Revain Aims to Verify Online Reviews As Authentic & True
Peer-to-peer recommendations matter to consumers. In the US, 91% of shoppers regularly read online reviews, and 84% trust them as much as friends (Bright Local, 2017). Aiming to reinvent consumer feedback, Russian platform Revain implements blockchain technology, an artificial intelligence (AI) filtration system and an incentive scheme to make reviews more genuine, constructive and transparent.
Several websites have come under scrutiny for how they have – or haven’t – filtered content, and consumers are paying attention. According to The Times, a third of reviews on TripAdvisor are fake. Ensuring all reviews on its platform are trustworthy, Revain designed an authentication system consisting of two stages: automatic filtering, then manual moderation by the company in question.
First, an AI filtration system powered by IBM Watson filters out low-quality reviews by flagging statements that use abusive language or are unnecessarily emotional, and verifies quality ones providing positive and constructive feedback. Once through the AI stage, reviews are checked by the company they’re targeted at. Companies are able to accept or reject them, but need to provide evidence if they disagree with the author. A decentralised ‘justice’ system sees high-profile users make a final decision if author and company are having a dispute. Importantly, conversations between parties are visible to all users of the platform.
After the filtration process, reviews are saved in the blockchain to ensure they can’t be edited, manipulated or deleted.
For every published and company-verified review, users are rewarded with cryptocurrency tokens, which can be traded on currency exchange platforms. This is financed by companies who sign up for Revain’s premium subscription plan, costing $227 per month.
Currently only reviewing cryptocurrencies, Revain plans to expand into other industries in future, including gaming, e-commerce, FMCG and restaurant and hotel booking.
For more on the power of peer recommendations, see Amazon Trades On What’s Trending.