Booking.com Scraper With Property Contact Leads

Booking.com Scraper — Hotels, Prices and Property Contact Leads

Booking.com Scraper With Property Contact Leads scrapes hotel, apartment, hostel, villa and other property listings from Booking.com and returns typed JSON — plus a flattened contact lead per property: contactEmail, contactPhone, contactWebsite, contactCompany and contactName, alongside price, rating, stars, address and rooms. It's built for hospitality sales teams, lead-generation agencies and travel-tech researchers who need a property list they can actually contact, not just browse. Paste a destination or Booking.com URLs and every result streams in as a ready-to-use lead row.

What is Booking.com Scraper With Property Contact Leads?

It's an Apify Actor that searches Booking.com by destination (or takes direct Booking.com URLs), scrapes each property's public detail page, and shapes the result into two things at once: a full property record (price, rating, rooms, facilities, address, images, policies) and a flattened contact-lead block (email, phone, website, company, contact name). Output is one JSON row per property, exportable as JSON, CSV, Excel, XML or HTML table.

No Booking.com account or login is used anywhere in the run — every field comes from the property's public page or a public web search.

• Discover properties by destination search (search) or by pasting Booking.com URLs directly (startUrls) — hotel detail pages or search-results pages both work
• Every row carries a contact-lead block built from the property's on-page trader/business details, best-effort backfilled by a keyless web search when that block is missing
• Filter search results by property type, star rating, minimum guest rating, price range and sort order before you scrape a single detail page
• Set check-in/check-out dates, room and guest counts, and date flexibility to pull live, stay-specific pricing instead of a generic rate
• Narrow the output to contactsOnly rows or to a specific email-domain allow-list so the export is a clean lead list, not a full property dump
• Export straight from the Apify Console as JSON, CSV, Excel, XML or HTML table, or read the dataset through the Apify API

What Booking.com property and contact data is publicly available to scrape?

Booking.com renders full property details — price, rating, rooms, facilities, images, address — to any anonymous visitor. Direct contact information is a different story: Booking.com deliberately keeps most property owners routed through its own messaging system, so email and phone are only reliably public for a subset of listings.

Data category	Availability
Property name, price, rating, stars, reviews	✅ Public on the property page
Address, coordinates, rooms, facilities, images, policies	✅ Public on the property page
Trader/business email, phone, company name (EU-regulated and business listings)	✅ Public — shown in the property's own legal/trader block
Property email, phone, website for listings without a trader block	❌ Not on the page — recovered only via best-effort keyless web search, when findable
Guest names, reservations, payment details	❌ Never collected — not on the public listing page and out of scope for this Actor

Booking.com Scraper With Property Contact Leads only reads what is already on the public property page, plus what a public Google search surfaces for the property's own name. Nothing behind a login, a partner account, or Booking.com's internal messaging system is touched.

What data can I extract with Booking.com Scraper With Property Contact Leads?

Every row groups into three kinds of data: the contact lead itself, the pricing and stay details, and the full property record underneath it.

Contact and lead fields

Field Name	Description
hasContact	true if any email, phone or website was found for the property
contactEmail	Property email — on-page trader email first, else SERP-backfilled, else null
contactPhone	Property phone — on-page trader phone first, else SERP-backfilled, else null
contactWebsite	The property's own website, discovered via SERP backfill (aggregators excluded), or null
contactCompany	Registered business/company legal name from the trader block, or null
contactName	Host name or trader first/last name, or null
emailDomain	Domain portion of contactEmail, or null
contactCountry	Trader country code, falling back to the property's own country, or null
isBusinessListing	true when Booking.com flags the property as an EU-regulated trader listing
contactSource	onpage_trader, serp, or null — where the contact was found

