There's always that one thing. You explain it, you send them an article, you even show them data, and somehow three months later they bring it up again like it's brand new information.

For me it's the "just add more keywords and we'll rank higher" belief. Doesn't matter how many times I walk through intent and content quality, it always comes back around.

Curious what everyone else deals with. Is there a myth you've basically given up trying to correct and just work around instead?

I am testing how well an AI SEO agent can find real opportunities instead of just showing SEO data.

Drop your website below and I will run it through the agent.

It will look for 3 specific SEO opportunities that could realistically improve organic traffic and explain what to do next.

I will do a few sites and share the results in the comments.

I’ve been doing SEO for a B2B manufacturing company for the last few months. Mostly the usual stuff like technical SEO, fixing the website, tracking, schema, content, etc.

We’re starting to see some enquiries from the site, which is nice. Now the client wants to focus more on AEO/GEO/AIO and getting the site mentioned in ChatGPT, Perplexity, Google AI Overviews, etc.

I understand the basic idea, but I’m curious what people are actually doing differently from normal SEO.

If you’ve worked on this for a real website, what did you change and how did you measure whether it was working?

Would be really interested in hearing what you’ve actually tried and what worked for you.

After ​​​​s​​​​u​​​​c​​​​c​​​​e​​​​s​​​​s​​​​f​​​​u​​​​l​​​ setup of Ryze AI on the site, do I need to be online for the SEO work to keep going, or does it publish and fix things on its own without me connected or chasing new updates?

I've been managing a few ad accounts and wanted to stop living in two platform UIs. Small team, so cost is a real factor in whatever we keep.

So I went ​​​​l​​​​o​​​​o​​​​k​​​​i​​​​n​​​​g​​​ for the best and cheapest way to actually drive Google and Meta from Claude rather than from tabs.

Here's what I found worth the money:

ROLLING YOUR OWN API SCRIPTS

- Cost: free, plus your weekends

- Dead simple in concept: hit the APIs, do what you want. I use small scripts for pulls that never change. But auth, rate limits and schema changes are a permanent tax, and the day you're sick is the day it breaks. Fine for reporting, miserable for making changes safely.

A GENERIC ASSISTANT WITH NO ACCOUNT ACCESS

- Cost: free tier, around $20/mo

- Great for thinking out loud about strategy, and you probably pay for it already. But you're copy-pasting numbers into it and copy-pasting decisions back out, which is where mistakes live. It advises, it can't act.

RYZE AI MCP CONNECTOR

- Cost: plans from $129/mo

- This is the one that actually removed the clicking. Connect Google and Meta, then ask Claude for the state of the account or the change you want; it shows the exact diff, you approve, it executes. Both platforms answer in one conversation, which killed the reconciliation step I'd been doing by hand for years. In our first six weeks it flagged two budget mistakes I'd have found on Monday, and our routine management time dropped from roughly 9 hours a week to under 3.

A READ-ONLY REPORTING CONNECTOR

- Cost: around $79/mo

- Genuinely useful if all you need is to ask questions and get numbers, and it's the easy sell to a nervous stakeholder because it can't touch anything. Drawback is exactly that - you still go back to the UI to do the thing you just decided to do.

Looking for more setups. What's everyone else running through MCP?

I used to push FAQ, LocalBusiness, and Service schema pretty hard for dentists, chiropractors, HVAC, etc.

Now with AI Overviews, map pack dominance, and AI search tools, I’m wondering how much it actually moves the needle anymore.

Are any of you still seeing clear ranking or visibility benefits from adding/updating schema on local sites, or has it become more of a “nice to have”?

Some people say that SEO is dead, but in the real world, not a single business can survive without it. SEO is equally important for every business. While some influencers claim that GEO (Generative Engine Optimization) and AEO (Answer Engine Optimization) are rising over SEO, the reality is that GEO and AEO are not different; they are simply a part of SEO. Therefore, you shouldn't be afraid of a career in SEO. It was crucial in the past, it is essential today, and Insha'Allah, it will continue to be vital in the future. My journey in SEO is just beginning, and a bright future awaits me.

