Booking.com Scraper

Booking.com Scraper creates a structured dataset of hotel listings collected from Booking.com. Each dataset item represents one hotel and can include nightly price, review score, location, and amenities, with optional hotel details, a year-round availability pricing calendar, and guest reviews. Query the source by destination name or Booking.com URL, set check-in and check-out dates, control the result limit with maxItems, and retrieve records through the Apify Dataset API or export them as JSON, CSV, Excel, or other supported formats.

Dataset at a glance

Property	Value
Source	booking.com (public hotel search and property pages)
Record unit	One hotel, with nested optional details, availability, and reviews
Input methods	Destination name (searchQueries) or Booking.com URLs (startUrls)
Main identifiers	hotelId, hotel page url
Delivery	Apify Dataset and API
Export formats	JSON, CSV, Excel, XML, HTML (Apify dataset exports)
Update model	Fresh records per Actor run
Pricing	$1 per 1,000 hotels; +$1 per 1,000 for details; +$0.10 per 1,000 for availability; +$1 per 1,000 for reviews

Coverage and available records

The Actor collects hotels from public Booking.com pages using one of two entry points:

• Query-based: Pass plain destination names (for example "Berlin, Germany") in searchQueries. The Actor resolves the Booking.com destination ID automatically.
• URL-based: Pass ready-made search-results or hotel page URLs in startUrls when you already know the exact dest_id or property page.

Record types and limits:

• Listing-level records are always collected: name, hotel ID, URL, city, address, coordinates, nightly price, review score, review count, and image URL.
• Hotel detail fields are conditional: facilities, house rules, surroundings, and description are returned only when hotelDetails is enabled.
• Availability records are conditional: a year-round daily availability and pricing calendar is returned only when scrapeAvailability is enabled.
• Guest review records are conditional: a nested guestReviews array is returned only when scrapeReviews is enabled, capped by maxReviews.
• Result cap: maxItems limits the number of hotels collected (0 means unlimited; the default is 10).

Known exclusions: content Booking.com only shows behind a booking flow is not collected; each run captures page state at run time (no historical snapshots); availability and reviews are not collected unless their toggles are enabled.

Data dictionary

Field names below match dataset record JSON properties exactly. Fields marked conditional appear only when the corresponding input toggle is enabled.

Hotel-level fields

Field	Type	Nullable	Description	Example
hotelId	number	No	Booking.com hotel identifier; best stable deduplication key	177530
name	string	No	Hotel name	Industriepalast Berlin
url	string	No	Hotel page URL	https://www.booking.com/hotel/de/industriepalast-berlin.html
pageName	string	No	URL slug for the hotel	industriepalast-berlin
countryCode	string	Yes	Country code	de
city	string	Yes	City as shown on the listing	Berlin
address	string	Yes	Street address	Warschauer Straße 43
latitude	number	Yes	Hotel latitude	52.5040844271257
longitude	number	Yes	Hotel longitude	13.4472857415676
reviewScore	number	Yes	Average guest review score	8.0
reviewCount	number	Yes	Number of guest reviews	5803
reviewScoreText	string	Yes	Review score label	Very Good
price	string	Yes	Nightly price as rendered	S$ 102.85
priceRounded	string	Yes	Rounded nightly price	S$ 103
currency	string	Yes	Currency code	SGD
imageUrl	string	Yes	Main hotel image URL	https://cf.bstatic.com/...
sourceQuery	string	Yes	Destination query that produced the record	Berlin
searchCheckIn	string	Yes	Check-in date used for the search	2026-09-25
searchCheckOut	string	Yes	Check-out date used for the search	2026-09-27

Hotel detail fields (conditional — hotelDetails)

Field	Type	Nullable	Description	Example
houseRules.checkInFrom	string	Yes	Earliest check-in time	3:00 PM
houseRules.checkInUntil	string	Yes	Latest check-in time	11:30 PM
houseRules.checkOutUntil	string	Yes	Check-out deadline	10:00 AM
houseRules.minCheckInAge	number	Yes	Minimum check-in age	18
facilities.relevantForYourTrip	string[]	Yes	Highlighted facilities	["Free Wifi", "Parking", ...]
facilities.spokenLanguages	string[]	Yes	Languages spoken at the property	["ar", "de", "en", ...]