Pricing and stay fields

Field Name	Description
price	Lowest room price found for the searched stay, or null
currency	Currency code for price
checkIn	Formatted check-in time window as published by the property (e.g. "From 15:00")
checkOut	Formatted check-out time window as published by the property
checkInDate	The checkIn date you requested in input, echoed back, or null
checkOutDate	The checkOut date you requested in input, echoed back, or null
breakfast	"Available" when breakfast is offered, or null
rooms	Array of room objects: id, name, description, size, occupancy, price
roomImages	Array of { roomId, images } — photos grouped per room

Property detail fields

Field Name	Description
order	Row position within the run
name	Property name
type	Accommodation type as published (e.g. hotel)
url	Canonical Booking.com property URL
source_url	The exact URL this row was scraped from
startUrlOrQuery	The destination search string or start URL that produced this row
hotelId	Booking.com's internal property ID
hotelChain	Hotel chain/brand name, or null for independent properties
address	Object: full, country, city
location	Object: lat, lng
breadcrumbs	Array of { name, url } — Booking.com's own category breadcrumb trail
image	Primary property image URL
images	Array of property image URLs (up to 50)
stars	Official star rating, or null
rating	Guest review score, or null
ratingLabel	Booking.com's text label for the score (e.g. "Superb")
reviews	Total guest review count
categoryReviews	Array of { name, score } — per-category review breakdown (cleanliness, location, etc.)
description	Property description text
highlights	Array of highlighted facility/feature labels
finePrint	Concatenated fine-print text from the property
policies	Array of { name, value } house-rule and policy entries
facilities	Array of { name, id } facility entries
licenseInfo	Property license/registration number, or null
hostInfo	Host display name (independent hosts), or null
traderInfo	Object: isBusiness, email, phone, companyName, firstName, middleName, lastName, registrationNumber, tradeRegisterName, address (street, street2, postalCode, city, countryCode, state)
timeOfScrapeISO	UTC ISO timestamp of when the row was scraped

All 46 fields are always present in every row — when includePropertyDetails is off, the detail arrays (rooms, roomImages, images, facilities, highlights, categoryReviews, policies) come back as empty lists rather than being dropped from the row, so your schema never changes between runs.

⚠️ Contact coverage is partial — plan outreach lists around it

This is the constraint worth reading before you build a campaign on the output. Booking.com does not publish most property owners' direct contact details — the platform routes guest and partner communication through its own messaging system. enrichContactsViaSearch (on by default) tries to close that gap with a keyless Google search — "<hotel name>" <city> official website contact email, then a site:<domain> follow-up query on the discovered domain — to recover the property's own website and a public email or phone when the on-page trader block is absent.

This backfill is best-effort, not a guarantee: it depends on the property having a discoverable public website with a listed contact, and on Google returning that page for the query. There is no published hit-rate figure for how often it succeeds — the Actor does not fabricate one, and it does not fabricate a contact either. A property with nothing findable comes back with hasContact: false and null in every contact field, never a guessed email. Turn on contactsOnly if you want your export to contain only rows that actually carry a usable contact.

Why not build this yourself?

Booking.com does not publish an open, self-serve search API for general use. Its Connectivity/Demand API access is scoped to registered accommodation partners and travel affiliates managing their own existing inventory and bookings — not ad hoc bulk search-and-contact workflows like sourcing a lead list across a destination. That leaves scraping the public site as the practical route, and the engineering behind it is not trivial.

Booking.com renders its property data through a layered set of sources rather than one predictable place: an inline Apollo GraphQL state blob, schema.org JSON-LD, window.booking environment variables, and DOM fallbacks for whatever the first three miss. A scraper that only reads one of these breaks the moment Booking.com stops populating it for a given property. This Actor reads all four and merges them, so a missing source degrades one field instead of failing the row.

The second cost is the contact layer itself. Recovering a property's own website and public email through a keyless search means running an independent SERP-fetching pipeline: proxy tier management (GOOGLE_SERP datacenter group, escalating to residential), a block detector that keys off the actual results container rather than loose keyword matching (so a normal page that merely contains the word "captcha" isn't discarded as blocked), and filtering out aggregator domains like Tripadvisor, Expedia and Booking.com's own result pages so the discovered "website" is actually the property's. Building and maintaining that pipeline is a separate project from the scraper itself.

