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Agoda Reviews Scraper

Pricing

from $0.85 / 1,000 reviews

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Agoda Reviews Scraper

Agoda Reviews Scraper

🏨 Scrape guest reviews from Agoda hotel listings β€” plus mirrored Booking.com reviews from the same listing, normalized into one schema. Includes ratings, review text, room/stay details, and reviewer trust signals. Exportable as JSON, CSV, Excel, or HTML for structured analysis.

Pricing

from $0.85 / 1,000 reviews

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0.0

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Developer

Frederic

Frederic

Maintained by Community

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2

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1

Monthly active users

3 days ago

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🌐 Agoda Reviews Scraper

Extract guest reviews from any Agoda hotel listing - and the mirrored Booking.com reviews shown on the same page - normalized into one clean, pay-per-result dataset πŸš€

Just enter one (or many) Agoda hotel URLs and click "Save & Start".

Great for:

  • 🧬 Market research & trend analysis across two review pools at once
  • πŸ“ˆ Competitor monitoring (your hotel, or theirs)
  • 🀝 Reviewer trust analysis - expert reviewers, review history, and vote counts
  • πŸ€– Feeding clean, structured review data into apps or ML pipelines

πŸ” What makes this different?

Most Agoda hotel pages quietly show reviews from two sources: Agoda's own guests, and a mirrored set of Booking.com reviews for the same property. This scraper pulls both - tagged with a provider field - so you get full review coverage from a single run instead of needing two separate scrapers.

πŸ”‹ Why use this scraper?

  • πŸ”Œ Fast: HTTP-first architecture, no browser automation
  • πŸ” Dual-source: Agoda + mirrored Booking.com reviews, one unified schema
  • 🀝 Reviewer trust signals: expert reviewer flag, reviewer's total review count, and both helpful and unhelpful vote counts - most competing scrapers only expose one vote direction, if any
  • 🧹 Strictly deduplicated: every review is tracked by ID per hotel, so re-runs or overlapping pages never produce duplicate rows - you only ever pay for unique reviews
  • ⏱️ Smart pagination cutoff: Agoda's reviews start repeating themselves past a certain depth per hotel. We detect that point and stop automatically, so you're never billed for fetching the same reviews twice
  • πŸ’Έ Datacenter-proxy friendly: built with careful cookie and session handling, so you don't need to pay for expensive residential proxies to get reliable results
  • βš™οΈ Typed output: schema-validated for consistency & integration ease
  • πŸš€ Multi-format export: CSV, JSON, Excel, XML, etc.

✏️ Input fields

  • urls (required) – List of Agoda hotel URLs
  • allowBookingReviews (optional, default true) – Also include mirrored Booking.com reviews for the same listing
  • maxReviews (optional) – Max number of reviews per hotel (unlimited by default)
  • maxReviewsPerSource (optional) – Max number of reviews per hotel and provider (unlimited by default)
  • sorting (optional) – Most helpful | Most recent | Score high-to-low | Score low-to-high
  • customerType (optional) – Filter by reviewer group: business, couples, solo, family, groups, etc.

When multiple limits are set, the one that's hit first takes precedence, e.g. in a situation where a hotel has 100 reviews from Agoda and 400 from booking.com, the number of results is determined like this:

  • maxReviews=200 - scrapes the first 100 reviews from Agoda, then the first 100 from booking.com
  • maxReviewsPerSource=50 - scrapes the first 50 reviews from Agoda, then the first 50 from booking.com
  • maxReviews=80 and maxReviewsPerSource=50 - scrapes the first 50 reviews from Agoda, then the first 30 from booking.com

πŸ”§ Output format

Each record is a single review, normalized across both providers:

{
"reviewId": 123456789,
"provider": "agoda",
"hotelId": 987654,
"hotelName": "Wombat's The City Hostel Munich",
"hotelUrl": "https://www.agoda.com/wombat-s-the-city-hostel-munich-werksviertel/hotel/munich-de.html",
"rating": 8.6,
"ratingLabel": "Excellent",
"title": "Great location and friendly staff",
"review": "Overall a really pleasant stay...",
"positiveText": "Staff were super helpful, clean rooms",
"negativeText": "Breakfast options were limited",
"date": "2025-02-23T17:50:44.000Z",
"checkInDate": "2025-02-20T00:00:00.000Z",
"checkOutDate": "2025-02-21T00:00:00.000Z",
"numNights": 1,
"roomTypeName": "Standard Double Room",
"customerType": "solo",
"username": "Guest",
"countryName": "Poland",
"isExpertReviewer": true,
"reviewerReviewedCount": 14,
"helpfulVotes": 3,
"unhelpfulVotes": 0,
"scrapedAt": "2025-06-21T10:00:00.000Z"
}

πŸ‘€ Who is it for?

  • πŸ”¬ Data scientists & analysts – Sentiment analysis and trend tracking across two review sources
  • 🧱 Researchers – Monitor competitors or markets in bulk
  • πŸ’» Developers – Integrate clean, deduplicated review data into your systems
  • πŸ’Ό Business owners – Keep an eye on guest feedback across both Agoda and Booking.com audiences

πŸ’¬ Support

Questions, edge cases, or feature requests? Open a support ticket or attach a failing run log - we'll take care of it.