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.
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 (?)
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.