Booking Scraper Pro

Extract hotel data, guest reviews, and sentiment insights from Booking.com — search any destination and get structured hotel details, ratings, category scores, prices, and up to 10 featured guest reviews with AFINN-165 sentiment analysis. A no-login Booking.com API alternative for market research, competitor analysis, and price intelligence.

What does Booking.com Scraper Pro do?

Booking.com Scraper Pro turns a destination search on Booking.com into clean, structured data. Give it a city, region, or country and it returns one flat record per hotel — name, address, GPS coordinates, review score, category scores, popular facilities, photos, starting price, and the property's featured guest reviews (the up-to-10 reviews Booking highlights on each hotel page), each with AFINN-165 sentiment for English content.

It extracts only publicly visible information — no login, no account, and no private user data.

Why scrape Booking.com?

• Hotel market research — benchmark hotels, scores, and prices across any destination.
• Competitor analysis — compare ratings, category scores, facilities, and guest sentiment.
• Brand & reputation monitoring — track what guests say and the sentiment behind it.
• Price intelligence — monitor starting prices across 14 currencies.

Running on the Apify platform gives you scheduling, a full REST API, one-click integrations (Google Sheets, Slack, Zapier, Make, n8n), automatic residential proxy rotation to reach Booking.com reliably, and run monitoring.

What data can Booking.com Scraper Pro extract?

Field	Type	Description
name	string	Hotel name
address / city / country	string	Location (country normalized from the hotel URL)
latitude / longitude	number	GPS coordinates
reviewScore	number	Overall Booking.com score (0–10)
totalReviewCount	integer	Total number of reviews on Booking.com
categoryScores	array	Sub-scores (Staff, Cleanliness, Comfort, Location, Facilities, Value, WiFi)
popularFacilities	array	Top facilities (WiFi, Parking, Pool, Spa, …)
priceFrom / currency	number / string	Starting price in the selected currency
photos	array	Photo gallery URLs with captions
reviews	array	Up to 10 featured guest reviews (see below)
sentiment	object	Aggregated sentiment distribution across the reviews

Each item in reviews contains: guestName, guestCountryCode, title, positiveText, negativeText, score (0–10), reviewDate, reviewUrl, and — for English content — sentimentScore, sentimentComparative, and sentimentLabel.

How to scrape Booking.com

1. Click Try for free / Start.
2. Enter a Destination (e.g. Munich, Germany, Paris, Tokyo, Japan).
3. Set Max Hotels and, optionally, check-in/check-out dates, adults, and rooms.
4. Choose your Language and Currency (set language to English for sentiment analysis).
5. Click Save & Start and watch results stream into the dataset.
6. Download the data as JSON, CSV, Excel, or HTML, or pull it via the Apify API.

How much does it cost to scrape Booking.com?

This Actor uses residential proxies (required — Booking.com blocks datacenter IPs), so cost scales with the number of hotels and reviews you collect. A typical hotel with its featured reviews and sentiment costs only a few cents of platform usage. To keep runs cheap: lower maxHotels, and set maxReviewsPerHotel to 0 if you only need hotel data. See the Actor's pricing on its Store page for exact per-result costs.

Input

See the Input tab for all options. Only Destination is required; everything else has sensible defaults.

Key fields:

• Destination (required) — city, region, or country to search.
• Max Hotels — how many hotels to scrape (default 10).
• Max Reviews Per Hotel — 0–10 featured reviews per hotel (default 10). Set 0 to skip reviews.
• Language — content language; set to en-us/en-gb for sentiment analysis (see FAQ).
• Currency — one of 14 supported currencies for prices.

