Fake reviews are inauthentic reviews — fabricated positive reviews for oneself or an ally, coordinated negative review bombing against a target, or extortion-based reviews demanding payment for removal. They distort the rating signals that customers, search engines, and AI answer engines rely on, and the damage compounds because review scores feed search ranking, AI summaries, and purchase decisions.
Fake reviews damage brands in three ways. Fabricated competitor reviews buy unfair advantage by inflating a rival's rating. Coordinated negative review bombing drops a target's rating, suppressing it in local search, feeding negative AI summaries, and converting fewer visitors. Extortion-based reviews hold a business hostage, demanding payment to avoid or remove damaging reviews. Each distorts the trust signal that review platforms exist to provide.
The lawful removal process targets inauthentic reviews through platform policy enforcement with documented evidence — review velocity anomalies, reviewer accounts with no other history, language clustering, timing correlation with a campaign, and mismatch between review content and verified customer records. Each platform has a defined process for challenging inauthentic reviews. Where the conduct constitutes defamation, tortious interference, or extortion, legal coordination supplements platform enforcement.
Posting fake positive reviews in response is the wrong strategy. It is unlawful in most jurisdictions, detectable and routinely exposed, and the exposure is itself a reputation catastrophe that dwarfs the original problem. It also does not work — platforms and informed customers discount suspicious positive bursts. The only durable strategy is legitimate removal of fake negatives and authentic improvement that earns real positives.
Authentic negative reviews are handled differently: with an honest, professional public reply that acknowledges the issue where valid, corrects the record where inaccurate, and signals operational follow-through. Authentic reviews are not removed; they are answered and out-earned. Conflating inauthentic removal with authentic response is the most common error in review-platform management.