The AI summary of reviews for ASIN B093B5VLNQ is inaccurate and misleading. It says “The bottle's leak resistance is a concern, with multiple customers reporting it leaks like a sieve.” This is not true. Only one review reports it “leaks like a sieve” not multiple customers. Rufus took one bad review, misleading attributed it to "multiple customers," and amplified a single bad review, presenting an inaccurate summary of reviews of our product.

This AI summary inaccuracy lowers our conversation rates and damages our business.

Who else has this problem?

I opened a support case.

AI review aggregation feature is harming our business. The feature takes language from reviews and makes the product seem defective when in fact that is the makeup of the product. The AI's current method can mislead consumers into believing that a few negative reviews are representative of the overall feedback, causing undue damage to sellers. In our case, there are a few low-star reviews. These lower reviews are an expected occurrence as the number of reviews increases and have significantly impacted our overall sales. However, since the introduction of AI-generated summary opinions, the problem areas identified by these few reviews have been disproportionately emphasized. For instance, the AI highlighted an old, particularly harsh review verbatim, tagging it as a major product issue. Consequently, our conversion rate has dramatically decreased, despite no other changes in our product ratings or conditions. We've been selling products to customers since 2013, maintaining a rating of 4.6. However, we're suddenly facing distress due to these inaccurate AI summaries.Generally, a product rating of 4.5-4.8 indicates a well-received item. However, the influence of the AI summary has overshadowed this positive rating. Consumers tend to trust AI-generated summaries and may prioritize these over reading individual reviews. When the AI quotes negative reviews verbatim, even if they are in the minority, it has a significant negative impact. This issue is compounded by the AI quoting harsh review language directly, affecting consumer perception more than necessary. The AI does more than just highlight these negative reviews; it directly quotes the most aggressive and negative comments. This practice exposes potential customers to highly negative opinions, leading them to form a strongly unfavorable impression of the product despite many positive reviews.Additionally, we have noticed that important product information, such as bullet points, "About the Brand" sections, and A+ content, is now hidden behind "see more" buttons at the mobile. This change reduces the visibility of detailed product descriptions and brand information, forcing consumers to rely more on the AI-generated summaries. This not only diminishes the value of the content we provide but also places undue emphasis on potentially misleading AI summaries.We believe that while AI plays a crucial role in enhancing the shopping experience, it should not overshadow the fundamental product information provided by sellers. If the AI review aggregation continues to disproportionately highlight negative reviews, and important product details remain hidden, it undermines the balanced presentation of products and affects consumer trust.

The AI review aggregation, especially in the "Customers say" section, is intended to provide objectivity and comprehensiveness. However, it can often mislead consumers, causing significant issues for sellers. When the AI highlights a small number of negative reviews, it can distort the overall feedback, creating an unfair perception of the product and leading to unjust harm.

This problem is particularly severe for new sellers with a limited number of reviews. Unlike established products with extensive feedback, new sellers can be disproportionately affected by a few negative comments. When the AI aggregates these limited reviews and features them prominently in the "Customers say" section, it can give a skewed impression of the product, leading consumers to make decisions based on incomplete or misleading information.

For instance, a new product with just a handful of reviews may have one or two negative comments. If the AI emphasizes these, it can overshadow any positive feedback and unjustly damage the product's reputation. This can hinder the growth of new sellers who are trying to establish themselves in the market.

To restore fairness and trust in the review system, it is essential to reconsider the AI review aggregation approach in the "Customers say" section. This includes ensuring that the aggregation accurately reflects the overall sentiment of the reviews, particularly for new products with fewer reviews. By doing so, Amazon can provide a more balanced and fair representation of all products, supporting both new and established sellers.

In conclusion, while the AI review aggregation feature aims to help consumers make informed decisions, its current implementation can lead to significant misrepresentations. Reevaluating this approach is crucial for maintaining the integrity and fairness of Amazon's review system.