Booking.com Hotel & Price Scraper

Scrape hotel search results from Booking.com with structured data including prices, ratings, availability, location, and amenities. Export to JSON, CSV, or Excel.

Features

• Dual extraction engine: API interception (primary) + HTML fallback for maximum reliability
• Fast & Enriched modes: Quick search-only scraping (default) or deep detail page extraction with room options, full amenities, review breakdowns, and photos
• Anti-detection: Browser fingerprint spoofing, user-agent rotation, viewport randomization, stealth scripts
• Proxy support: Built-in residential proxy rotation with Apify Proxy (RESIDENTIAL group recommended)
• Smart pagination: Offset-based with configurable max results (up to 1,000 hotels)
• Advanced filters: Property type, minimum review score, children with ages, star rating, price range
• CAPTCHA detection: Automatically detects and backs off on CAPTCHA pages with retry logic
• Rich data output: 20+ fields per hotel including GPS coordinates, price breakdowns, availability, and optional detail data
• Production error handling: Clear failure reporting via Actor.fail() with descriptive status messages
• Graceful degradation: If a detail page fails (CAPTCHA, timeout), search data is still pushed

Use Cases

• Price monitoring: Track hotel pricing trends over time by scheduling daily or weekly runs. Compare rates across destinations and date ranges to identify pricing patterns.
• Competitive analysis: Benchmark your property against competitors in the same destination. Monitor review scores, pricing strategies, and availability across the market.
• Market research: Analyze hotel supply in a destination — count properties by star rating, average price per night, and review scores to assess market saturation.
• Travel deal alerts: Combine with Apify webhooks to get notified when prices drop below a threshold. Automate deal-finding across multiple destinations.
• Academic research: Collect structured hospitality data for tourism studies, pricing elasticity research, or geographic analysis of accommodation supply.

Fast vs. Enriched Mode

	Fast Mode (default)	Enriched Mode
Input	enrichData: false	enrichData: true
Speed	~50–100 hotels/min	~10–20 hotels/min
Data source	Search result cards only	Search cards + detail pages
Fields	14 base fields	14 base + room options, full amenities, review breakdown, photos, description
Cost	Lower (fewer requests)	Higher (1 extra page per hotel)
Best for	Price monitoring, market overview	Competitive analysis, full property comparison

Input Parameters

Parameter	Type	Required	Default	Description
destination	string	Yes	—	City, region, or property name
checkIn	string	Yes	—	Check-in date (YYYY-MM-DD)
checkOut	string	Yes	—	Check-out date (YYYY-MM-DD)
adults	integer	No	2	Number of adult guests
rooms	integer	No	1	Number of rooms
children	integer	No	0	Number of children (requires childrenAges)
childrenAges	array	No	[]	Ages of children (0–17), one per child
currency	string	No	USD	Currency code (USD, EUR, GBP, CZK, etc.)
language	string	No	en-us	Booking.com language code
maxResults	integer	No	100	Max hotels to return (1–1,000)
sortBy	string	No	price_low	Sort order: price_low, price_high, rating, review_score
minPrice	integer	No	—	Min price per night filter
maxPrice	integer	No	—	Max price per night filter
starRating	array	No	[]	Filter by star ratings, e.g. [3, 4, 5]
propertyType	array	No	[]	Filter by type: hotel, apartment, hostel, resort, villa, guesthouse
minReviewScore	number	No	—	Minimum review score (0–10)
enrichData	boolean	No	false	Enable detail page scraping for richer data
detailTimeout	integer	No	30	Detail page load timeout in seconds (5–120)
proxyConfig	object	No	Apify RESIDENTIAL	Proxy configuration

Example Input (Fast Mode)

{
    "destination": "Prague, Czech Republic",
    "checkIn": "2026-03-15",
    "checkOut": "2026-03-18",
    "adults": 2,
    "rooms": 1,
    "currency": "EUR",
    "maxResults": 50,
    "sortBy": "price_low",
    "starRating": [3, 4, 5]
}

Example Input (Enriched Mode)

{
    "destination": "Barcelona, Spain",
    "checkIn": "2026-04-10",
    "checkOut": "2026-04-14",
    "adults": 2,
    "children": 1,
    "childrenAges": [8],
    "currency": "EUR",
    "maxResults": 20,
    "enrichData": true,
    "propertyType": ["hotel", "resort"],
    "minReviewScore": 8.0
}

Output

Each hotel record contains structured data. The data_source field indicates whether the record was enriched with detail page data.

