Booking.com Occupancy Scraper — Room Rates & Calendar

Disclaimer: Unofficial tool for publicly accessible Booking.com hotel calendars and lead room rates. Booking.com is a trademark of Booking Holdings Inc. Not affiliated with, sponsored by, or endorsed by Booking.com. For informational, research, revenue-management, and market-analysis use only. Respect applicable terms of use and law.

Booking.com scraper for the public availability calendar and lead room rates — a practical Booking.com occupancy scraper, Booking.com calendar scraper, and Booking.com API alternative. Paste hotel URLs or IDs, a search URL, or a city. Export occupancy % (30 / 60 / 90 / 365 days), sold-out nights, cheapest nightly rates, min-stay, optional lead room inventory, and booking-pace deltas as a JSON dataset. Call from Python, Node.js, cURL, or Apify MCP / AI assistants.

Built for hotel revenue managers, comp-set tracking, OTA rate shopping, and demand research. No Booking.com account required. This is not a dump of search cards for a single stay.

Booking.com occupancy (hotel calendars)	Airbnb occupancy (STR calendars)	Idealista (long-term ES/IT/PT)
Booking.com Occupancy Scraper ◄── you are here	Airbnb Occupancy Scraper	Idealista Scraper

When to use this Actor

• You need a Booking.com occupancy monitor / Booking.com room rates scraper that returns structured JSON
• You already know hotel URLs (portfolio / comp set) or have a city / search URL
• You want sold-out nights, occupancy 30/90, and a forward rate calendar — not a generic hotel-card dump
• You want to scrape Booking.com calendars with Python, Node.js, or MCP and export a dataset

When not to use this Actor

• Historical occupancy — Booking.com only exposes a forward calendar (chunked; this Actor reads up to 366 days)
• Every room type × every date — the public calendar is the cheapest available rate and property sold-out flag. Lead room names come from a reference stay, not a 90-day room-type matrix
• Guest PII, reservations, or extranet — public calendar and search fields only
• Short-term rental occupancy on Airbnb — use Airbnb Occupancy Scraper
• Whole-market 10k-hotel crawls in one run — cap with maxHotels and schedule by neighborhood

Key Features

• Hotel URLs, slugs, or IDs — /hotel/fr/royal-saint-michel.html, gb/gardencourthotel, or numeric IDs
• Search / location discovery — paste a Booking.com search URL or type Paris, France to take search pages, then pull calendars
• Forward calendar — 1–366 days of available / sold-out, min stay, cheapest nightly rate
• Occupancy windows — 30 / 60 / 90 / 365-day sold-out rates plus horizon totals
• Lead rooms — room name, occupancy, meal plan, stay price, and sold-out for a reference check-in
• Booking pace — schedule the Actor with monitor: true and a stable monitorStoreName (named Key-Value store). First run is the baseline; later runs emit newly sold-out / newly opened nights
• Honest metrics — unavailableRate and occupancyEstimate are the same calendar signal (property sold-out, not remaining rooms of each type)
• HTTP JSON path — Chrome TLS impersonation + public GraphQL; no Playwright
• Apify Proxy ready — datacenter is usually enough; residential if challenged
• MCP / AI ready — call from assistants via Apify MCP

Use Cases

Use case	What you get
Comp-set occupancy	Forward sold-out % for rival hotels in your market
Booking pace	Nights that flipped sold-out (or opened) since the last scheduled run
Rate calendar	Cheapest public nightly rate per date, plus ADR / min / max
Lead room snapshot	Named room type and stay price for a reference occupancy
Demand screening	30/90-day occupancy windows + stars / review score
Market snapshot	First pages of a city search, then calendars for each hotel

Quick Start

Known hotels:

{
  "hotels": ["https://www.booking.com/hotel/fr/royal-saint-michel.html"],
  "lookAheadDays": 90,
  "includeCalendar": true,
  "includeRooms": true,
  "currency": "USD"
}

City search (hotels, then calendars):

{
  "location": "Paris, France",
  "lookAheadDays": 90,
  "maxHotels": 20,
  "includeHotelDetails": true
}

Scheduled booking-pace monitor:

{
  "hotels": ["gb/gardencourthotel"],
  "lookAheadDays": 90,
  "monitor": true,
  "monitorStoreName": "booking-occupancy-monitor",
  "includeCalendar": false
}

Input Parameters

Parameter	Type	Default	Description
hotels	Array	—	Hotel URLs, cc/pagename slugs, or numeric IDs
startUrls	Array	—	Hotel URLs and/or Booking.com search URLs
location	String	—	City / area used to resolve a destination
lookAheadDays	Integer	90	Forward nights (1–366)
maxHotels	Integer	25	Cap (0 = unlimited)
checkInDate / checkOutDate	String	~+14d / +1 night	Reference stay for lead rooms
adults / children / rooms	Integer	2 / 0 / 1	Occupancy sent to Booking.com
includeHotelDetails	Boolean	true	Name, city, stars, reviews
includeRooms	Boolean	true	Lead room for the reference stay
includeCalendar	Boolean	true	Per-day calendar[] array
monitor	Boolean	false	Booking-pace vs previous run (needs named store)
monitorStoreName	String	booking-occupancy-monitor	Named KV store for pace snapshots
currency	String	USD	ISO code
proxyConfiguration	Object	Apify datacenter	Residential if challenged

Output Format

Each dataset item is one hotel (or an error row if that hotel failed).

