TripAdvisor Reviews API

TripAdvisor carries no rates and no availability, and pretending otherwise would waste your time. What it carries is one of the most-read reputation signals in travel, and Veetal Connect API returns it in the same schema as every other source so it can be compared rather than read in isolation.

TripAdvisor reviews API

The full review list for a property, auto-paged and newest first: score, text in the language it was written in, traveller type, stay date, per-category scores and the hotel's management responses. Narrow the pull by date, language or sort order — and remember that only the date orders make an incremental run meaningful, since a truncated relevance-sorted pull is a biased sample rather than a recent one.

TripAdvisor ratings API

Overall score and review volume for a property and, through the stored layer, for every competitor configured against it. Read a specific import to reconstruct how a score moved rather than only where it stands today.

Semantic analysis of TripAdvisor reviews

Review text classified into topics and sentiment — cleanliness, staff, breakfast, noise, check-in — so thousands of comments become a ranked list of operational priorities instead of a single average.

Use cases

• Reputation and marketing agencies. Monitor dozens of properties across TripAdvisor, Booking.com, Google and Expedia on one comparable scale, and produce client reporting from a single feed instead of a per-platform export.
• Hotels and chains benchmarking a comp set. Read your own reputation and that of every competitor configured against you in the same call. A score of 4.3 means one thing next to a comp set at 4.0 and something very different next to one at 4.6.
• Revenue teams using reputation as a pricing input. Reputation moves what a property can charge. Tracking score and review volume against the comp set turns a soft signal into a variable your pricing can actually use, rather than a number someone quotes in a meeting.
• Operations, from the text rather than the score. Semantic analysis over the review text surfaces which topics are getting worse while the headline score has not moved yet — the early warning an average cannot give you, and the one that translates into a task for housekeeping or the front desk.
• BI and data teams. Reputation lands in the same warehouse as rates, availability and demand, so a dip in score can be read next to what you were charging that week.

Why compare TripAdvisor with the other channels

TripAdvisor, Booking.com, Google and Expedia measure different populations with different prompts, so their scores are not interchangeable. Reading them side by side on one normalized scale is what tells you whether a dip is your property or the platform.