Comparison Of AI Citation Patterns Offers Strategic SEO Insights via @sejournal, @martinibuster

BrightEdge published new data showing the different kinds of sites five AI search surfaces tend to show in generated answers. The data makes it possible to see how those differences shape which types of sites each AI engine shows, with strong implications for how to promote to each one.

The research focused on five AI search surfaces:

1. ChatGPT
2. Google AI Overviews
3. Google AI Mode
4. Google Gemini
5. Perplexity

AI Engines Cite Different Sources But Recommend The Same Brands

The BrightEdge research compared the top cited website sources across AI engines to measure how much they overlap (Source Overlap). What the data shows is that there was a wide discrepancy across the five AI search engines tested, with the lowest level of overlapping source citations between any two AI search surfaces at 16% and the highest level of agreement between any two engines at 59%.

• Lowest level of agreement: 16%
• Highest level of overlap: 59%

Significant Agreement In Brand Citations

BrightEdge also measured brand name overlap between the five AI search surfaces and found that there was more agreement between all five. The lowest overlap between any two AI surfaces was 36% and the highest level of overlap between any two surfaces was 59%.

• Lowest level of overlap: 36%
• Highest level of brand citation overlap: 55%

This suggests that name brands that are tightly associated with products and services tend to perform similarly across most of the tested AI search surfaces and may also reflect how widely brands are cited by trusted websites and possibly user intent and expectations.

In my opinion, the takeaway here is that associating a brand with a product or service in a consumer’s mind is a powerful way to influence user expectations which can then translate into branded search. This is something that the SEO community has been slow to pick up on, even though Google has been hinting at user signals playing a strong role in rankings. I say that the SEO community has been slow to pick it up because Google’s been doing this since at least 2004 (Navboost) and most directly with the brand navigation signals in search (Google’s brand signals patent).

Wide Divergence Of Cited Sources

BrightEdge analyzed citations from the five AI surfaces across three types of websites (Institutional, Commercial and Editorial, and User Generated Content) and discovered wide variance between all five engines, despite the convergence on citing strong brands.

Three Categories Of Sites Analyzed

1. Institutional sites, including government, academic, and big brand industry leaders
2. Commercial and editorial sites, including media, reviews, and listings
3. User Generated Content (UGC), including forums, video platforms, and social content

The data shows that every engine draws from all three categories, but weights the mix differently: institutional sources range from a low citation rate of 10% to a high of 26% of citations. Citations of UGC sites range from a low of 0.2% to a high of 18% of citations.

The largest category overlap across all five search engines are found in citations of corporate brand, commercial, and editorial sites, with a low end of 37% on Gemini to as high as 51% on AI Overviews.

BrightEdge offers this takeaway about that data:

“Review sites, comparison content, trade press, retailer listings, and finance data are the sources AI most frequently reaches for. Investment in PR, trade coverage, review site visibility, and category comparison content translates into visibility across every engine, not just one.”

Something that BrightEdge doesn’t mention is that AI search engines surface sponsored articles from trusted websites that are clearly labeled to conform with FTC guidelines on native advertising and Google’s guidelines on sponsored posts. This enables companies to tightly associate their brands with specific products and services and increase the likelihood of being cited in AI search surfaces.

Gemini And AI Overviews Differ On Website Authoritativeness

The difference between the kinds of websites Gemini and Google AI Overviews uses as sources shows that Gemini is more conservative, tending to show more trust toward institutional sites at a higher rate than user generated content (UGC). Institutional sites are academic, government, academic, and big brand sites.

AI Overviews, on the other hand, trusts both institutional and UGC sources of information, with nearly twice as many citations going to UGC websites.

• Authoritativeness Of Institutional Versus UGC Content
• Gemini: 26% institutional, 0.2% community
• AI Overviews: 10% institutional, 18% community

Another revealing finding is that there is a wide variance in thhe top level domains that are cited by each AI search surface. Gemini tended to link out to only the very most trustworthy and authoritative websites. For example, Gemini tended to cite .gov and .org websites at higher rates than any of the other AI engines.

