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"As the number of ratings increase, customers can see a larger set and thus a more accurate rating," said Patrick Miller, co-founder of Flywheel Digital, an agency that helps large consumer brands sell on Amazon. "For brands, this means the black-hat review clubs and sellers will have less impact, as fake reviews as a percentage of legit reviews should decrease." "The more customers who purchased the product [who] provide feedback, the more accurately the star rating reflects the experience of all purchasers," is how Amazon spokesperson Angie Newman put it, without directly referencing fake reviews. Amazon does not provide many specifics about how a product's overall star rating is calculated, other than stating that it is not a simple average but instead uses "machine-learned models" that take into account factors such as how recent the rating or review is and whether it was a verified purchase or not. It's not clear whether one-tap ratings will carry as much weight in these models as written reviews. "The upside is they are getting more feedback, and as long as it's done correctly, maybe it's more representative of the entire population of buyers," said Matt Moog, the CEO of PowerReviews, a company that sells product review technology to big retailers and consumer brands. "The downside is it's less descriptive." "If you want to give the whole marketplace more feedback to work with, then Amazon has succeeded," Thomson said. "The problem is it's not useful feedback." Amazon, though, is known for making changes and then experimenting and altering an approach depending on the behavior it produces and its unintended side effects. For that reason, some in the Amazon ecosystem predict further changes are on the way.

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