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URL: https://apify.com/plowdata/agoda-reviews-scraper

โ‡ฑ Agoda Reviews Scraper ยท Apify


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from $0.85 / 1,000 reviews

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Agoda Reviews Scraper

๐Ÿจ Scrape guest reviews from Agoda hotel listings โ€” 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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๐Ÿ‘ Frederic

Frederic

Maintained by Community

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1

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8 days ago

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๐ŸŒ 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 ๐Ÿš€

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

Great for:

  • ๐Ÿงฌ Market research & trend analysis across two review pools at once
  • ๐Ÿ“ˆ Competitor monitoring (your hotel, or theirs)
  • ๐Ÿค Reviewer trust analysis - expert reviewers, review history, and vote counts
  • ๐Ÿค– Feeding clean, structured review data into apps or ML pipelines

๐Ÿ” 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.

๐Ÿ”‹ Why use this scraper?

  • ๐Ÿ”Œ Fast: HTTP-first architecture, no browser automation
  • ๐Ÿ” Dual-source: Agoda + mirrored Booking.com reviews, one unified schema
  • ๐Ÿค 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
  • ๐Ÿงน 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
  • โฑ๏ธ 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
  • ๐Ÿ’ธ 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
  • โš™๏ธ Typed output: schema-validated for consistency & integration ease
  • ๐Ÿš€ Multi-format export: CSV, JSON, Excel, XML, etc.

โœ๏ธ Input fields

  • urls (required) โ€“ List of Agoda hotel URLs
  • allowBookingReviews (optional, default true) โ€“ Also include mirrored Booking.com reviews for the same listing
  • maxReviews (optional) โ€“ Max number of reviews per hotel (unlimited by default)
  • maxReviewsPerSource (optional) โ€“ Max number of reviews per hotel and provider (unlimited by default)
  • sorting (optional) โ€“ Most helpful | Most recent | Score high-to-low | Score low-to-high
  • customerType (optional) โ€“ 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

๐Ÿ”ง 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"
}

๐Ÿ‘ค Who is it for?

  • ๐Ÿ”ฌ Data scientists & analysts โ€“ Sentiment analysis and trend tracking across two review sources
  • ๐Ÿงฑ Researchers โ€“ Monitor competitors or markets in bulk
  • ๐Ÿ’ป Developers โ€“ Integrate clean, deduplicated review data into your systems
  • ๐Ÿ’ผ Business owners โ€“ Keep an eye on guest feedback across both Agoda and Booking.com audiences

๐Ÿ’ฌ Support

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

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