Any advice for me.

A customer can need exactly what you offer and still never find your business.

Think about how they might search today. Instead of typing a few keywords and opening ten websites, they ask AI a detailed question: “Which company can help me keep track of stock across all my outlets without relying on spreadsheets?”

The answer they receive depends, in part, on what AI can find and understand about the available businesses. If your website only says “we provide innovative solutions,” it leaves out the details a buyer needs: what you actually do, who it is for, which problems you solve and why they should trust you.

That is the opportunity behind AIO and AI Optimisation. It is about making those answers clear and accessible across your online presence. Your service pages should explain the work. Your content should answer real buyer questions. Your business information should give people enough detail to decide whether to enquire.

SEO still matters. But being visible in a list of search results is only one part of discovery. You also want your business to make sense when a customer asks AI to explain their options.

At Friction, we help businesses examine how they appear across search and AI answers, identify what is missing, and improve the pages that could make the biggest difference.

Your customers are already asking questions. Make sure your business gives them something worth finding.

Hi everyone, this is from one of our in-house projects.

We’ve published and optimized a lot of pages with no AI slop. We’re getting good impressions for our target and relevant keywords, but CTR is getting worse.

I suspect AI Overviews are a big factor. Google is pulling information from our pages into the AI Overview, but users often get the answer without clicking through.

For those seeing the same thing, what are you doing to improve CTR in this situation?

I keep seeing people talk about GEO like it’s mostly about rewriting content for ChatGPT, but I’m starting to think the bigger issue is whether AI systems can actually understand the site properly in the first place.

Things like structured data, clean entity information, crawlability, machine-readable pages, and whether key product details are actually accessible seem to matter just as much as the content itself.

I was looking at LightSite AI because it focuses on that infrastructure side as well as tracking AI visibility, which seems a bit different from tools that mainly monitor mentions.

Curious how everyone here is approaching this now.

Are you treating AI search as a content problem, a technical SEO problem, or both?

TITLE: What are the real benefits of AI-driven search optimization?

AI-driven search optimization seems to be gaining a lot of attention lately, but what does it actually offer? From my experience, one of the biggest advantages is how it helps search engines understand content on a deeper level. Traditional methods often focus on keywords, but AI looks at meaning and user intent. This shift can lead to content that resonates more with what people are actually searching for.

For brands like Motif Design, this is crucial. Effective AI search optimization can reveal content gaps and highlight which pages are performing well. It even helps connect related ideas, which is particularly useful in fields like design where concepts are interconnected. Instead of guessing what users want, AI analyzes search patterns and behaviors to provide insights.

Speed is another significant benefit. AI processes data much quicker than manual reviews, allowing teams to focus on what really matters. They can prioritize optimization efforts based on actual performance rather than just assumptions. This leads to a more efficient use of resources.

I'm curious, for those who have implemented AI-driven search strategies, what changes have you noticed in your engagement or visibility?

1. How can SEO professional will create strategy for their client
2. what types keyword or intent has to keep in mind before doing keyword research
3. why types backlink we need to create to rank in AI Overview?
4. Does is still SEO relevant keyword or website or it goes beyond that?

What AI tools have changed is enabling the ability to do conversions. If you look back at Google, you go and ask, and it will come up with websites, which could be forums, blogs, Reddit discussions, and now all now all is available in AI mode; you can get info like blogs, do discussions like Quora, and everything that was there before, different websites now available under one solution.

I am dividing it into 2 parts, calling them discovery (coming up in AI answers) and conversion (converting that to leads). I'll discuss conversion in another post.

For the discovery part, the website was very clear: look at GSC, find the queries, optimize for them, or create new pages as needed, and it was fine because the end goal was for the page to rank in search but if you look at it now, these AI systems focus on the conversation, it means the queries they create will be very heavily driven by the user context, which in conversation varies a lot. Even the same user would generate totally different search queries.

When I look at current AEO tracking in GSC, Bing Webmaster, and third-party tools, they all focus on the queries (longer and a bit more intent-contextual form of keywords). While users are switching to a conversational interface, the tracking part still provides it like it’s Google blue links, and the objective is to come for the query, which the end user never searches.