Gemini: 13% .gov, 23% .org

Gemini’s answers tend to trust institutional websites more than user generated content, citing them 26% of the time but distrusts UGC sites, only citing them a fraction of a percentage point. AI Overviews trusts UGC content to a vastly greater extent. Why is that?

It could be that the technologies underlying Gemini and AI Overviews differ. For example, it could be that Google’s FastSearch, which prioritizes speed over other ranking signals, may be a reason why UGC sites are sources more often than they are in Gemini. It’s an interesting question.

I did an informal experiment by asking both Gemini and AI Overviews to compare the use of a specific op-amp (an electrical part) in a specific amplifier.

• Gemini’s answer cited institutional sources (Texas Instruments and the amplifier’s manufacturer).
• AI Overviews cited the two institutional websites but also multiple user generated content (UGC) sites.

Gemini’s answer was typically conservative, citing the institutional website (Texas Instruments, the manufacturer).

AI Overviews citations of various UGC sites were useful in the context of this question because actual users shared their experiences with this op-amp as well as actual electronic measurements of the op-amp and comparisons to other ones.

.Edu Sites Not Authoritative?

Another interesting finding is that all of the AI search engines don’t often cite .edu websites. Perplexity cited .edu sites at a higher rate than any of the other AI engines, citing .edu websites 3.2% of the time.

Those results contradict a longstanding belief in SEO circles that .edu sites are more authoritative. BrightEdge’s research shows that .edu sites are not authoritative for the kinds of questions that users are asking AI search engines.

ChatGPT Cites A Higher Diversity Of Sources

The data also shows that ChatGPT shows a more diverse variety of website sources, relying on its top ten sources only 18.5% of the time, with Google AI Mode right behind it with 19.4%. Gemini (26.3%) and Perplexity (26.7%) show a greater amount of the same sites drawn from their top ten.

Percentage Of Top 10 Sources

• ChatGPT: 18.5%
• Google AI Mode: 19.4%
• Gemini: 26.3%
• Perplexity: 26.7%

Gemini And Perplexity Rely On Authoritative Sites

Gemini and Perplexity tended to rely the most on authoritative websites. As already noted, Gemini trusted institutional sites the most and Perplexity cited .edu sites more than any of the other AI engines.

Perplexity showed a similar pattern of conservatively linking out to the most trusted and authoritative sites. BrightEdge’s report explains:

“Perplexity concentrates more of its citations in institutional medical, government, encyclopedic, and medical publisher sources than any other engine. Combined, those four categories account for approximately 30% of Perplexity’s citations.”

Five AI Engines, Five Distinct Citation Profiles

Here is the breakdown showing the citation distribution for each AI search surface, with Gemini and Perplexity showing a strong preference for authority sites.

Gemini

• 26% institutional sites
• 23% .org
• 13% .gov
• 0.2% UGC

Perplexity

• 86% of brand mentions appear in position 5 or earlier
• 30% of citations from institutional medical, government, encyclopedic, and publisher sources
• 22% institutional sites
• 3.2% .edu
• 1.5% UGC sites

ChatGPT

• Top 10 sources account for 18.5% of citations
• 20% .org
• 12% .gov
• 0.5% UGC

Google AI Mode

• Top 10 sources account for 19.4% of citations
• 14% institutional sites
• 7% UGC

Google AI Overviews

• 18% UGC
• 10.6% of citations from a single video platform
• 10% institutional sites
• 2.9% from a forum platform

Google AI Is Not One System

Google’s AI Mode and Ai Overviews show almost the same websites, with a 59% rate of overlap of cited websites. Gemini has the least amount of overlap.

• Gemini vs AI Overviews: 34%
• Gemini vs AI Mode: 27%

These differences show that the Google’s AI systems rely on different mixes of sources, with Gemini showing the widest amount of difference.

Takeaways

The data makes it easy to view each AI search surface with a shorthand description of what kinds of sources each AI engine tends to cite. There is a wide variance in source citations with clear preferences of which kinds of sites each engine prefers to link to. If there is one big takeaway from the data, in my opinion it would be the importance of establishing a brand connection to products and services.

