How Amazon Product Reviews Can Be Ranked According To Relevance


Everyone knows how important product reviews are on your product’s page. Such feedback enables potential buyers to decide whether they are going to purchase your products or not. Reviews also show buyers exactly what a product looks like, as customers tend to post pictures of the product they receive.
Amazon’s newly released “Machine Learning System” makes it simpler to select customer reviews that will be more useful to consumers by training the system to automatically recognize the most relevant reviews. The system will be able to rank and approve reviews faster – rather than waiting for consumers to “vote” for the most useful reviews.

The Machine Learning process is as follows:

  • All product reviews, whether approved or not, are placed into the Machine Learning System.
  • The system will use its programming to check, analyze and select the most relevant customer reviews.
  • The more relevant reviews will surface to higher/more visible positions to encourage more people to buy your goods.
  • And just like that, reviews are easily approved and ranked.

If you want to learn more about the Amazon Machine Learning System, click here.
The AWS machine learning algorithm does not pass judgement on the actual content of the reviews, just that consumers found the review useful.

Asking for Amazon Product Reviews

Product reviews won’t increase in number if you don’t make the effort to ask your customers for reviews. It is important to reach out to your customers in a timely matter. Automated feedback tools, like that offered by SellerMobile, can help manage and execute feedback emails efficiently.
Although it’s true that you can’t force your customers to write a positive review for your product(s), you can continue to provide excellent service and high-quality products to encourage positive feedback. Meeting customer expectations, and following up after a shipment, may also sway your customers to leave a positive review.

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