Booking Scraper PRO

What is Booking Scraper PRO?

Booking Scraper PRO returns one dataset row per Booking.com property from a destination search or from Booking.com URLs: property name, link and ID, guest review score with its label and review count, star class, area and distance from the centre, deal flags, main photo and, for dated searches, the nightly price in your chosen currency. Hotel revenue managers, travel analysts, agencies and AI agents use it to map supply in a city, benchmark competitors on rating and price, and build property lists, with optional detail enrichment for descriptions, amenities and coordinates.

Why travel teams use this Booking.com scraper

• Search like a guest. search takes a destination such as Amsterdam; checkIn, checkOut, adults, children and rooms set the stay.
• Prices in your currency. currency covers 18 currencies and language sets the Booking locale.
• Ratings ready to rank. reviewScore, reviewScoreWord and reviewCount sit on every rated property.
• Filters before collection. minPrice, maxPrice and minStars narrow the search on Booking.com itself.
• Detail on demand. enrichDetails opens each property page for description, amenities, check-in and check-out times and coordinates.
• URLs welcome. startUrls accepts Booking.com search pages and individual property pages.

Best fit for this Actor

• Best fit for competitor sets, destination supply maps and rating benchmarks across Booking.com properties.
• Designed for dated searches when price matters: Booking.com shows nightly prices for a specific stay, so set checkIn and checkOut to fill price, priceText and taxesAndFees. Undated searches return names, scores and locations.
• For full-city coverage, run several focused searches, such as by district, star class or price band, and merge the datasets on hotelId.
• When you want what guests actually wrote, then pass the property url values to Booking.com Reviews Scraper.
• To compare the same hotels on another platform, continue with TripAdvisor Scraper.

Example workflow: from a city search to a rate benchmark

A revenue manager at a boutique hotel in Amsterdam starts with search set to Amsterdam, a weekend checkIn and checkOut, currency set to EUR, minStars at 4 and maxResults at 50. The dataset returns each competitor's price, reviewScore, reviewCount and distanceFromCenter. They keep properties within a mile of their own, compare price against reviewScore to see who charges a premium for ratings, and export the table to their pricing sheet. They then schedule the same input for each upcoming weekend and compare rates week over week.

Input

{
  "search": "Amsterdam",
  "checkIn": "2026-11-13",
  "checkOut": "2026-11-15",
  "adults": 2,
  "children": 0,
  "rooms": 1,
  "currency": "EUR",
  "language": "en-gb",
  "minStars": 4,
  "maxResults": 50,
  "enrichDetails": false
}

Field	Type	What it controls
search	string	Destination to search, such as Amsterdam or Paris, France. Use this or startUrls.
startUrls	array	Booking.com search-results URLs or individual property URLs.
checkIn, checkOut	strings	Stay dates in YYYY-MM-DD format, for nightly prices.
adults, children, rooms	integers	Occupancy. Defaults 2, 0 and 1.
currency	string	Price currency, such as USD, EUR or GBP. Default USD.
language	string	Booking locale, such as en-gb, de or fr. Default en-gb.
minPrice, maxPrice	integers	Nightly price range in the selected currency.
minStars	integer	Minimum star class, 0 to 5. Default 0.
maxResults	integer	Cap on properties saved, up to 1,000. Default 25.
enrichDetails	boolean	Open each property page for description, amenities, times and coordinates. Default false.
proxyConfiguration	object	Apify Proxy settings. Default uses Apify Proxy.

Output

One row per property. Fields stay null when Booking.com leaves them off the card or the search.

