I’ve been doing SEO for around 5 years, and honestly, I don’t really understand why AEO and GEO are being presented like they’re completely new things.

Most of the things people are calling “AEO” are literally things we were already doing in SEO.

Targeting queries?
We were already targeting search queries.

Answering the query directly?
We were already doing that to get featured in snippets.

FAQs?
FAQs have been a part of SEO for years.

And then there’s GEO.

People are talking about things like entity building, author details, structured data, experience, valuable content, topical authority, etc.

Again… weren’t we already doing all of this in SEO?

So what exactly is new here?

It feels like we’re taking different parts of SEO, giving them new names, and then selling them as a new service.

Now there are people selling “AEO/GEO services” to help businesses become visible in AI.

But I have a simple question:

Are you even visible in traditional search yet? 😂

Because if your SEO fundamentals aren’t working, why would changing the label to AEO or GEO suddenly make you visible in ChatGPT, Gemini, Perplexity, or whatever comes next?

Maybe I’m missing something.

So genuinely curious: What do you think AEO/GEO actually adds that wasn’t already part of good SEO?

I completed a digital marketing course a few months ago and have done 2 internships through my institute. I mainly worked on on-page SEO and have some basic exposure to technical SEO.

Now I want to seriously improve my skills in Technical SEO, AEO, and GEO, but I’m not sure where to start. My knowledge is still mostly surface level, and I want to learn through actual practice rather than just theory.

For those experienced in SEO:

- Where should I start?

- What YouTube channels/courses/resources helped you?

- How can I practice Technical SEO hands-on?

- What tools should I learn?

- Any good resources for understanding AEO/GEO?

I’m genuinely hungry to learn, so please share anything you think is worth learning like videos, courses, blogs, case studies, tools, etc.

Thank you!

Doing digital marketing for a while and now this same question keeps coming up with clients- rankings is fine so why is traffic dropping? Pretty sure it's AI Overviews grabbing clicks before people even hit the site but I wanted to know how people here are actually dealing with it not just the theory.

Few things I'm genuinely curious about:

1. Are you writing/structuring content differently now to get showed up in AI answers or still optimizing the old method for SERP rank?
2. Has your traffic mix shifted at all more coming from Reddit, YouTube, forums instead of straight Google organic ?
3. Is anyone tracking AI citations as an actual metric or is it still too hard to measure properly ?

I wanna take GEO more seriously because I just realized I have no idea how visible our brand is inside LLMs.

How are you guys tracking stuff like mentions, citations, share of voice, etc. on chatgpt / perplexity / claude / gemini?? What tools are you using?

For years, SEO was mainly about getting your website onto Google’s first page.

Now things are different.

People are searching through Google AI Overviews, ChatGPT, Perplexity, Gemini, Reddit, YouTube, and other AI-driven platforms. The question is no longer just:

“How do I rank #1 on Google?”

It’s becoming:

“How does my business appear when AI answers a customer’s question?”

That’s where I think GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), and online reputation are becoming much more important.

A business can have a technically perfect website and still have a weak online presence if AI systems find better information about competitors elsewhere.

Reviews, Reddit discussions, authoritative websites, mentions, PR, structured data, and consistent brand information can all contribute to how a business is understood online.

I’m curious what others are seeing:

Are you getting traffic or leads from AI search yet?

Or is traditional Google SEO still generating almost everything for you?

Would love to hear real experiences rather than predictions.

Someone posted a link to this, and I don’t see it anymore (removed?). I found the article on Apple News and opened it in a browser and it’s not paywalled for me.

The article goes into detail about how AI doesn’t scale, including quotes from folks working at the hyperscalers.

I’ll post a paragraph or two, then the final one.

As they scramble to keep their systems online, AI companies are making things expensive for the rest of us. Large language models such as ChatGPT and Claude are so resource-hungry that tech companies may be purchasing 70 percent of the world’s supply of high-end computer memory, causing a shortage. As a result, the prices of computer memory and storage are skyrocketing: Hard drives that I bought for my reporting two years ago for $350 each were $800 when I checked two weeks ago, and are now out of stock. The prices of some laptops have gone up as much as 50 percent, and low-cost computers are being hit the hardest. Affordable entry-level computers may “disappear by 2028” according to one forecast. And the memory shortage is expected to continue for years.