Other Takeaways

• Gemini and Perplexity rely on high authority brand and institutional websites.
• ChatGPT cites a broader range of sources, showing a higher mix of websites.
• Google’s AI Overviews cites UGC sites more than any other AI search.
• Gemini shows the least amount of overlap among the three Google AI systems.
• AI Overviews and AI Mode show the highest level of overlap.
• Citation overlap varies widely across all five AI engines, indicating major differences in source selection.

Read the BrightEdge report: Why AI Engines Cite Different Sources but Recommend the Same Brands

Featured Image by Shutterstock/Toey Andante

GoDaddy Transferred A Domain By Mistake And Refused To Fix It via @sejournal, @martinibuster

GoDaddy is alleged to have transferred a domain name without authorization from it’s longtime registrant, transferring the domain name without the proper authorization and the required documentation. The victim spent nearly ten hours with customer service only to receive the response that there is nothing GoDaddy could do to fix the problem.

Domain Transfer Happened On A Saturday

Interestingly, the rogue domain transfer happened on a Saturday, which could be an important detail because some domain registrars outsource their customer service on the weekends and I have heard of other occasions where mistakes have occurred due to less quality control. I know of a case where high-value domain names worth six to seven figures were stolen on a weekend where an attacker was able to manipulate the weekend customer service into changing the email address of the account, enabling the thief to transfer away all of the one and two-word domains to another account.

What happened with this specific domain was not a case of robbery but something worse. A weekend customer service person made a mistake processing a legitimate domain name change by another GoDaddy customer, and instead of initiating the change on the correct domain they transferred the victim’s domain instead.

Compounding the error, GoDaddy’s weekend customer service failed to follow their own protocol for preventing unauthorized transfers, thereby allowing the domain to be transferred to someone else.

32 Calls And Nearly 10 Hours Of Phone Calls

The process of getting GoDaddy to reverse it’s mistake was a bureaucratic nightmare. They placed thirty-two phone calls and spent 9.6 hours on the phone talking to GoDaddy’s customer service.

“Lee called GoDaddy on Sunday. They confirmed the domain was no longer in his account but could not say where it went due to privacy concerns. They told him to email undo@godaddy.com. He did but did not receive any type of response when emailing that address. Of course Lee didn’t really feel like this was the appropriate level of urgency for this issue. He asked for a supervisor who was even less helpful. Lee was not happy. He may have said some hurtful things to GoDaddy’s support personnel during this call. That first call lasted 2 hours, 33 minutes, and 14 seconds.

On Monday morning, Lee and a coworker started working in earnest on this issue because there was still no update from GoDaddy. Calling in yielded a different agent who told Lee to email transferdisputes@godaddy.com instead. By Tuesday the address had changed again to artreview@godaddy.com. The instructions shifted by the day. It seemed like every GoDaddy tech support person had a slightly different recommendation.”

Compounding the error was that every time the victim called GoDaddy the call generated a new case number with none of the case numbers tied to any of the previous ones.

GoDaddy’s Response

After four days of trying to get through to someone at GoDaddy to get the problem resolved, GoDaddy finally responded with the following resolution:

“After investigating the domain name(s) in question, we have determined that the registrant of the domain name(s) provided the necessary documentation to initiate a change of account. … GoDaddy now considers this matter closed.”

GoDaddy’s response contained links to how to dispute a domain name change at ICAAN, the global organization that manages the domain name system, instructions on how to look up the domain name registration information and a customer support page about contacting legal representation.

That’s it.

Error Fixed, But Not By GoDaddy

The person who wrote about the issue said that they contacted a friend within GoDaddy who was then able to have the matter properly dealt with. Ultimately the error was not fixed by GoDaddy but by the innocent person who discovered someone else’s domain name in their GoDaddy account.

As previously stated, the entire fiasco began with a mistake on the part of GoDaddy on a legitimate domain change request. GoDaddy changed the domain name being changed to the victim’s domain name. The person who ended up with the victim’s domain name in their account contacted the victim and between the two of them they began the process of transferring the domain back to the rightful registrant.

