Reviews and ratings are an important part of consumers’ shopping journeys, but false reviews can upset the trust shoppers place in retail sites. Amazon.com has introduced a new platform it developed in-house that promises to make the reviews and ratings on its site more useful for its millions of customers.
Amazon spokesperson Julie Law wrote in an email toInformationWeek, “The enhanced system will use a machine-learned model to give more weight to newer, more helpful reviews from Amazon customers. The system will continue to learn which reviews are most helpful to customers, and improve the experience over time.”
The new system will use a variety of criteria to determine the relative rank of reviews on the site. These include date (newer reviews are weighted more heavily than older ones), confirmed purchase of a product and, most importantly, whether others found it useful.
In an online discussion last week, some on the BrainTrust of industry insiders at RetailWire saw the move as a good step towards Amazon trying to manage one of its big problems.
“This type of technology has already been in use for some time on sites like Yelp and it has helped,” said Gajendra Ratnavel, CEO of L Squared Digital Signage. “Fraud in reviews needs to be controlled. In fact, as the online world matures, the reviews become a little like currency.”
“More shoppers visit Amazon to research products than any other destination, and product ratings and reviews have a significant influence on sales online and offline,” said Keith Anderson, vice president of strategy and insight at Profitero. “Unfortunately, unscrupulous sellers and brands have tried to game the system. This likely isn’t a silver bullet, but it’s good to see Amazon investing continuously in setting the standard for credibility.”
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Others, however, were not certain that the technology as described would effectively address the issue.
“I see where the new platform will provide more timeliness just like many of Amazon’s predecessor algorithms, which Amazon is nonpareil in creating, but I don’t see where/how it eliminates the issue of fake reviews,” said Naomi Shapiro of Upstream Commerce.
“As described here, this is quite unimpressive,” said Ken Lonyai, digital innovation strategist and cofounder of Screenplay InterActive. “It’s taken them, what, 15 years to start thinking about this? Why is a newer review necessarily better than an old review? There are much more useful criteria. So Amazon, here’s a gift: reviews from people who have a larger span of time between purchase date and review date are far more valuable than people who open a box and write a review without spending enough time using what they bought.”
“Any company can claim to employ ‘AI‘ and ‘machine learning,’ but execution and knowledge of users is what makes it valuable,” said Mr. Lonyai.
One BrainTrust member further noted that while Amazon’s striving for review authenticity is an important goal, there could be ulterior motives behind the company’s move.
“I would like to believe that Amazon’s investment in this area will be with a view to increasing the authenticity of the reviews and to provide a balanced perspective, as opposed to optimizing their display to maximize sales,” said Alexander Rink, CEO of 360pi.