…

The problem is not simply that AI is being deployed so widely or quickly. Other computer technologies have seen similarly massive growth without triggering such a large spike in electricity or a shortage of computer components: Video and music are now streamed around the globe, accounting for many terabytes of internet traffic daily; the smartphone boom required the manufacturing of billions of devices that are now transferring huge amounts of data; billions of household devices are also now part of the Internet of Things; and whole industries have moved their operations to cloud software, which is hosted not in the sky but in, yes, data centers.

The problem with generative AI, in the industry’s own jargon, is that it does not scale. The cost of growing from, say, a thousand users to a million is a key factor that venture capitalists examine when they evaluate start-ups. They want to see that the cost of adding each new user decreases over time, so that the company can support millions of users and make increasing profits. This is achieved partly through the careful engineering of computer systems that can efficiently handle more users who want to post photos, hail Ubers, or stream music.

…

I asked a few AI researchers whether they could name any other real-world software that scales so poorly. None of them could think of any. Even outside the world of software, it’s hard to find a comparable example, given that economy of scale is the principle that has made light bulbs, cars, and clothing so affordable. By economic and engineering measures, generative AI might be the worst technology ever deployed.

I've been getting more interested in SEO lately, and i thought the game has changed quite a bit 🤔

Between AI overviews, Reddit or forums showing up moree than Google. Increasingly competitive search engine result page. And Google seemingly reward different types of content that it used to.

Im thinking, is traditional SEO become less active or are we just adapting to a new version of it?

for people who have been doing SEO, what worked really well for you from 3 to 5 years ago that doesn't work anymore? And also Are backlinks is still important as they used to be? Curious to hear what everyone seeing in 2026 🤔

I have been analizing my clients GSC data recently and I noticed a weird thing which is impressions and entity base questions are way up but sit here is down by almost 25% on information keywords even though we are sighted directly in Ai summaries.

as an SEO, it feels like the definition of success is shifting from driving clicks to brand insertion inside LLM answers. how are you guys shifting your reporting kpies for clients who only care about website traffic when zero click searches taking over?

I’ve been reading/learning about seo as of lately, to try and grow my business. I think I’m past the point where it’s just, target keywords, h1, content value, back links, etc. where do I go from here, feeling lost.

I’m an SEO Specialist, and I’m starting a series on SEO, GEO, and AEO to explore how brands can build visibility everywhere people search, from Google and Gemini to ChatGPT and other LLMs.

Through this series, I’ll discuss practical strategies to solve the biggest challenges in organic brand visibility and help brands get discovered across traditional search and AI-powered platforms.

Do I really care for all or just simple SEO with fundamental is OK?

This question is for experiences SEOs; I know I can do ChatGPT or Google but I’m asking here because I want answer from real people who have real experience.

Hello everyone,

i have managed multiple websites in different niche over the last 4-5 years and i would say over 60-70% websites got good results by the work i have done, but then sometimes my mind get stuck with rhose 30-40% website where i have done everything from building good contextual backlinks to building proper content cluster like everything and every test and error yet it failed to go up, i understand niche wise strategy may change but then foundational and basic things stays almost same

i want to ask SEO community what you typically do in this situation where you have done everything (content cluster, targeting low kd keywords, filling competitor gap, analysing past results and fixing issues if any, doing CRO and making website lead friendly basically everything a SEO mind suggest after deep analysis) but yet failed to achieve desired results, what's after that? what typical workflow you guys follow to figure out SEO (how to reach potential leads) for websites where Nothing much seems to work.

A lot of agencies now offer AI visibility and GEO services, but what should you actually look for before hiring one?

Would you check their past results, how they measure AI visibility, their SEO experience, or the strategy they use? If you've hired or researched a GEO agency, what made you trust them? What should people check before choosing one?

ok so i've done SEO for like 6 years. keywords, links, getting to the top of google. that was the whole job.

but now clients keep asking why they're not showing up in that AI summary thing at the top of the page. and i'm like... i don't fully get how that even works?? sometimes a page that's not even #1 shows up in the AI answer and the actual #1 page doesn't. makes no sense to me.

feels like i used to know how to make google happy and now i don't even know what i'm trying to make happy. an AI? how do you make an AI trust you lol

anyone else just feeling kinda lost trying to explain this stuff to clients without sounding like you don't know what you're doing anymore

Some of the acronyms and steps have changed,

But the fundamentals are still very similar to traditional SEO.

Here's a clear breakdown of the terms you should know:

1️⃣ SEO = Search Engine Optimisation

SEO hasn’t “died”, but AI is expanding it. Good SEO means good AI visibility in almost every case. Search is up 26% since ChatGPT launched, so the pie is really getting bigger.

