sixteen.
Source: Linkeddit Answer Radar, run de56db16 and the two smoke checks of 6 September 2026; aggregate in the Google AI Overviews tracker.
This is not a parser failure and not a geography block. Google's Search Central documentation says Overviews appear only when its systems decide one is additive and that they often do not trigger. The shape of our questions, long vendor comparisons in a niche B2B category, is the shape that often does not. The same day, the generic query "best CRM for small business" triggered an Overview twice on single checks, with 12 and then 8 sources.
3What did ChatGPT and Perplexity cite for the same questions?
Everything Google declined to answer, the assistants answered. Perplexity attached exactly ten citations to every one of its 19 answers, across sixty-seven distinct domain votes; ChatGPT searched on 12 of 20 and attached 3.35 per answer across every measured answer. The domains they leaned on for our unbranded category questions were not the same.
| Question | ChatGPT cited | Perplexity cited |
|---|---|---|
| Best competitive intelligence tools for B2B SaaS | alpha-sense.com, contify.com, crayon.co, klue.com, meertrack.com | agilegrowthlabs.com, alpha-sense.com, contify.com, klue.com, meertrack.com, proven-saas.com, saashero.net |
| Best AI visibility tools for B2B SaaS | crowdreply.io, respan.ai, spottlo.com, tracemetry.com, wellows.com | alhena.ai, gracker.ai, llmpulse.ai, trakkr.ai, wellows.com |
| Best AI brand monitoring tools | getmentioned.co, meltwater.com, mention.com, mentionowl.com, reddit.com, techradar.com | aiclicks.io, airops.com, dageno.ai, moz.com, otterly.ai and five more |
| Which tools track how often ChatGPT mentions my brand | answered from memory, no sources | ahrefs.com, beamtrace.com, dageno.ai, keyword.com, llmpulse.ai, reddit.com, seranking.com |
| How do I monitor my brand's visibility in AI search | answered from memory, no sources | ahrefs.com, blog.hubspot.com, business.adobe.com, semrush.com, seranking.com, tryprofound.com |
Two patterns. First, ChatGPT answered the AI visibility and AEO questions from memory in five of six cases, so for those questions its recommendations (Semrush, Ahrefs, BrightEdge, Clearscope) reflect what it learned in training, not a page it read. Second, Perplexity cited reddit.com in two of these answers and Gemini in three, ChatGPT in two, Claude in none, the same ordering as our longer-run measurement, where 3 of 144 customer-project Perplexity citations were a Reddit page against 1 of 83 for ChatGPT.
A poster in r/SEO ran the same kind of check on their own category and reported the version of this most vendors feel:
“Of the 15 sources cited across the answers for my category, not one was my own domain.”
Our own domain was cited in 4 of ChatGPT's 45 domain votes and 3 of Perplexity's 67, almost entirely on questions that named us. The per-question detail, including where we were absent and what was cited instead, is in how we track our own AI visibility.
4What does an AI Overview cite when it does appear?
Our two observed Overviews are two observations, so the honest source for this section is other people's larger samples, read with their denominators. SE Ranking analysed 100,000 US keywords across 20 niches after Google moved AI Overviews onto a newer model and posted the results in r/GeminiAI: Overview appearance fell from 60.85% to 55.21% of keywords, source-less Overviews rose from 0.11% to 10.63%, and the most cited domains were youtube.com at 9.40% of citations, reddit.com at 4.39%, then facebook.com, quora.com and indeed.com. That is a vendor's sample over general keywords, and it says so.
On overlap with organic results, Search Engine Journal reported analysis putting 54% of AI Overview citations inside the top twenty organic results, up from about a third at launch. Ahrefs, in the comparison we covered in AI Overviews versus AI Mode, found 11% of Overviews carried no citation at all.
| Surface | Appears | Typical sources | How it cites |
|---|---|---|---|
| Google AI Overviews | Only when Google decides; often not, and 0 of 16 on our B2B questions | What ranks in Google, plus YouTube, Reddit and Q&A sites on general keywords | A short source list, often behind Google redirect links; some Overviews carry none |
| ChatGPT | Every question, but searched on only 12 of our 20 | Reference sites, review sites, vendors' own pages | Few citations, 3.35 per answer in our measured answers; none on memory answers |
| Perplexity | Every question, always searched | The widest mix: vendor comparisons, community threads, video, review platforms | Ten per answer in this run; 9.87 across our measured answers |
When an Overview does appear for one of your questions, Answer Radar resolves each Google redirect link to its publisher and records whether the Overview named or recommended you, so the comparison in the title can be made row by row. For our category, on this day, the row was empty on the Google side.
5Why is the overlap between engines so small?