Availability fields (conditional — scrapeAvailability)

Field	Type	Nullable	Description	Example
availability[].date	string	No	Calendar date	2026-09-25
availability[].available	boolean	No	Whether the hotel is available that date	true
availability[].price	string	Yes	Daily price (string)	56
availability[].minLengthOfStay	number	Yes	Minimum length of stay	2

Guest review fields (conditional — scrapeReviews)

Field	Type	Nullable	Description	Example
guestReviews.summary.totalReviewCount	number	Yes	Total review count in summary	5802
guestReviews.reviews[].reviewScore	number	Yes	Reviewer score	9.0
guestReviews.reviews[].guestName	string	Yes	Reviewer name	Héloïse
guestReviews.reviews[].guestCountry	string	Yes	Reviewer country	France
guestReviews.reviews[].guestType	string	Yes	Traveler type	Solo traveler
guestReviews.reviews[].roomType	string	Yes	Room type reviewed	Single Bed in Female Dormitory Room
guestReviews.reviews[].positiveText	string	Yes	Positive review text	Everything went great...
guestReviews.reviews[].negativeText	string	Yes	Negative review text	The rooms didn't have air con...

Example dataset record

Real record produced with a destination query (searchQueries: ["Berlin"]), dates 2026-09-25 to 2026-09-27, with details, availability, and reviews enabled. The availability and reviews arrays are truncated for readability.

{
  "hotelId": 177530,
  "name": "Industriepalast Berlin",
  "url": "https://www.booking.com/hotel/de/industriepalast-berlin.html",
  "pageName": "industriepalast-berlin",
  "countryCode": "de",
  "city": "Berlin",
  "address": "Warschauer Straße 43",
  "latitude": 52.5040844271257,
  "longitude": 13.4472857415676,
  "reviewScore": 8.0,
  "reviewCount": 5803,
  "reviewScoreText": "Very Good",
  "price": "S$ 102.85",
  "priceRounded": "S$ 103",
  "currency": "SGD",
  "imageUrl": "https://cf.bstatic.com/xdata/images/hotel/square600/488699632.webp",
  "sourceQuery": "Berlin",
  "searchCheckIn": "2026-09-25",
  "searchCheckOut": "2026-09-27",
  "houseRules": {
    "checkInFrom": "3:00 PM",
    "checkInUntil": "11:30 PM",
    "checkOutUntil": "10:00 AM",
    "minCheckInAge": 18
  },
  "facilities": {
    "relevantForYourTrip": ["Free Wifi", "Parking", "Pet friendly", "Non-smoking rooms", "Family rooms"],
    "spokenLanguages": ["ar", "de", "en", "es", "it"]
  },
  "availability": [
    { "date": "2026-09-25", "available": true, "price": "56", "minLengthOfStay": 2 },
    { "date": "2026-09-26", "available": false, "price": "0", "minLengthOfStay": 1 }
  ],
  "guestReviews": {
    "summary": { "totalReviewCount": 5802 },
    "reviews": [
      {
        "reviewScore": 9.0,
        "guestName": "Héloïse",
        "guestCountry": "France",
        "guestType": "Solo traveler",
        "roomType": "Single Bed in Female Dormitory Room",
        "positiveText": "Everything went great, the location is perfect...",
        "negativeText": "The rooms didn't have air con..."
      }
    ]
  }
}

The record above was produced with this input:

{
  "searchQueries": ["Berlin"],
  "checkIn": "2026-09-25",
  "checkOut": "2026-09-27",
  "maxItems": 10,
  "hotelDetails": true,
  "scrapeAvailability": true,
  "scrapeReviews": true,
  "maxReviews": 10,
  "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] }
}

