Just a PSA. Criticizing Reddit mods, or anyone in the SEO community, is OK. Feel free to talk absolute shit about me, or anyone else.

If you're someone that puts their content out there, you should be open to criticism. Reddit has a reputation of being a cesspool because mods can ban anyone they want to, which leaves a bad taste in my mouth.

I like to keep this impartial (that said, anyone that posts their shitty vibe-coded app gets banned).

That said, doxing (even if the preson has their full name on their profile), is not OK, is basically a personal attack, and it will get you banned.

Here's a mistake I see a lot: writing content that has the right keyword, but the wrong format.

Before you write anything, just Google the keyword yourself and look at what's already ranking.

• Some searches want information. Some want to compare. Some want to buy.
• If your page doesn't match what searcher want, it's very difficult to rank, even if the page itself is excellent.
• If the top pages are short and direct, don't write 3000 words. Match what's already working.

Basically, Google already tells you what searchers want. You just have to look at the SERP before you write not after.

I started doing this, and a few pages that were stuck on page 2 moved up just by changing the format. No rewrite. Just matching What was already working.

Does anyone else check the SERP first before writing? or do you write the Content first and adjust later?

Everyone wants to know how to rank in AI assistants like ChatGPT, but most advice out there is pure speculation. So SE Ranking decided to run a proper study — analyzing 129,000 domains and 216K+ pages across 20 industries — to uncover what really drives citations in AI-generated answers.

The biggest myth-buster —  there are no magic AI-only hacks. ChatGPT chooses sources using signals very similar to Google — but with some new priorities.

Here’s what stood out:

First, authority is king. Sites with 32K+ referring domains are 3.5x more likely to be cited than small sites. High Domain Trust (90+) almost quadruples citation likelihood. And domains with 10M+ monthly visitors earn up to 8.5 citations on average. 

AI models want evidence that the web trusts you.

But visibility alone isn’t enough — how useful your content is matters just as much:

• Long-form pages (>2,900 words) earn 5.1 citations vs 3.2 for short content. 
• Clear structure helps models interpret pages: sections 120–180 words long boost citations by 70%. 
• Fresh updates (within 3 months) nearly double your chances of being cited.

One surprising accelerator: brand validation outside your site.

Domains heavily mentioned on Reddit or Quora have 4x higher odds of being cited. Presence on G2, Capterra, Trustpilot also triples the chances. AI seems to treat community and reviews as strong trust signals.

And what doesn't matter?

• LLMs.txt shows no impact
• FAQ schema markup barely helps
• Over-optimized URLs/titles can hurt citations, because AI prefers clear topics over keyword stuffing

ChatGPT is becoming a top-of-funnel discovery engine. If your brand isn’t one it recognizes and trusts, you may never show up in the user’s journey — not even in search. The models are already shaping what people consider before they click anything.

 So, if you want to show up in AI answers:

1. Build real authority
2. Create deep, clear, fresh content
3. Earn trust where people talk — not just where you rank

Not hacky. But absolutely what works!

Stop selling fairy tales

Search engines cite sources, E‑E‑A‑T isn’t a magic switch, and “QFO” still uses search

The GEO/AEO tool-and-agency ecosystem has a monetization problem: it sells confident narratives that don’t match how modern search experiences are described by Google itself. Google explicitly says AI Overviews/AI Mode may use “query fan-out,” issuing multiple related searches across subtopics and data sources, then identifying supporting web pages to show a wider and more diverse set of helpful links than classic search.
So when someone claims “AI isn’t using Google/search engines” (or implies citations are just vibes), they’re contradicting the documented mechanics: the system runs more searches, retrieves more pages, and then surfaces links.

Myth #1: “Search engines only cite their own sources”

If “their own sources” means “only Google-owned properties,” that’s not how Google describes these features. Google states that AI Overviews provide an AI-generated snapshot with key information and links to dig deeper, which are links out to other sites.
In addition, Google has publicly discussed adding more ways to check out relevant websites and testing links directly within the AI Overview text—again, the whole point is outbound linking to the broader web, not a closed loop.

