r/LLMTraffic

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

Our brand was basically invisible in AI until about 4 months ago. Then something clicked and now we show up consistently in maybe half of the relevant prompts.

I have a hunch about what caused it. But before I write up my internal case study and potentially be wrong, I'd love to hear from others who actually made this shift happen. What did you do, in what order, and how long did each piece take to actually show up in the models?

Edit: Thanks all, very helpful. Starting with Parse (free tier) for the Month 1 diagnostic exactly as the top comment laid out. If it surfaces a Reddit gap, going to use Signals for the Month 3 seeding. Will post the actual case study in 6 months.

There are two things that I have been noticing in LLM visibility lately.

First is long-form content with real value.
I have seen that many strong brands are now making sure they publish deeper content, often 2000+ words. The reason, from what I see, is that they try to cover multiple related queries in one piece of content. In this way, users can find detailed answers in one place instead of jumping between pages.

Second is abandoning a site for a long time can hurt visibility.
I noticed one brand that used to get mentioned in AI tools like ChatGPT and even AI Overviews, but now their brand is barely showing in citations.

One possible reason is that they left their website untouched for a long period. No fresh blogs, no updates, and very little new activity. Over time, that can reduce relevance and visibility.

These are two major shifts I have been noticing lately in AI/LLM visibility. Curious if others are seeing the same thing?

This might seem like a stupid question but like how do you reliably track it? Like i need specifc data on my mentions and citations and whether it was positive or mentioned me as the solution. Also i need to track what the conversion was from llm to my site percentage wise and then further what the traffic i got was like, whether the traffic converted or not? And then after all of this this is just tracking i then need to make it better, i know i have traffic from llms cause users convert and i am using aeo content but analytics is key.

I have been reading about AI agents and that they will be shopping on behalf of actual customers in the future.

1. Does that mean as a seller we need to get our catalogs to be AI agent friendly, are there any tools or services that I can use?
2. Has anyone seen any benefits of being AI agent ready
3. What is a good amount of money (USD) to spend on AI readiness, what tools should I use etc?
4. Can I self build it using claude or something like that?

show you

From u/lilray on X (via GlennGabe) - thanks for sharing

As of May 7, 2026, FAQ rich results are no longer appearing in Google Search. We will be dropping the FAQ search appearance, rich result report, and support in the Rich results test in June 2026. To allow time for adjusting your API calls, support for the FAQ rich result in the Search Console API will be removed in August 2026.

As this sub and many of our related experts that we share, like u/jakehundley - Mod of r/agency - a great sister sub to r/SEO and r/SEO_Digital_Marketing - this isn't surprising.

As we said - Google doesnt actually read FAQ Schema anyway - because less than 0.001% of site qualify

4-person team, under $1M ARR, B2B niche vertical. AI visibility keeps coming up on discovery calls and I can't keep dodging the topic.

Budget is painfully tight. Is Parse overkill for us at this stage? Should I wait six months until we have more revenue and hope we don't lose ground in the meantime?

Edit: Thanks, going with Parse free tier for monitoring and putting the actual budget into one Signals Reddit seed plus a niche podcast appearance. Much better use of the money than I would have done on my own.

Ran an informal study. 500 product-recommendation prompts across ChatGPT's search mode, logged every cited source. Plan was to share the breakdown internally, but now I'm curious whether what I'm seeing is consistent with other verticals or just mine.

What have others observed? Is the source distribution relatively stable across niches, or does it vary a lot by category?

Edit: Thanks, this matches my data surprisingly well. Running my full 500-prompt breakdown against Parse's aggregate for a sanity check before publishing. Will post the writeup here once it is done.

CMO wants "share of voice in LLMs" added to the quarterly dashboard. My marketing-ops instincts are flagging this as measurable but not obviously tied to revenue, which is the definition of vanity.

Has anyone actually correlated AI share of voice to pipeline in a way that held up to board scrutiny? Or is this window-dressing for a channel nobody's yet figured out how to value?

Edit: Thanks, giving the board exactly the framing you described (Parse Score components + cohorted close rate). CMO was convinced, metric going on the dashboard. Already scheduled a follow-up review for Q2.

I'm at an SEO conference in my city.

And I met this 22-year-old "SEO expert" who was looking for a job, and he gave me a 20-minute speech about how SEO was dead and that there was no point in working on it.

That now you should only focus on geo-optimization! I didn't say much because I disagreed with him so much, haha, but I listened anyway!

I wanted to tell you about it because it's funny, the opinion of some young people on this subject!

Been noticing an interesting pattern across AI search engines lately.

ChatGPT seems to pull heavily from sources like Wikipedia and Reddit.
AI Mode and AI Overviews appear to reference platforms like YouTube, LinkedIn, Facebook, Medium, and Yelp much more frequently.
Gemini also seems heavily influenced by Reddit, YouTube, and Wikipedia content.