How to use Booking.com Scraper With Property Contact Leads

1. Open Booking.com Scraper With Property Contact Leads on Apify and click Try for free
2. Enter a Destination (search) — or paste one or more Booking.com Start URLs (startUrls) to skip search entirely
3. Set Max properties per destination or URL (maxItems) to the number of leads you want
4. Leave Backfill missing contacts via web search (enrichContactsViaSearch) on to maximize contact coverage, or turn it off for a faster, on-page-only run
5. Optionally turn on Contacts only and/or set an email-domain allow-list to narrow the export to usable leads
6. Click Start, then export the dataset as JSON, CSV, Excel, XML or an HTML table

How to scale to bulk lead generation

maxItems caps rows per destination or per start URL, not a single global count when you pass multiple startUrls — each URL you list gets its own budget. Point startUrls at several Booking.com search-results pages (one per city, region, or chain search) to build a multi-destination lead list in a single run; each URL is scraped and enriched in turn, and rows are pushed to the dataset live as each property finishes, so you can start working the list before the run completes.

What can you do with Booking.com property contact leads?

• 🏨 A hospitality sales rep sourcing partnership leads searches a destination, enables contactsOnly, and works the resulting contactEmail/contactPhone list directly into outreach — no manual lookup per property.
• 🏢 A lead-generation agency running this for a hotel-chain client sets emailDomainFilter to the chain's own domains (e.g. ["hilton.com", "ihg.com"]) to isolate corporate-owned properties from independents in the same destination.
• 📊 A travel-tech market researcher pulls price, stars, rating and propertyType across a destination to map pricing distribution and category density without touching contact data at all.
• 🤖 An AI agent pipeline calls the Actor as a tool, filters the returned rows on hasContact, and hands the qualified subset to a downstream outreach or CRM-sync step — all through the Apify API, no scraping code of its own.

How does Booking.com Scraper With Property Contact Leads handle rate limits and blocking?

Two independent proxy ladders, one for page fetching and one for contact search.

Property pages are fetched with impit (Chrome-impersonating HTTP) first, falling back to a headless Playwright Chromium session when impit comes back blocked, empty, or under a captcha challenge. Both run behind a proxy tier ladder — Residential first, then Datacenter, then no proxy — retrying up to three times per tier before escalating. A response is treated as blocked when it's under 3,000 characters or contains a captcha/robot-check marker, so a soft block that returns a normal-looking but empty page is caught rather than parsed into an empty row.

Contact search runs its own ladder: the keyless GOOGLE_SERP proxy group first, escalating to Residential if that's blocked, for up to five escalations. Block detection is keyed on the presence of Google's actual results container (div#search, div#rso, or an anchor-wrapped h3) rather than scanning for stray words like "captcha" — a real results page that happens to mention captcha in a snippet is not discarded. A genuine "no results" page is also detected separately and is not treated as a block, so a property that truly has no public footprint doesn't burn retries.

⬇️ Input sample

Required per schema: none. Every parameter below has a default and can be left as-is for a first run.

