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Scrape Booking.com hotel reviews and guest feedback

Extract guest reviews from Booking.com hotel pages - reviewer names, review positions, nationalities, scores, comments, room types, and stay durations - to analyze guest satisfaction patterns across properties.

Booking

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What this robot does

Booking.com is one of the richest sources of verified guest reviews in the travel industry - every review comes from someone who actually stayed at the property. These reviews contain granular feedback: what guests loved, what disappointed them, the purpose of their trip, and their overall score. For hotel operators, travel analysts, and hospitality consultants, this review data reveals patterns that summary scores hide.

Which room types get the best feedback? What complaints recur across seasons? How does breakfast quality affect overall ratings?

This robot extracts individual guest reviews from any Booking.com hotel page: the reviewer name, review position, review score, comments, reviewer nationality, trip type, room type, and stay duration. Turn scattered guest feedback into structured datasets for sentiment analysis and operational improvement.

What structured Booking.com review extraction enables:

  • ✓ Individual guest reviews with scores, comments, and stay details - far richer than aggregate rating numbers alone.
  • ✓ Sentiment pattern detection: identify what guests consistently praise or complain about. Spot recurring issues that drag down your property's score.
  • ✓ Seasonal feedback analysis: correlate review sentiment with stay dates to understand how your hotel performs across high-season, low-season, and event periods.
  • ✓ Competitive review benchmarking: extract reviews from competitor hotels to compare guest satisfaction themes across properties in your market.
PositionNameDateReviewTypeScoreNationalityRoom TypeDays of stay
#1Maria S.January 2024Great location and helpful staff, but the room was smallCouple8ItalyDouble Room3
#2James T.December 2023Excellent breakfast and clean rooms. Would recommend to friendsFamily9United KingdomFamily Suite5
#3Sophie L.November 2023Good value for money, though noise from street was an issueSolo7FranceSingle Room2
#4Ahmed K.October 2023Modern amenities and friendly service. Perfect for business tripsBusiness9EgyptStandard Room4
#5Lisa M.September 2023Beautiful views but WiFi connection was unreliable at timesCouple7GermanyDeluxe Room6

How to scrape hotel reviews from Booking.com in 4 steps

No Booking.com API access, no scraping libraries, and no technical setup. Navigate to a hotel's review section and the robot captures every review.

  • A free Browse AI account (no credit card required).
  • The URL of a Booking.com hotel review page.
1
Sign up for free
Create your Browse AI account in under a minute. No credit card required. You will find this prebuilt robot in the robot library ready to use.
2
Paste the Booking.com hotel review URL
Go to any hotel on Booking.com and navigate to its reviews section. Copy the URL. Paste it into the robot. Queue review pages from multiple properties to build a comparative review dataset across competing hotels.
3
Run the robot
Click run. The robot loads the Booking.com reviews page and extracts each review's position, reviewer name, score, comments, reviewer nationality, trip type, room type, and days of stay.
4
Connect integrations or export your data
Your review data is ready for analysis. Push to Google Sheets for sentiment tracking, sync to Airtable for a guest feedback database, or pipe through Zapier into a business intelligence tool for trend reporting.

Ready to get started?

Try this robot free →

What can you do with Booking.com review data?

Guest review data from Booking.com drives operational improvements, competitive strategy, and market intelligence:

  • Sentiment analysis at scale: Extract hundreds of reviews and analyze positive vs. negative comment patterns. Quantify what percentage of guests mention cleanliness, location, or value.
  • Operational improvement: Identify the most frequent guest complaints. If 30% of negative reviews mention slow Wi-Fi, that is a clear investment priority.
  • Competitive review mining: Extract reviews from the top 5 hotels in your market. Compare what guests praise in competitor properties against your own feedback themes.
  • Seasonal quality tracking: Filter reviews by stay date to see if guest satisfaction shifts between seasons. Identify whether summer staffing, winter heating, or holiday demand creates recurring issues.
  • Trip type segmentation: Analyze reviews by traveler type (business, couple, family, solo). Different segments value different things - business travelers may prioritize Wi-Fi while families care about pool quality.
  • Response prioritization: Identify the most impactful negative reviews that need management responses. Focus on recent low-scoring reviews that mention specific, actionable issues.
🏨
Hotel general managers
Turn Booking.com reviews into actionable intelligence. Identify recurring complaints, track sentiment trends, and prioritize operational improvements.
📈
Hospitality consultants
Analyze guest feedback patterns across client properties. Compare review sentiment against competitors to build data-driven improvement recommendations.
🗺️
Destination marketing organizations
Aggregate review sentiment across hotels in your region. Understand visitor experience quality and identify area-wide improvement opportunities.
📊
Market research analysts
Study guest satisfaction patterns across hotel categories, price tiers, and destinations using structured Booking.com review data.

What data does this Booking.com review scraper extract?

Each guest review from Booking.com yields these structured fields:

FieldWhat it contains
PositionThe review's position or rank on the hotel's review page.
NameThe name of the reviewer who submitted the guest review.
DateWhen the guest stayed at the property.
ReviewThe full text of the guest's review comment.
TypeThe purpose of the trip (business, couple, family, solo, group).
ScoreThe numerical rating the guest assigned (out of 10).
NationalityThe country flag/nationality of the reviewer.
Room TypeThe room category the guest stayed in.
Days of stayThe number of nights the guest spent at the property.

Booking.com verifies that reviewers actually stayed at the property, making these reviews more reliable than unverified platforms. Review volumes vary by property - popular hotels may have thousands of reviews spanning years of guest feedback.

Frequently asked questions

How does this Booking.com review scraper work?
It visits the reviews section of any Booking.com hotel page and extracts each individual review - reviewer name, position, score, comments, trip details, room type, and stay duration - into structured data rows.

Do I need Booking.com API access?
No. The robot extracts reviews from publicly visible hotel review pages on Booking.com without any API credentials.

Are Booking.com reviews verified?
Yes. Booking.com only allows reviews from guests who completed a stay through the platform, making the review data more trustworthy than open review platforms.

Can I extract reviews from multiple hotels?
Yes. Queue review page URLs from different hotels and all reviews flow into one dataset for cross-property comparison and analysis.

Is this Booking.com scraper free?
Browse AI's free plan includes credits to run this robot. Sign up without a credit card and start extracting hotel review data.

How many reviews can I extract per hotel?
The robot paginates through available review pages. The number of reviews captured depends on how many pages the hotel has and your Browse AI plan's extraction limits.

Guest reviews tell the story behind the rating - combine Booking.com feedback with other travel platforms for complete reputation analysis:

  • Booking.com hotel data scraper - Pair review sentiment with property details - ratings, pricing, and amenities - for a complete picture of each hotel.
  • Hotels.com reviews scraper - Compare Booking.com reviews with Hotels.com feedback for the same properties. See if guest sentiment differs across platforms.
  • TripAdvisor hotels scraper - Cross-reference Booking.com review sentiment with TripAdvisor ratings and rankings for a multi-platform reputation view.

Analyze hotel guest feedback from Booking.com

Scores, comments, trip types - structured review data for hospitality intelligence.

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