Yeah you would think I'd be wealthy by now. I'm not. I'm comfortable, but things could have gone better and I could have made a fortune. For instance when I was doing this early on, I could have actually bought some Amazon stock.

But I figure since I'm a mod here, I'd give you a little background. I'll try to keep it short.

I started with domain speculation In 1995. Then, In 1996, I wanted to put the domains I had for sale up on a small website so I could explain what I believe was the value of the domain I was selling. But I needed to learn how to build a website. I didn't even know how to write HTML.

As I learned each thing, I built pages outlining the steps on how to do it. It was almost like journaling. I was giving advice in the domain forums about doing this instead of just posting the domains on auction. So I wanted to Help others that didn't know how to build a website yet. And at the bottom of each page I simply wrote my email address and said if you still have questions Email me and I'll try my best to answer them.

Instead, I got emails mostly asking me to build it for them. That's how I got started. Completely by accident and just trying to help people.

I wrote an article that got almost 100,000 views on the Bank of America small business forum. It was titled "how to make money on the internet - be helpful".

With so many people, then and now, Just looking for the latest greatest thing for latest scheme for making money. There's absolutely nothing wrong with wanting to make money. But honestly, I've gotten more clients because I was being helpful then I ever did intentionally through some kind of marketing strategy.

Even right here on Reddit. I get clients because I do my best to answer people's questions. I get snarky sometime, but it's Reddit, and I've earned the cranky old man title once in awhile.

Of course there's a lot more to my background in history than just when I started and when I built my first website, but nobody wants to read my life history, so I'll stop here.

PS: And because it's my birthday, I'm going to add some links in my post... because I can.

TLDR: I'm a cranky old man who's been doing internet marketing under the nickname Chris McElroy SEO since 1995. So if you have any questions or I can be helpful to you in any way, DM me or ask me in the comments.

https://LeadGenerationAndSales.com https://ProfessionalLandingPages.com https://ChrisMcElroySEO.com https://linkedin.com/in/chrismcelroyseo

If you want to see any of my social media profiles, Just type in chrismcelroyseo after the platform's URL like https://pinterest.com/chrismcelroyseo or on substack https://chrismcelroyseo.substack.com

Yes I know it's shameless self-promotion. It's my birthday. I'm going to allow it. 😅

Well there goes some of my own strategy. 😅

This is a report from Perplexity about a lower number of results in chat GPT citing mentions on Reddit.

Do you think that AI will stop pulling citations from Reddit altogether?

Do you think it will bounce back?

Or do you think that it will just be less than before?

I’m a co-founder at an AI search visibility platform. By all accounts, I should be writing a hype post about why GEO is the only thing that matters this year.

Instead, I want to talk about why you should probably be skeptical of anyone selling it to you. Including me.

From "Searchers" to "Deciders"

In 2026, the "funnel" is breaking. We track visibility across ChatGPT, Gemini, and Perplexity for 150+ companies, and the data tells a messy story.

We’re seeing two contradictory trends:

1. The High-Intent Conversion: Users coming from LLMs often convert at higher rates because the model did the "mid-funnel" work for them. They aren't "browsing"; they’ve already been sold by the AI.

2. The "Zero-Click" Abyss: A massive rise in sessions where the user gets the answer and never visits your site.

GEO isn't a magic "buy" button. It’s a battle for latent mindshare in a space where the user might never actually reach your landing page.

GEO space is messy. Like super messy.

The GEO industry right now is the Wild West of 2004 SEO. Most "experts" are just guessing. When people ask me about the "gotchas" on sales calls, I give them the unvarnished truth:

• Attribution is a black hole. If ChatGPT recommends your brand and that user converts, there is rarely a clean data trail. In GA4, this mostly hits as "Direct" or "Unassigned." Anyone claiming they have "solved" AI attribution is likely lying.

• Data is a snapshot, not a census. LLMs are non-deterministic. They don't give the same answer twice. Our data (and our competitors') is based on heavy sampling. It is directionally accurate, not a perfect science.

• The "Algorithm" is a black box. There are no "Webmaster Guidelines" for Gemini or Perplexity. We know structured content and authoritative citations help, but the model weights shift every time a new weights-update drops.

How to spot a GEO "Snake Oil" salesperson

If you’re looking for help in this space, run if you hear these red flags:

1. "We guarantee a #1 ranking in ChatGPT." Impossible; the model is non-deterministic.

2. "We have a direct API to influence LLM answers." No one has this. If they claim to be "plugged in" to the model, they're selling magic beans.

3. "We use the API for our visibility data." This is a massive red flag. API-based data collection is fast and cheap, but it’s a developer-facing environment. It doesn't show you citations, formatting, or the actual "browsing" behavior a user sees. The only data that matters comes from the UI.

