Booking.com Scraper Pro - Hotels, Reviews & Sentiment Analysis

Extract hotel data, guest reviews, and sentiment insights from Booking.com. Search any destination, get comprehensive hotel information including ratings, facilities, photos, and analyze review sentiment with AFINN-165 NLP.

✨ Features

Hotel Data

• Complete hotel details (name, description, property type)
• Location data (address, city, country, GPS coordinates, location score)
• Check-in/check-out times and cancellation policy
• Category scores (Staff, Cleanliness, Comfort, Location, Facilities, Value, WiFi)
• Popular facilities (WiFi, Parking, Pool, Spa, etc.)
• Photo gallery extraction (up to 20 photos with captions)
• Price information with multi-currency support (14 currencies)

Review Analysis

• Guest reviews via Booking.com's GraphQL API (overcomes 30-review limit)
• Guest details (name, country, traveler type)
• Positive and negative review text
• Room type and stay duration
• Hotel replies to guest reviews
• Review scores (0-10 scale)

Sentiment Analysis

• AFINN-165 NLP analysis on review text
• Sentiment score and label (positive/negative/neutral)
• Aggregated sentiment distribution per hotel
• Average sentiment across all reviews

🎯 Use Cases

Hotel Market Research

{
  "destination": "Munich, Germany",
  "maxHotels": 50,
  "includeReviews": true,
  "maxReviewsPerHotel": 100,
  "analyzeSentiment": true
}

Result: Comprehensive data on 50 Munich hotels with review sentiment analysis.

Competitor Analysis

{
  "destination": "Paris, France",
  "maxHotels": 20,
  "includeReviews": true,
  "maxReviewsPerHotel": 50
}

Result: Compare hotel ratings, facilities, and guest feedback for competitive benchmarking.

Guest Feedback Monitoring

{
  "destination": "Barcelona, Spain",
  "maxHotels": 10,
  "includeReviews": true,
  "maxReviewsPerHotel": 200,
  "analyzeSentiment": true
}

Result: Deep analysis of guest sentiment with positive/negative review breakdown.

Location-Based Analysis (Multi-Currency)

{
  "destination": "Tokyo, Japan",
  "checkIn": "2025-06-01",
  "checkOut": "2025-06-05",
  "adults": 2,
  "rooms": 1,
  "maxHotels": 30,
  "language": "en-us",
  "currency": "JPY"
}

Result: Hotel availability with prices in Japanese Yen for specific dates.

German Market Research

{
  "destination": "Berlin, Germany",
  "maxHotels": 40,
  "includeReviews": true,
  "maxReviewsPerHotel": 100,
  "language": "de",
  "currency": "EUR"
}

Result: Hotels with German descriptions and reviews, prices in Euros.

