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Live preview · 15,401 hotels ranked
Hotels
Sources we aggregate
| TripAdvisor | Open crowd platform — a review does not require a booking through the site |
|---|---|
| Booking.com, Agoda, Expedia, Trip.com, Ostrovok | Verified-stay reviews — each rating is tied to a reservation completed on that platform |
| Reviewer weighting | Uniform. Every reviewer who clears the admission rules counts the same, whichever of the six platforms they rated on |
| Professional editorial | None ingested. No hotel-inspection publication feeds a Rankquant hotel score |
Peer-set dimensions
- City — or in major metros, neighborhood
- Price tier — budget / mid-scale / upscale / luxury / ultra-luxury
- Star rating (nominal) — 3/4/5 star, as a coarse category input
- Property type — hotel, resort, boutique, bed-and-breakfast
A 4-star Midtown Manhattan hotel with a normalized 4.7 is compared against other 4-star Midtown hotels at similar price points — not against a $80 motel in a different city. This makes the score immediately actionable for travelers.
Frequently asked questions
Why normalize within city and price tier?+
Because hotels at different price points and in different cities live in different review-inflation regimes. A 3-star budget hotel with a 7.5/10 on Booking.com may be a strong pick for its category; a 5-star luxury hotel with 9.2/10 may be merely average for its. Global averages don't let you tell these apart.
Can you normalize hotels I've never heard of?+
Yes, provided enough of its reviewers carry a rating history we can normalize against. The catalog filter is 50 or more reviews per property; obscurity is not a disqualifier, thin reviewer overlap is. A hotel that clears the filter is ranked on the mean reviewer z itself, reported as measured. Thin samples are charged for separately, in the AI-adjusted percentile, rather than guessed at.
What about review-bombing (positive or negative)?+
Two mechanisms, neither of them a prior over categories. First, every reviewer is normalized against their own rating history, so a reviewer who hands out top marks to everything adds little by handing out one more. Second, the AI-adjusted percentile discounts the mean by n / (n + 53), so a bulk positive push on a new property is pulled toward the corpus average until genuine coverage accumulates; bulk negative campaigns are diluted the same way. Outlier review clusters are flagged for editorial review.
Do you show nightly rates?+
No. We hold no price feed from Booking.com or anyone else, and Expedia and Hotels.com are not currently integrated. The "Book" button builds a Booking.com search from the property name, city and your chosen dates and hands you off; the rate you see is Booking.com's, on Booking.com. That link carries no affiliate tracking and earns Rankquant nothing.
Status: 15,401hotels with ≥50 reviews are live in the catalog, ranked by z-normalized percentile across 1.17 M reviewers from TripAdvisor, Booking.com, Agoda, Expedia, Trip.com, and Ostrovok. Tier / price / star filters and per-hotel detail pages will arrive once those fields are scraped — for now the catalog shows the bias-corrected ranking only. See full methodology for the math.