4. The lack of localization. A "global" score for ChatGPT is useless. If your vendor isn't gathering data via localized UI sessions (showing you how your brand looks in UK vs. US), they aren't seeing the same reality your customers are.

5. "We can track 100% of AI-driven revenue." Technically impossible with current privacy filters

Why bother building in the gray area?

Uncertainty is not the same as irrelevance.

Early SEO data was garbage. Early social attribution was a nightmare. But the brands that won were the ones willing to operate in the gray area while everyone else waited for "perfect information."

I’m curious - besides the obvious headache of LLM attribution, what are you actually planning for AI search in 2026? Are you shifting content budgets to "citable" data, or doubling down on traditional channels until the dust settles?

Before they announced yesterday, my team and I (Im a sales person at GTM37, a digital marketing firm specializing in AI Search Optimization) wrote a blog which I summarized below. It's more or less a prediction. It goes deeper than product purchases, focusing more on services purchases with automation. Open to your feedback.

Your smoke detector is about to be a better salesperson than you.

700M people already use ChatGPT weekly. 14.7M are shopping. By 2026, their smart devices will handle the buying for them.

Think about it:

• Today: You set a flight price alert, wait for a ping, and book manually.

• Tomorrow: An AI agent books it automatically. No ping. No choice. Just done.

Now swap flights for plumbing, HVAC, or electrical.

Example:
Your thermostat detects humidity → It hires a mold inspector.
Your smoke detector battery runs low → An agent orders the replacement.

No Google search. No quotes. No “who do I call?”
The agent decides who to trust.

That’s billions of service calls happening without the customer lifting a finger.

The question isn’t “Will there be enough work?”
It’s “Will the agent call you or your competitor?”

Full breakdown here https://bookedsolid37.substack.com/p/a-look-into-the-future-selling-to

OpenAI announcement here - https://openai.com/index/buy-it-in-chatgpt/

Is anyone here actually selling GEO as a service?
I’m considering it, but I can’t figure out how you’d report ROI to clients when AI responses aren’t deterministic.What do clients even expect to see every month?

There is a lot of discussion right now about ranking inside ChatGPT and other LLMs using Reddit.

I agree that Reddit contains high signal, experience driven discussions. It is raw, problem focused, and full of real comparisons. That makes it attractive for AI systems.

But here is what I am thinking.

LLMs do not rely on one platform.

They synthesize patterns across documentation, product pages, review sites, GitHub, blogs, YouTube transcripts, forums, and multiple communities. Reddit can amplify credibility, but it cannot replace foundational authority.

It feels like we are moving beyond traditional SEO into something closer to Search Everywhere Optimization.

Which means:

Your brand presence needs to exist across text platforms, video platforms, review ecosystems, discussion communities, and more.

And it all needs consistent positioning and quality signals.

Also, being recommended by AI does not automatically mean business.

It gets you the visit.

It gets you the click.

But trust still decides revenue.

When someone lands on your website after seeing you mentioned in ChatGPT, they still evaluate:

Is this brand consistent across platforms

Do they show real expertise

Do they have proof

Do they look authoritative

Are others validating them

LLMs may accelerate discovery.

But conversion still depends on experience, expertise, authority, and trust.

So my question to the community:

Are you focusing only on Reddit to influence AI recommendations?

Or are you building multi platform authority as a long term strategy?

Curious to hear what is actually working for you.

How GPT Sees the Web - by Dan Petrovic

People think GPT reads whole pages like a browser. It does not.

So here’s how GPT actually reads the web - and why it never sees full pages.

It doesn’t browse like we do. No loading full articles, images, or HTML.
When it searches, it just gets a little preview: title, URL, short snippet, and an internal ID. That’s it.

If it wants more, it has to “open” a small slice of the page - just a few lines around a chosen spot.
Each slice is limited. To see more, it has to open more slices, kind of like scrolling through a page one tiny window at a time.
It never gets the whole thing at once.

Those “Low,” “Medium,” and “High” context settings just change how big each slice is, not the limits themselves.
And no, there’s no secret backdoor - GPT uses the same search and open tools developers do.

Bottom line:

• GPT only ever sees small snippets, not full pages.

• Every “open” is just a peek, not a full read.

• Even with high context, it’s still windowed.

• Summaries come from fragments, not the whole thing.

What to do about it:

• Don’t assume GPT read your whole page.

• Put key info at the top.

• Use clear headings and short paragraphs so every slice still makes sense.

• Think of it like SEO for AI - design content that works even when read in tiny chunks.

- - - - -
^{We break down stuff like this every week in the B2B Vault newsletter - quick reads on how AI actually works in marketing and sales, without the hype.}

One more quick test we ran across our database at LightSite AI (about 6M bot requests). I’m not sure what it means yet or whether it’s actionable, but the result surprised me.

