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Ever seen a page use a keyword 23 times and get zero AI citations?
We audited one. "best CRM for small business" in the title, H1, meta, alt text, and body. Textbook SEO.
The page ChatGPT, Perplexity, and Google AI Overview all cited that phrase 3 times. But it covered pricing,
integrations, migration from spreadsheets, implementation time, and use cases by team size.
AI doesn't match your phrase to the query. It builds a map of the topic and checks if your page covers it.
Takeaway: stop asking "what keywords do we target?" Ask "what topic do we need to own, and how completely do we cover it?"
We’ve looking for Shopify Agency partners. Comment below if you own an agency or recommend one 👇🏼
You’ll get free Pro access to Flozi.
I gave Opus 5.5 and Sonnet 5.5 the same job: “Search Console growth has stalled for this site, help me debug it.” Same data access, same repo.
Both found the real story. Growth hadn’t stalled; the main site had lost ~70% of its clicks since its peak, and a subdomain’s traffic was hiding it in the totals. Both linked the drops to this year’s core updates and found the same losing pages.
The difference was in how they worked:
→ Opus went wide without being asked. It checked brand-search demand, found money keywords ranking ~#5 with zero clicks, cross-checked GA4, and looked through the repo history for site changes.
→ Sonnet went careful. It tracked a fixed set of pages to prove the drop was a real ranking loss, not a mix shift, and flagged that “lines up with a core update” is timing, not proof.
→ Opus occasionally stated a guess as a finding. Sonnet never did.
My takeaway: for open-ended “something’s wrong, find it” analysis, I’d start with Opus, because it decides what to investigate next on its own. But I’d still verify its causal claims, or have a second pass check them.
One run each, so treat this as an observation, not a benchmark.
I keep seeing SaaS teams approach AEO like SEO. Add schema. Rewrite metadata. Make pages “AI-friendly.”
I don't think that's the core problem. After digging into what actually helps SaaS products get named in ChatGPT, Perplexity, and AI Overviews, I think 3 signals matter most:
1) Retrievability: can AI find and extract a clear answer from your site?
2) Authority: does AI have enough confidence to associate that answer with your brand?
3) Third-party presence: are you mentioned in the sources AI already trusts?
The easiest way to diagnose this: Take 20 questions your buyers would actually ask AI.
“Best X for Y”
“X alternatives”
“X vs Y”
“Is X good for Z?”
Run them without mentioning your brand.
Then check:
→ Not appearing at all = retrieval problem
→ In the sources but not the answer = attribution problem
→ Mentioned but described vaguely = positioning problem
→ Competitors everywhere = third-party presence problem
That changes how you should think about AEO. You're not just optimizing a webpage.
You're trying to become a product that AI can find, understand, trust, and confidently recommend.
I wrote 12 practical SaaS AEO hacks based on this framework.
Link in the comments.
I was alwasy skeptic the way schema has been sold for AI search, so I read some research on this, and the top findings are:
1) AI-cited pages are nearly 3x more likely to have schema (correlation only).
2) Adding schema to 1,885 pages showed no meaningful AI citation boost (Ahrefs).
3) Results: AI Overviews –4.6%, AI Mode +2.4%, ChatGPT +2.2% (mostly noise).
4) AI systems ignore JSON-LD and mainly read visible HTML.
5) High schema coverage does not improve LLM visibility (Search Atlas).
6) Google confirms structured data is not a ranking factor or required for AI features.
7) Stronger signals: backlinks, authority, content depth, freshness, and E-E-A-T.
8) Schema still helps rich results, but not AI citations.
adding article link in comments
How to build a brain for growth? This question bothered me most because whenever I saw people talking about building a company brain always wondered how to do it.
I have been doing it for a client using (GitHub + Claude Code) and have been able to achieve something I can leverage with any AI, like Claude or ChatGPT: a brain to execute growth.
