On 14th August, Amazon, the world’s largest online retailer, introduced a new feature that uses generative AI to create and display summaries of customer reviews on product pages.
The feature aims to give a quick snapshot of the pros and cons of the products and customer sentiment around them, allowing shoppers to make quick and accurate buying decisions.
While it can be an excellent add-on for customers, sellers around the world have some concerns about the reliability of AI-generated review summaries and their impact on conversions.
This article explains how AI review summaries work, the pros and cons of it, and what the future holds for Amazon AI reviews!
Let’s find out!
Here is a quick peek into the article:
The primary goal of the Amazon AI review summary is to make it easier for shoppers to understand the common attributes of a product without reading through multiple reviews.
It provides a short summary that highlights the product features and customer sentiment frequently mentioned across verified customer reviews.
This summary is followed by AI-generated tags showcasing relevant themes and words used by customers. You can also click on each theme to read the full reviews.
For example, if a customer wants to understand if the product is easy to use, they can just click on the “ease of use” attribute and read the review highlights from other shoppers related to that attribute.
The feature is currently available for a small subset of mobile shoppers in the US. Amazon uses reviews from verified shoppers to eliminate fake product reviews and ensure that customers get accurate information about the product.
Amazon AI-generated review summaries offer several benefits to both customers and sellers. Here are some of them:
Customers no longer have to scroll through hundreds of reviews to understand the features and benefits of the product. They can also quickly find the most relevant information using attribute filters.
With AI-generated review summaries, sellers can create a better customer experience for the shoppers. It can reduce friction in the shopping journey and improve conversions.
Sellers can build trust with customers, as these review summaries are based on verified purchases and real customer feedback. They can also easily check the original reviews by clicking on the summary or the keywords.
Sellers can gain a comprehensive understanding of their and competitors’ products by analyzing the review summaries and attributes. It helps them further improve the product.
Despite the benefits, Amazon AI-generated review summaries have some drawbacks as well. Such as:
AI can oversimplify product reviews and may not give an accurate picture of the product’s quality and performance to the shopper.
AI can also miss some subtle nuances in the original review that are extremely important for the product and generate false information due to the nature of large language models.
AI can also emphasize the wrong attribute in the review, which may paint a skewed picture in the minds of shoppers.
For example, even if the product has a strong rating, if one negative attribute is mentioned in the original reviews multiple times, AI can amplify it on the summary and scare away shoppers.
It’s also unclear how well Amazon handles or filters fake reviews to avoid inaccurate information in the review summaries.
Amazon’s AI-generated review summaries are a novel and innovative feature that could potentially revolutionize the way customers shop online.
However, it can also pose some unique challenges that need to be addressed.
The future of Amazon AI reviews will depend on how well Amazon can balance the trade-offs between convenience and accuracy, persuasion and bias, and innovation and ethics.
It will also depend on how customers and sellers will adapt to and embrace this new way of interacting with reviews.
As Amazon continues to improve its AI technology and expand its features, it will be interesting to see how AI will shape the online shopping experience and influence customer behavior and satisfaction.