Amazon is summarizing product reviews with AI. Are book reviews next?
Amazon is testing summarizing product reviews with AI. What's the potential impact for reader reviews and book sales?
As reported by CNBC and a sharp marketer who monitors the world’s largest online retailer for a living, Amazon is testing the use of generative artificial intelligence (AI) to summarize some product reviews. Generative AI uses technology to produce content such as text, graphics, audio, and video.
The summaries, which include a disclaimer that Amazon is using AI to create them, pull from user reviews to share what customers do and don’t like about products. (See an example of a review here.)
In theory, they save discerning shoppers time scrolling through reviews for key product features and issues.
Amazon hasn’t officially announced that it’s summarizing product reviews with AI, but it confirmed the news when asked by CNBC.
Will Amazon roll this out to reader reviews?
You might be wondering if and when this will apply to reader reviews and the impact it might have on reviews and book sales.
Nobody knows for certain, but we can make educated guesses.
“Amazon is always testing what converts better on their product pages. If they find that the AI-generated review summaries convert well on laundry machines, then they’ll likely roll it out for books as well,” says Bryan Cohen, author and CEO of Best Page Forward.
Dave Chesson, founder of Kindlepreneur, a top marketing resource for authors, agrees. “I think it makes sense to do it considering that when looking at the reviews of the book, as a shopper, it requires a lot of time to sift through the reviews and find one with legitimate, constructive feedback on the book,” he says.
Impact summarizing product reviews with AI might have on books
Authors engaged in the ongoing struggle to generate reader reviews might be concerned that AI-generated summaries will discourage reviewers. Amazon is probably tracking review trends as part of the test, too.
Once readers realize that too-brief reviews – “Loved it” or “Hated it” – don’t contribute to meaningful summaries, they might get more specific.
Chesson has a concern about AI incorporating those too-brief reviews into summaries, too.
“If they develop the system where it compiles the good and the bad to create two paragraphs, I worry what will happen when the feedback isn’t well-thought-out.
“For example, I’ve seen negative reviews in the past where the reviewer will say something about how they haven’t read the book and then proceed to give an opinion. Or, perhaps there aren’t many negative reviews and so the system reaches and gives full discussions on things that aren’t really a thing,” he says.
Once readers realize that too-brief reviews – “Loved it” or “Hated it” – don’t contribute to meaningful summaries, they might get more specific.Click to tweet
Stephanie Chandler, founder and CEO of the Nonfiction Authors Association, shares his concern, adding, “While they haven’t yet mastered how to distinguish between poor product reviews and positive ones, surely they will figure out how to separate these details based on the starred reviews,” she says.
Encouraging readers to write more helpful reviews
Chandler believes authors can get ahead of this by encouraging readers to write more meaningful reviews.
“As authors we may need to ask reviewers to get more specific with their feedback so that AI-generated review summaries are reflective of the content of the books,” she adds.
Even so, Cohen wonders if readers will be disappointed by the new review experience if it rolls out to all product categories.
“If these changes all come to pass, the next question will be how book reviewers will react to their words being summarized and then passed over,” he notes.
Upsides to summarizing product reviews with AI
Any flaws in the process will likely be eliminated by the time book reviews are summarized. When it happens, it’s possible the AI-generated summaries will help readers make quicker decisions about what to read next.
“If the AI system can help piece this together, which I think it can, this will create a much better shopping experience,” Chesson says.
A better customer experience can lead to higher sales for books that readers review favorably, too.
“If the AI summaries help get a higher percentage of readers to buy, then both Amazon and the authors who publish there will be very happy,” adds Cohen.
Want to help readers write more meaningful reviews now? Download the Build Book Buzz Reader Book Review Forms now. There’s one for fiction; another for nonfiction. They encourage reviews by taking the mystery out of the process for your fans. Learn more at https://buildbookbuzz.com/reader-book-review-form/
Do you think review summaries will help readers make better-informed decisions about what to buy and read? Why or why not? Please tell us in a comment.
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This is interesting. I do check book reviews, specifically if I’m reading something that I don’t think is all that great, to see whether I’ve missed the point. But before I buy a book or audiobook, I make a point of checking the less enthusiastic reviews (1 & 2 stars) if there seem to be a lot of them, to see why. I’m wondering how AI would amalgamate all the reviews – whether it would produce an “average” review. So if a book has equal numbers of 5 and 1-star reviews, the average might be 3 stars. Same with reviews. And there are plenty of 1 & 2-star ratings without reviews, because readers are too polite to trash a book, perhaps. I wonder how they would factor in. Definitely a thought-provoking post. Thanks!
Gabi, I got the impression from the image of one of the new AI-generated summaries shown in the second link of my first paragraph that the summaries just repeat what’s already available for number of reviews and average star rating. Since these are summaries of existing reviews, starred “reviews” with no text won’t be factored into the written summary (because there’s nothing to summarize), but the stars remain part of the average rating.
Sandy