I have seen many tools talking about whether a website is ready for AI, and all they do is check if content is available without JavaScript, but now agents are actively interacting, like submitting forms, navigating through pages, so agentic interaction readiness is more important than AI readiness.
Google launched WebMCP, which helps you test the exact thing. I tested Flozi today and wrote a simple guide on how to test any @webflow website from setup to testing.
(link in the comments)
The Technical and user-level differences between Traditional Search vs AI search
- Traditional Search: Type in a search box, get results, visit websites, focus on one-shot search.
- AI Search: Ask questions; AI visits websites and gets the answers, focused on conversation.
If you notice the last ones, what is changing is that products like Google AI Mode and ChatGPT are serving it.
So traditional search is dying then?
No, AI search requires websites to provide answers, and those websites are indexed by search engines like Google and Bing, so what has changed is how users now consume information: conversation rather than traditional search, and getting indexed on Google is still valuable.
For agencies, the base model of retention has changed primarily
- The cost to produce any asset (website, designs) has reduced
- Now systems dictate the output
If you want to retain a client, don't just offer them a website; include growth because it's the impact of your work on their business that matters more now.
I keep auditing the website, as I did for 69, and now compare it to previous audits; every website passed the crawlability check, but they are still lacking in
- AI Access: 88%
- Answer Readiness: 27%
- Schema: 24%
- Query Alignment: 20%
The problem isn't whether AI can access your site.
It's whether your content answers what buyers actually ask.
Touchpoints are the next funnels because they let you understand the user behaviour, and the difference is that they are outside your website, unlike funnels.
Touchpoints are new funnels because they define the buyer's decision in AI Search (AEO). Here is an example to understand them and how to find them for your website:
Let's say the buyer needs a Dubai website partner. One line to the AI: "Help me find some agencies."
1) Touchpoint 1: The ask itself
No budget, no priority stated. The AI filled the gap with assumptions.
2) Touchpoint 2: The shortlist
Six agencies scored, two chosen to go deeper on. A judgment call, made silently, that shaped everything after.
3) Touchpoint 3: The evidence
Team size, case studies, growth numbers, all pulled from the agencies' own websites. Nobody had called a single reference yet.
4) Touchpoint 4: The conflict of interest
One agency's "AI visibility" pitch relied on a tool they co-built themselves. Flagged in a footnote. Never resolved.
5) Touchpoint 5: The money
Two options, 5-10x apart in price. No budget was ever named to weigh against them.
6) Touchpoint 6: The ending
"Want me to dig deeper?" But the conversation ended with asking for reach-out details for both.
Note: There could be infinite conversations and touchpoints, and the goal isn't to find them all, just ideal ones.
If you are looking for free and accurate AEO tracking ? Try Microsoft Clarity's AI visibility Feature
It gives a breakdown of the authority your website holds for branded and non-branded queries, with competitive share.
Touchpoints are new funnels because they define the buyer's decision in AI Search (AEO). Here is an example to understand them and how to find them for your website:
Let's say the buyer needs a Dubai website partner. One line to the AI: "Help me find some agencies."
1) Touchpoint 1: The ask itself
No budget, no priority stated. The AI filled the gap with assumptions.
2) Touchpoint 2: The shortlist
Six agencies scored, two chosen to go deeper on. A judgment call, made silently, that shaped everything after.
3) Touchpoint 3: The evidence
Team size, case studies, growth numbers, all pulled from the agencies' own websites. Nobody had called a single reference yet.
4) Touchpoint 4: The conflict of interest
One agency's "AI visibility" pitch relied on a tool they co-built themselves. Flagged in a footnote. Never resolved.
5) Touchpoint 5: The money
Two options, 5-10x apart in price. No budget was ever named to weigh against them.
6) Touchpoint 6: The ending
"Want me to dig deeper?" But the conversation ended with asking for reach-out details for both.
Note: There could be infinite conversations and touchpoints, and the goal isn't to find them all, just ideal ones.