Field	Type	Description
hotelId	Integer	Booking.com hotel id
hotelUrl	String	Canonical hotel URL
name / city / countryCode	String	Public listing fields
starRating / reviewScore / reviewsCount	Number	Stars and guest reviews
unavailableRate	Number	Sold-out ÷ counted nights in the 365-day window (same as occupancy365d)
occupancyEstimate	Number	Same value; labeled as an estimate
occupancy30d / occupancy90d / occupancy365d	Number	Windowed sold-out rates
soldOutDays / availableDays	Integer	Horizon counts
firstAvailableDate	String	Next open night
adr / minPrice / maxPrice	Number	From priced available nights
leadRoomName / leadPrice	String / Number	Reference-stay lead unit
rooms	Array	Lead blocks (id, name, occupancy, meal plan, price)
calendar	Array	Per-day available / soldOut / minNights / price
bookingPace	Object	When monitor is on
scrapedAt	String	UTC timestamp

Example (truncated):

{
  "type": "hotel",
  "source": "booking.com",
  "hotelId": 58439,
  "name": "Hôtel Royal Saint Michel",
  "city": "Paris",
  "countryCode": "fr",
  "unavailableRate": 0.1475,
  "occupancy30d": 0.2,
  "occupancy90d": 0.1475,
  "soldOutDays": 9,
  "firstAvailableDate": "2026-08-25",
  "adr": 612.4,
  "leadRoomName": "Double Room",
  "currency": "USD",
  "hotelUrl": "https://www.booking.com/hotel/fr/royal-saint-michel.html"
}

Integration examples

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('crawloop/booking-com-occupancy-scraper').call({
  hotels: ['https://www.booking.com/hotel/fr/royal-saint-michel.html'],
  lookAheadDays: 90,
  currency: 'USD',
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items[0]?.unavailableRate, items[0]?.occupancy90d);

Python

from apify_client import ApifyClient

client = ApifyClient(token)
run = client.actor("crawloop/booking-com-occupancy-scraper").call(
    run_input={
        "hotels": ["https://www.booking.com/hotel/fr/royal-saint-michel.html"],
        "lookAheadDays": 90,
        "currency": "USD",
    }
)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item.get("hotelId"), item.get("unavailableRate"), item.get("hotelUrl"))

cURL

curl "https://api.apify.com/v2/acts/crawloop~booking-com-occupancy-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"hotels":["https://www.booking.com/hotel/fr/royal-saint-michel.html"],"lookAheadDays":90}'

MCP and AI assistants

Use this Actor from AI tools via Apify MCP. Connect your Apify account, then call crawloop/booking-com-occupancy-scraper.

Example prompts:

• "Run Booking.com Occupancy Scraper for https://www.booking.com/hotel/fr/royal-saint-michel.html with 90 look-ahead days and return unavailableRate, occupancy30d, occupancy90d, soldOutDays"
• "Scrape Booking.com occupancy for hotels in Paris, France, max 15, and summarize 90-day sold-out rates as JSON"
• "Monitor these Booking.com hotel URLs weekly for booking pace, then run Airbnb Occupancy Scraper for STR comps in the same city"

FAQ

Is this an official Booking.com API?
No. It reads the same public GraphQL calendar and search the website uses and returns structured dataset rows — a practical Booking.com API alternative for pipelines.

Booking.com occupancy scraper vs a hotel listings scraper?
This Actor is calendar-first: occupancy %, sold-out nights, nightly rates, and booking pace. It is not a dump of search cards for one check-in.

Do I need a Booking.com login?
No — public calendars and search fields only.

Can I scrape Booking.com occupancy with Python or Node.js?
Yes — use the Apify client examples above, or call the Actor from cURL / Apify MCP.

Is occupancy the same as occupied rooms?
No. Treat occupancyEstimate as property sold-out share for the requested occupancy. Remaining rooms of a specific type are not on the public calendar. When the calendar is longer than 365 days, unavailableRate matches occupancy365d.

Can I get every room type for 90 days?
Not from this public calendar. Use includeRooms for the lead unit on a reference stay, and calendar for property-level sold-out / cheapest rate.

Can I get historical occupancy?
No. The calendar is forward-only. Schedule the Actor to build your own history.

How many hotels per search?
A location search pages in steps of 25. Cap with maxHotels. Pass explicit hotels for a known portfolio.

Related Actors

Actor	Focus
Booking.com Occupancy Scraper ◄── you are here	Hotel calendars, room rates, occupancy %, booking pace
Airbnb Occupancy Scraper	STR calendars, occupancy %, booking pace
Idealista Scraper	Long-term rental / sale listings (ES/IT/PT)

Suite next step: after hotel occupancy snapshots, run Airbnb Occupancy Scraper for short-term rental calendars in the same destination.