The company feels that this category is challenging. Mr. Khalifa of Fakespot pointed to a peculiarity that he has noted in several production lists, most of which carry high star ratings and thousands of reviews. “I looked at asparagus with 10,000 reviews,” he said, but only two of the five-star ratings had written reviews. what about the rest?
Last year, Amazon began testing a one-tap rating system, designed to encourage customers to leave a simple star rating in place of a full review. Its motivations were varied: it could help reduce the impact of fake reviews by dramatically increasing input from buyers; Overall, it produces more feedback for working with Amazon; And it dramatically increases visible numbers ahead of overall ratings, giving customers confidence. The experiment met with some criticism from vendors, who worried that the one-star rating left them without any explanation or recourse.
This year, Amazon rolled out one-tap ratings more widely, and they are influencing star ratings across the board. Buyers looking for a new iPad with 4.8 stars compiled from more than 49,000 public ratings can come across the listing. A deeper look suggests that fewer than 6,000 of those ratings are associated with actual reviews. In production, the ratios are even more extreme.
As Amazon has expanded into the product category after the product category, Amazon reviews have been extended to the extent of its look. The most basic products of all can bring it to its breaking point.
It has taken just 60 people to write a full review for Yellow Onion on Amazon, while more than 6,000 have left ratings, averaging 4.7 stars. Some people have complaints about local whole foods, shopkeepers in particular, or whole foods in general, while others seem to have been written by people who may not like onions very much at first. Others are jokes. (“In fact, we consider the funny review part of our customer-centric culture,” said Mr. Andrews.)
Some reviewers are in a state of critical disappointment, realizing that there is not much to say here, not unlike Amazon. A review titled “Onion” posted in January asks and answers: “What can you say about an onion.”
Amazon spent decades recruiting millions of customers to help create and operate a vast, complex assessment tool to extract and represent human desire, preference and subjective, unintentional experience. When he fed that machine an onion, the machine replied: Onion. Yes.