We tracked the same hotel rooms on Booking.com, Agoda & Expedia for 60 days across 15 cities. See rate parity violations, fee gaps & who's really cheapest.
TL;DR: Actowiz tracked identical room types at 2,500 hotels across 15 cities on Booking.com, Agoda, and Expedia over 60 days. Findings: the same room on the same dates showed different prices across OTAs in 42% of observations; Agoda's headline rates ran lowest in Bangkok, Bali, and Singapore while taxes-and-fees presentation reversed many gaps at checkout; and mobile-only/member rates broke advertised parity in 32% of cases.
Hotels promise OTAs rate parity; OTAs compete to break it through member pricing, mobile rates, and packaging. For hotels, parity violations leak revenue and damage direct-booking strategy. For OTAs and metasearch, parity gaps are the competitive product. Nobody can manage what they can't see — and seeing it requires scraping identical room-date pairs across platforms continuously.
| Parameter | Coverage |
|---|---|
| Platforms | Booking.com, Agoda, Expedia |
| Cities | 15 — incl. Dubai, London, NYC, Singapore, Bangkok, Delhi, Paris, Bali |
| Hotels matched on all three | 2,500 (3–5 star mix) |
| Room-date pairs tracked | 180,000+ (same room type, same check-in dates, 1–30 day lead times) |
| Capture | every 12 hours, 60 days, desktop + mobile, logged-out + member states |
| Fields | Headline rate, taxes/fees, total checkout price, cancellation terms, member/mobile flags, availability |
Tax/fee presentation differs by OTA and market. Comparing headline rates alone, Agoda "won" 28% of pairs — but at total checkout price the win rate shifted to Booking X% / Agoda Y% / Expedia Z%. Any rate intelligence built on headline prices is structurally wrong; capture must include the full checkout stack.
We match property identity, then room-type names, occupancy, bed configuration, and cancellation terms across OTAs before comparison; ambiguous matches are excluded, so parity gaps reflect verified identical room-date pairs.
Yes — capture runs in logged-out and member states, desktop and mobile, flagging each rate's visibility condition. Member/mobile rates are where most modern parity breaks occur.
Yes — property-level parity monitoring with alerts is a standard configuration: your properties, your comp set, your key OTAs, refreshed daily or intraday.
MakeMyTrip, Goibibo, Trip.com, Hotels.com, Traveloka, and metasearch (Google Hotels, Trivago, Kayak) are available; coverage is configurable by city and property list.
Our web scraping expertise is relied on by 4,000+ global enterprises including Zomato, Tata Consumer, Subway, and Expedia — helping them turn web data into growth.
Watch how businesses like yours are using Actowiz data to drive growth.
From Zomato to Expedia — see why global leaders trust us with their data.
Backed by automation, data volume, and enterprise-grade scale — we help businesses from startups to Fortune 500s extract competitive insights across the USA, UK, UAE, and beyond.
We partner with agencies, system integrators, and technology platforms to deliver end-to-end solutions across the retail and digital shelf ecosystem.
Use Newme Data API to automate fashion product data collection, pricing intelligence, catalog tracking, and competitor market analysis.
Unlock Hertz & Avis Rental Car Data for Dynamic Pricing Intelligence to track rental rates, availability, and market trends in real time.
Brazil Car Rental Pricing Intelligence Report 2026 reveals rental price trends, market shifts, competitor rates, and opportunities for smarter pricing.
Whether you're a startup or a Fortune 500 — we have the right plan for your data needs.