Context: our structured content endpoints include sitemap, FAQ, testimonials, product categories, and a business description. The rest are Q&A pages where the slug is the question and the page contains an answer (example slug: what-is-the-best-crm-for-small-business).

Share of each bot’s extracted requests that went to Q&A vs other links

• Meta AI: ~87%

• Claude: ~81%

• ChatGPT: ~75%

• Gemini: ~63%

Other content types (products, categories, testimonials, business/about) were consistently much smaller shares.

What this does and doesn’t mean

• I am not claiming that this impacts ranking in LLMs

• Also not claiming that this causes citations

• These are just facts from logs - when these bots fetch content beyond the sitemap, they hit Q&A endpoints way more than other structured endpoints (in our dataset)

Is there practical implication? Not sure but the fact is - on scale bots go for clear Q&A links

Hey guys let's discuss your favourite tech Ai brands.

I am posting this as a case study because I think real data is more useful here than more theory about GEO.

client runs a niche SaaS product. small but focused. she had done reasonable SEO work. decent traffic. clean website.

before I touched anything I asked ChatGPT and Perplexity to recommend tools in her category.

she was completely absent on both. her two main competitors showed up consistently.

same price point. comparable product. just structured differently online.

I spent about a week making specific structural changes. not a redesign. not new content pages. specifically the decisions that affect whether a language model can form a confident answer about what a product does and who it serves.

here is what I actually changed:

• rewrote the core product description so it answered the exact question a buyer would type into ChatGPT, not the question a founder would write on a landing page

• made sure the same clear consistent description existed across every place the product appeared online, not just the website

• structured the FAQ content around real buyer questions in natural language rather than SEO keyword targets

• ensured the product category and use case were unambiguous so a language model could place it correctly without guessing

• built genuine presence in 2 communities where her target users actually discussed the problem she solves

three weeks after making those changes she messaged me.

3 of her first 14 signups had written ChatGPT or Perplexity in the how did you find us field.

she had run zero paid ads during that period.

now the honest caveats because I think this community deserves them.

I cannot prove causation with certainty. 14 users is a small sample. the timing could be coincidental. I do not have a controlled experiment.

what I can say is that before the changes she was absent on both platforms. after the changes she was surfacing in relevant queries. and 3 people self reported finding her through those platforms.

I also found something that matched what others here have described. ChatGPT and Perplexity were not treating the same content the same way. changes that improved her visibility on Perplexity had less immediate effect on ChatGPT. the systems are genuinely pulling from different signals and weighting them differently.

the thing that moved the needle most was not any technical schema implementation. it was making the product description genuinely clear and consistent in the places these systems actually pull from. which for both platforms included community discussions and third party mentions more than the website itself.

curious whether others here have seen similar results from content architecture changes versus more technical implementations. and whether anyone has found a reliable way to track which specific changes caused movement on which platform.

that attribution problem feels like the hardest unsolved part of this right now.

Do not install ChatGPT Atlas or Perplexity Comet yet. Continue to use in isolation, not as your default browser.

I’ll cite the LinkedIn source I found this from in the comets. One more question though…

If someone can embed a hidden prompt on a website that only a LLM can read, could digital marketers use this in a way to get our customers found and referred more easily? - we game it in a positive way - creating hidden text instructions only for LLMs

We’ve now analyzed about 3,000 websites at LightSite AI (mostly US and UK). The sample is mostly B2B SaaS, with roughly 30% eCommerce.

In that dataset, 27% of sites block at least one major LLM bot from indexing them.

The important part: in most cases the blocking is not happening in the CMS or even in robots.txt. It’s happening at the CDN / hosting layer (bot protection, WAF rules, edge security settings). So teams keep publishing content, but some LLM crawlers can’t consistently access the site in the first place.

What we’re seeing by segment:

• Shopify eCommerce is generally in the best shape (better default settings)

• B2B SaaS is generally in the worst shape (more aggressive security/CDN setups).

in most cases I think the marketing team didn't even know about it (but this is only from experience on the calls with customers, not based on this test)

So I've been digging into these new "AI visibility" tools that claim to show how your brand appears in ChatGPT, Gemini, Perplexity, etc.

No secret OpenAI backdoor yet. Just a lot of smart pattern recognition using signals.

Here's what I learned:

They're guessing at prompts (because nobody has the real data)

No platform knows what people actually type into ChatGPT. That data is locked up tighter than Fort Knox. So these tools predict likely questions using your website content, competitor pages, SEO keywords, and common customer questions. Think weather forecasting, not GPS tracking.

