Amazon.com, Inc. (NASDAQ:AMZN) is taking the authenticity of reviews seriously as evident by the new move to introduce a machine learning platform to detect fake reviews.
The new platform was developed in-house and is designed to make reviews more honest thus making them useful to customers. Amazon has identified that most customers rely on product reviews before making a decision whether to purchase a product or not. There is thus a need to make sure that the reviews are legitimate to avoid misleading the customers. False reviews can lead to distrust and thus resulting in a negative impact on sales.
According to Amazon spokeswoman Julie Law, the system will identify the reviews that are useful to customers and will keep learning so that it can improve the reliability if the data. This will in turn lead to a positive response from customers because information from reviews will be genuine.
The platform will make use of artificial intelligence to screen the reviews. It will also prioritize newer reviews from verified buyers. It will also choose the reviews based on the rating process. The reviews from verified buyers that will be flagged as useful will appear higher on the list. The machine learning technology is currently available in the U.S. only. Amazon has not revealed whether the feature will be available for other regions.
The company introduced the new upgrade about a week ago but it there are hardly any changes noticeable on the website. According to L Squared Digital Signage CEO Gajendra Ratnavel, other websites like Yelp have been using the same technology to get rid of fake reviews.
Amazon.com, Inc. (NASDAQ:AMZN) identifies the value of reviews and the new upgrades are a strategy to make the website more trustworthy. The review system is a vital part of the company’s website. Sources revealed that the company recently sued some fake reviews made on some of the products on the website. The company hopes that the efforts will bring allow more customers to shop on the website without the fear of purchasing fake products.
