🏨 Booking.com Reviews Scraper [From 💰$0.50/1K]

What does Booking.com Reviews Scraper do?

Booking.com Reviews Scraper is a hospitality sentiment extraction tool that scrapes verified hotel guest reviews directly from Booking.com—capturing separated positive (positive_text / liked_text) and negative (negative_text / disliked_text) comments, 1–10 review scores, room types booked, nights stayed, traveler categories, guest nationalities, and hotel management replies.

Whether you are benchmarking hotel guest satisfaction across competing properties, auditing housekeeping or check-in complaints across a hospitality portfolio, or training an AI sentiment model on structured pros-and-cons review pairs, this scraper delivers clean, analysis-ready records in seconds.

🛡️ Zero Proxy Configuration Required: Anti-blocking and regional routing are handled automatically out of the box — just paste your target URLs and click Start.

What data can you extract with Booking.com Reviews Scraper?

⭐ Review Score & Headline — numeric rating (1.0–10.0 scale), review title, unique review id, and review date
👍 Positive Guest Feedback (positive_text / liked_text) — structured praise highlighting what the guest enjoyed most about their stay
👎 Negative Guest Feedback (negative_text / disliked_text) — separated complaints, friction points, and improvement requests
🛏️ Room & Stay Metadata — exact room_type booked (e.g., Deluxe King Room), nights_stayed, and source hotel_url
🌍 Guest & Traveler Profile — reviewer_name, reviewer_country, and traveler_type (Couple, Family, Solo traveler, Group, Business)
📣 Property Management Reply — official owner_response text posted by the hotel team

Why scrape hotel guest reviews from Booking.com?

💪 Pre-split Pros & Cons for instant NLP and AI analysis — unlike single-paragraph review sites, Booking.com separates liked_text and disliked_text, making it effortless to isolate operational complaints without complex prompt engineering
🕵️ Segment guest satisfaction by room type and traveler group — discover whether negative scores come from specific room categories, business travelers, or international guests
✨ Benchmark competing hotels in your market — compare guest sentiment, response rates, and recurring complaints across rival properties in the same neighborhood
👍 Zero proxy or account setup — built-in anti-blocking and proxy rotation work automatically out of the box
📩 Automate reputation alerts — connect recurring runs to Slack, Google Sheets, Make, or n8n to flag low-score reviews the day they are posted

How do I use Booking.com Reviews Scraper?

Booking.com Reviews Scraper is designed for fast, zero-configuration operation in Apify Console:

1. Click Try for free on the Actor page to open Apify Console.
2. Paste one or more Booking.com property URLs into Start URLs (for example, https://www.booking.com/hotel/us/the-plaza.html).
3. Set Max Results (maxItems) to control how many hotel reviews to collect.
4. Click Start to launch the review extraction run.
5. Download your hotel review dataset from the Dataset tab in Excel, CSV, JSON, or HTML table format.

Input

Booking.com Reviews Scraper uses a clean 2-parameter JSON configuration. Click on the Input tab for the interactive form.

{
  "startUrls": [
    {
      "url": "https://www.booking.com/hotel/us/the-plaza.html"
    }
  ],
  "maxItems": 40
}

🏨 startUrls — array of Booking.com hotel property URLs (https://www.booking.com/hotel/{country}/{property-slug}.html)
🔢 maxItems — maximum number of hotel reviews to collect per run (default: 40; Free plan runs collect up to 40 reviews per run, while paid Apify plans support unlimited review extraction)

Output sample

Results are streamed in real time to your default Apify Dataset. Each record represents a verified Booking.com guest review with separated positive and negative feedback:

[
  {
    "id": "rev_88412093",
    "hotel_url": "https://www.booking.com/hotel/us/the-plaza.html",
    "rating": 9.0,
    "title": "Unforgettable stay right on Central Park",
    "positive_text": "Location was unbeatable, beds were super comfortable, and concierge staff went above and beyond.",
    "negative_text": "Breakfast room was quite busy around 9 AM.",
    "reviewer_name": "Charlotte",
    "reviewer_country": "United Kingdom",
    "traveler_type": "Couple",
    "room_type": "Deluxe King Room",
    "nights_stayed": 4,
    "date": "2026-09-18",
    "owner_response": "Thank you for choosing The Plaza, Charlotte! We look forward to welcoming you back."
  }
]

How much does it cost to scrape Booking.com reviews?