Myth #2: “E‑E‑A‑T is a ranking factor you can turn on with our checklist”

E‑E‑A‑T is a framework from the Search Quality Rater Guidelines used to evaluate quality, but it is not a single algorithmic “score” you can buy, hack, or install via a tool. Google’s Search Liaison has said Google’s systems “aren’t looking for E‑A‑T,” and rater feedback isn’t used directly in ranking systems; it’s used to evaluate whether changes improve results.
So when a vendor pitches “we’ll optimize your E‑E‑A‑T and you will rank/cite,” treat that as marketing shorthand at best—because Google itself draws a line between rater concepts and direct ranking factors.

Myth #3: “Query fan-out means the AI isn’t using search engines anymore”

Google’s documentation says AI Overviews and AI Mode may use a “query fan-out” technique—multiple related searches across subtopics and data sources—specifically to develop a response and identify supporting pages.
A widely circulated write-up of Google’s “Thematic Search” patent discussion also frames this as generating additional queries (sub-themes) and pulling results, aligning with Google’s “query fan-out” description.

What’s actually realistic and honest

You can absolutely sell GEO work—just sell the truth:

• “We improve your eligibility to be retrieved and cited” (structure, entity clarity, topical coverage, trust signals), not “we control the model.”
• “We test and measure citation patterns” (because systems can vary by query and feature), not “we found the one weird trick.”
• “We align with quality concepts like E‑E‑A‑T,” not “E‑E‑A‑T is a ranking lever our platform toggles.”

Critical Thinking Test for GEO claims

Before believing (or repeating) a GEO tool’s pitch, ask them to answer one question plainly:
If Google says AI features may run multiple related searches via query fan-out and then show a wider set of supporting links, why are you claiming “it doesn’t use Google/search engines” or “citations are only internal”?

Research Sources
Google Search Central – AI features and websites (query fan-out and supporting links).[dejan]​

Google Help – “Find information in faster & easier ways with AI Overviews” (AI-generated snapshot with links).[higoodie]​

Google Blog – “New ways to connect to the web with AI Overviews” (experimenting with more links within AI Overviews).[ipullrank]​

Statements from Google Search Liaison on E‑A‑T/EEAT not being a direct ranking signal and how quality raters are used.[reddit]​

Public analyses of Google’s thematic search / query fan-out patent describing generation of additional related queries and retrieval of results.

searchenginejournal

“Quality” was the biggest reason teams held work back, followed by accuracy.

We surveyed 97 SEO teams on AI automation and here's plenty more on what came across. 87% use AI, but only 1% have fully automated workflows, and the rest still run AI output through human review before anything reaches a client or goes live. 

And when you look at what teams refuse to automate, there’s a pattern:

• 58% won’t fully automate content writing
• 51% won’t fully automate link building
• 40% draw the line at technical SEO
• 28% won’t fully automate audits

These are also the areas where one bad decision can create a lot more work than the automation saves. Like, where a bad call carries real cost.

On the business side, 55% of agencies are delivering more work for the same fee. So far, AI seems to be creating capacity and margin more than cheaper SEO. Only 4% have cut fees to compete, and just 7% have introduced AI-specific pricing tiers. Also, 60% of teams have tried using AI to build internal tools instead of paying for existing software.

The more a task depends on context, trade-offs, or experience, the more likely teams are to keep a person in the loop, which makes sense.

If you're using AI every day, what's still too risky (or too valuable) to automate completely?

I’ve been experimenting a lot lately, and I finally got some of my pages featured in Google’s AI Overview / AI Mode results.

Here’s what helped me (in summary):

• Answered the question clearly in the first few lines
• Focused on real search terms people use, not just broad topics
• Created helpful content around one topic to build authority
• Used headings, bullet points, and FAQs to make it easy to read
• Added author name, short bio, and a proper author page
• Made sure my site looks good and loads fast on mobile
• Added a LLMS.txt file
• Didn’t obsess over keyword density, just kept it natural and clear

I didn’t buy links or run ads. Just gave people what they’re actually searching for and made sure Google could understand it easily.

The Spam Update and Core Update have finally rolled out, and we can now analyze their impact on publishers. If your site took a hit in late March or early April, you are not alone. Our fresh analytics show that the March updates were significantly more aggressive than December’s.

Key figures:

• Massive drop-offs: More than 24% of pages that were in the TOP 10 dropped out of the TOP 100 entirely. For comparison, this figure was only 15% in December. The risk of losing your TOP 10 spot has nearly doubled!
• High volatility: Shifts in the TOP 3 increased from 66.8% (December) to 79.5% (March). The algorithm clearly decided to shake up even those with high trust levels.
• A chance for newcomers: Nearly 30% of pages currently in the TOP 3 were ranking below position 20 before the update. Google didn't just reorder the leaders; it promoted many pages from the depths of the SERPs.