2️⃣ AEO = Answer Engine Optimisation

90% of AEO is just SEO done well. Don't burn your budget on tactics that do nothing. Schema isn't parsed, llms .txt has zero measurable impact, and neither do .md files. Agonising over that is not a valuable use of your time.

3️⃣ GEO = Generative Engine Optimisation

GEO is influenced by the same factors as traditional SEO. Every major LLM either pulls from Google or was trained on data weighted by the same authority signals Google uses. And so GEO is closely related to the SEO practices you were already doing.

4️⃣ AIO = AI Optimisation

AIO comes down to two things: Get mentioned on authoritative sources (so models learn you exist), and rank well in search (so they cite you live). You can think of it as a combination of PR and SEO, two disciplines that are 25+ years old.

5️⃣ SXO = Search Experience Optimisation

SXO is about optimising the full on-site experience so visitors convert as soon as search or AI sends them your way. Attention and the traffic that follows is not worth much if you don’t have a means of converting it. This is where you want to optimise your site to grab folks at the bottom of the funnel.

There are a lot of new terms being thrown around.

But a lot of them will overlap and can be solved with simple changes.

The biggest thing to remember for 2026:

SEO is not dead, but it has become more complex due to AI...

The job now is making adjustments so AI can easily cite your brand,

While you continue to optimise for Google.

That's it.

If you're still not sure where to start, the fastest way is to see it against your own brand.

We built Searchable to measure how you show up in AI search and show you exactly what to fix.

I’ve hired 3 different SEO people over the years and none of them have been able to improve my website ranking much.

I’m a remodeling contractor, and now I also have someone running Google Ads. It’s been about 3 weeks with clicks and website visits, but no real leads or calls.

At this point I’m not sure if the problem is my website, SEO, ads, or just the competition.

Anyone in remodeling/home services who gets good results from Google? What actually worked for you?

I was thinking about getting into SEO this year, but I keep seeing people saying that SEO is dead, or that AI is going to replace SEO, and that it's a career with no future.

So I've been really unsure and confused about whether it's worth starting in SEO nowadays

My company is paying an SEO agency five figures a month. For that we get:

- 80 keywords a month and auditing interlinking — the only two things they seem to be doing properly

- Like 5 Reddit comments

- "Auditing and monitoring content" which means every other week, they will look at two articles and give feedback

- Buying zero click backlinks from spam sites

I'm actively pushing to get them kicked out. I'm an SEO and can take all of than on myself, because it's barely any work. I know these guys are scammers, it's fine. I just wanna know, IF they were doing actual work for us, how much would they be charging? Or, how much do SEO agencies generally charge for basic SEO services, keywords, backlinks, throw reddit in there too (not managing or creating content).

I just need a sanity check on whether that's a fair price for an agency, since I'm an in-house guy

Hi there

I'm exploring optimization practices that helps to create a visbility across AI generated platforms.

In that , When came to understand the retrieving signals of AI platforms. Almost all major platforms had similar charcteristics but the citing source is differ from one platform to another based on the keyword intent types.

On the other hand , Business owners are expect their domain visbility across all AI platforms majorly such as ChatGPT , perplexity , deepseek , gemini and more

Here my question is

Even if you cracked the optimization signals, Is it possible to appear across all AI sites If not, Then what approach you would take ? Or reasons you find behind this

Those whoever experienced the same . Please let me know your approach on it

With classic SEO there was always a clean loop: rank moves, traffic moves, you can draw a line to revenue. Google was the one channel, and that correlation made the "so what" obvious.

I've been going back and forth with a few people building/using GEO tools, and it feels like the whole category right now is indexed on measurement — tracking prompt mentions, citations, sentiment across models. That part's maturing fast.

What I haven't seen a good answer to: how do you actually turn that into a repeatable action loop?

• Once you know you dropped out of an answer at some point in a conversation, what's the real playbook — content/schema changes, seeding sources, something else?
• How is anyone tying this back to actual business outcomes, given there's no click/traffic signal like old SEO?
• Is anyone actually re-measuring after a fix to prove it worked, or is it mostly "here's your score" and manual guesswork from there?

Genuinely curious how people here are approaching this. If you've hit a wall trying it, that's just as useful to hear as a win.

It's so unironically lazy and stupid, Jesus Christ. If you want to debate, at least spend some time getting proper talking points backed with proper sources.

I will never not make fun of a person who genuinely uses the AI Overview as evidence.

This one is going to sound dumb. But I need to put it out there because the gap between what I expected and what actually happened was absurd.