Parameter	Required	Type	Description	Example Value
search	No	string	City, region or landmark to search for accommodation. Ignored when startUrls is provided. Default "".	"New York"
startUrls	No	array	One or more Booking.com URLs — hotel detail pages or search-results pages. Overrides search. Default [].	["https://www.booking.com/hotel/us/grand-example.html"]
maxItems	No	integer	Maximum properties to scrape (and turn into leads) per destination or per start URL. Minimum 1, maximum 20000. Default 10.	50
enrichContactsViaSearch	No	boolean	When on, properties without an on-page email/phone are looked up with a keyless "<hotel name>" <city> then site:<domain> Google search. When off, leads use only on-page trader data. Default true.	true
contactsOnly	No	boolean	When on, properties with no email, phone or website found are dropped from the output entirely. Default false.	false
emailDomainFilter	No	array	Allow-list of email domains. Only properties whose contactEmail matches one of these are kept. Empty keeps all. Default [].	["hilton.com", "ihg.com"]
includePropertyDetails	No	boolean	When on, each row also carries rooms, facilities, images, category review scores and policies. Default true.	true
propertyType	No	string	Filter by accommodation type. Enum: none, hotels, apartments, hostels, guest houses, homestays, bed and breakfasts, holiday homes, boats, villas, motels, resorts, holiday parks, campsites, luxury tents. Default "none".	"hotels"
sortBy	No	string	How to sort search results. Enum: distance_from_search, price, review_score_and_price, review_score, class. Default "distance_from_search".	"review_score_and_price"
minimumRating	No	string	Minimum guest rating (e.g. 7, 8, 9). Leave empty for no filter. Default "".	"8"
starsCountFilter	No	string	Filter by star rating. Enum: any, 1, 2, 3, 4, 5. Default "any".	"4"
currency	No	string	Currency for displayed prices. Enum: USD, EUR, GBP, CAD, AUD, CHF, JPY, CNY, INR, BRL, MXN. Default "USD".	"EUR"
language	No	string	Interface language for the search. Enum: en-gb, en-us, de, fr, es, it, pt-br, nl, pl, ru, ja, zh. Default "en-gb".	"en-us"
checkIn	No	string	Absolute date (YYYY-MM-DD) or relative (e.g. 2 weeks). Leave empty for flexible search. Default "".	"2026-09-10"
checkOut	No	string	Absolute date (YYYY-MM-DD) or relative (e.g. 1 week). Leave empty for flexible search. Default "".	"2026-09-13"
flexWindow	No	string	Allow check-in/check-out dates to shift by this many days in either direction. "0" is exact dates only. Enum: 0, 1, 2, 3, 7. Default "0".	"3"
rooms	No	integer	Number of rooms for the stay. Minimum 1, maximum 9. Default 1.	1
adults	No	integer	Number of adult guests. Minimum 1, maximum 30. Default 2.	2
children	No	integer	Number of children. Minimum 0, maximum 30. Default 0.	0
minMaxPrice	No	string	Min-max price filter as a string: "MIN-MAX" (e.g. "50-200") or "MIN+" for a minimum only (e.g. "100+"). Default "0-999999".	"100-300"
proxyConfiguration	No	object	Proxy settings for property-page fetches. Residential is on by default — Booking.com blocks direct datacenter traffic. Default {"useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"]}.	{"useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"]}

Example input

{
  "search": "Paris",
  "maxItems": 25,
  "enrichContactsViaSearch": true,
  "contactsOnly": true,
  "emailDomainFilter": [],
  "includePropertyDetails": false,
  "propertyType": "hotels",
  "minimumRating": "8",
  "starsCountFilter": "4",
  "currency": "EUR",
  "checkIn": "2026-09-10",
  "checkOut": "2026-09-13",
  "flexWindow": "3",
  "minMaxPrice": "100-300"
}

Common pitfall: minMaxPrice must be a string in exactly "MIN-MAX" or "MIN+" form — a bare number like "150" has no - or + for the parser to split on, so the exception is caught silently and the price filter is simply not applied to the search. Also remember search is ignored the moment startUrls is non-empty — the two are either/or, not additive.

⬆️ Output sample

Typed, normalized JSON with the same 46 keys on every row, whether or not a value was found — missing contacts and detail arrays come back as null or [], never as a dropped key. Rows are pushed to the dataset live as each property finishes, so you can start working the data before the run ends. Export as JSON, CSV, Excel, XML or HTML table, or read the dataset through the Apify API.