Domain Name Ownership Is Non-Existent

A common mistake made by many developers and business owners is that they believe that they own a domain name. That is incorrect, nobody owns a domain name. Domain names are registered but never owned. The registration entitles the registrant to use the domain name but they never actually own it. That is how the domain name system works and it’s a part of the reason for why this issue played out the way it did. However,  the problem in this case was due solely to a mistake by GoDaddy.

The post that detailed the nightmare refers to GoDaddy’s “domain ownership protection” services but that’s not actually what it is called. There is no such thing domain name ownership protection.

What GoDaddy sells is a Domain Protection service that protects against unauthorized transfers and accidental expiration. The victim paid for that protection but because the error was due to GoDaddy’s own mistake the protection did nothing for the victim, the domain change went through without the proper documentation.

Read the blog post about how GoDaddy made a mistake and not only failed to fix the problem, they didn’t even acknowledge they had made a mistake.

GoDaddy Gave a Domain to a Stranger Without Any Documentation

Featured Image by Shutterstock/AVA Bitter

Google’s AI Overviews Cut Organic Clicks 38%, Field Study Finds via @sejournal, @MattGSouthern

A randomized field experiment finds Google’s AI Overviews reduce organic clicks to external websites by 38% on queries where they appear, while self-reported search satisfaction stays nearly unchanged when the summaries are removed.

The working paper by researchers at the Indian School of Business and Carnegie Mellon University was posted to SSRN this month. Authors Saharsh Agarwal and Ananya Sen describe it as the first randomized field experiment to test how AI Overviews affect user behavior in a real browsing environment.

How The Experiment Worked

Agarwal and Sen built a Chrome extension that randomly assigned 1,065 U.S. participants to one of three groups. People were recruited from Prolific and used Chrome on desktop. They also had to meet minimum browsing-history thresholds, so the sample reflects active desktop Chrome users rather than all Google users.

The control group saw Google Search normally. A “Hide AIO” group had the extension remove AI Overviews in real time. A third group was redirected to Google’s AI Mode for all searches. The study ran for two weeks per participant between January and February 2026.

Researchers pre-registered the experiment with the AEA RCT Registry before data collection. Over 95% of users in the Hide AIO group did not detect any changes during the study.

What The Researchers Found

AI Overviews appeared on 42% of queries, and removing them increased outbound clicks from 0.38 to 0.61 per search. They reduced outbound organic clicks by 38% on triggered queries, with zero-click search rising from 54% to 72%.

Effects were strongest when AI Overviews appeared at the top of the page, which occurred 85% of the time. Removing top-position AI Overviews nearly doubled outbound clicks, but lower ones had no effect.

Sponsored clicks and search frequency remained steady, indicating substitution between AI Overviews and organic visits.

The User Experience Finding

The endline survey used a 1-to-5 Likert scale to assess participants’ search experience. Responses from the control and Hide AIO groups were nearly identical across all measures, including satisfaction, information quality, and ease of finding information.

The researchers wrote that AI Overviews “divert traffic away from publishers without delivering measurable improvements in user experience.”

How AI Mode Compared

Participants directed to AI Mode had lower outbound click rates, higher zero-click rates, and lower satisfaction at endline compared to other groups.

The authors note that these results are exploratory, as higher attrition, some uninstalling of the extension, or finding workarounds may have influenced the outcomes.

Why This Matters

Independent measurements of the impact of AI Overviews on traffic have mostly been correlational. Pew Research found users click 8% of the time with AI Overviews, compared to 15% without. Ahrefs analyzed GSC data and reported a 58% drop in click-through rate for top-ranking pages when AI Overviews appeared.

This experiment adds a different approach by randomly assigning users to see AI Overviews or not, isolating the causal effect.

Google VP Liz Reid claims AI Overviews cut “bounce clicks,’ but provides no data backing the user-benefit side. The Agarwal and Sen paper tested a related question with a randomized design, finding no measurable change in satisfaction or ease of finding info.

Looking Ahead

The paper is a draft on SSRN and is not peer-reviewed. Authors will add more results, and we will provide an update if findings change.

AI Overview CTR Fell 61%, But Clicks Didn’t Collapse via @sejournal, @MattGSouthern

Brand-cited AI Overview CTR fell 61% from Q3 to Q4, according to a new report from Seer Interactive, but the clicks on those pages barely moved.

