The company appears to have found the category challenging. Fakespot’s Mr Khalifah pointed out a feature he has seen on many product lists, most of which have high star ratings and thousands of reviews. “I saw asparagus with 10,000 reviews,” he said, but only two of the five-star reviews had reviews. What about the rest?
Last year, Amazon began testing a one-tap rating system designed to encourage customers to submit a simple star rating instead of a full review. The motivations were varied: it could help minimize the impact of fake reviews by dramatically increasing buyer input. Overall, it provides more feedback for Amazon to work with. and it dramatically increases the visible numbers alongside the overall ratings, which gives customers confidence. This experiment has been criticized by sellers who feared that one-star reviews left them no explanation or recourse.
This year, Amazon has spread the one-tap reviews much more widely, and they affect overall star ratings. Buyers looking for a new iPad may come across a 4.8-star list compiled from more than 49,000 public reviews. A closer look reveals that fewer than 6,000 of these reviews are associated with actual reviews. The conditions are even more extreme during production.
As Amazon has expanded into product categories by product category, the Amazon rating has been stretched to the limit of its form. The most basic products of all could push it to its breaking point.
Only 60 people took the time to write full reviews for the yellow onion on Amazon, while more than 6,000 left reviews averaging 4.7 stars. Some are complaints about local whole foods, a specific buyer, or whole foods in general, while others seem to be written by people who may not like onions that much. Others are jokes. (“In fact, we consider funny reviews to be part of our customer-centric culture,” said Andrews.)
Some reviewers have reached some sort of critical dejection and seem to realize, much like Amazon itself, that there really isn’t much to say here. A review published in January entitled “Onions” asks and answers, “What can you say about an onion?”
For decades Amazon has recruited millions of customers to build and operate a huge, complicated review apparatus that can extract and represent human desires, preferences, and subjective, unrecognizable experiences. When it fed an onion to this machine, the machine replied: O.nion. Yes.