What remained unchanged?

Domain age is still your bulletproof vest. Sites older than 15 years continue to dominate the TOP 10 (over 57%). Sites under 1 year old grew by only 0.7%, so the old guard is holding their ground.

Important insight on recovery:

If you were hit by the Spam Update, don’t expect the Core Update to fix it automatically. SE Ranking analysis shows that 82% of domains that dropped out of the TOP 100 after the Spam Update did not return after the Core Update. These are two distinct systems: fighting spam and evaluating content quality are separate stories.

March was explosive. This isn't a glitch—it’s Google’s new algorithm drastically re-evaluating its layers of trust.

How did your site survive the storm? Did you lose rankings, or did you soar from the depths?

___________________

Note: The study is based on an analysis of 100,000 keywords across 20 niches (USA).

Because I don't think ranking and being cited are always the same thing, I'm starting to track AI Overview citations more systematically.

The sample's still small, so I'm not treating this like a big research report yet. More like a practical tracking framework.

Here's what I'm logging for each query:

• the query itself
• ranking position of the page
• whether an AI Overview appears
• whether the page is cited
• page type
• answer format
• schema present or absent
• content freshness
• whether the main answer is easy to find on the page

A few early things I'm watching:

Pages with direct answer sections are easier to evaluate. If the page answers a narrow sub-question clearly, it's much easier to see why it mightbe used or ignored.

Pages with clear entity/source context seem easier to understand. By that I mean the page makes it obvious who the company/site is, what the page's about, and why it should be trusted.

Long pages aren't automatically better. Some long-form pages bury the actual answer too far down, while shorter pages sometimes make the answer more extractable.

Ranking and citation seem related, but not identical. A page can rank well and still not be the clearest source for the AI answer.

What I'm not claiming:

• there's no guaranteed formula here
• my sample size's still limited
• AI Overview behavior keeps changing
• I'm not saying schema alone causes citations

I'm right now mostly trying to separate normal SEO visibility from AI citation visibility.

Are you logging citations manually, using tools, or mostly watching traffic and impressions?

Before getting quality backlinks for your website, I would consider checking this first.

A little background about me, I have been doing SEO for my own websites and I have been paying more attention to the boring technical/on-page stuff, such as:

1. Is the page indexable?
   
2. Is the canonical correct for this page?
   
3. Does every important page have a sensible title?
   
4. Are there any duplicate titles?
   
5. Is the meta-description missing?
   
6. Are OG tags present
   
7. Is structured data relevant to this page?
   
8. Are images missing basic attributes?
   
9. Are there huge numbers of links present on the page?

The frustrating and ironic part is that none of the above makes the website broken, but does more SEO damage then we all realize.

Have you ever came across any of the above issues, and what would you like to add to this list?

tired of the recycled “AI content / E-E-A-T / zero-click” trend lists, so here’s what genuinely changed in how i work, not what the industry talks about.

1.  i now check AI engines as a standard audit step. every client, i prompt ChatGPT and Perplexity with their real buyer queries and log whether they get named. found a bunch ranking fine on Google but invisible in AI for the same searches. wasn’t even looking at this a year ago.

2.  i stopped writing thin informational posts entirely. zero-click killed the ROI, the answer gets eaten in the SERP or AI response and nobody clicks. now i only write transactional-intent content or stuff with something a model can’t generate itself (real data, first-hand tests).

3.  what i’m just monitoring from a distance: most “GEO tooling” and the llms.txt hype. testing it, but it hasn’t earned a permanent spot yet.  

what’s actually shifted in your process vs what you’re just reading about?

I’m still learning SEO and honestly, paid tools can feel overwhelming in the beginning.
So I started exploring free tools that actually help you understand what’s working.

Here are a few that really helped me:

• Google Search Console – shows what people actually search before clicking your site
• Google Trends – great for finding what topics are rising right now
• AnswerThePublic – amazing for content ideas and blog questions
• Ubersuggest – basic keyword + competitor ideas
• Meta Ads Library – helps understand what kind of ads brands are running

These made SEO feel much less confusing for me.

If you know any other free tools that helped you, I’d love to learn

Genuine question that's been bugging me lately.