The drop looks alarming on a dashboard, though it isn’t quite what it seems. Seer’s analysis of 5.47 million queries across 53 brands clearly shows what’s happening

What Happened In Q4

In September, brand-cited pages in AI Overviews received 15.8 million impressions and 398,798 clicks, with a CTR of 2.52%.

In October, impressions doubled to 33.1 million, and clicks increased slightly to 400,271, but CTR dropped to 1.21% as rapid impression growth outpaced clicks.

This isn’t a performance collapse but a math issue caused by faster impression growth than clicks.

November Is A Different Story

November’s impressions rose to 39.5 million, but clicks dropped to 301,783, and CTR fell to 0.76%.

Something pulled clicks down while visibility increased, and Seer’s data can’t explain why. For Q4, both patterns combine into a 61% figure, showing it’s important to analyze months separately in Search Console data.

What Seer Can’t Tell You

The agency is clear on one limit: it can’t determine whether the October impression surge was due to Google serving AI Overviews for more queries where brands were already cited, or because the brands earned citations through their SEO. Both explanations fit, and neither can be confirmed without a detailed analysis of the account.

Websites with similar data face the same ambiguity. Growing impressions are good if earned, but noise if they result from Google’s decisions. Your dashboard might not clarify this without account-level query analysis.

How This Fits With Past AIO CTR Coverage

Several studies show lower CTRs when AI Overviews appear. Ahrefs analyzed 146 million results and found a 20.5% AIO trigger rate, which was higher for informational and question queries.

A SISTRIX analysis in Germany reported a 59% drop in CTR at position one with AIOs, and Pew Research found that U.S. users clicked 8% of the time with AIOs versus 15% without.

Seer’s October data raises the question of whether a falling CTR on cited pages always means fewer clicks or can indicate greater visibility with the same click count.

Other Findings Worth Noting

Brand-cited pages get about 120% more clicks per impression than uncited pages on AIO SERPs, but cited pages lag behind no-AIO pages by 38%. A citation helps, but it doesn’t restore previous rankings.

Seer reports that organic CTR on AIO SERPs rose from 1.3% in December 2025 to 2.4% in February 2026, but calls this a leveling off rather than a recovery and advises against forecasting based on two months’ data.

Why This Matters

A falling CTR in your Q4 data doesn’t necessarily mean you’re losing clicks; check impressions for the same period before assuming there’s a problem.

Benchmarks show general trends, but your data tells your specific story. If clicks stay flat or grow faster than impressions, it’s a different issue than actual decline.

Looking Ahead

The main thing to watch is whether added AI Overview visibility starts driving more clicks, or whether cited pages continue absorbing more impressions without much traffic upside.

If that pattern holds, the value of being cited may look different from what CTR alone suggests. You may need to separate visibility, clicks, and citation coverage before deciding whether AI Overview exposure is helping or simply changing how performance gets measured

Featured Image: TaniaKitura/Shutterstock

Google Pushes “Bounce Clicks” Explanation For AI Overview Traffic Loss via @sejournal, @MattGSouthern

Google’s head of Search, Liz Reid, told Bloomberg’s Odd Lots podcast that AI Overviews are reducing “bounce clicks” from publisher pages, continuing an argument she has made in public appearances since last year.

Reid appeared on the April 23 episode of Odd Lots. Hosts Joe Weisenthal and Tracy Alloway asked how AI Overviews affect publisher traffic and ad revenue.

What Reid Said

Reid described what she called “bounce clicks” as the category of clicks AI Overviews are reducing.

She said users who quickly click and return to search no longer need to visit the page because they get the fact from the Overview. Those wanting to read longer still click through. She acknowledged fewer ad clicks for some queries but said increased query volume balances this. The argument aligns with Reid’s points in other public appearances.

The Pattern

Reid published a Google blog post in August stating that organic click volume from Google Search to websites was “relatively stable” year-over-year and that “quality clicks,” defined as visits where users don’t quickly click back, had increased.

