It's finally here! Amazon Rufus AI Search Share Revealed, Cross-Border Sellers Must See Data
It's finally here! Authoritative data on the actual impact of Amazon's Rufus AI has finally been revealed, which is important information for all cross-border e-commerce sellers and branded overseas sellers that cannot be ignored.
According to ChannelX's latest report, Amazon's Rufus AI shopping assistant has handled about 13.7% search requests on the platform! This number far exceeds the expectations of industry experts. What's even more eye-opening is that to support this massive system, Amazon deployed 80,000 AWS chips during Prime Day, processing 3 million tags per minute.
What does this mean for Taiwanese cross-border sellers? More than traditional SEO, you now need to think about how AI understands and recommends your products. research by Azoma founder Max Sinclair has shown that Rufus can handle more than 270 million queries per day, assuming that each Rufus query contains an average of 10-11 words (about 15.75 tokens)!
It's not just Amazon, the entire e-commerce ecosystem is shifting to AI. platforms such as ChatGPT and Perplexity have also introduced AI shopping features, which will redefine how consumers discover and buy products. For example, if you're selling a smart home product, AI will make recommendations based on how the product will be used in different rooms, not just based on keyword matching.
Now, there are smarter AI optimization tools to help cross-border sellers improve product visibility. Whether you're an Amazon Germany seller or a multi-category layout seller, you need to rethink your product content strategy: no more monotonous product photos on white backgrounds, embrace rich life-scene images and detailed contextual descriptions.
It's just getting started, but it's already affecting hundreds of millions of purchasing decisions. Are you ready for the age of AI shopping?
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# Amazon Rufus #AI shopping # cross-border e-commerce # product optimization # e-commerce trends # Taiwan sellers # brands going overseas # data analysis