B
Lycia Boutique Hotel
inflated rating · 4.74★ claimed → 4.54★ adjusted
A+
Nur Beach Hotel
looks legit · 4.58★, holds up
A
Mavilim Otel
looks legit · 4.77★, holds up
A+
The Kaş Otel
looks legit · 4.24★, holds up
A
Kaş Evderhan
looks legit · 4.76★ claimed → 4.59★ adjusted
A
Aqua Princess Hotel
looks legit · 4.34★, holds up
C
Radisson Blu Hotel, Kaş
inflated rating · 4.67★ claimed → 4.34★ adjusted
A
Demeti Kaş
looks legit · 4.34★, holds up
A
Hideaway Hotel
looks legit · 4.83★, holds up
A+
Kastellorizo
looks legit · 4.50★, holds up
A
Seatown Hotel
looks legit · 4.86★, holds up
A+
Payam Hotel
looks legit · 4.79★, holds up
B
Aphrodite Pension
inflated rating · 4.81★ claimed → 4.51★ adjusted
A
Hotel Sonne
looks legit · 4.86★, holds up
A
Stone Hill Kaş
looks legit · 4.86★, holds up
A
Limon Pansiyon
looks legit · 4.95★, holds up
A+
Brow City Kaş
looks legit · 4.97★, holds up
A
Harnup Camping
looks legit · 4.85★, holds up
A
Caretta Pansiyon
looks legit · 4.88★ claimed → 4.74★ adjusted
A
Kaş Sun Glare Otel
looks legit · 4.92★ claimed → 4.75★ adjusted
A+
Medimar Hotel (+12)
looks legit · 4.95★, holds up
A
Can Mocamp
looks legit · 4.45★ claimed → 4.34★ adjusted
D
Peninsula Gardens Hotel - Adults Only
manipulation detected · 4.24★ claimed → 4.14★ adjusted
B
Upper House Boutique Hotel
inflated rating · 4.16★ claimed → 3.91★ adjusted
A+
Suna Sun Hotel (14+) | Kaş
looks legit · 4.85★, holds up
A
Sole'n Blu Hotel
looks legit · 4.76★ claimed → 4.62★ adjusted
D
Seaview Otel
manipulation detected · 4.38★
A
Sardunya Hotel
looks legit · 4.67★, holds up
B
Rhapsody Boutique Hotel Kaş
inflated rating · 4.57★ claimed → 4.31★ adjusted
D
Meis Exclusive Hotel
manipulation detected · 4.28★ claimed → 4.04★ adjusted
A
Medusa Hotel
looks legit · 4.48★ claimed → 4.38★ adjusted
A+
Lukka Exclusive Hotel
looks legit · 4.63★, holds up
B
Leonis Hotel Kaş
inflated rating · 4.76★ claimed → 4.53★ adjusted
A+
Kas Marin Restaurant
looks legit · 4.24★, holds up
A
Kaş Lisiya Hotel
looks legit · 4.68★ claimed → 4.55★ adjusted
A
Kaş Joy Glamping
looks legit · 4.94★, holds up
A
Kaş Athena Hotel
looks legit · 4.87★ claimed → 4.74★ adjusted
A
Kaş Artemis Hotel
looks legit · 4.31★ claimed → 4.19★ adjusted
A
Casa Bi Otel
looks legit · 4.81★, holds up
D
Hera Hotel
manipulation detected · 4.05★ claimed → 3.74★ adjusted
A
hotel Luna Kaş
looks legit · 4.76★, holds up
A
Carruba Boutique Hotel
looks legit · 4.67★, holds up
A
Aysima Hotel
looks legit · 4.92★, holds up

how it works

1. your agent collects the reviews

It opens the listing in its own browser, sorts by newest and collects them: all of them, or the 500 most recent at a big listing. We don't scrape Google.

2. we run the stats

Burst days, throwaway accounts, cross-posted text, solicited reviews, rating drift. Statistics, not vibes.

3. you get a grade

A to F, plus the rating credible reviewers actually give, with the evidence one click away. The place then appears here for everyone.

Google usually asks the browser to be signed in before it will sort or load more reviews. The agent reads Maps through your signed-in browser, much like scrolling the listing yourself. Heavy use could trip Google's rate limits; if you plan to check many places, a secondary Google account is a sensible choice.

No agent? Scripts can POST the same review JSON to /api/submissions; the format is at /api/sources/google-maps. Everything required is visible on the review card; review ids and exact timestamps are optional. Results from a single unconfirmed submitter are labeled as such until a second source agrees.

methodology

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.

where does the review data come from?

From the agents and scripts that submit it. Every submission is checked for structure and consistency (Google's own review and profile ids, timestamps against displayed dates, the rating average against the displayed rating, the count against the listed count, overlap with what we already hold), and a place submitted by one unconfirmed source carries an unverified source note until a second, independent submission agrees. Places we pulled ourselves before October 2026 need no such note.

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.