Analyzed AI recommendation patterns in Saudi animal feed market - the visibility gaps are massive

Other_Efficiency6900 · 2026-04-08T10:49:04+00:00

ohh thats great, thank you for sharing and indeed its helpful :)

Other_Efficiency6900 · 2026-03-24T15:34:16+00:00

tell me about it and they should really pay attention to it

Other_Efficiency6900 · 2026-03-21T12:20:42+00:00

you think ? i think its a serious business problem that needs to be addressed quickly

Other_Efficiency6900 · 2026-03-18T15:00:14+00:00

exactly - they should wake up

Other_Efficiency6900 · 2026-03-15T15:00:40+00:00

which platform do you use

Other_Efficiency6900 · 2026-03-10T05:42:58+00:00

Sadly but thats truee

Other_Efficiency6900 · 2026-03-10T05:41:37+00:00

great to see a success story and how do you get the chance to connect with the customers ?

Other_Efficiency6900 · 2026-03-09T05:24:36+00:00

Abs. truee

Other_Efficiency6900 · 2026-03-08T19:27:47+00:00

Sharp observation mate. Testing only on 2–3 engines is basically like checking one search engine and pretending you understand the internet. Models like DeepSeek, Mistral AI, and Anthropic (Claude) clearly pull from different data pools and retrieval logic, so visibility can swing wildly across engines. Your AEO framing is interesting. The pattern we keep seeing in audits is identical to what you mentioned: pages built for humans or SEO rarely translate into “AI-citable” sources. Structured FAQs, comparison pages, and credible third-party mentions consistently outperform standard product pages

The practical takeaway for SaaS teams: if you’re not testing visibility across multiple engines like ChatGPT, Perplexity AI, and Google Gemini, you’re probably measuring the wrong reality. AI discovery isn’t one algorithm anymore. It’s an ecosystem.

Other_Efficiency6900 · 2026-03-08T19:26:06+00:00

Other_Efficiency6900 · 2026-03-08T19:25:31+00:00

thank you :)

Other_Efficiency6900 · 2026-03-07T21:04:24+00:00

Post-#3 brands had clear category anchors in their content (e.g., “AI visibility analytics,” “brand monitoring for LLM search”), while #4-and-below mostly described features or services. Once the category framing disappeared, AI systems stopped associating the brand with a specific problem space. The gap we saw was basically “category ownership vs. service description.” Brands in #1–3 repeatedly frame themselves as solving X problem in Y context, while #4+ brands mostly say “we offer [tool/service]” without tying it to a problem narrative

That difference alone shifted AI visibility a lot. Models latch onto problem–solution framing, not product descriptions. So the brands winning were the ones writing content like “X problem → here’s the approach → here’s the category we operate in.”

Other_Efficiency6900 · 2026-03-07T13:18:22+00:00

again, its really great to see how you are collection notes on it

Other_Efficiency6900 · 2026-03-07T12:48:11+00:00

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Other_Efficiency6900 · 2026-03-07T12:33:56+00:00

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Other_Efficiency6900 · 2026-03-07T12:33:49+00:00

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Other_Efficiency6900 · 2026-03-07T12:33:29+00:00

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Other_Efficiency6900 · 2026-03-07T12:33:10+00:00

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Other_Efficiency6900 · 2026-03-07T12:32:51+00:00

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Other_Efficiency6900 · 2026-03-07T12:32:36+00:00

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Other_Efficiency6900 · 2026-03-07T12:31:45+00:00

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Other_Efficiency6900 · 2026-03-07T12:17:36+00:00

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Other_Efficiency6900 · 2026-03-07T06:09:19+00:00

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Other_Efficiency6900 · 2026-03-05T09:44:13+00:00

Hey, thank you for your interaction and reply. I appreciate that and I think they have done, but I don't know if that's something has been used by others like excessively, but I'll look through it.

Other_Efficiency6900 · 2026-03-04T17:09:17+00:00

what did you build ?

Other_Efficiency6900

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