For that purpose, the company is deploying a new Al machine-learning system that has been built in-house to boost the prominence and weight of verified customer purchase reviews, e-commercefacts.com reports. In order to evaluate the quality of a product that is bought online, the customer is especially looking at the ratings and reviews of users, who have supposedly bought them before.
Thereby the customer can have an idea about the product without having seen it himself beforehand. It is all about trust in the digital shop and essential that the customer can rely on the authenticity of the review. The retailers are therefore putting greater emphasis on verified and helpful reviews to assure their credibility.
The system is designed to combat fake product reviews and inflated star ratings. It is doing this by an algorithm that is capable of differentiating between original products and those modified to fix issues or customer complaints sold through the same listing. The reviews of the fixed product will be used to outweigh older one of the broken product to create a more consistent and useful rating of the product user would currently receive. After having problems with fake reviews this new system might eventually end astroturfing at Amazon.
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