Example output

{
  "order": 1,
  "url": "https://www.booking.com/hotel/fr/grand-example-paris.html",
  "startUrlOrQuery": "Paris",
  "name": "Grand Hotel Example Paris",
  "type": "hotel",
  "description": "A boutique hotel near the city centre with 42 rooms.",
  "stars": 4,
  "price": 289,
  "currency": "EUR",
  "rating": 8.6,
  "ratingLabel": "Very good",
  "reviews": 1204,
  "breakfast": "Available",
  "checkIn": "From 15:00",
  "checkOut": "Until 11:00",
  "checkInDate": "2026-09-10",
  "checkOutDate": "2026-09-13",
  "location": { "lat": 48.8566, "lng": 2.3522 },
  "address": { "full": "12 Rue de Example", "country": "FR", "city": "Paris" },
  "image": "https://cf.bstatic.com/xdata/images/hotel/max1024x768/example1.jpg",
  "rooms": [
    { "id": "101", "name": "Deluxe Double Room", "description": "City view, 24 sqm", "size": "24 m²", "occupancy": 2, "price": 289 }
  ],
  "highlights": ["Free WiFi", "Non-smoking rooms"],
  "finePrint": "Guests are required to show a photo ID and credit card at check-in.",
  "policies": [
    { "name": "Check-in", "value": "From 15:00" },
    { "name": "Pets", "value": "Pets are not allowed." }
  ],
  "images": [
    "https://cf.bstatic.com/xdata/images/hotel/max1024x768/example1.jpg",
    "https://cf.bstatic.com/xdata/images/hotel/max1024x768/example2.jpg"
  ],
  "roomImages": [
    { "roomId": "101", "images": ["https://cf.bstatic.com/xdata/images/hotel/max1024x768/room101.jpg"] }
  ],
  "categoryReviews": [
    { "name": "Cleanliness", "score": 8.9 },
    { "name": "Location", "score": 9.4 }
  ],
  "hotelChain": null,
  "licenseInfo": "FR-PARIS-000123",
  "hostInfo": null,
  "traderInfo": {
    "isBusiness": true,
    "email": "reservations@grandhotelexampleparis.com",
    "phone": "+33123456789",
    "companyName": "Grand Hotel Example Paris SARL",
    "firstName": null,
    "middleName": null,
    "lastName": null,
    "registrationNumber": "RCS Paris 123 456 789",
    "tradeRegisterName": "RCS Paris",
    "address": {
      "street": "12 Rue de Example",
      "street2": null,
      "postalCode": "75001",
      "city": "Paris",
      "countryCode": "FR",
      "state": null
    }
  },
  "breadcrumbs": [
    { "name": "France", "url": "https://www.booking.com/country/fr.html" },
    { "name": "Paris", "url": "https://www.booking.com/city/fr/paris.html" }
  ],
  "hotelId": "1234567",
  "facilities": [
    { "name": "Free WiFi", "id": "1" },
    { "name": "Airport shuttle", "id": "2" }
  ],
  "timeOfScrapeISO": "2026-07-25T10:32:11.402931+00:00",
  "source_url": "https://www.booking.com/hotel/fr/grand-example-paris.html",
  "hasContact": true,
  "contactEmail": "reservations@grandhotelexampleparis.com",
  "contactPhone": "+33123456789",
  "contactWebsite": "https://grandhotelexampleparis.com",
  "contactCompany": "Grand Hotel Example Paris SARL",
  "contactName": null,
  "emailDomain": "grandhotelexampleparis.com",
  "contactCountry": "FR",
  "isBusinessListing": true,
  "contactSource": "onpage_trader"
}

How do you filter and target specific properties?

Targeting starts with how you point the Actor at Booking.com: destination search vs. direct URLs. search is more accurate for casual discovery — Booking.com applies its own relevance ranking to a city or region name — while startUrls is more precise when you already have a Booking.com search-results URL with filters (dates, price, star rating) baked into the query string, or a specific set of hotel detail pages you already know you want.

Scope precision comes from propertyType, starsCountFilter, checkIn/checkOut with flexWindow, rooms/adults/children, and minMaxPrice — narrow to hotels only, four-star and up, a specific stay window with a few days of flexibility, and a price band, all before a single detail page is scraped.