Output

You can download the dataset in various formats such as JSON, HTML, CSV, or Excel. Each hotel is one flat record:

{
  "name": "Hotel Kraft",
  "url": "https://www.booking.com/hotel/de/kraft.html",
  "propertyType": "Hotel",
  "address": "Schillerstrasse 49, Ludwigsvorstadt, 80336 Munich, Germany",
  "city": "Munich",
  "country": "Germany",
  "latitude": 48.1345,
  "longitude": 11.5641,
  "reviewScore": 8.4,
  "totalReviewCount": 1558,
  "categoryScores": [
    { "category": "Staff", "score": 9.2 },
    { "category": "Location", "score": 9.4 }
  ],
  "popularFacilities": ["Free WiFi", "Bar", "Family rooms"],
  "priceFrom": 167,
  "currency": "EUR",
  "sentiment": { "avgScore": 3.1, "distribution": { "positive": 9, "negative": 0, "neutral": 1 } },
  "reviewCount": 10,
  "reviews": [
    {
      "guestName": "Kim",
      "guestCountryCode": "us",
      "title": "We had an amazing time in Munich.",
      "positiveText": "Loved how quiet and clean it was. Location was also great",
      "negativeText": null,
      "score": 10,
      "sentimentScore": 8,
      "sentimentLabel": "positive",
      "reviewDate": "2025-12-13T14:05:25.000Z",
      "reviewUrl": "https://www.booking.com/reviews/0a3ac1ae90066ff8"
    }
  ],
  "scrapedAt": "2026-07-01T12:00:00Z"
}

Tips & advanced options

• Lower cost / faster runs: reduce maxHotels, or set maxReviewsPerHotel to 0 for hotel data only.
• Sentiment analysis: AFINN-165 is an English lexicon, so keep language at en-us or en-gb. For other languages the review text is still returned; the sentiment fields are skipped rather than mislabeled.
• Reliability: the Actor automatically retries on a fresh IP if Booking.com serves an anti-bot challenge, and fails the run (instead of returning an empty dataset) if no hotels could be scraped.
• Automate it: schedule daily/weekly runs and pipe results to Google Sheets, Slack, or a webhook via the Apify Integrations tab.

FAQ

Do I need a Booking.com account?

No. The Actor extracts publicly available data from Booking.com search results and hotel pages — no account or API key required.

How many reviews do I get per hotel?

Up to 10 featured reviews per hotel — the reviews Booking.com highlights on each property page — each with the full positive/negative text, score, date, and sentiment. This is the review set Booking exposes reliably; the Actor reads it directly from the page.

How does the sentiment analysis work?

It uses AFINN-165, a research-validated English lexicon (~2,500 scored words), on the combined positive/negative review text. Because it is English-only, sentiment is calculated when language is en-us/en-gb and skipped (fields set to null) for other languages to avoid mislabeling.

Can I get data in different languages and currencies?

Yes. Set language for hotel descriptions and review text (14 languages) and currency for prices (14 currencies: USD, EUR, GBP, JPY, CNY, AUD, CAD, CHF, INR, BRL, MXN, KRW, SGD, THB).

What if I get blocked?

Residential proxies are enabled automatically and the Actor retries on fresh IPs. If issues persist, reduce maxHotels to lower request volume, or re-run.

Integrations

• Zapier / Make / n8n — schedule runs and push top-rated hotels or negative-sentiment reviews to Sheets, Slack, or Airtable.
• API — see the API tab for programmatic access and to run the Actor from your own code.
• Feedback — found an issue or need a field added? Use the Issues tab.

Disclaimer

Our Actors are ethical and do not extract any private user data, such as email addresses, gender, or location. They only extract what the user has chosen to share publicly. We therefore believe that our Actors, when used for ethical purposes by Apify users, are safe. However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers.

You are responsible for ensuring your use complies with applicable laws (including GDPR/DSGVO and copyright), Booking.com's Terms of Service, and Apify's Terms of Service. This tool is not affiliated with Booking.com. All trademarks belong to their respective owners.

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Custom solutions & enterprise

Need a custom data feed, modified output format, or enterprise integration? Contact: Furkanc58@gmail.com

• Daily/weekly data feeds (Snowflake, S3, BigQuery, Google Sheets)
• Custom scrapers for platforms not yet covered
• White-label solutions for agencies
• Priority support and SLAs

Response within 24–48 hours.

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