In an October Wall Street Journal interview, she explicitly used the phrase “bounced clicks” and said that ad revenue with AI Overviews had been relatively stable.

The Bloomberg appearance makes the same basic case Reid made in August, describing some lost clicks as low-value visits where users would have quickly returned to Search.

What Reid Didn’t Say

In none of those three appearances has Reid provided supporting data.

Her August blog post included no charts, percentages, or year-over-year comparisons. On Bloomberg, she told Weisenthal and Alloway that Google tracks whether people come to search more often as one of its key signals, without providing numbers.

Weisenthal and Alloway asked about traffic and monetization, but the interview didn’t include follow-up questions requesting evidence for Reid’s explanation.

Google has not publicly shared data that would let outside observers test that distinction.

What Independent Data Shows

Chartbeat data published in the Reuters Institute’s Journalism and Technology Trends and Predictions 2026 report found that global publisher Google search traffic dropped by roughly a third. Google Discover referrals fell 21% year-over-year across more than 2,500 publisher websites.

Seer Interactive’s analysis found that organic click-through rate for queries with AI Overviews fell from 1.76% in 2024 to 0.61% in 2025, a 61% drop. Seer noted those queries tend to be informational searches that historically had lower CTRs.

Pew Research Center’s study of 68,000 real search queries found users clicked on results 8% of the time when AI Overviews appeared, compared with 15% when they did not.

Digital Content Next, a trade body whose members include the New York Times, Condé Nast, and Vox, reported a median 10% year-over-year decline in Google search referrals across 19 member publishers between May and June 2025. DCN CEO Jason Kint said at the time that the member data offered “ground truth” about what was happening to publisher traffic.

Why This Matters

Reid’s “bounce clicks” description answers a question the data raises, but it answers it without data of its own. That’s worth keeping in mind when evaluating any public claim from a platform that controls the measurements.

A business owner can’t verify from Reid’s Bloomberg appearance whether AI Overviews are cutting only low-value clicks or cutting across query types. The independent data measures total clicks and click-through rates, not the subset of clicks Reid describes as low-value. If Google has internal data that separates the two, it hasn’t shared it in the eight months since the August blog post.

Looking Ahead

Reid said that Google measures how often people return to Search. That signal tracks Google’s retention. Publishers need a traffic metric, but Google hasn’t shared one. Until it does, “bounce clicks” should be treated as a claim rather than a finding.

Google Won’t Act On Spam Reports If They Contain Personal Information via @sejournal, @martinibuster

Google updated their spam reporting documentation to make it clearer that spam reports are not wholly confidential and that it’s possible for personal identifiable information to be shared with the sites receiving a manual action.

Change In Response To Feedback

Google’s changelog noted that they were updating the spam reporting form based on feedback they’d received about personal information contained in the spam report that is shared with spammy sites that receive a manual action (formerly known as a penalty).

The update contains a new notice that spam reports containing personal information will not be processed.

The changelog noted:

“Clarifying when and why we may take manual action based on spam reports
What: Further clarified when and why we may take manual action based on spam reports.
Why: To address feedback we received about the change on using spam reports to take manual action.”

Google removed the following from their documentation:

“If we issue a manual action, we send whatever you write in the submission report verbatim to the site owner to help them understand the context of the manual action. We don’t include any other identifying information when we notify the site owner; as long as you avoid including personal information in the open text field, the report remains anonymous.”

The above wording was replaced with the following:

“Don’t include any personally identifying information in your submission. To comply with regulations, we must send the submission text to the site owner to help them understand the context of a manual action, if one is issued.

Because of this, we won’t process your submission if we determine it contains personally identifying information to protect privacy. Not including such information fully ensures your information is safe and prevents your submission from being discarded.”

Action Moving Forward

On the one hand it’s good that Google won’t proceed with a manual action if the report contains personal information. This means that if you’re submitting spam reports to Google, don’t name your site, business name, personal name or anything else that you don’t want the affected spammer to know.

Read the updated documentation here:

Report spam, phishing, or malware

Learn more about Google’s spam reporting tool: Google Just Made It Easy For SEOs To Kick Out Spammy Sites

Featured Image by Shutterstock/andre_dechapelle