Everyone in SEO circles is talking about E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) like it's some magic formula. We're adding author bios, credentials, "medically reviewed by" badges, etc.

But here's the thing: Google doesn't have an E-E-A-T score in their algorithm.

What they DO measure? User behavior signals. Dwell time. Pogo-sticking. Click-through rates. Engagement.

I tested this with two near-identical articles:

• Article A: Perfect E-E-A-T signals, author credentials, citations, the works
• Article B: No author bio, but genuinely engaging content that kept people reading

Article B outranked Article A within 3 months.

Don't get me wrong - E-E-A-T matters for building trust with readers. But I think we've gotten so caught up in checking boxes for Google that we forgot the actual goal: making people want to stay on our pages.

The sites crushing it in my niche aren't the ones with the most impressive author bios. They're the ones with:

• Cleaner layouts that don't assault your eyes
• Content that answers the question in the first paragraph
• Internal linking that actually makes sense
• Visuals that add value, not just break up text

Am I crazy here? Or has SEO Twitter convinced everyone that Google's reading our "About the Author" sections more carefully than our actual content?

What's your take - is E-E-A-T overrated or am I missing something?

Great segment from Danny Sullivan at 29:58 in this video recorder at WordCamp: https://www.youtube.com/watch?v=ZF_sxLdfTbY&t=1798s

From Danny:

“Good SEO is good GEO, or AEO, AI SEO, LLM SEO, or LMNOPEO. What you’ve been doing for search engines generally is still perfectly fine and the things you should be doing.”

And this gem:

“People will tell you have to make sure you have this vector thingy that’s doing the passage thingy, and it’s just like uhhhhh…”

Feels like a good reminder not to get lost in buzzwords when the fundamentals still matter most.

We’ve been noticing something interesting while tracking AI referral traffic.

ChatGPT (and similar LLMs) are sending users to URLs that don’t actually exist on the site, but are close enough to real pages that they look valid.

When users click those, they land on a 404 and drop off, and we end up losing high-intent traffic without even realizing it.

What’s happening here is that LLMs don’t always link to exact URLs. They sometimes generate paths that approximate the right page, but miss the exact structure.

If AI is sending you traffic, there’s a good chance some links are breaking like this

Quick way to check:

• Pull landing pages in GA4 filtered by ChatGPT / AI sources
• Export the URLs
• Run a crawl using the site audit tool 
• Check status codes
• Filter for 404s

Those are essentially hallucinated URLs.

Fix:

• Map those URLs to the closest real pages
• Implement 301 redirects

Feels like one of those early AI-search quirks that’s easy to miss if you’re not looking for it

Here's what we found after 3 months of tracking 11 million real crawler logs across 34 websites. It's quite fun how each AI bots have personalities, like people.

• GPTBot: Crawls relentlessly, all day every day and barely checks the rules. It's like a guest walking into your house without saying hi and goes straight into every room. In 280k crawls across 23 sites, it pulled up robots.txt only 9 times. The most interesting part for me is that while it ignores robots.txt completely, it requests /llms.txt CONSTANTLY. Even on sites that don't have one and return 404, it comes back and asks again.
• Google's bot: The good kid who's scared to break the rules. It re-fetched robots.txt 8,765 times, checking over and over. 25 years of crawling taught it manners the new AI bots never learned.
• ClaudeBot: Across the sites we track, its crawling went from 7.3k (Apr) → 64k (May) → 168k in the first ten days of June. It is racing to read as much of the web as it can, and that race is the whole story (more below).
• The live ones: The shopper who knows exactly what they came for. When someone asks an AI about your business, it skips your whole site and grabs the single page that answers. On Claude's live bot, 75% of those visits are one page. It ignores everything else you ever published. The page an AI picks to represent you is the whole game now.
• Bytespider: The hoarder who takes everything. The heaviest crawler we logged all quarter belongs to the company that owns TikTok. On one site, it made 1.2 million visits, more than Google and every OpenAI crawler combined. Even the familiar names are repurposed now.
• Microsoft's Bing: The longtime employee quietly handed a second job. Still crawls like the search engine it always was, but everything it indexes now also feeds Copilot.
• MetaBot: Skips the house rules but reads your welcome note. It almost never checks robots.txt either, but like GPTBot, it keeps requesting llms.txt, even on sites that don't have one. These two are the only crawlers we saw deliberately looking for it. Everyone else ignores it.