Query and input reference

Input	Type	Required	Default	Accepted values	Description
searchQueries	array (JSON)	No*	["Berlin, Germany"]	Destination names (e.g. "Paris", "Berlin, Germany")	Query-based entry point; destination IDs are resolved automatically
startUrls	array (requestListSources)	No*	[]	Booking.com search-results or hotel URLs	URL-based entry point; overrides queries when set
checkIn	string	No	2026-09-25	YYYY-MM-DD	Check-in date
checkOut	string	No	2026-09-27	YYYY-MM-DD	Check-out date
adults	integer	No	1	1 or more	Adults per room
rooms	integer	No	1	1 or more	Number of rooms
children	integer	No	0	0 or more	Number of children
childrenAges	array	No	[]	One integer per child	Ages of children
maxItems	integer	No	10	0 (unlimited) or positive integer	Maximum hotels to collect
hotelDetails	boolean	No	false	true / false	Collect detail fields per hotel (charged as hotel details)
scrapeAvailability	boolean	No	false	true / false	Collect the year-round availability calendar (charged as availability)
scrapeReviews	boolean	No	false	true / false	Collect guest reviews (charged as reviews)
maxReviews	integer	No	10	0 (unlimited) or positive integer	Maximum reviews per hotel
lang	string	No	en-us	en-us, en-gb, de, fr, es, it, nl, pt-pt	Booking.com language code
currency	string	No	EUR	ISO currency code (e.g. EUR, USD)	Preferred currency for prices
proxyConfiguration	object	No	Apify proxy, RESIDENTIAL group	Apify proxy groups or custom proxies	Residential proxies are recommended; datacenter IPs are frequently rate-limited

* Provide either searchQueries or startUrls — at least one source is required.

Minimal request:

{ "searchQueries": ["Berlin, Germany"], "checkIn": "2026-09-25", "checkOut": "2026-09-27" }

Advanced request (destination query with enrichment):

{
  "searchQueries": ["Paris"],
  "checkIn": "2026-09-25",
  "checkOut": "2026-09-27",
  "adults": 2,
  "rooms": 1,
  "maxItems": 1000,
  "hotelDetails": true,
  "scrapeAvailability": true,
  "scrapeReviews": true,
  "maxReviews": 20,
  "lang": "fr",
  "currency": "EUR",
  "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] }
}

Retrieve the data through the API

The Actor runs on the Apify platform, so there is no server to host and no crawling infrastructure to maintain.

1. Start the Actor with a JSON input (console or API).
2. Wait for the run to finish, or use a synchronous endpoint if you want the response inline.
3. Retrieve items from the run's default dataset.
4. Paginate or export the dataset.

Python example:

from apify_client import ApifyClient

client = ApifyClient("YOUR-APIFY-TOKEN")

run_input = {
    "searchQueries": ["Berlin, Germany"],
    "checkIn": "2026-09-25",
    "checkOut": "2026-09-27",
    "maxItems": 10,
}

run = client.actor("datascrapers/booking-com-scraper").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["hotelId"], item["name"], item["price"], item["reviewScore"])

Apify generates ready-to-run Python, JavaScript, and cURL examples on the Actor's API tab. Do not put a real API token in shared code or URLs.

Data quality and record handling

• Conditional fields: detail, availability, and review fields are present only when their input toggle is enabled. Listing-only runs return a leaner record.
• Source changes: Booking.com page structure and values can change; unreadable fields are returned as null rather than fabricated.
• Deduplication: each run appends fresh records; the Actor does not deduplicate hotels across runs. Use hotelId as the stable key and filter repeated runs against previously stored IDs.
• Rate limits and geo-behavior: Booking.com can serve region- or currency-specific pages. Keep the default residential proxy enabled and match the destination's country in your proxy settings for consistent coverage.
• Normalization: price and availability values are read from the page and kept as strings; dates use YYYY-MM-DD format. Review scores are normalized to numbers.

