Booking.com Hotels Search Scraper

Build a search-results snapshot for a given destination and stay dates: one row per property, with pricing signals, review scores, and location details you can drop into sheets, reports, or internal tools.

Who it’s for

• Revenue & pricing teams comparing how listings rank and price for the same city and dates.
• Travel product & partnerships scouting supply and positioning for a market.
• Analysts who need repeatable exports instead of manual browsing.

What you can do with it

• Compare many hotels at once for the same check-in / check-out window.
• Track what appears in search for a destination ID and search type you already use elsewhere in your workflow.
• Cap how many properties you pull so runs stay predictable.

How it works (in plain terms)

You set where (destination ID + search type from your usual Booking workflow), when (check-in and check-out dates), and optional filters (guests, rooms, currency, language, price band, etc.). The tool pages through search results until it reaches your maximum number of hotels or there are no more results.

Input

Field	Required	What it means
Destination ID (dest_id)	Yes	The destination identifier (e.g. from a city search flow).
Search type (search_type)	Yes	How that destination is interpreted (e.g. city vs other types from the same flow).
Check-in (arrival_date)	Yes	Stay start date, yyyy-mm-dd.
Check-out (departure_date)	Yes	Stay end date, yyyy-mm-dd.
Maximum results (maxResults)	No	Upper limit on how many hotels to collect across pages (default 100).
Adults, rooms, children ages (adults, room_qty, children_age)	No	Party size and room count when you need them.
Price band (price_min, price_max)	No	Narrow listings by price when supported.
Sort & filters (sort_by, categories_filter)	No	When your workflow already knows valid values from Booking helper endpoints.
Locale & money (languagecode, currency_code, location)	No	Response language, display currency, or region hints.
Units (units, temperature_unit)	No	Metric vs imperial and temperature display.

Output

• One row per hotel in search order for each page, until your cap or the end of results.
• Each row includes property details you’d use in a market view: name, class, scores and review counts, coordinates, check-in/out times, price breakdown when present, photo URLs, and similar fields from the search payload.
• Every row includes when that record was written so stakeholders know which snapshot they’re looking at.

Sample output (one dataset row, trimmed)

{
	"hotel_id": 14696450,
	"accessibilityLabel": "Treebo Alfa Suites.\n3 out of 5 stars.\n7.4 Good 20 reviews.\n‎Western Suburbs‬ • ‎9 km from centre‬.\nLimited-time Deal.\nBreakfast included.\n Hotel room : Beds: 1 double or 2 singles.\nOriginal price 243 USD. Current price 86 USD..\nIncludes taxes and charges.\nFree cancellation.\nNo prepayment needed.",
	"property": {
		"blockIds": [
			"1469645005_429960406_1_1_0"
		],
		"countryCode": "in",
		"checkinDate": "2026-04-02",
		"position": 0,
		"mainPhotoId": 827171905,
		"reviewScore": 7.4,
		"photoUrls": [
			"https://cf.bstatic.com/xdata/images/hotel/square500/827171905.jpg?k=5bda188422b2136afadd8aab513898dbc51c25f07b624f5d65b55eb6a4b75252&o=",
			"https://cf.bstatic.com/xdata/images/hotel/square1024/827171905.jpg?k=5bda188422b2136afadd8aab513898dbc51c25f07b624f5d65b55eb6a4b75252&o=",
			"https://cf.bstatic.com/xdata/images/hotel/square2000/827171905.jpg?k=5bda188422b2136afadd8aab513898dbc51c25f07b624f5d65b55eb6a4b75252&o="
		],
		"propertyClass": 3,
		"checkout": {
			"untilTime": "11:00",
			"fromTime": "00:00"
		},
		"id": 14696450,
		"name": "Treebo Alfa Suites",
		"ufi": -2092174,
		"longitude": 72.8397413791853,
		"currency": "INR",
		"reviewScoreWord": "Good",
		"priceBreakdown": {
			"benefitBadges": [
				{
					"identifier": "Limited Time Deal",
					"variant": "constructive",
					"text": "Limited-time Deal",
					"explanation": "Limited-time Deal"
				}
			],
			"taxExceptions": [],
			"strikethroughPrice": {
				"currency": "USD",
				"value": 242.794835960267
			},
			"grossPrice": {
				"value": 86.4184557196514,
				"currency": "USD"
			}
		},
		"optOutFromGalleryChanges": 1,
		"rankingPosition": 0,
		"checkin": {
			"untilTime": "00:00",
			"fromTime": "13:00"
		},
		"accuratePropertyClass": 3,
		"wishlistName": "Mumbai",
		"reviewCount": 20,
		"isFirstPage": true,
		"checkoutDate": "2026-04-04",
		"qualityClass": 0,
		"latitude": 19.1487834697158
	},
	"scrapedAt": "2026-03-25T05:30:59.416Z"
}

Good to know

• Destination ID and search type must match the pair you get from your destination search step; mismatches lead to empty or invalid results.
• Availability and prices change frequently; treat exports as a point-in-time view.
• Use data in line with Booking.com’s terms and the laws that apply to you.