Chapter 1 · 5 min read
how your OTA listings shape what AI says about you
AI assistants read your OTA listings as source material. We checked one resort across 27 factual dimensions and found contradictions on half of them.
Read the chapter →Reference guide · 3 chapters
OTA Listing Health and Content Coherence
Your OTA listings sell rooms and, increasingly, tell AI assistants what your hotel is. This guide covers what to check across channels, which contradictions matter most, and why a gap is more dangerous than a disagreement.
Updated August 202624 minPracticalFree to cite
The channels, and what they say about you
An OTA listing was written to convert someone already on the OTA. It is now also read as a reference document about your hotel — by travellers comparing tabs, and by the assistants that build answers from whatever is dense, current and readable. That makes a contradiction between channels a contradiction in the answers travellers receive.
These pieces cover how the OTA machine actually ranks and charges, and what happens when the facts across your channels stop agreeing.
Chapter 2 · 10 min read
how OTA ranking algorithms actually work
Booking.com is not “mostly about price”. OTA ranking systems are machine-learning engines optimising for platform revenue, and the same signals shape AI.
Read the chapter →Chapter 3 · 10 min read
OTA commissions and the visibility gap
Everyone blames 15–25% OTA fees. Cloudbeds 2026 data shows OTAs drive 63%+ of independent hotel bookings. The fix isn’t another rate deal. It’s visibility.
Read the chapter →Measure this for your hotel
Check listing coherence
Tharro compares your factual claims across every channel you appear on and flags the contradictions and the gaps separately.
Check listing coherence →See where your hotel stands today.
Five minutes to set up. One market free for 14 days.