Export and pipeline examples

Destination	Recommended method	Typical use
PostgreSQL / Supabase	Dataset API poll or webhook consumer	Store hotel inventory alongside price history
Google Sheets	Apify Google Sheets integration	Share destination shortlists with teams
BI tools (Looker, Tableau)	Scheduled export via Apify scheduler	Rate benchmarking and market snapshots
S3 / cloud storage	Scheduled export + integration	Archival of daily price and availability snapshots

Pricing and cost examples

The Actor uses pay-per-event pricing with four chargeable events:

Event	Trigger	Rate
Scraped result	Every hotel record pushed to the dataset	$1 per 1,000 hotels
Hotel details	hotelDetails enabled, profile visited	$1 per 1,000 hotels
Availability calendar	scrapeAvailability enabled, calendar fetched	$0.10 per 1,000 hotels
Reviews	scrapeReviews enabled, reviews fetched	$1 per 1,000 hotels

Example costs:

Records	Configuration	Estimated base cost
1,000	Listing only	$1.00
10,000	Listing only	$10.00
1,000	Listing + details	$2.00
1,000	Listing + details + availability	$2.10
1,000	Listing + details + availability + reviews	$3.10

Apify paid plans reduce the per-1,000 rate. Compute units consumed by the run are billed by your Apify plan. Estimates depend on the verified pricing model and the options selected for the run.

Limitations and responsible data use

• The Actor collects publicly accessible data from Booking.com pages only.
• Field availability depends on what Booking.com renders at run time; some values can be null or missing, and site changes can alter fields.
• Availability and reviews are only collected when their toggles are enabled.
• The Actor does not provide historical snapshots unless you store them yourself.
• Large runs require residential proxies; without them, coverage may degrade due to rate limiting.
• You are responsible for compliance with Booking.com's terms of service, applicable privacy law, and any contractual obligations before using the data.

Dataset questions

What does one dataset item represent?

One hotel from Booking.com. Availability and guest reviews are nested inside the hotel record as availability and guestReviews arrays, so a hotel with hundreds of reviews still produces a single dataset item.

Which field should I use as a unique identifier?

hotelId is the stable Booking.com identifier and is the recommended deduplication key. The url (hotel page URL) is a reasonable secondary key.

Are fields nullable or conditional?

Yes. Detail fields (house rules, facilities) exist only when hotelDetails is enabled; availability exists only when scrapeAvailability is enabled; guestReviews exists only when scrapeReviews is enabled. Within available records, fields that Booking.com does not render are returned as null.

Can I retrieve the records as CSV or JSON?

Yes. The dataset can be exported as JSON, CSV, Excel, XML, or HTML from the Apify Console, and queried through the Dataset API.

Does the Actor return historical data?

No. Each run captures the state of the pages at run time. To track price changes over time, schedule repeated runs and store the outputs yourself; each record includes searchCheckIn and searchCheckOut to distinguish snapshots.

What counts as a billable result?

Four pay-per-event charges apply: a scraped-result charge for every hotel record ($1 per 1,000), a hotel-details charge for each enriched profile ($1 per 1,000), an availability-calendar charge for each calendar fetched ($0.10 per 1,000), and a reviews charge for each hotel whose reviews are fetched ($1 per 1,000). A listing-only run incurs only the scraped-result charge.

Why am I getting empty results?

This usually means Booking.com blocked the request or served a region/currency page you do not expect. Keep the default residential proxy enabled, match the destination's country in your proxy settings, and confirm your checkIn / checkOut dates are valid and in YYYY-MM-DD format.

Related datasets from Data Scrapers

• Tripadvisor Reviews Scraper — Guest review records that can be joined with hotels by name or location for reputation analysis.
• Yelp Scraper — Local business and hospitality listings useful alongside hotel supply research.
• Apartments Scraper — Rental listings for comparative lodging market analysis.

Data Scrapers support

Need an additional field, record type, or export workflow? Contact Data Scrapers at stardustspotlight@gmail.com. Include a sample source URL, required fields, expected record volume, and preferred delivery format.