Field	What it contains
name, url, hotelId	Property identity and link
reviewScore, reviewScoreWord, reviewCount	Guest rating on a 0 to 10 scale, its label and review count
stars	Star class when Booking.com shows one
price, currency, priceText, taxesAndFees	Nightly price for dated searches
address, city, country, distanceFromCenter	Location from the property card; on city searches city holds the district and country the city
roomType, bedConfig	The room offered for the stay
freeCancellation, breakfastIncluded, badges	Deal flags
image	Main photo URL
propertyType, description, amenities, checkInTime, checkOutTime, latitude, longitude	Detail fields with enrichDetails
checkInDate, checkOutDate, scrapedAt	Stay dates searched and collection time

Example row from an undated Amsterdam search:

{
  "name": "Holiday Inn Express Amsterdam - North Riverside by IHG",
  "url": "https://www.booking.com/hotel/nl/holiday-inn-express-amsterdam-motorkade.en-gb.html",
  "hotelId": "holiday-inn-express-amsterdam-motorkade",
  "propertyType": null,
  "reviewScore": 8.2,
  "reviewScoreWord": "Very good",
  "reviewCount": 12546,
  "stars": null,
  "price": null,
  "currency": "USD",
  "priceText": null,
  "address": "Amsterdam Noord, Amsterdam",
  "city": "Amsterdam Noord",
  "country": "Amsterdam",
  "distanceFromCenter": "1.4 miles from centre",
  "freeCancellation": false,
  "breakfastIncluded": false,
  "badges": [],
  "image": "https://cf.bstatic.com/xdata/images/hotel/square240/269458643.webp?k=519e81855baad947382232b5ab719093f75caf08430bce8225d07d850638134e&o=",
  "checkInDate": null,
  "checkOutDate": null,
  "scrapedAt": "2026-10-01T13:02:43.323Z"
}

Pricing

This Actor uses Pay per event plus Apify platform usage. Each property saved is one Property scraped event; with enrichDetails on, each property also adds one Property detail enrichment event. Every run has one Actor Start event plus the platform usage of the run. For example, 50 properties without enrichment are 50 Property scraped events plus the start event and usage; with enrichment they are 50 of each. maxResults caps the count, so it doubles as a spending limit. The live Pricing tab on this page shows the current event prices.

API example

curl -X POST "https://api.apify.com/v2/acts/khadinakbar~booking-scraper-pro/run-sync-get-dataset-items?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"search": "Lisbon", "checkIn": "2026-11-13", "checkOut": "2026-11-15", "currency": "EUR", "maxResults": 25}'

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("khadinakbar/booking-scraper-pro").call(run_input={"search": "Rome", "minStars": 4, "maxResults": 30})
rated = [p for p in client.dataset(run["defaultDatasetId"]).iterate_items() if p.get("reviewScore")]
print(sorted(rated, key=lambda p: p["reviewScore"], reverse=True)[:10])

Use with AI agents (MCP)

Connect the Actor to Claude, ChatGPT or Cursor through Apify MCP and ask:

Find 4-star hotels in Rome for two adults from 13 to 15 November, priced in euros. List the ten best rated with their nightly price and distance from the centre.

The agent sets search, checkIn, checkOut, currency, minStars and maxResults, reads rows with get-dataset-items, sorts by reviewScore, and cites each url. Each property is one event, so maxResults keeps the cost of the request predictable.

Best results

Starting situation	Helpful action	Expected outcome
Rate shopping	Set checkIn, checkOut and currency	Nightly prices with taxes and fees
A big city	Split into district or star-band searches	Wider coverage across runs
Rating benchmarks	Sort by reviewScore, then reviewCount	Well-reviewed properties first
Amenity or description checks	Turn on enrichDetails	Description, amenities and coordinates
A known competitor set	Paste property pages into startUrls	Exactly those properties

Builder's note

I built this for the revenue-manager question of who charges what next to whom, so every row pairs rating, location and, for dated searches, price. I kept detail enrichment optional because most benchmarking only needs the search card, and opening every property page is the slow, extra-cost step.

FAQ

Why is the price empty?

Booking.com shows nightly prices for a specific stay. Add checkIn and checkOut to the input.

Can I get guest reviews?

This Actor returns scores and review counts. For review text, use the property URLs with the Booking.com Reviews Scraper linked above.

How do I cover a whole city?

Run several focused searches and merge them on hotelId.

Responsible use

This Actor collects publicly available Booking.com property data. Respect Booking.com's terms and applicable laws such as the GDPR when you store or share results. Booking.com is a trademark of its owner; this independent Actor is not affiliated with or endorsed by Booking.com.