Quality and contact thresholds are minimumRating for guest rating, and — unique to this Actor — contactsOnly and emailDomainFilter for the lead itself: keep only rows with a usable contact, or only rows whose email matches a chain's own domain. Volume is controlled with maxItems, applied per destination or per start URL.

{ "search": "Barcelona", "propertyType": "hotels", "starsCountFilter": "4", "minMaxPrice": "80-250" }

{ "startUrls": ["https://www.booking.com/searchresults.html?ss=Rome&checkin=2026-10-01&checkout=2026-10-04"], "flexWindow": "3", "adults": 2 }

{ "search": "Miami", "minimumRating": "8", "contactsOnly": true, "emailDomainFilter": ["marriott.com", "hilton.com"] }

Note that contactsOnly and emailDomainFilter stack with AND logic when both are set: a row must have a contactEmail matching one of the listed domains, and (redundantly, since a matching email already implies hasContact: true) also satisfy contactsOnly. In practice, setting emailDomainFilter alone already limits you to rows with a matching contact — contactsOnly only adds something new when emailDomainFilter is empty.

How does it work?

Property pages are parsed in layers, richest source first: an inline Apollo GraphQL state blob (data-capla-store-data="apollo"), schema.org JSON-LD, window.booking environment variables, then DOM selectors as a last resort. Each layer is best-effort and results are merged, so a missing or restructured source degrades individual fields rather than failing the row.

Contacts are built the same way, layered rather than single-sourced. The on-page trader/business block — populated for EU-regulated and registered-business listings — is read first. When it's empty, enrichContactsViaSearch runs a two-step keyless Google search: first "<hotel name>" <city> official website contact email to locate the property's own domain (filtering out aggregators like Booking.com, Tripadvisor, Expedia and Airbnb), then a site:<domain> follow-up query mining that domain specifically for a public email or phone. null is returned over a fabricated value at every step.

Integrations

Booking.com Scraper With Property Contact Leads is an Apify Actor, so it works with anything that can call the Apify API or consume a dataset.

Python example

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")

run = client.actor("<YOUR_USERNAME>/booking-scraper-with-property-contact-leads").call(run_input={
    "search": "Lisbon",
    "maxItems": 30,
    "contactsOnly": True,
    "emailDomainFilter": [],
})

for lead in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(lead["name"], lead["contactEmail"], lead["contactPhone"], lead["price"])

Works in Go, Ruby, Node.js, cURL — any language that can make an HTTP request.

Export to spreadsheets or CRM

Export the dataset as CSV or Excel directly from the Apify Console and import it into a CRM or spreadsheet — map name, contactEmail, contactPhone, contactWebsite, contactCompany and contactCountry to your lead columns, keeping hasContact and contactSource alongside them so you can see coverage and provenance at a glance.

Is it legal to scrape Booking.com?

Scraping publicly accessible listing data is broadly treated as permissible where no login or authentication is bypassed, and this Actor reads only what Booking.com already shows an anonymous visitor plus what a public Google search surfaces.

Property listings, pricing, ratings and the trader/business contact block are business records, not personal data about a private individual — so the legal lens that applies here is Booking.com's terms of service and database/unfair-competition rules around systematic reuse of a compiled listing set, not GDPR-style personal-data regimes.

One responsibility note, not legal advice: if you use the contact fields as an outreach lead list, complying with applicable messaging and email laws in your jurisdiction — such as CAN-SPAM in the US, or PECR and GDPR's rules on unsolicited B2B email in the EU/UK — is on you as the sender. Consult legal counsel for commercial outreach campaigns built on this data.

❓ Frequently asked questions

What if a property has no email or phone found after enrichment?

It's returned with hasContact: false and null in contactEmail, contactPhone and contactWebsite — never a guessed value. Booking.com hides most direct property contacts, and the keyless SERP backfill is best-effort, so some properties genuinely have nothing publicly findable. Turn on contactsOnly to drop these rows from your export entirely.

Can I get the full property details along with the contact leads?