📊 Output Data

Sample Hotel Record

{
  "hotelId": "grand-hotel-munich",
  "name": "Grand Hotel Munich",
  "url": "https://www.booking.com/hotel/de/grand-hotel-munich.html",
  "description": "Located in the heart of Munich, this elegant hotel offers...",
  "propertyType": "Hotel",
  "address": "Maximilianstrasse 15, 80539 Munich, Germany",
  "city": "Munich",
  "country": "Germany",
  "postalCode": "80539",
  "latitude": 48.1351,
  "longitude": 11.5820,
  "neighborhood": "Altstadt-Lehel",
  "locationScore": 9.4,
  "reviewScore": 8.7,
  "reviewScoreWord": "Fabulous",
  "totalReviewCount": 2341,
  "categoryScores": [
    {"category": "Staff", "score": 9.2},
    {"category": "Facilities", "score": 8.5},
    {"category": "Cleanliness", "score": 9.0},
    {"category": "Comfort", "score": 8.8},
    {"category": "Value for money", "score": 8.1},
    {"category": "Location", "score": 9.4},
    {"category": "Free Wifi", "score": 8.7}
  ],
  "popularFacilities": ["Free WiFi", "Parking", "Restaurant", "Spa", "Fitness center"],
  "checkInTime": "3:00 PM",
  "checkOutTime": "11:00 AM",
  "cancellationPolicy": "Free cancellation before March 1, 2025",
  "mainPhoto": "https://cf.bstatic.com/xdata/images/hotel/max1280/...",
  "photos": [
    {"url": "https://cf.bstatic.com/xdata/images/hotel/max1280/...", "caption": "Hotel exterior"}
  ],
  "priceFrom": 189,
  "currency": "EUR",
  "sentiment": {
    "avgScore": 3.2,
    "avgComparative": 0.28,
    "distribution": {"positive": 42, "negative": 5, "neutral": 3}
  },
  "reviewCount": 50,
  "reviews": [
    {
      "guestName": "Marco",
      "guestCountry": "Italy",
      "guestCountryCode": "IT",
      "guestType": "Couple",
      "positiveText": "Excellent location, friendly staff, beautiful rooms",
      "negativeText": "Breakfast could be more varied",
      "title": "Amazing stay!",
      "score": 9.0,
      "roomType": "Deluxe Double Room",
      "numNights": 3,
      "checkinDate": "2025-01-12",
      "checkoutDate": "2025-01-15",
      "hotelReply": "Thank you for your wonderful review, Marco!",
      "sentimentScore": 4,
      "sentimentComparative": 0.35,
      "sentimentLabel": "positive",
      "reviewDate": "2025-01-15T10:30:00Z",
      "helpfulVotes": 5,
      "reviewUrl": "https://www.booking.com/reviews/..."
    }
  ],
  "scrapedAt": "2025-01-31T12:00:00Z"
}

Sentiment Analysis Fields

• sentimentScore: AFINN-165 score (negative = bad, positive = good)
• sentimentLabel: Classification (positive, negative, or neutral)
• avgComparative: Normalized score per word for comparison

🚀 Quick Start

Basic Destination Search

{
  "destination": "Berlin, Germany",
  "maxHotels": 20
}

With Reviews and Sentiment

{
  "destination": "London, UK",
  "maxHotels": 30,
  "includeReviews": true,
  "maxReviewsPerHotel": 50,
  "analyzeSentiment": true
}

Custom Date Range

{
  "destination": "Amsterdam, Netherlands",
  "checkIn": "2025-03-15",
  "checkOut": "2025-03-18",
  "adults": 2,
  "rooms": 1,
  "maxHotels": 25
}

⚙️ Input Parameters

Parameter	Type	Default	Description
destination	string	required	City, region, or country (e.g., "Munich, Germany")
checkIn	string	tomorrow	Check-in date (YYYY-MM-DD format)
checkOut	string	day after check-in	Check-out date (YYYY-MM-DD format)
adults	integer	2	Number of adults per room (1-10)
rooms	integer	1	Number of rooms needed (1-10)
maxHotels	integer	20	Maximum hotels to scrape (1-100)
includeReviews	boolean	true	Extract guest reviews
maxReviewsPerHotel	integer	50	Reviews per hotel (0-500)
analyzeSentiment	boolean	true	Enable AFINN-165 sentiment analysis
language	string	en-us	Content language (en-us, en-gb, de, fr, es, it, pt-pt, nl, pl, ru, ja, zh-cn, ko, ar)
currency	string	USD	Price currency (USD, EUR, GBP, JPY, CNY, AUD, CAD, CHF, INR, BRL, MXN, KRW, SGD, THB)

🔧 Technical Details

GraphQL Review Extraction

• Uses Booking.com's internal GraphQL API
• Overcomes the 30-review pagination limit on web pages
• Extracts hotel replies (partner responses)
• Captures review metadata (dates, room types, stay duration)

Anti-Bot Protection

• Playwright with Stealth plugins
• Residential proxies (required)
• Session management and cookie persistence
• Headed browser mode for reliability