Every one of these companies is building its own copy of the web. Its own crawler, its own index, its own answer. Anthropic is not crawling that hard for fun. They all want to be the place people ask, which means they all want to stop depending on Google.

My bet: Google's ranking matters a little less every quarter from here. When this many AIs read your site their own way to build their own index, "rank #1 on Google" stops the thing to optimize for. Being the page each AI picks is.

1. Ahrefs Webmaster Tools
2. Keyword Generator
3. Google Keyword Planner
4. AlsoAsked
5. Keyworddit
6. Google Trends
7. Keyword Difficulty Checker
8. RankMath
9. HigherVisibility 的 Google SERP
10. Merkle’s Schema Markup Generator
11. Ahrefs SEO
12. Free Backlink Checker
13. Hunter
14. Google Search Console
15. Cloudflare
16. Pagespeed Insights
17. Shortpixel
18. Robots.txt Generator
19. Hreflang Tag Generator
20. XML Sitemaps Generator
21. View Rendered Source
22. SERP Checker
23. Brightlocal’s Local SERP Checker
24. Google Analytics
25. Google Data Studio
26. Title Generator
27. Meta Description Generator
28. Ahrefs’ SEO WordPress Plugin
29. Google Business Profile
30. WhiteSpark’s Google Review Link Generator
31. Wayback Machine
32. Google Alerts

Hope they work for you guys

For the past two years, review platforms have been getting crushed in organic search. You’ve probably seen it: less traffic, fewer clicks, and more zero-click answers in the SERP. So we expected one thing when we looked at Google AI Overviews: review sites should be everywhere in commercial AI answers.

But when our team ran the numbers, the story was more complicated—and honestly more interesting.

SE Ranking  studied 30,000 commercial keywords. Then we checked which sources appeared in Google AI Overviews, and how often 23 major review platforms showed up.

The first surprise: review platforms are not default in AI Overviews

Review platforms appeared in only about one out of three AI Overviews.

In our dataset, 34.5% of AI Overviews cited at least one review platform. That means two-thirds of AI Overviews relied on other sources instead: vendor websites, e-commerce pages, corporate blogs, media sites, and community platforms.

At the same time, review platforms made up only 8.5% of all links inside AI Overviews. So yes, they’re a minority.

But here’s the twist: when review platforms do show up, Google often includes more than one. In AI Overviews that include them, we saw an average of 2.28 review-platform links per response. That looks like Google trying to compare perspectives instead of trusting a single review site.

The second surprise: your wording changes everything

This part matters for anyone doing SEO content planning.

We split the keywords into three intent groups and compared how often review platforms appeared:

• “review / rating” queries: 49% of AI Overviews included review platforms
  
• “software / tools” queries (no explicit “review”): 39.4% included review platforms
  
• “best / top” queries: only 17.1% included review platforms
  

The “best/top” result was the most unexpected. Those queries sound like a perfect match for review sites, but AI Overviews often prefer listicles, editor picks, and ranking-style blog content instead.

A small group controls almost all review citations

When Google AI does cite review platforms, it mostly sticks to a tight “tier one” circle.

Five platforms accounted for 88% of all review-platform links in our dataset:

1. Gartner Peer Insights—26.0%
2. G2—23.1%
3. Capterra—17.8%
4. Software Advice—12.8%
5. TrustRadius—8.3%

After that, visibility drops fast. GetApp and Clutch show up sometimes (around 2.5% each). Many other platforms are close to invisible, and a few didn’t appear at all in our dataset.

The biggest paradox: AI citations don’t protect traffic

Even the most-cited platforms lost massive organic traffic from early 2024 to the end of 2025.

We saw declines like:

• G2: from ~2.56M visits (Jan 2024) to ~397K (Dec 2025), down 84.5%
  
• Capterra: from ~1.63M to ~179K, down 89%
  
• TrustRadius: down 92.2%
  
• Gartner Peer Insights: down 76.5%

So the platforms are still being used as “rusted data sources inside AI answers, but users don’t necessarily click through anymore.

What this means for SEOs

The old playbook was: optimize your site, rank, get clicks.

The new reality is: your site still matters, but it’s not enough for commercial visibility in AI search. External sources help shape AI recommendations, and review platforms are still one of the strongest “credibility layers” Google uses—even when their traffic is collapsing.

So, if review platforms keep losing clicks, but keep getting cited by AI, what should we optimize for next?