Fast Mode Output (data_source: "search")

{
    "hotel_id": "12345",
    "name": "Grand Hotel Prague",
    "url": "https://www.booking.com/hotel/cz/grand-prague.html",
    "price": {
        "per_night": 142.00,
        "total": 426.00,
        "currency": "EUR",
        "original_price": 178.00,
        "discount_percent": 20.0
    },
    "rating": {
        "score": 8.7,
        "review_count": 3421,
        "review_word": "Fabulous"
    },
    "location": {
        "address": "Kralodvorska 4, Prague 1",
        "city": "Prague",
        "country": "Czech Republic",
        "latitude": 50.0875,
        "longitude": 14.4280,
        "distance_from_center": "0.3 km from center"
    },
    "stars": 5,
    "property_type": "Hotel",
    "amenities": ["Free WiFi", "Spa", "Restaurant"],
    "images": ["https://cf.bstatic.com/xdata/images/hotel/max1024x768/123456.jpg"],
    "availability": {
        "rooms_left": 3,
        "free_cancellation": true,
        "no_prepayment": false,
        "deal_badge": "Genius discount"
    },
    "check_in": "2026-03-15",
    "check_out": "2026-03-18",
    "scraped_at": "2026-02-06T14:30:00Z",
    "data_source": "search",
    "detail": null
}

Enriched Mode Output (data_source: "search+detail")

When enrichData is enabled, the detail object is populated with data from the hotel's detail page:

{
    "hotel_id": "12345",
    "name": "Grand Hotel Prague",
    "url": "https://www.booking.com/hotel/cz/grand-prague.html",
    "data_source": "search+detail",
    "detail": {
        "description": "Located in the heart of Prague's Old Town, Grand Hotel Prague offers...",
        "all_amenities": ["Free WiFi", "Spa", "Restaurant", "Airport Shuttle", "24-hour Front Desk", "Bar", "Non-smoking Rooms", "Room Service", "Fitness Center"],
        "room_options": [
            {
                "name": "Superior Double Room",
                "max_occupancy": 2,
                "beds": "1 large double bed",
                "price_per_night": 142.00,
                "price_total": 426.00,
                "currency": "EUR",
                "meal_plan": "Breakfast included",
                "free_cancellation": true
            }
        ],
        "review_summary": {
            "overall_score": 8.7,
            "total_reviews": 3421,
            "staff": 9.1,
            "cleanliness": 9.0,
            "comfort": 8.8,
            "location": 9.5,
            "facilities": 8.6,
            "value_for_money": 8.2,
            "free_wifi": 9.3
        },
        "photo_urls": [
            "https://cf.bstatic.com/xdata/images/hotel/max1024x768/123456.jpg",
            "https://cf.bstatic.com/xdata/images/hotel/max1024x768/123457.jpg"
        ]
    }
}

Note: The enriched output includes all Fast Mode fields (price, rating, location, etc.) plus the detail object. If detail page extraction fails for a hotel, it falls back gracefully with data_source: "search" and detail: null.

How It Works

1. Input validation: All parameters are validated (date ranges, price filters, star ratings) before crawling begins. Invalid inputs produce clear error messages.
2. Search URL construction: Builds Booking.com search URL with all filters and pagination offset.
3. Phase A — API Interception: Captures Booking.com's internal GraphQL/REST API responses for structured data extraction.
4. Phase B — HTML Fallback: If API interception yields no results, falls back to CSS selector-based extraction from rendered HTML.
5. Pagination: Automatically paginates through results (25 per page) until maxResults is reached or no more results exist.
6. CAPTCHA handling: Detects Cloudflare challenges and reCAPTCHA. Backs off for 30 seconds on first detection, aborts after consecutive blocks.
7. Error reporting: Uses Actor.fail() with descriptive messages for zero results, CAPTCHA blocks, and invalid input. Partial results still succeed via Actor.exit().