Yes. includePropertyDetails (default true) adds rooms, facilities, images, category review scores and policies to every row. Turn it off for a lean, contact-focused record — the row keys stay the same either way, just with empty arrays where the detail would be.

How accurate is the contact and price data?

The Actor returns data exactly as it appears on the public listing (or public search result, for SERP-backfilled contacts) at request time. Accuracy depends on whether the property keeps its own listing and website current. For high-volume outreach, spot-check a sample of contactEmail/contactPhone rows before a full send.

How many properties can I get per run?

maxItems accepts 1 to 20,000, applied per destination or per start URL — pass multiple startUrls to multiply that budget across several searches in one run.

How do contactsOnly and emailDomainFilter interact?

They combine with AND logic. emailDomainFilter keeps only rows whose contactEmail matches an allowed domain; contactsOnly separately drops any row with hasContact: false. Since a matching email already implies hasContact: true, setting both together behaves the same as emailDomainFilter alone.

What's the difference between search and startUrls?

search runs a destination search on Booking.com. startUrls takes direct Booking.com URLs — hotel pages or search-results pages — and is used instead of search whenever it's non-empty; the two are not combined.

Is a Booking.com account, login or API key required?

No. Property scraping and the contact-search backfill are both keyless — no Booking.com login, no Google API key, no third-party enrichment key. The only credential you need is your Apify token.

Does Booking.com Scraper With Property Contact Leads work with Claude, ChatGPT and AI agent frameworks?

Yes. It's callable as a standard HTTP endpoint through the Apify API, so LangChain, CrewAI, n8n or a hand-written tool definition can invoke it and receive typed JSON with no parsing step.

How does this compare to other Booking.com and contact-lead scrapers?

Checked on the Apify Store on 25 July 2026: meticulous_snail/booking-hotel-owner-leads targets the same niche — Booking.com hotel and property owner leads, listed free — but its Store page currently has no published README, so its extraction method and field set are not documented. Outside the Booking.com niche, alizarin_refrigerator-owner/company-contact-enricher enriches arbitrary company websites into B2B contacts but requires you to bring your own Apollo.io, Hunter.io, Anthropic and Firecrawl API keys for live data (a free demo mode is available). bovi/zoominfo-scraper reads public ZoomInfo company pages with a fully managed proxy and no user-supplied key, but returns ZoomInfo's own masked current emails/phones plus historical addresses, not a property's direct contact. This Actor's difference is that it sources leads directly from Booking.com property pages with no external API key of any kind — the SERP backfill is keyless.

Can I filter properties by price, stay dates or type before I scrape?

Yes. propertyType, starsCountFilter, minimumRating, minMaxPrice, and checkIn/checkOut with flexWindow are all applied on the Booking.com search itself, so you narrow the result set before any detail page — and any contact enrichment — happens.

🔗 Related scrapers

Scraper Name	What it extracts
Apartments.com Scraper — Floor Plan & Units	Apartment listings with floor plans and unit-level pricing and availability
Realtor.com Agent Scraper — Recent Sold Listings	Real estate agent profiles paired with their recent sold-listing history
Google Maps Scraper — By Radius / GeoJSON Territory	Local business listings within a custom radius or territory boundary
LinkedIn Company URL Mass Profile Finder — Executive Contacts	Company profiles enriched with executive contact leads
Instagram Phone and Email Lead Finder	Instagram profiles enriched with phone and email contact leads

Conclusion

Booking.com Scraper With Property Contact Leads turns a destination search or a list of Booking.com URLs into a property dataset with a contact lead attached to every row — on-page trader data first, best-effort keyless search backfill second, and null instead of a guess whenever neither turns up anything. The output stays the same 46-key shape whether you're pulling a lean lead list with contactsOnly or the full property record with rooms and facilities. Start it from the Apify Console or call it through the Apify API.

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Found a bug, or need a contact or property field that Booking.com publishes but this Actor doesn't return yet? Open an issue on the Actor's Issues tab — reports that include the property URL are the fastest to reproduce and fix.