How do you make sense of competitor data in AI-generated answers?
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One interesting finding from our database is that the number of competitors appearing in AI answers does not determine a brand's share of voice.
In one category with 1,868 named brands, a single brand held 21% share of voice. Meanwhile, two brands competing against fewer than 400 held under 8%.
We recently launched ReSO AI to help teams make sense of these differences and identify opportunities to improve their AI visibility.
What's more challenging for you: understanding how often AI recommends your brand compared to competitors, or figuring out how to improve those recommendations?
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the number of competitors alone probably doesn’t tell the full story. I’d look at how often each brand appears, which questions trigger recommendations, and whether the same brands keep showing up.
@isabella_wandrei AI visibility seems worth monitoring, but I’d want to connect it to actual outcomes too. More recommendations are encouraging, though qualified visits and conversions matter much more to mmy business
my biggest question would be what separates the brands that get recommended from those that barely appear. If ReSO AI can help identify those patterns and suggest specific improvements, that would be useful beyond simply tracking rankings.
@ludovica_eleazer I agree. And we do have that (ever-evolving) list. That is the basis of the fixes ReSO suggests and the team guides.
AI visibility does not stop at tracking ranks but rather than start after it..