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how it works

what signals do we look for?

We read a place's full review history and weigh the signals that are costly for a review farm to fake:

  • Burst campaigns: clusters of 5 star reviews dumped on a single day by low-history accounts. A genuine surge keeps a place's normal share of Local Guides, so it isn't counted against it.
  • Drip-feed farms: reviews arriving nearly every day at a pace no organic business sustains, a paid stream spread thin to dodge obvious spikes.
  • Cross-posted text: the same review copied word-for-word onto other businesses, a farm seeding a whole chain.
  • Throwaway accounts: single-review profiles padding the average up.
  • Review solicitation: reviewers themselves reporting that the business rewards, pressures, or steers reviews (“free dessert if you leave 5 stars”). An LLM reads every such mention; only firsthand reports of policy-violating practices count, and the penalty deepens with each independent witness. Politely asking for a review is allowed by Google and never counted.
  • Too-perfect records: a spotless, unanimous 5 star history often signals curated or incentivized reviews, so it can't earn a top grade, even when we can't prove fraud.
what's the “adjusted rating”?

What hard-to-fake reviewers actually give, vs the headline number. A gap means the rating is inflated. Two groups qualify:

  • Credible reviewers are Local Guides who also wrote a substantive review. The badge alone is gameable (farms run Local Guide accounts that drop bare 5 star ratings), so we only count ones that put real words behind the stars.
  • Established accounts have 30+ lifetime reviews, regardless of badge or text. Farms pad accounts with a handful of reviews to look plausible, but aging thousands of accounts past 30 is the expensive part.

Each place is anchored to whichever group gives the more conservative rating. When a place corrects the headline number, the “per credible reviewers” / “per established accounts” label tells you which.

what does a high score mean?

It means we found no evidence the business is manipulating or inflating its own reviews. It does not promise the rating is accurate: a clean place can still be mis-rated by too few reviews, reviewers who self-select, or honest reviews that just don't match your experience. We measure whether the number looks gamed, not whether it's right.