Amazon review moderation, and how to protect your star rating.
A rating of four stars or more changes what shoppers buy, and assistants like Alexa for Shopping read reviews too. Our review moderation process puts 20 years of Amazon platform knowledge into an AI flow that finds the reviews that break the rules, so they can be reported.
Why four stars matters
Star ratings are one of the first things a shopper sees, in search, on the product page and now in AI shopping assistants. Products at four stars and above win more clicks and more sales, and a dip below four can cost a range far more than the reviews themselves suggest.
Early reviews matter most. When a new product has only a handful, one unfair review can drag the rating down at exactly the moment the launch needs momentum. On one Dr Scholl's launch, a single early review could have had a serious impact, so we moderated it straight away.
What breaks the rules
A negative review isn't a reason to report it. Honest feedback, good or bad, is what makes reviews useful, and brands should answer it, not try to bury it. But many low ratings aren't really reviews of the product at all. Amazon's Community Guidelines exclude reviews that are about things like these.
- Delivery, packaging or courier problems that the product didn't cause
- Seller service or questions, which belong in seller feedback
- A different product, or using it for something it isn't for
- Promotional content, links or competitor plugs
- Repeated or coordinated reviews that point to bots or a campaign
Amazon explains how reviews work for shoppers in its guide to writing and finding reviews. Our moderation framework turns the full guidelines, and industry review standards, into codes we can apply consistently.
Our six step process
- Download. Every review for the range, with its rating, date and text, using review research tools.
- Classify. Each review under three stars is checked by AI against our moderation framework.
- Code. Reviews that break the guidelines get a moderation code that says why.
- Report. We draft the report for each claim and submit it through Amazon's review tools, then follow up on the cases.
- Escalate. Patterns that suggest bots or competitor activity go to the brand's Amazon account manager.
- Prioritise. We rank ASINs where moderation would make the biggest difference, either low rated products that could reach four stars or high volume products where every tenth of a star counts.
Why it runs on 20 years of knowledge
The AI does the reading. The judgement comes from people who have run Amazon accounts for a long time and know how Amazon treats each type of claim. That knowledge sits in the framework, in the codes and in the way reports are written, which is why the tool gets better results than a general model asked to find bad reviews.
- Four stars and above wins clicks, sales and AI recommendations
- Report reviews that break the guidelines, answer the ones that don't
- Check every review under three stars, consistently
- Prioritise the ASINs where a lift in rating is worth the most
Moderation is one part of the job
The best way to a strong rating is a good product with an honest listing, so moderation sits alongside the rest of the account. Clear images and copy set the right expectations, which cuts complaints in the first place. Our Amazon team runs it all together, and the tool behind this process, Freak Reviews, is part of Freak Lab.
Sources
- How to write, find and edit Amazon reviews, About Amazon UK
Questions clients ask us.
Can you remove negative Amazon reviews?
You can't remove a review because it's negative. You can report reviews that break Amazon's Community Guidelines, such as feedback about delivery, reviews of the wrong product, promotional content or suspicious patterns, and Amazon removes those it agrees with.
Why does a four star rating matter on Amazon?
Shoppers filter and compare on star ratings, and products at four stars and above tend to win the click and the sale. AI shopping assistants also use ratings and reviews when they decide what to recommend.
How does AI help with review moderation?
It reads every review at speed. We use it to check each review under three stars against a moderation framework built from Amazon's guidelines and industry review standards, give it a code and draft the report, with a person checking before anything is submitted.
What should I do about fake or competitor reviews?
Look for patterns, such as several one star reviews with similar wording in a short time. We escalate those through Amazon's reporting routes and, for larger activity, to the brand's Amazon account manager.
More from the Resource Centre.
AI shopping assistants like Alexa for Shopping are changing which brands get found.
Amazon's assistant now sits in the search bar and answers with a few picks. What that means for brands, and what to change in your listings now.
How we score Amazon images before shoppers ever see them.
The five measures behind our neural marketing framework, what each one tests and how we use them to fix Amazon images before they go live.
Amazon A+ content that sells, and what we changed for Feliway.
How we plan A+ content and the image stack above it, from search research to testing, with the changes that doubled Feliway's monthly sales.
Got a brief like this?
Tell us where you want to grow, and we'll show you how we'd get there.