Because each engine reads a different slice of the web and decides differently whether to read at all. Google's surface starts from its own index and ranking and adds a trigger decision on top. ChatGPT starts from memory and searches only when it judges the question needs it. Perplexity searches every time through its own layer. Gemini grounds nearly every answer and cites barely more than half. Claude searches most of the time and attaches few sources. Four different instruments, plus one that sometimes does not switch on.
A practitioner in r/GEO_optimization who watched a new site sit at zero citations across six engines for three weeks drew the conclusion that applies here too:
“The barrier isn't reachability, it's authority and retrieval ranking.”
For Google there is a third barrier before either of those: the surface has to appear. That is why Answer Radar reports an appearance rate in every Google AI Overviews segment and never pools it with the assistants. Pooling would turn sixteen absent Overviews into sixteen misses and send a team to fix pages Google never summarised.
See whether an Overview appears for your buyers' questions, and who it cites when it does
6How do you measure this for your own category?
- 1. Ask the same questions of every engine on the same day. A comparison across days compares Google on Tuesday with ChatGPT on Thursday. Ours ran within seven minutes.
- 2. Read appearance before presence on Google. If the Overview appeared on 2 of 20 questions, the presence rate is over two answers, and the eighteen tell you Google is not the surface deciding those buys today.
- 3. Separate memory answers from searched ones on ChatGPT and Claude. A memory answer that names a competitor is a fact about training data, not about a page. Eight of ChatGPT's twenty answers in our run were memory answers.
- 4. Resolve Google's redirect links. When an Overview does appear, its sources are often opaque google.com links until followed. Without resolving them the comparison in this post's title is a list of google.com against a list of publishers.
- 5. Keep the question set frozen and re-run. Google confirmed in late August 2026 that some Overviews now expand into a fuller AI Mode style answer by default, which will change what appears and what is cited. A frozen set is the only way to see it.
The help guides on tracking Google AI Overviews and reading the appearance rate walk through the rows. The ranking side, for when an Overview does appear on your questions, is in how to show up in Google AI Overviews.
Part of the whole picture
Frequently asked questions
Do Google AI Overviews and ChatGPT cite the same sources?+
Rarely, and for many B2B questions the comparison cannot even be made, because the Overview does not appear. In our run of 21 buying questions on one day, ChatGPT and Perplexity answered every question and Google showed an AI Overview on none of the 16 searches it parsed cleanly. Where studies have compared the two on queries that do trigger an Overview, the overlap is small: Google's surface leans on what ranks in Google plus community and video sources, ChatGPT on reference sites and vendors' own pages.
Why did Google show no AI Overview for our questions?+
Google decides per search whether an Overview is additive, and its own documentation says Overviews often do not trigger. Long, vendor-comparison questions in a niche B2B category are exactly the shape that often does not. The same day, the generic query 'best CRM for small business' triggered an Overview with 12 and then 8 sources on two single checks. Appearance depends on the query, and a brand should measure it before measuring anything else.
What does an AI Overview cite when it does appear?+
On general keyword sets, large third-party samples put YouTube and Reddit at the top of the cited domains and find that about half of citations overlap with the top twenty organic results for the query. In our two observed Overviews on 'best CRM for small business', the sources were vendor pages and review sites. The honest answer for your category is the one you measure on your own questions, because appearance and sources both vary by query type.
How is an absent AI Overview recorded, and does it count against a brand?+
Answer Radar records an absent Overview with status empty and reason not shown, grades it absent, and keeps it out of presence and recommendation rates. It counts toward the appearance rate, which is shown divided by shown plus absent, with provider errors on neither side. It is a fact about Google, not a miss for your brand, because there was no answer to be in.
Should a B2B brand optimise for AI Overviews at all?+
Measure first. If the buying questions in your category rarely trigger an Overview, the ChatGPT, Perplexity, Gemini and Claude answers to those same questions are where the recommendations are being made today. If your category has informational, question-shaped queries that do trigger Overviews, the appearance rate tells you which ones, and those are the queries worth a page.
How many of our questions did each engine actually answer?+
Of 21 questions, ChatGPT returned 20 answers and 1 error, Claude 20, Gemini 21, Perplexity 19, and Google AI Overviews 16 absent plus 2 errors, with 6 samples across the run never returning. ChatGPT answered 8 of its 20 from memory without searching, so its grounded sample was 11. Every number in this post carries its denominator for that reason.
Related guides
- Google AI Overviews tracker in Answer Radar
- How We Track Our Own AI Visibility With Answer Radar
- Google AI Overviews vs AI Mode: What Differs for Brands
- How to Show Up in Google AI Overviews (2026)
- Google AI Overviews by Country: Availability and Tracking
- Help: Reading the Appearance Rate Metric
- How to Rank in Perplexity: What It Reads and Cites
- Which Websites AI Engines Actually Cite