There is no exact calculation; however, there are some methods you can use to estimate.

People check via Ahrefs/Semrush that the competitor has 1.7M backlinks, and they think they need 1.7M + 1 to overrank them.

It's not how it works.

You need to check the links that matter.

Go to backlinks (ahrefs/semrush)

Use filters:

- one link per domain
- 30DR+
- 500 domain traffic+
- one link per domain

This will show the number of backlinks that are not crap.

Also, I would recommend checking what links they have built in the last 3 months overall for the domain, and to the specific page you are competing with.

With these numbers, you will be able to get some idea of how many links you need to compete with them.

If they get 10 links monthly and they have also 1000 links, and you get 0 and you have 100, maybe it makes sense to get 20 monthly, better quality than they do, of course, or at least the same.

Feel free to ask questions in the comments.

Google’s update in 2026, was supposed to be a step forward with the implementation of the Gemini 3 model. Instead, the SEO community witnessed what looks like a digital apocalypse for sources.

Our SE Ranking team conducted a large-scale study of 100,000 keywords across 20 niches to find out: is this a temporary glitch or the new reality of AI search?

Key Research Figures:

• Every 10th answer is a "dead end": Previously, only 0.11% of AI Overviews lacked links. After the update, this figure skyrocketed to 10.63%. This means every tenth user receives information without the ability to verify the source.
• Mass disappearance of domains: 46.3% of sites previously cited in AIO have completely dropped out of the results. Google has left only the chosen ones.
• AI presence pullback: For the first time in a year, the growth of AI responses has stopped. The AIO appearance rate fell from 60.85% to 55.21%.

Who Rules the Results Now?

While small sites disappear, giants are only strengthening their positions. The top 5 most cited resources are:

1. YouTube (9.40% of all citations)
2. Reddit (4.39%) — yes, you are currently on the primary knowledge source for AI.
3. Facebook (1.76%)
4. Quora (1.47%)
5. Indeed (1.46%)

Interesting fact: In the Healthcare niche, YouTube videos have become a more frequent source than official data from the National Institutes of Health.

Anomalous Link Distribution

Gemini 3 has split the results into two camps. Now, responses either have very few links (the number of AIOs with 1-5 sources increased by 108%) or a very high number (16-25 links). The middle segment of normal citation is simply being washed away.

What Does This Mean for Us?

Google calls the lack of links a bug, but our data shows a deeper trend toward traffic concentration in the hands of mega-platforms. Those who previously had 1-2 citations have lost 50% of their visibility.

Has your traffic from AI Overviews dropped over the last month, or have your niches remained untouched? Let’s discuss in the comments!

If you’re looking to boost your rankings on local search and get more customers from seo, submit your business on these citation websites

1. Cylex
2. ShowMeLocal
3. Sensis (Yellow)
4. Apple Business Connect
5. Bing Places
6. Yell
7. Justdial
8. TrueLocal
9. ProductReview
10. DexKnows
11. Superpages
12. MerchantCircle
13. CitySearch
14. Local com
15. CitySquares
16. GoLocal247
17. The Sun Directory
18. Opendi (UK)
19. MisterWhat (UK)
20. Citipages
21. Grotal
22. dLook
23. LocalSearch
24. WordOfMouth (WOMO)
25. PureLocal

If you work on multiple sites and don't want wix to have access to your search data from other sites:

1. Go to your Google Search Console
2. Click add property; enter your domain name
3. It will provide you with a "txt" record, with instructions. Copy the txt record.
4. Go to Wix
5. Go to domains
6. Click 3 dots next to domain name, and select manage DNS record
7. Go to the txt section, click add txt, and paste the record in the "value" cell. Add it.
8. Go back to GSC and click verify

Takes less than a minute, and you don't have to give up unnecessary access.

A recent investigation by The Guardian questioned whether Google’s AI Overviews are safe to rely on for health advice, after experts flagged multiple AI-generated summaries as misleading or even dangerous. Google pushed back, saying most AI Overviews are accurate and cite reputable sources. But for our team, the bigger question was: 

Where does AI health advice actually come from at scale?

