The tech giant has sued over 1,000 unidentified people alleged of providing fake reviews on Amazon.com. The company filed the case in the United States last week, saying that its brand reputation was being tarnished by misleading reviews.


The company explained that more than 1,100 defendants peddle their false review service for just $5 on the website Fiverr.com, a service that offers minor tasks. According to Amazon, many of the fake reviewers were detected, whose real names are unknown and who had used multiple accounts and IP addresses to avoid being caught.

Apparently, Amazon started its campaign against the fake reviewers by hiring a few Fiverr members. In its complaint, the company said that a very small minority of sellers and manufacturers tries to gain unfair competitive advantages by posting false customer reviews for their products on Amazon. However, such reviews threaten to undermine the trust that customers, sellers and manufacturers place in Amazon, thus tarnishing the popular brand. The company announced it went to court in order to protect its customers from this misconduct.

In the meantime, it should be noted that Amazon is not suing Fiverr, because the latter bans advertising for services such as writing bogus reviews, according to its terms and conditions. In addition, the company did not dispute Amazon’s allegations regarding its freelancers and promised to do its best to remove services violating its terms of use. The startup was also aware that Amazon forbids fictional or paid-for reviews. As for the online retailer, the company did try to remove the adverts for reviewers on Fiverr, but it had to admit that doing so would not address the root cause of the problem or serve as a deterrent to others.

Industry observers note that this legal action comes after Amazon sued a number of websites in spring for selling fake reviews. It is also known that it uses artificial intelligence to address the problem of fictional product reviews and inflated star ratings, saying that this system will bring more accurate reviews to the top and use them as a basis to create a star rating. Earlier, star ratings were formed as an average of all reviews. This approach allowed fictional reviews to heavily influence the first-glance rating.