Data Quality

• Comprehensive hotel details from multiple page sections
• Structured JSON output for easy integration
• ISO 8601 timestamps
• Null handling for missing fields

💡 Integration Examples

Zapier - Weekly Market Report

1. Schedule Booking.com Scraper weekly
2. Filter hotels by reviewScore > 8.0
3. Send top-rated hotels to Google Sheets
4. Create weekly PDF report via Zapier

n8n - Sentiment Alert Workflow

1. Run scraper daily for your target market
2. Filter reviews where sentimentLabel === "negative"
3. Send alerts to Slack for negative sentiment spikes
4. Store data in Airtable for trend analysis

Make.com - Competitor Tracking

1. Scrape competitor destinations monthly
2. Compare average review scores over time
3. Track facility changes and pricing
4. Update competitive analysis dashboard

⚠️ Requirements

Residential Proxies Required

Booking.com blocks datacenter IPs. Residential proxies are automatically used by this scraper for reliability.

Cost: Residential proxies add costs depending on data volume (see current proxy pricing in Apify Console).

Rate Limits

• Respectful scraping with delays between requests
• Session warmup for anti-bot compliance
• Automatic retry with error handling

📈 Output Formats

Export scraped data in multiple formats:

• JSON - For API integrations and databases
• CSV - For Excel/Google Sheets analysis
• Excel - For advanced data analysis
• HTML Table - For quick viewing

❓ FAQ

Do I need a Booking.com account?

No! This scraper extracts publicly available data from Booking.com search results and hotel pages. No account or API key required.

Can I scrape specific hotel URLs?

This scraper is optimized for destination-based search. Enter a city or region, and it will find and scrape hotels in that area.

How does the sentiment analysis work?

We use AFINN-165, a research-validated lexicon of ~2,500 words with sentiment scores. It analyzes the combined positive and negative review text to determine overall sentiment.

Can I get more than 30 reviews per hotel?

Yes! Unlike web scraping that's limited to 30 visible reviews, we use Booking.com's GraphQL API to fetch up to 500 reviews per hotel.

What data is included in hotel replies?

When hotel management responds to a review, we capture their response text in the hotelReply field. Great for analyzing customer service responsiveness.

How accurate are the review scores?

Review scores are extracted directly from Booking.com's data (0-10 scale). The reviewScore field shows the official Booking.com rating.

Can I filter by review score or price?

The scraper extracts all hotels matching your destination search. You can filter the output data by reviewScore, priceFrom, or categoryScores in your automation workflow.

Can I get data in different languages?

Yes! Set the language parameter to get hotel descriptions and reviews in your preferred language. Supported: English (US/UK), German, French, Spanish, Italian, Portuguese, Dutch, Polish, Russian, Japanese, Chinese, Korean, Arabic.

Can I get prices in my local currency?

Yes! Set the currency parameter to get prices in any of 14 supported currencies: USD, EUR, GBP, JPY, CNY, AUD, CAD, CHF, INR, BRL, MXN, KRW, SGD, THB.

How fast is the scraper?

~2-5 hotels per minute depending on review count. A 20-hotel search with 50 reviews each takes approximately 10-15 minutes.

What if I get blocked?

Residential proxies are automatically enabled. If issues persist, try reducing maxHotels or maxReviewsPerHotel to lower request volume.

🆘 Support

• Email: via Apify
• Response Time: < 24 hours
• Documentation: This README + inline help

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Legal Disclaimer

This actor is a general-purpose tool for analyzing publicly accessible web data. The user bears sole responsibility for ensuring their specific use complies with:

• Applicable laws (GDPR/DSGVO, copyright law)
• The target website's Terms of Service
• Apify's Terms of Service

The provider (webdatalabs) expressly disclaims liability for any unauthorized or unlawful use. By using this actor, the user agrees to indemnify the provider against any third-party claims arising from their use of the data.

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This tool is not affiliated with Booking.com. All trademarks belong to their respective owners.

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