Integration Examples

Scheduled Runs (Price Monitoring)

Set up a daily schedule in Apify Console to track prices over time:

1. Go to your Actor run → Schedules tab
2. Create a schedule with cron expression 0 8 * * * (daily at 8:00 AM)
3. Results accumulate in the default dataset — export via API or download

Webhook Notifications

Trigger actions when a run completes:

1. Go to Integrations → Webhooks
2. Set event to ACTOR.RUN.SUCCEEDED
3. Point to your endpoint (Slack webhook, email API, etc.)

API Access

Retrieve results programmatically after a run:

# Start a run
curl -X POST "https://api.apify.com/v2/acts/YOUR_ACTOR_ID/runs" \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"destination": "Paris", "checkIn": "2026-04-01", "checkOut": "2026-04-03"}'

# Get dataset items
curl "https://api.apify.com/v2/datasets/DATASET_ID/items?format=json" \
  -H "Authorization: Bearer YOUR_TOKEN"

Python Client

from apify_client import ApifyClient

client = ApifyClient("YOUR_TOKEN")
run = client.actor("YOUR_ACTOR_ID").call(run_input={
    "destination": "London",
    "checkIn": "2026-05-01",
    "checkOut": "2026-05-03",
    "maxResults": 200,
    "currency": "GBP",
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['name']}: {item['price']['per_night']} {item['price']['currency']}")

Proxy Recommendations

Booking.com has aggressive anti-bot protection. For best results:

• Use Apify Proxy with RESIDENTIAL group (default configuration)
• The scraper includes stealth measures (fingerprint spoofing, timing randomization) but residential proxies significantly improve success rates
• Expected extraction speed: 50–100 hotels/minute with residential proxies

FAQ

How fast is the scraper? With residential proxies, expect 50–100 hotels per minute. A typical 100-hotel run completes in 1–3 minutes. Larger runs (500–1,000 hotels) take 5–15 minutes depending on pagination and page load times.

What happens if Booking.com blocks the scraper? The scraper detects CAPTCHAs and anti-bot challenges automatically. On first detection, it backs off for 30 seconds and retries. After two consecutive blocks, it aborts with a clear error message. Using residential proxies minimizes blocking.

Why are some fields null? Not all fields are available for every property. Star ratings (stars) depend on Booking.com's HTML structure which varies across page renders. GPS coordinates require API interception to succeed. The scraper returns null rather than guessing.

Can I scrape specific hotel pages (not search results)? Yes! Set enrichData: true and the scraper will visit each hotel's detail page to extract room options, full amenities, review breakdowns by category, descriptions, and photo galleries. This is slower but gives you the richest data available.

How much does it cost to run? Costs depend on proxy usage, memory allocation, and run time. Typical estimates:

Results	Approximate Cost
100 hotels	~$0.10–0.25
500 hotels	~$0.50–1.25
1,000 hotels	~$1.00–2.50

What currencies are supported? USD, EUR, GBP, CZK, JPY, CNY, AUD, CAD, CHF, and INR. The currency input parameter controls which currency Booking.com uses for pricing.

Can I filter by property type or review score? Yes. Use propertyType to filter by hotel, apartment, hostel, resort, villa, or guesthouse. Use minReviewScore to only return properties scoring above your threshold (0–10 scale).

Limitations

• Maximum 1,000 results per search (Booking.com platform limit)
• Maximum stay duration: 30 nights
• CAPTCHA pages trigger backoff and may cause early termination after consecutive blocks
• Results depend on Booking.com's current page structure — the dual extraction engine mitigates breakage risk
• Star rating field may be null on some page renders