Booking.com Review Scraper

Scrape guest reviews from any Booking.com hotel page and run sentiment analysis on guest feedback at scale. This Booking.com review scraper extracts ratings, reviewer details, stay dates, and full review text from thousands of hotel listings — perfect for hospitality analytics and reputation management.

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Use Cases

• Sentiment Analysis — Analyze guest feedback to identify strengths, weaknesses, and recurring themes across reviews.
• Competitor Benchmarking — Compare your hotel's review profile against competitors and track rating trends.
• Guest Experience Research — Understand what guests truly value by mining detailed review data from Booking.com.
• Market Research — Gather hospitality market intelligence across regions, chains, and price segments.
• Review Monitoring — Set up recurring runs to track new reviews and respond to guest concerns quickly.
• Reputation Auditing — Generate comprehensive reputation reports for any Booking.com-listed property.

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How It Works

1. Provide a single Booking.com hotel review URL.
2. The actor navigates paginated review pages using headless Chrome.
3. Reviews are extracted — text, rating, date, reviewer info, room type, and trip details.
4. Pagination continues up to the maxPages limit (default 10).
5. Structured review data is saved to a dataset you can export as JSON, CSV, or Excel.

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Input

Field	Type	Default	Description
startUrl	string	required	Full Booking.com hotel review URL (e.g. https://www.booking.com/reviews/gb/hotel/example.html)
maxPages	integer	10	Maximum number of review pages to scrape (each page typically contains ~10 reviews)
concurrency	integer	5	Number of concurrent page loads to speed up scraping
useSystemChrome	boolean	false	Use system-installed Chrome instead of bundled Chromium
headless	boolean	false	Run browser in headless mode (no visible window)
proxy	object	—	Proxy configuration for rotation and geo-targeting

Proxy Configuration

{
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "US"
  }
}

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Output

Each item in the dataset represents one guest review:

Field	Type	Description
reviewId	string	Unique Booking.com review identifier
reviewText	string	Full review text written by the guest
rating	number	Overall review score (1–10 scale)
title	string	Review headline/title
date	string	Date the review was posted
reviewerName	string	Guest name (as displayed on Booking.com)
reviewerCountry	string	Guest's home country
roomType	string	Type of room stayed in
stayType	string	Travel type — solo, couple, family, business, group
nights	string	Number of nights stayed
sourceUrl	string	URL of the hotel review page

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Example

Input

{
  "startUrl": "https://www.booking.com/reviews/gb/hotel/example.html",
  "maxPages": 5,
  "concurrency": 3,
  "headless": true
}

Output (excerpt)

[
  {
    "reviewId": "review_12345",
    "reviewText": "Excellent location right in the city center. The staff were incredibly friendly and helpful. Room was clean and well-maintained. Breakfast selection was good but could be improved.",
    "rating": 9.0,
    "title": "Perfect city center hotel",
    "date": "2026-08-15",
    "reviewerName": "John D.",
    "reviewerCountry": "United Kingdom",
    "roomType": "Deluxe Double Room",
    "stayType": "Couple",
    "nights": "3 nights",
    "sourceUrl": "https://www.booking.com/reviews/gb/hotel/example.html"
  },
  {
    "reviewId": "review_12346",
    "reviewText": "Good value for money but the walls are thin. Could hear neighbors. Breakfast was average.",
    "rating": 6.5,
    "title": "Decent stay, noise issues",
    "date": "2026-08-10",
    "reviewerName": "Maria S.",
    "reviewerCountry": "Germany",
    "roomType": "Standard Twin Room",
    "stayType": "Solo",
    "nights": "2 nights",
    "sourceUrl": "https://www.booking.com/reviews/gb/hotel/example.html"
  }
]

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Integrations

This actor pairs well with other Apify tools for end-to-end hospitality analytics workflows:

• FAST Booking.com Hotel Scraper — Scrape hotel details, pricing, and availability alongside reviews.
• Booking.com Hotel Details Scraper — Extract hotel metadata (amenities, address, photos) to enrich review data.
• Google Sheets Actor — Export review datasets directly to Google Sheets for team sharing.
• Sentiment Analysis Actors — Feed extracted review text into NLP actors for automated sentiment scoring.
• Slack / Email Notifiers — Set up alerts when new negative reviews are detected.

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FAQ

How many reviews can I scrape per run? Each page contains roughly 10 reviews. With the default maxPages of 10, expect around 100 reviews per run. Increase maxPages for larger extractions.

Does this work for hotels outside the UK? Yes. The actor handles Booking.com review pages across all countries and languages.

Can I scrape reviews from multiple hotels? Provide one hotel URL per run. For multiple hotels, call the actor in a loop or use Apify's actor chaining feature.

Is the data publicly available? Yes. This actor only extracts review data that is publicly visible on Booking.com hotel pages.

What proxy should I use? Residential proxies are recommended for large-scale scraping to avoid rate limiting. Use Apify Proxy with the RESIDENTIAL group.

Can I run this on a schedule? Yes. Use Apify Scheduler to run the actor daily or weekly and monitor review trends over time.

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SEO Keywords

booking.com review scraper, hotel reviews data, guest review extraction, sentiment analysis hotel, booking.com api alternative, hotel review data, guest feedback extraction, hospitality analytics, hotel sentiment tracking, review monitoring, competitor hotel reviews, booking.com data, hotel reputation management, guest experience data, travel review scraping, hotel review extractor, booking.com reviews api, hotel review sentiment, hospitality data mining, booking hotel reviews

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For AI Agents

This actor is designed for integration into AI-powered hospitality analysis pipelines.

Input: Single JSON object with startUrl (Booking.com hotel review page URL), optional maxPages, concurrency, headless, and proxy.

Output: JSON dataset of structured review objects. Each review includes rating, text, reviewer metadata, stay details, and source URL.

Chaining: Pipe output into sentiment analysis actors (VADER, BERT-based) for automated scoring. Combine with hotel detail scrapers for enriched datasets.

Scheduling: Use Apify Scheduler for weekly review monitoring. Store datasets over time for trend analysis.

Rate limits: Each run produces up to maxPages × ~10 results. Pricing is $0.0025 per result.

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Legal Disclaimer

This actor extracts publicly available review data from Booking.com hotel pages. It does not bypass authentication, access private data, or circumvent access controls. Users are responsible for ensuring their use complies with Booking.com's Terms of Service and applicable data protection regulations (GDPR, CCPA). Use extracted data only for legitimate business intelligence, analytics, and research purposes. The developer assumes no liability for misuse of scraped data.