Booking.com Reviews Scraper uses Pay-Per-Event (PPE) pricing (apify-default-dataset-item) with a $0.00 startup fee—you only pay for verified guest reviews delivered to your dataset:

🆓 Free plan — $0.005 per review ($5.00 / 1,000 reviews, up to 40 reviews/run)
🥉 Starter (Bronze) plan — $0.0011 per review ($1.10 / 1,000 reviews)
🥈 Scale (Silver) plan — $0.0008 per review ($0.80 / 1,000 reviews)
🥇 Business+ (Gold) plan — $0.0005 per review ($0.50 / 1,000 reviews)

With the monthly free credit on the Apify Free plan, you can extract up to 1,000 Booking.com guest reviews per month for free.

💡 Predictable, All-Inclusive Pay-Per-Event Pricing: There is a $0.00 run start fee and no separate proxy configuration required. You only pay the flat per-result rate above for data successfully delivered to your dataset — works out of the box on both Free and Paid Apify plans.

How many results can you scrape with Booking.com Reviews Scraper?

Booking.com Reviews Scraper can extract thousands of guest reviews per hotel property on paid Apify plans (up to 40 reviews per run on the Free plan). Keep these practical details in mind when planning your extraction:

• Direct hotel property URLs (/hotel/{cc}/{slug}.html) — pass individual Booking.com hotel pages in startUrls to extract their verified guest review feed.
• Score-only reviews — if a guest submits a numerical rating on Booking.com without writing optional liked_text or disliked_text comments, the text fields will return empty/null while preserving the rating, room_type, nights_stayed, and traveler_type.
• Multi-property hospitality portfolios — pass dozens of hotel URLs in startUrls to consolidate reviews across an entire hotel chain or city market in one run.

Want to scrape Airbnb, Trustpilot, Google Maps, or Zillow?

Combine Booking.com Reviews Scraper with our other published hospitality, review, and local business Actors:

🏡 Airbnb Reviews Scraper — extract verified Airbnb guest reviews, star ratings, translated review text, and host replies (From $0.50 / 1K)
⭐ Trustpilot Reviews Scraper — extract company customer reviews, star ratings, verification status, and business replies (From $0.50 / 1K)
📍 Google Maps Places Scraper — extract local brokerages, property managers, commercial businesses, phones, websites, and ratings (From $0.55 / 1K)
🏡 Zillow Search Scraper — extract US homes for sale, rentals, sold prices, Zestimates, beds/baths, and coordinates (From $0.90 / 1K)

Integrations and Booking.com Reviews Scraper

Booking.com Reviews Scraper integrates seamlessly with your hospitality BI dashboards, spreadsheets, and automation workflows through Apify integrations:

• No-Code Automation — trigger negative-review Slack/email alerts and AI reply drafts via Make, Zapier, or n8n.
• Spreadsheets & Warehouses — sync hotel reviews directly into Google Sheets, Airtable, BigQuery, Snowflake, or Power BI.
• Webhooks — fire automated webhook payloads to your reputation management platform as soon as a run completes.

Using Booking.com Reviews Scraper with the Apify API

You can launch review extraction runs and fetch dataset items programmatically using the official apify-client libraries for Node.js and Python, or connect this Actor directly to AI hospitality analysts via the Apify MCP Server (https://mcp.apify.com).

Check the API tab for ready-to-copy Node.js, Python, and cURL examples.

Frequently asked questions about Booking.com Reviews Scraper

🏨 Can I scrape hotels from any country on Booking.com?
Yes. Pass any international Booking.com hotel URL (/hotel/gb/..., /hotel/fr/..., /hotel/jp/..., /hotel/ae/..., /hotel/us/...) and the scraper will extract the property's guest reviews automatically.

👍 Why are liked_text and disliked_text in separate fields?
Booking.com prompts guests to enter positive and negative feedback in two separate boxes. Keeping liked_text and disliked_text distinct in the JSON output lets you run targeted sentiment analysis on guest complaints without positive praise diluting the signal.

🛡️ Do I need to configure proxies or a Booking.com account?
No — everything works out of the box with zero setup. Regional routing, session management, and anti-blocking are handled automatically so you do not need to configure custom proxy settings.

Is it legal to scrape public hotel reviews from Booking.com?

Our scrapers are ethical and only extract publicly visible guest review scores, review comments, and property management replies displayed on public Booking.com hotel pages. They do not extract private booking reservations or personal account data. For more details on the legality of web scraping, read Apify's guide on is web scraping legal.

Your feedback

We keep this Actor under active maintenance. If a run finishes successfully but returns fewer results than you expected, hangs, or errors — please open an Issue before posting a public review so we can diagnose and fix it for you.

🛠️ How to report — Use the Actor’s Issues tab in Apify Console. Include the run ID, your input JSON, and what you expected vs. what you got.
⏱️ Response time — We aim to reply within 24 hours on business days.
⭐ Reviews — Happy with the results? A short positive review helps other users find a reliable scraper. Ran into a problem? Open an Issue first — we’ll work with you to resolve it before you leave a rating.