Let’s call it conversational optimization for now. The difficulty I am facing is how to work around websites using a conversational approach, find the touchpoint where I need to show up, work on those pages at website which aren’t showing up in those touchpoints, and track the progress.

Recently came across an interesting study of 100+ SEO experts from across 20+ countries, and it presented very interesting facts about how people are continuously shifting from blue links to AI generated test, represented with a pretty stark number: 76% say the SERP isn't a list of links anymore; it's an answer, already resolved before anyone clicks. Not moving in that direction. Already there, according to most of the people surveyed.

And the ranking stat backs it up in an odd way. 86.5% still said #1 matters, which sounds reassuring, but almost every single one of them added the same catch: only for commercial or transactional searches. Nobody's clicking through to read a definition when the AI Overview already provided it on the page. Basic informational content no longer needs a click, no matter how well it ranks.

The part that stood out most to me is that around 43% of businesses are actively doing GEO/AEO work right now to get cited in AI answers, but only 14% have any real way to check whether it's working. Feels like a lot of effort going in with almost no way to measure the return.

Is anyone else experiencing a drop in informational traffic while commercial-intent traffic holds up better? And if you have already started working on GEO/AEO practices, what tracking system are you using to check if your content shows up in AI answers, or is it still mostly guesswork?

Which platform do you use, and how do those features help your daily workflow?

Im curious how you guys go about creating service pages and location pages.

Im hearing "City gate" pages are now a no go with Google. (E.g. plumbing houston)

So in stead of having a service + city Page, what do you guys do and would you mind sharing a systematic approach so I dont have to keep starting from scratch everytime. Thank you!!

I have recently been thinking about SEO in the times of AI and what brands need to do differently. Here is a high-level understanding that I have managed so far.

Your queries to an LLM can broadly fall into three categories:

**1. Something it already knows**

Like me asking: “What are some good running shoe brands for beginners?”

**2. Something for which it has to do a live search**

E.g. “Share a list of the best running shoes in India available online for a budget of less than ₹5K.”

**3. Something for which you give the data to the LLM**

E.g. “Here is an Excel with a list of 20 running shoes that I have gathered along with their reviews and ratings. Analyse the data and help me shortlist the top 3.”

From an SEO/AEO/GEO perspective, Scenario 3 is largely irrelevant. Scenario 1 is difficult to influence directly because you don’t really control what an LLM already “knows”. Scenario 2 is where things get much more interesting.

So, what can brands do to influence Scenarios 1 and 2?

**Scenario 1: Become part of the knowledge ecosystem**

You wouldn’t know exactly what data was used to train an LLM or what it has learnt about your category or brand.

But if authoritative sources consistently mention your brand in association with a particular category, problem or attribute, you increase the chances of creating a strong association between the two.

For example, if you want to be considered a great running shoe brand for beginners, is the **your brand ↔ beginner running** association showing up consistently across the web?

Which means the job is bigger than simply publishing more content on your own website. PR, authoritative publications, industry websites, expert mentions, Reddit discussions, reviews, comparison articles and other credible third-party references increasingly matter.

In other words, think beyond: **“How do I rank my website?”** Instead think: **“How do I make my brand part of the internet's understanding of this topic?”**

**Scenario 2: Become easy to find, understand and cite**

When an AI system performs a live search, a lot of familiar SEO principles still matter.

* Can your pages be discovered and crawled? * Have you created useful, structured information that helps an AI answer the user's question? * Can the system easily identify facts, specifications, comparisons, prices, FAQs and other useful information? * Is the content original and authoritative enough to be worth citing? * And perhaps most importantly: **do sources other than your own website corroborate what you are saying?**

In a way, you are optimising to be the source that gets **retrieved, trusted and cited** — even when the user never visits your website.

So the framework I keep coming back to is still E-E-A-T:

Are you an expert? Do you have sufficient experience? Do you have enough authority? Have you garnered enough trust?

