Booking Reviews Scraper

Booking.com Reviews Scraper (Hotels & Attractions)

Extract verified customer reviews from Booking.com hotel stays and attractions, including ratings, guest profiles, stay details, languages, and timestamps.

Ideal for reputation monitoring, sentiment analysis, hospitality analytics, and travel intelligence.

✨ Features

🏨 Hotel Reviews Extraction

Verified guest reviews from hotel stays

Positive & negative feedback separation

Overall review score (numeric)

Stay details (room type, dates, number of nights)

Guest type (couple, solo traveler, family, friends)

Review approval & moderation status

🎡 Attraction Reviews Extraction

Reviews from attractions & experiences

Star ratings & numeric ratings

Travel companion type (friends, family, etc.)

Review language & posting date

User profile details (name, country)

🌍 Multilingual Support

Extract reviews in all available languages

Language code detection

Ready for translation & NLP pipelines

👤 Reviewer Metadata

Username (when available)

Country & country code

Anonymous / public reviewer flag

Helpful vote count (hotels)

🕒 Time & Freshness

UNIX timestamps

Human-readable UTC dates

Posted date references

🧩 Clean & Structured Output

Normalized JSON schema

Separate structures for Hotels and Attractions

Easy ingestion into databases, dashboards, or AI systems

INPUT - How to find Hotel ID from a url ?

go to any url like https://www.booking.com/hotel/fr/le-relais-du-marais.html

Open browser console with shortcut

Windows / Linux: Ctrl + Shift + J

macOS: Cmd + Option + J

paste following JS code in console

(() => {
  const link = document.querySelector(
    'link[rel="alternate"][href^="android-app://com.booking"]'
  );

  const match = link?.href.match(/\/hotel\/(\d+)/);
  return match ? Number(match[1]) : null;
})();

Copy the returned hotel id to provide as input to apify actor, here it's 230630

INPUT - How to attraction ID ?

You can directly provide full url like https://www.booking.com/attractions/fr/prjyfitkuhfz-one-day-admission-to-disneylandr-paris.html

or extract id directly from url; here it's prjyfitkuhfz

Both are supported for input

OUTPUT Samples

Hotel Stays Review

{
  "reviewScore": 10.0,
  "photos": null,
  "negativeHighlights": null,
  "isTranslatable": false,
  "positiveHighlights": null,
  "isApproved": true,
  "textDetails": {
    "title": null,
    "textTrivialFlag": 0,
    "__typename": "TextDetails",
    "positiveText": "I liked the view from the room we had and the bed was comfy",
    "lang": "en",
    "negativeText": "For the price i paid i think it would’ve been nice to have a bath also and a smart tv also instead of 2 separate beds put together it would be nice if it was just 1 double bed"
  },
  "editUrl": null,
  "bookingDetails": {
    "checkoutDate": "2025-12-18",
    "numNights": 3,
    "customerType": "COUPLES",
    "__typename": "BookingDetails",
    "roomId": 23063001,
    "checkinDate": "2025-12-15",
    "roomType": {
      "id": "23063001",
      "name": "Double or Twin Room",
      "__typename": "RoomTranslation"
    },
    "stayStatus": "stayed"
  },
  "__typename": "ReviewCard",
  "reviewedDate": 1766088315,
  "reviewUrl": "f374d16a03d521e6",
  "helpfulVotesCount": 0,
  "guestDetails": {
    "avatarUrl": null,
    "anonymous": false,
    "guestTypeTranslation": "Couple",
    "username": "Benjamin",
    "__typename": "GuestDetails",
    "showCountryFlag": true,
    "countryName": "United Kingdom",
    "countryCode": "gb",
    "avatarColor": null
  },
  "partnerReply": null,
  "utc_date": "2025-12-18 20:05:15"
}

Attraction Review

{
  "id": "RSD7rzAb5og5",
  "epochMs": 1766141741000,
  "content": "Magical experience 🤩",
  "travelPartnerTypes": [
    "friends"
  ],
  "rating": null,
  "numericRating": 5,
  "language": "en-gb",
  "isApproved": true,
  "providerName": null,
  "postedOn": "Posted December 19, 2025 on Booking.com",
  "supplierResponse": null,
  "user": {
    "name": "Catrena",
    "cc1": "gb",
    "avatar": null,
    "__typename": "AttractionsReviewUser"
  },
  "votes": null,
  "__typename": "AttractionsReview",
  "photos": [],
  "utc_date": "2025-12-19 10:55:41"
}

🚀 Use Cases

⭐ Online reputation monitoring

🧠 Sentiment analysis & NLP

🏨 Hotel & attraction benchmarking

📊 Customer satisfaction analytics

🧳 Travel & tourism market research

🤖 AI training datasets

🔎 Competitor review intelligence

🌍 Multilingual feedback analysis

💡 Notes

Reviews are extracted from public Booking.com pages

Only approved & visible reviews are returned

Some reviews may not include ratings or photos

Output structure differs slightly between Hotels and Attractions

Data reflects Booking.com availability at scraping time

🛟 SUPPORT

Share your runs with the developer team and create issues on error to help us improve actor quality.

You might discover edge case we didn't test yet

We stay available anytime