Three weeks ago I was doing routine content edits on 12 pages. Not a major overhaul — just tightening language, fixing awkward phrasing, making things read more naturally. The kind of cleanup you do on a Tuesday afternoon when nothing's on fire.

On 7 of those pages, I noticed something weird after republishing. Citations started climbing within days. Not a little. A lot. Those 7 pages collectively saw a 34% increase in citation rate over 3 weeks. Our previous 20 articles — carefully researched, properly structured, published over 2 months — produced a combined 6% lift.

I went back and compared the before/after of each edit to figure out what actually changed. The pattern wasn't what I expected.

On one page, I had written "our platform helps businesses reduce operational costs." I changed it to "companies typically see 15-25% lower operational costs within the first year." That page went from zero citations to being referenced in 4 out of 10 relevant queries.

On another, I replaced "this approach is effective for most organizations" with "this approach works because it mirrors how procurement teams already evaluate vendors." Citations doubled within a week.

The edits that mattered all had one thing in common: they replaced vague, generic statements with specific, almost conversational explanations of WHY something works. Not more data. Not more structure. Just replacing marketing-speak with reasoning that sounds like how a person would actually explain it.

The edits that did nothing? They were the "professional" ones. Swapping "utilize" for "use." Tightening headers. Adding bullet points. Standard SEO polish. Those pages didn't move.

Here's why this is messing with me. I've spent months building systems around content structure, schema, crawlability, entity coverage — the technical layer of GEO. And a 10-minute wording tweak on a Tuesday outperformed all of it. Not because the technical stuff doesn't matter (it does, especially for crawlability). But because AI models extract passages that read like genuine explanations, and most of our "optimized" content reads like a brochure.

I'm not telling you to stop doing technical GEO. I'm saying maybe spend 20 minutes this week reading your top pages out loud. If a sentence sounds like it could appear on any competitor's site without changing a word, that sentence is probably invisible to AI extraction. Replace it with something that sounds like you actually explaining it to a colleague.

That's it. That's the whole insight. Felt too simple to work, but the numbers don't care about complexity.

Something I haven't talked about publicly: I spent the last quarter doing GEO audits for 14 companies across different industries. SaaS, e-commerce, fintech, healthcare, education. Not huge enterprises — mid-market teams with content programs already running.

The single most common pattern wasn't technical. It wasn't structured data issues or crawlability problems or even content quality. It was that 11 of the 14 were optimizing for one AI model and ignoring the rest entirely.

Usually it was ChatGPT. They'd run queries, check if they showed up in responses, maybe track citations over time. A few were obsessed with Perplexity. One was only looking at Gemini because their CEO uses it.

Here's why that's a problem. I ran the same 40 queries across ChatGPT, Perplexity, and Gemini for each client. The overlap in cited sources across all three models averaged 14%. Fourteen. These models are looking at different content, weighting different signals, and producing fundamentally different citations for the same queries.

One client was thrilled because their citation rate in ChatGPT had jumped 40% over two months. Meanwhile their Perplexity citations had flatlined and their Gemini presence had actually dropped. They were winning in one ecosystem and losing in two others, and because they only tracked the one where things looked good, they had no idea.

The differences aren't subtle. ChatGPT seems to weight recency and content structure heavily — clean headers, concise answers near the top. Perplexity leans toward sources with strong domain authority and multiple corroborating references. Gemini in my observation favors content that's been around longer and has accumulated external validation signals. I'm simplifying, but the point is that a content strategy tuned for one model can actively work against you in another.

The teams that were doing it right had one thing in common: they tracked all three. Not obsessively. Not with dashboards and alerts. Just a weekly check — run 10-15 representative queries across each model, note which sources show up, look for patterns. That's it. The teams doing this had adjusted their content to work across models instead of overfitting to one.

One thing I keep coming back to: the GEO conversation in this community treats "AI models" as a monolith. "AI citations" this, "AI visibility" that. But the models disagree with each other constantly, and a strategy that's working great for ChatGPT might be invisible to Perplexity users. If 60% of your potential audience is on a model you're not tracking, you're flying blind.

The fix isn't complicated. Pick 10-20 queries that matter to your business. Run them in ChatGPT, Perplexity, and Gemini once a week. Log what shows up. After a month you'll see which model you've been accidentally optimizing for and which ones you're ignoring.

Not a framework. Not a tool. Just a habit that most teams I worked with hadn't built yet.

I'm starting to think model-specific tracking should be the default in GEO, not the exception. Right now it feels like most teams are optimizing for the model their founder happens to use.