Hotel rate shopping
Collect rates for a set of properties and their competitors across OTAs and brand sites for a rolling window of stay dates, from the point-of-sale markets you care about, every day or several times a day.
Industries
What we scrape in travel and hospitality
Hotel rates, flight fares, availability, reviews and attraction listings from OTAs, airlines and review sites, by date and point-of-sale market.
Travel prices depend on who is asking, from where, for which dates and how far ahead. We scrape OTAs, airline sites, hotel brand sites and short-term rental pages from the markets you choose, for the date grid you define, and record every rate with its room or fare class, cancellation terms and the moment we saw it. Reviews and attraction listings are collected the same way. The result is a rate table you can compare across channels and over lead time.
Sources
Typical sources
Public pages and documents we have scraped in this vertical. Named sites are examples, not an exhaustive list.
- Booking.com, Expedia and Agoda hotel pages
- Airline websites and metasearch such as Google Flights and Skyscanner
- Hotel brand sites and loyalty rate pages
- Airbnb and Vrbo rental listings
- TripAdvisor and Google reviews for hotels and restaurants
- Attraction, tour and ticketing sites
- Car rental aggregators
- Destination event calendars
Schema
Fields
A common starting schema. You decide the final columns and names; we keep them stable across runs.
property_or_routechannelcheck_in_or_departlead_daysroom_or_fare_classratecurrencyrefundableavailabilitymarketscraped_at
Output
What a row looks like
property_or_route | channel | check_in_or_depart | lead_days | room_or_fare_class | rate | currency | refundable | availability | market | scraped_at |
|---|---|---|---|---|---|---|---|---|---|---|
| Example Hotel, Lisbon | OTA A | 2026-11-14 | 38 | Double, breakfast | €142 | EUR | true | 3 rooms left | DE | 2026-10-07 |
Values are illustrative placeholders to show shape and types, not records from any client or source.
Use cases
Jobs we are usually asked for
Flight fare tracking
Scrape fares for defined routes and date ranges from airline and metasearch sites, recording fare class, baggage allowance and refundability, so pricing behaviour over lead time is visible in one table.
Review and attraction datasets
Pull reviews with rating, date, language and traveller type for hotels, restaurants and attractions in a destination, plus listing details such as opening hours and ticket prices, refreshed on a schedule.
Questions
About travel & hospitality scraping
Can you scrape Booking.com or airline sites?
Public search and listing pages, yes, within polite volume limits. Both use strong anti-bot measures and the quote accounts for that. We do not log into partner extranets or loyalty accounts.
How do you handle prices that vary by country?
We route requests through the countries you specify and record the market with every rate. A German and a US point of sale appear as separate rows for the same room and date.
How large can the date grid be?
Hundreds of properties across a 90-day window daily is a normal job. Larger grids are spread over the day or sampled, and the scoping reply sets the volume.
Do you provide rate parity reports?
We deliver the rates; parity checks are a simple comparison you run in your own tools or we add as a derived column. No dashboard is included.
Need travel & hospitality data? Tell us the sites.
Send the sources and the fields you need. An engineer looks at them the same day and replies with a plan and a price.