Paste an Amazon product URL and we estimate how trustworthy its reviews are — from the structure of the reviews (star distribution, number of ratings, verified-purchase share, posting bursts), not their text. We surface only the products that pass, with the reasoning shown. Fakespot and ReviewMeta shut down in 2025 — this fills that gap.
Works with amazon.com product URLs. We never store or republish review text — only public aggregate data is analyzed.
Fake (or incentivized) reviews are positive ratings written in exchange for money or free product. Even items showing ★4.5+ can hide poor quality. The tell-tale signs show up in the structure of the reviews, not their wording.
Spot fakes from three structural signals
Star distribution: a wall of 5-stars, or a 5★/1★ split with little in between, is a red flag.
Verified-purchase share: lots of unverified reviews can mean incentivized ratings.
Posting bursts: many reviews on the same day suggest a review campaign.
A free tool that estimates how trustworthy an Amazon product's reviews are from structural data — star distribution, number of ratings, verified-purchase share, and posting-date clustering — and surfaces only genuinely good products, with the reasoning shown.
Q. How do you detect fake reviews?
We look at the structure of the reviews, not their text: an extreme concentration of 5-star ratings, a bimodal split, a low verified-purchase share, and reviews clustered on a single day are common signs of manipulation.
Q. Is the verdict accurate?
It is an estimate from public structural data and does not guarantee authenticity. Mistakes are possible, so make the final purchasing decision yourself.
Q. Is this a replacement for Fakespot or ReviewMeta?
Both shut down in 2025. Ryohin Checker offers a similar structural approach, with the difference that it only recommends products that pass — it does not disparage the rest.
As an Amazon Associate, Ryohin Checker earns from qualifying purchases. Verdicts are estimates inferred from public page data (star distribution, number of ratings, posting dates, verified-purchase share) and do not guarantee authenticity (mistakes are possible). We do not store or republish review text. Rankings and recommendations are not influenced by commissions.