So now I’m wondering:

As SEO professionals, should we still focus mainly on ranking webpages… or should we start structuring content distribution around the platforms AI engines actually cite and trust?

For example:

Long-form expertise on LinkedIn/Medium
Community visibility on Reddit
Video-first explanations on YouTube
Strong entity consistency across Wikipedia/business citations
UGC and discussion-based signals instead of only backlinks

Feels like “being mentioned everywhere” may become more important than just showing in Google.

Curious how others are adapting their SEO/content strategy for AI search discovery right now.

Hello people, I'm 25M. I have scoured through the internet like forever without getting anything I can settle on to work, earn and develop a skill. I have bachelor's in urban planning and GIS systems. I recently stumbled on GEO and I my mind just had a shift and thought this is something I'm gonna do. Having zero background in tech and programming, I feel a little bit left behind in the streets of LLMs. Either way I have started lerning about GEO and I hope to be a consultant starting next year. The only issue there is very scanty information on the internet for learning. Who knows how I can be useful for a business or an individual in relation to GEO?

I tried to do this in-house for the last two months. Built a spreadsheet, 20 prompts, ran them daily across ChatGPT, Claude, and Perplexity, logged mentions.

Honestly the data is a mess. Different runs give different answers, and I can't distinguish a real trend from random variance. Is this actually doable manually if I'm more careful, or am I stuck needing a tool?

Edit: Giving up on the spreadsheet, signed up for Parse's free tier today. Keeping the sheet for spot-checks only from now on. Sanity restored. Thanks Sara.

I’ve been looking heavily into the tech space recently, specifically tools that use AI to fully automate SEO and local GEO. It seems like we are reaching a point where AI can handle the ongoing audits, content generation, and local profile updates completely on autopilot. Do you guys think this automated technology is the definitive future of digital marketing? More importantly, would you consider building and running these systems manually to be a thing of the past, or will there always be a need for a human to manually pull the levers? I’d love to hear from people who are actually in the trenches doing this work.

I’ve noticed that LLMs and AI search experiences often pull information from blog posts far more than other content formats. Whether it’s summaries, citations, or visibility in AI-generated responses, blogs seem to dominate disproportionately.

But now that a huge amount of blog content itself is becoming AI-generated, I’m wondering whether this model will continue to work long term.

Will AI-written blogs still be enough to gain visibility and citations in LLM-driven search experiences, or will factors like originality, expertise, real-world insights, first-party data, and brand authority start becoming much stronger differentiators?

Curious how others are thinking about content strategy in an AI-heavy search ecosystem.

Trying to pressure-test the framing here. Three dots I'm connecting:

1. LLMs cite Reddit heavily for product-recommendation prompts
2. AI search optimisation is the thing every marketing team's now told to care about
3. Therefore Reddit marketing is suddenly much more valuable than it was, because it feeds the AI retrieval layer

Is this how you'd frame it, or am I oversimplifying? Keen to hear where it breaks.

Edit: Good refinement, reckon the "Reddit as retrieval surface" framing is exactly right. Using Parse to find our under-cited prompt families and Signals to seed the Reddit-citable gaps. "Post things and hope" is not a strategy, agreed.

We spent several years on traditional SEO for Google, but now GeoSmart is here and starting to become essential for optimizing our content for AI!

What do you think will be next? SEO for superintelligence? What are your predictions?

I run a small agency, 12 clients, mostly B2B SaaS. Adding AI visibility as a service line because it keeps coming up on sales calls.

The thing I'm blocked on isn't strategy, it's the deliverable. SEO has standardised client reporting after 20 years. AI visibility has basically nothing. What does your weekly or monthly client-facing report actually look like?

Happy to share ours in exchange for yours.

So I've been going down a rabbit hole lately trying to figure out how brands actually show up in Ai answers.

Like with Google, the game is clear. Rankings, backlinks, keywords, traffic there's a whole system you can track and improve. Makes sense.

But with chatgpt or perplexity or any LLM… I genuinely have no idea how visibility even works.

If someone asks chatgpt what's the best CRM for small businesses, what actually decides which brands get mentioned?

• How strong your seofoundation is?
• Digital PR and third-party mentions?
• Structured data and technical stuff?
• Pure brand authority built over time?

And the bigger question how are brands even tracking this? With seo you have Search Console, Ahref , semrush or ubbersuggest, rankings. With AI search… what's the equivalent?

Because every marketing blog right now is saying "GEO is the future, optimize for LLMs" but I haven't seen a single one actually break down a real strategy that works.

So if you've figured out any part of this even just one thing that seems to move the needle I genuinely want to know.

What are you actually doing differently for AI search visibility?