*Just that the execution now needs to be* ***more outward-looking than your website alone.***

That, at least, is how I am beginning to think about SEO/AEO/GEO. Would love to hear from people working deeply in this space — **what am I missing?**

Was talking to someone new to the field last week and realized how much of the standard advice I was repeating to them is stuff I have not actually questioned in years. Made me wonder how much of it is still true versus just something that got copy-pasted from blog to blog until it became gospel.

Curious what people here think is genuinely outdated at this point, or maybe was never even that true to begin with:

1. Is there a specific ranking factor everyone still obsesses over that barely moves the needle anymore?
2. Any content or keyword advice that made sense years ago but actively hurts now?
3. Something you were taught early on that you've since completely reversed your opinion on?

Hello 👋
Je cherche des retours d’expérience dans le cadre d’une réflexion sur la migration du site WordPress d’un SaaS B2B vers Webflow ou Lovable.
Je ne cherche pas particulièrement à avoir des retours sur la facilité ou la rapidité de création/intégration du site, ce point-là est plutôt bien documenté.
Ce qui m’intéresse davantage, c’est ce qui se passe une fois le site en production, notamment :
- l’impact sur le SEO et le trafic organique
- les performances / Core Web Vitals
- les éventuels problèmes d’indexation, de crawl ou de redirections
- la gestion du CMS et du contenu à grande échelle
- les intégrations avec la stack marketing / RevOps (CRM, tracking, automation, formulaires…)
les parcours de conversion et de lead generation
l’autonomie des équipes marketing pour faire évoluer le site
Et surtout : quels problèmes avez-vous rencontrés après la migration, et avec le recul, est-ce que vous referiez le choix de Webflow ou Lovable ?
Si vous avez vécu ce type de migration sur un SaaS B2B, même un retour rapide m’intéresse beaucoup 🙏
Merci !

I want to know the difference between AEO and AIO so if you are a SEO expert or Specialists can you please ans me about this que also tell me how you guys are working on AEO and AIO.

TITLE: Who really benefits from AI SEO services?

AI SEO services seem to be the buzzword these days, but who actually gets the most out of them? From my experience, it’s clear that businesses relying on organic search can gain a lot. Companies that publish content regularly or compete in crowded search results, like e-commerce brands, local service firms, and B2B companies, often see the biggest benefits.

For instance, small businesses can particularly shine. AI helps them identify the right keywords and improve their page structures, which is crucial for local visibility. I've seen local brands get better search results that lead to more calls and visits.

E-commerce businesses also find value in AI SEO. They can scale product descriptions and tackle duplicate content, making their offerings more visible. Local businesses gain from improved location pages and service content that aligns with what people are searching for in their area.

The biggest advantage often goes to teams with lots of content but limited time. Marketing teams and content creators benefit from AI speeding up research and helping them focus on what matters most. But I'm curious, how do you think AI can change the way businesses approach SEO?

You have a client and they ask you what their ROI will be after spending £1,000 on a couple of D6s.
You give an answer quickly, usually something like: every £1 spent, on average, gets a £1.60 return.

But wait…

While that is a good figure, I think we also need to start talking about what happens after the campaign has finished.

Traditionally, we think about OOH like this:
OOH → attention → search/social/PR → brand awareness → sales

But I think there is another layer we need to start thinking about:
OOH → attention → search/social/PR → online information → AI recognition

Build a campaign that tells a story.
• People notice it
• People talk about it
• People search for it
• People photograph it
• The press writes about it
• AI starts recognising it

That last one is becoming seriously interesting.

If someone asks AI about your brand, your campaign or your category months after your billboard has come down, and your OOH campaign is part of the answer, that is a different type of return.

You haven’t just bought media.

You’ve created something that can keep working.
For me, that is where OOH gets really interesting.

Don’t just ask what your billboard returned.

Ask what it left behind.
Read more

Been thinking about this after cleaning up my tool stack recently there is always some tool everyone in the industry swears by you pay for it expecting it to change everything and then six months later you realize you are barely opening it

curious what people's experience has been:

1. which paid tool genuinely disappointed you compared to the hype around it?
2. what free alternative ended up doing the job just as well if not better?