Why genuine reviews vanish, and fakes survive
By ReputationKiln Editorial · Published
It is genuinely maddening when a real, glowing review from a real customer vanishes while an obvious fake sits there for months. Usually it is not malice, it is an automated filter making a probabilistic call and getting it wrong, because the same systems that catch fakes also catch some genuine reviews that happen to look suspicious, a new reviewer, an odd device, similar wording. That is the cost of policing reviews at scale, and it cuts both ways.
But there is a separate thing, recognised by regulators as its own kind of misconduct, which is review suppression: not the honest removal of a fake, but the quiet burial of genuine criticism. Telling the two apart matters, because one is an imperfect system and the other is a practice the law now watches.
Legitimate removal versus suppression
Reviews can fairly be removed for clear reasons, applied the same way to positive and negative ones: a fabricated transaction, private or confidential information, unlawful content, or something plainly off-topic. The problem is suppression that targets honest negatives specifically, putting them through extra hurdles or slow queues while positives publish instantly, pushing them behind extra clicks while advertising the overall score as comprehensive, or using baseless legal threats to frighten genuine reviewers into silence. Regulators have been explicit that misrepresenting a displayed set of reviews as representative, when negatives have been filtered out, is deceptive, and that negatives should not face tougher treatment than positives.
Why this matters to you, and the limit
This is why a wall of nothing but five stars is a signal rather than a triumph, and why a business that suppresses its honest criticism is not just being unfair, it is on the wrong side of the rules. The limit is fairness in the other direction: a single vanished review is far more likely to be an imperfect filter than a conspiracy, and you have the same flagging and appeal routes everyone else does. The lesson is not that the system is rigged against you, it is that an honest spread, criticism included, is what both the filters and the customers are built to trust.
Sources
- A retailer paid USD 4.2 million to settle FTC allegations it used a third-party review tool to auto-post four and five-star reviews while holding back hundreds of thousands of lower-starred ones. — FTC v. Fashion Nova (2022). https://www.ftc.gov/news-events/news/press-releases/2022/01/fashion-nova-will-pay-42-million-part-settlement-ftc-allegations-it-blocked-negative-reviews · checked 2026-06-04