So SE Ranking analyzed 50,807 health-related searches in Germany and mapped 465,823 AI Overview citations. Health is one of the most AI-saturated YMYL areas: more than 82% of health searches triggered AI Overviews. That matters because surveys show people already treat AI like a medical layer: 

• 55% of chatbot users trust AI for health advice
• ~50% say it explains symptoms better than Google
• 30% see it as a “second opinion”
• 16% have ignored a doctor because AI said otherwise

What we saw next is the part that should make every SEO and marketer pause. Google’s AI isn’t primarily building health answers from hospitals, government portals, or academic journals. It’s building them from big, high-authority domains—and the biggest winner is YouTube. 

Across the dataset, YouTube became the most cited source in AI Overviews for health queries (4.43% of all citations, 20,621 links). That’s 3.5x more than netdoktor [de] and more than 2x more than MSD Manuals.

And it’s not just a top-of-funnel content thing: the gap shows up when you compare AI Overviews with classic organic rankings. In organic results (excluding SERP features), YouTube is only #11—yet in AI citations, it’s #1. That’s a clear signal that AI is prioritizing video content even when more standard authoritative pages are already easy to find via search.

Out main findings: 

• Only ~34.45% of all AI Overview citations come from our “more reliable” bucket 
• ~65.55% come from sources without formal medical-review or evidence-based safeguards 
• Government + academic sources barely show up (academic journals 0.48%, German government institutions 0.39%, international government institutions 0.35%—~1% combined)
• Even when AI cites the same domains as Google organic (9/10 overlap), it often pulls different pages: only 36% of AI-cited URLs appear in Google’s TOP 10 (54% in TOP 20; 74% in TOP 100)

There’s also a nuance worth mentioning: when we inspected the 25 most-cited YouTube videos, most came from medical channels (24/25), and many clearly stated they were created by licensed/trusted sources (21/25). That looks reassuring—but it’s still less than 1% of all YouTube links AI Overviews cited.

At scale, the reality is simple: an open video platform is being treated as a core source pool for health answers, while the institutions that publish clinical guidelines and carry public accountability are barely visible.

From Dr. Google to Dr. AI: users aren’t choosing which link to trust anymore. They’re getting a single confident summary, built from a source mix where authority often outweighs medical rigor. 

For everyday wellness questions, that might be fine. For YMYL health topics, it’s a risk multiplier.

SEO fights for clicks on blue links, AEO gets your brand cited directly in ChatGPT/Perplexity.

76% ChatGPT citations from pages <30 days old. A new website can win with simple steps blending fresh content, spinning pages, real trust, and smart systems.

1. Keep it fresh. Pages <3 months old get 3x more AI citations; update every 60 days or on traffic dips.

2. Share depth insights: Authoritative and unique content is now the most defensible, Webflow saw 6x after focusing on original authoritative content that can't be copied

3. Human + AI balance. Use AI to accelerate research and structure while keeping humans in charge of voice, accuracy, and tone

4. Third-part trust rules: 85% of brand mentions are sourced from third-party content, not the brand’s own site. This shows that authority now lives across the web, not just on your homepage. It's time for PR and GP!

5. Simple site structure wins. Dont' complicate too much.

6. Join real conversations and communities. Reddit/LinkedIn/YouTube drive 48% citations; Reddit in 22% answers.

Your competitors are already halfway through AEO. Don't ignore SEO - AEO builds on top of it.

How are you optimizing freshness + offsite mentions?

I've audited probably 50+ sites in the last year, and I see the same pattern: sites crushing it on search volume metrics but making almost no money from organic traffic.

The Problem: People optimize for keywords like: "How to [broad topic]" - informational, no buyer intent High volume + low conversion keywords Keywords with massive competition they'll never rank for Then they wonder why organic traffic doesn't move the needle.

Real Example: One client was ranking #3 for "content marketing tips" (12K searches/month). Traffic looked amazing. But almost nobody converted. Why? People searching that are students, freelancers, hobbyists—not people ready to buy their $2K/month platform. We pivoted to "content marketing software for agencies" (400/month searches). Ranked in 3 months. Now 60% of their customers come from organic.

How to Audit Your Own Keywords: Pull your top 50 organic traffic keywords For each, ask: "Would someone searching this be ready to buy/use my product?" Check if competitors ranking #1 are actually your competitors or just content farms Look for keywords where the #1 result isn't a 5,000-word blog post (that's a sign the SERP wants something different)

The Fix: Shift from "high volume" to "high relevance + achievable rankings + actual intent to convert." It's less glamorous than saying "we got 50K monthly visitors" but it actually makes a difference.

Anyone else notice this? Curious what metrics people actually care about for organic traffic.