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quiqueqs commented on How do you deal with SEO nowadays?    · Posted by u/jackota
quiqueqs · 10 days ago
It's a crazy market right now. Since LLMs provide 0 analytics insight, all of the available optimization tools are pretty trying to guess or reverse-engineer prompts and their answers. Since it's still pretty much a black box, I think most of the effort is being spent in experimenting.

The one concrete thing I've noticed are some companies changing their SEO blog strategies. Where previously they tried to position themselves as thought-leaders, I've seen an increase if blog posts where they add transparency to what they offer (very clear product descriptions, pricing, use cases, etc.). I believe the general idea is that this type of summarized content is more likely to be picked up by LLMs.

Disclaimer: I've built one of these AI visibility tools (Cartesiano.ai), so I've seen just how much noise & uncertainty is around this space.

quiqueqs commented on Ask HN: How does ChatGPT decide which websites to recommend?    · Posted by u/nworley
nworley · 10 days ago
This is exactly what set me off in trying to figure out the visibility gap.

What’s strange is that we’re moving into a world where recommendations matter more than a click, but attribution still assumes a traditional search funnel. By the time someone lands on your site, the most important decision may have already happened upstream and you have no idea.

The UTM case you mentioned is a good example: it only captures direct "AI to site" clicks, but misses scenarios where AI influences the decision indirectly (brand mention to later search to visit). From the site’s perspective tho... yeah it looks indistinguishable from organic search. It makes me wonder whether we’ll need a completely new mental model for attribution here. Perhaps less about “what query drove this visit” and more about “where did trust originate.”

Not sure what the right solution is yet, but it feels like we’re flying blind during a pretty major shift in how people discover things.

quiqueqs · 10 days ago
This is why most of these AI search visibility tools focus on tracking many possible prompts at once. LLMs give 0 insight into what users are actually asking, so the only thing you can do is put yourself in the user’s shoes and try to guess what they might prompt.

Disclaimer: I've built a tool in this space (Cartesiano.ai), and this view mostly comes from seeing how noisy product mentions are in practice. Even for market-leading brands, a single prompt can produce different recommendations day to day, which makes me suspect LLMs are also introducing some amount of entropy into product recommendations (?)

quiqueqs commented on Show HN: Coronavirus symptoms checker (differentiate coronavirus from cold/flu)   coronavirus-signs-and-sym... · Posted by u/quiqueqs
phyzix5761 · 6 years ago
According to the Wang et al study only 50% of cases present with cough and 70% of cases present with fatigue. It seems on your website that cough is a requirement for the corona diagnosis. Is my assumption correct?

(https://jamanetwork.com/journals/jama/fullarticle/2761044?gu...)

quiqueqs · 6 years ago
Hi, correct - cough, fever and difficulty breathing are the 3 factors with the highest weight. This is based on a study of 55,000 confirmed cases in Wuhan, China (source: https://www.lbc.co.uk/hot-topics/coronavirus/coronavirus-sym...)
quiqueqs commented on Show HN: Coronavirus symptoms checker (differentiate coronavirus from cold/flu)   coronavirus-signs-and-sym... · Posted by u/quiqueqs
quiqueqs · 6 years ago
Based on the information provided on the website of CDC (Center for Disease Control and Prevention).

u/quiqueqs

KarmaCake day123May 17, 2011View Original