Amazon taps generative AI to enhance product reviews

Amazon announced this morning it will begin to leverage generative AI to help customers better understand what customers are saying about a product, without necessarily having to read through dozens of individual reviews. The retailer says it will use the new technology to provide a short paragraph of text right on the product detail page that will highlight the product features and customer sentiment mentioned across the customer reviews.

This blub of text could be used to get an overall sense of the common themes across the reviews more easily, Amazon noted.

In addition to the summary text, Amazon will also highlight key product attributes as clickable buttons. For example, if a customer wanted to know about the product’s “ease of use” or “performance,” they could tap a button to see just those reviews that mention those terms.

Amazon had already offered a similar feature by surfacing frequently used words found in the reviews, which were also available as clickable buttons.

The new AI-powered features will initially be rolled out to a subset of U.S. shoppers on mobile devices across a “broad selection” of products, Amazon said. During these tests, the company will work to learn and fine-tune its AI models to improve their effectiveness. It’s also working to expand the highlights feature over time to include additional categories, as the feature becomes more broadly available to customers.

Of course, the AI summaries will only be as good as the data they ingest. And Amazon has struggled for years with fake and misleading product reviews, including paid reviews.

In 2021, the company admitted it had blocked 200 million fake reviews the year prior, for example. It has also tried to crack down on the sources of fake reviews for years via lawsuits and other actions, including suing sellers who bought fake reviews. Last year, it also sued the admins from 10,000 Facebook groups who were engaged in fake review brokering.

More recently, the FTC got involved, forcing a supplement maker to pay $600,000 in a case involving hijacked Amazon reviews — a situation where products are combined into a single listing to boost the reviews of one product with the good reviews of another.

With the growing capabilities of AI, fake reviews may now be even tougher to spot as the technology advances to sound more human, which could lead to another explosion of fake reviews. That would make Amazon’s AI-powered summaries of reviews less helpful, if the company doesn’t have other means of keeping AI-written reviews off its site.

Amazon addresses the concern around fake reviews today, saying it will only summarize those reviews from verified purchases. Plus, it continues to invest “significant resources” to proactively stop fake reviews.

“This includes machine learning models that analyze thousands of data points to detect risk, including relations to other accounts, sign-in activity, review history, and other indications of unusual behavior, as well as expert investigators that use sophisticated fraud-detection tools to analyze and prevent fake reviews from ever appearing in our store,” notes the retailer.