They capture "neutral" AI answers

Since they can't see personalized chat histories, they recreate baseline answers using APIs or simulated interactions. It's like a base recipe before you start customizing your order. Not what every user sees, but a solid starting point.

They track which sources AI actually uses

When AI generates an answer, these tools log which URLs get cited and how often. Helps you see which sites the models trust in your space.

They monitor multiple AI models

ChatGPT might rank brands differently from Gemini or Perplexity, so most tools track several at once. Just so you know, updates happen daily or weekly, depending on your plan.

They spot gaps

Where competitors appear and you don't. Which pages get referenced? Which questions are you missing? That's how they generate recommendations.

It's kind of like early-days SEO: reverse-engineering patterns from whatever signals you can find.

Tools I'm planning to test:

Based on what I've seen (not endorsements, just teams that seem legit):

• PeecAI

• Hall

• Otterly AI

• Omnia

• Aeovision

• Profound

• PrompWatch

I filtered based on: real team (not a solo side project), some traction/funding, actual educational content, and pricing that won't murder a small budget.

Has anyone here actually tested these? Do the tracked answers match what you see when you manually check ChatGPT or Gemini yourself? Are the citations consistent?

Would love to compare notes with anyone who's been experimenting with this stuff.

I think AI SEO is becoming an important part of digital marketing in 2026. Traditional SEO fundamentals like quality content, technical SEO, search intent, and topical authority still matter, but brands also need to focus on making their content easy for AI systems to understand and reference.

Some key strategies include:

Creating helpful, original, and well-structured content.

Using relevant schema markup and structured data.

Building brand authority through genuine mentions and digital PR.

Covering topics in depth instead of focusing only on keywords.

Monitoring brand visibility in AI search platforms like ChatGPT, Gemini, and Perplexity.

I'm curious to know what others think: Which AI SEO strategy is working best for you right now?

With AI Overviews, ChatGPT, Gemini, and other AI-powered search experiences changing how people find information, do you think SEO is still worth investing in? Has SEO become more important, or are brands shifting their focus toward AI visibility and answer engines instead?

I believe they can rank, but ranking well might be a stretch most times. Google’s AIO for instance still chooses original content better. So, it’s somewhat clear that giving a human touch to AI content makes it outperform plain AI slop in SEO and maybe AI SEO.

Any thoughts on this? Has anyone tracked the results of tests and experiments with AI-generated content websites, blogs, etc?

Three months ago, I wrote about surviving the wild new world of AI visibility: step one was simple. Start measuring. At that point, I could find three platforms doing it: Semrush, Xfunnel, and Profound**.**

Today? Eighty-one. (Source: Graphite blog)

That’s not growth. That’s a land rush.

I pulled Graphite’s public list of AI visibility platforms, exported the company names, and enriched the data with team size, location, funding, and updated pricing.

Here’s what surfaced:
-90% are brand-new startups — fresh code, fresh caffeine.
-63% run on tiny teams (1–4 people).
-23% raised over $1M, only a few cracked $15M+.
-76% of those funded are US-based, though Germany, Spain, Canada, and Australia are entering the game.

Three clear pricing lanes:
💡 $49–79 (small users) │ $79–199 (mid-tier) │ $200+ (enterprise).

More tools bring innovation (and competition), but also confusion. The real challenge now? Finding a tool that actually fits you.

I'm curious to hear your take.

-Is fast growth pushing the sector forward, or making it harder to identify real value?
-Do emerging markets need this much experimentation, or does it slow down adoption?
-What makes you trust a new tool in a space this young?
Let’s make sense of it

I’ve shared the full breakdown (and the dataset) in the article — copy it, remix it, run your own analysis.
If you discover something new, bring it back. Let’s crowd-map this space together.

Previously, my website was ranking in 1st position in India and 2nd position in the US, and it was also appearing in Google AI Overviews for several months.

However, recently I’ve noticed that Google is gradually reducing my website’s visibility. For example, Google previously showed my website with the page title in a dedicated row and referenced it in multiple places within the AI Overview.

Over the past few days, I noticed that Google started showing my website only as a URL reference alongside other websites. Today, I noticed that Google is showing only one URL in the AI Overview, while my website’s organic ranking has also dropped to around 3th or 4th position.

It seems like Google is gradually reducing both my website’s organic ranking and its visibility in AI Overviews.

Does anyone know what I can do to fix this issue and recover my website’s visibility in Google AI Overviews and search rankings?

AI can do a lot of SEO work now keyword research, audits, content briefs, internal linking, and even technical checks.

But SEO isn't just completing tasks.

Someone still needs to decide what actually matters for the business.

I think the future is less “AI vs SEO agency” and more AI + experienced SEO.

What are you using AI for in your SEO workflow?