Extract Booking.com Data
GroupBWT provides Booking.com hotel data scraping and extraction across Booking Holdings—stable, governed, decision-grade.
software engineers
years industry experience
working with clients having
clients served
We are trusted by global market leaders
Why Extract Data From Booking Holding
Pricing and product teams need totals, policies, and maps they can trust.
Booking Holdings brands shift layouts, fees, and anti-bot signals frequently.
See the True Final Price
Capture the last payable total with taxes, fees, deposits, time, and page version. Eliminate mismatches and cut reconciliation delays for pricing, finance, and product.
Compare Market Prices Fairly
Record locale, currency, device, and exchange rate each time. Compare markets on equal terms across weeks and tests for decisions backed by reliable data.
Plan Supply with Map Detail
Collect pins, clusters, coordinates, and prices with detail intact. Guide supply, bidding, and content using neighborhood-level precision and complete coverage.
View Packages in One Record
Merge flights, hotels, fares, and fees into one clean record. Measure attach rates and upsell results without manual work or delays, keeping all data aligned.
Keep Updates Steady in Peaks
Use per-site request limits and session tracking for traceability. Deliver hourly change sets reliably through promotions, spikes, and operational windows.
Keep Analytics Stable Always
Standardize rooms, rates, meal plans, and refund rules in one schema. Analytics remain stable when brands shift layouts, terms, or formats over time.
Audit Records Fast and Easily
Tag each record with URL, element path, time, session, and version. Speed audits and speed approvals for finance, compliance, and engineering teams.
Contain Changes, Recover Quickly
Sign page structures and run small checks before full rollout. Hold suspect records, alert owners, and restore the last good parser when needed.
Booking.com Data
Extraction Use Cases
GroupBWT builds and runs tailored data collection systems and solutions for the Booking Holdings group—prices, availability, policies, maps, and reviews you can rely on.
Custom means: your processes, your schedule, your data format. Built to handle site updates, access limits, and quality checks.
Six common needs we support:
Final price & price alignment
When it matters: You need the final number (taxes/fees included) to stop price differences.
How we build it: End-step capture with itemized lines + timestamp + page version; location/device recorded for every capture; changes flagged automatically.
Case: Hospitality platform pricing engine—multi-site (Booking.com, Hotels.com, Airbnb) daily updates, unified data format, API delivery, cost-managed proxy plan.
Faster-than-hourly updates
When it matters: Promotions, events, or operations windows where hourly updates aren’t enough.
How we build it: Controlled sessions, automatic retries, system health checks/alerts; snapshots combined into time series.
Case: Flight-disruption service—airport departures/arrivals every 15 minutes with access limit handling and monitoring.
Map results and local coverage
When it matters: Map views hide floors/supply; you need pins, clusters, and price details.
How we build it: Map image capture with coordinates, group state, and pin price; location data standardized for street-level comparisons.
Case: Resort/attraction coverage maps;
Case: City-level site selection mapping from public map images.
Make data consistent across sites
When it matters: You’re blending Booking with comparison sites, brand sites, or regional sites without breaking business reporting.
How we build it: Standard data fields for room/rate/board/refund rules; data checked at source; multiple output formats (JSON, CSV, XML).
Case: Multi-site + comparison engine data unification—large-scale standardization adapted from previous multi-source methods, now applied to hotel data.
Handling heavy forms and access limits
When it matters: Heavy checkout flows, form security, verification tests, or speed limits.
How we build it: Session tracking, paced access, rotating identifiers, structured exports with change logs.
Case: Transport data collection at scale—session control and speed planning designed for consistent updates during peak times.
Reviews and policy insights
When it matters: Quality scoring, cancellation risk, content operations.
How we build it: Policy extraction + review sampling, light text analysis tags, language standardization.
Case: Guest review + OTA review pipeline for hospitality insights; initial system capturing Tripadvisor + Booking policy changes.
Your teams work with consistent data, deliver updates faster, and pass audits.
Custom, Governed, Enterprise-Ready
Unlike generic vendors that offer to extract Booking.com data services without governance, we deliver custom runs designed for compliance and stability.
Extract Booking.com Data That
Plugs Into Your Stack
We deliver booking com data extract in production-ready formats. Our Booking.com scraping services align with your schema, security controls, and BI cadence.
JSON for Structured Price Delivery
Push prices, availability, policies, and map pins as clean JSON with metadata stamps for traceability.
XML for Multi-Property Catalogs
Export nested room types, rate plans, and fees in XML optimized for catalog and OMS workflows.
CSV for Analytics and Auditing
Deliver flat files with defined columns for Excel, Tableau, or Looker, including totals, taxes, and refund flags.
SFTP or API Transfer Options
Enable scheduled SFTP drops or real-time API pushes to match release cycles without rework.
Integration With Existing Systems
Our pipelines to extract Booking.com data services integrate directly with BI or ERP tools.
Schema Validation at Source
Check every field against a governed template to block missing or incorrectly formatted values.
Unified Cross-Format Schema
Maintain one schema for JSON, XML, and CSV so format changes need no downstream edits.
Metadata for Full Context
Tag each row with source URL, selector path, session ID, locale, device, and capture time.
Flexible Update Scheduling
Set event-based refreshes, hourly deltas, or daily snapshots based on market volatility.
Compliance-Ready Pipelines
Capture only public fields and meet GDPR, CCPA, and platform rate-limit requirements.
Extract Booking.com Data
Without Risks
Unstable Booking.com feeds can raise costs, slow releases, and create compliance issues. Our tested process delivers consistent, traceable outputs, so data stays ready for business teams to act quickly with reliable information.
Keep Price Displays Consistent
Booking page layouts change often. We capture room, rate, tax, and refund details with the page version recorded. This ensures totals stay accurate across languages and devices, preventing reporting errors for finance and product teams.
Reveal Hidden Extra Charges
Some costs appear late at checkout. We record itemized totals, deposits, and local fees at the last step with timestamps. This replaces manual reconciliations with a single trusted source for pricing, operations, and finance teams.
Get Map-Based Hotel Listings
City maps hide floors and available rooms. We collect pins, clusters, and prices with coordinates intact. This lets you compare areas by demand, close supply gaps, and make better bidding and content choices with full coverage data.
Unify Market Views for Accuracy
Device, language, and currency can change what travelers see. We log these details with each price, then standardize views. Markets and weeks can be compared like-for-like, giving clean results for experiments and performance tracking.
Bypass Access Limit Data Loss
Strict limits can interrupt collection. We pace sessions, track them, and retry safely. This keeps hourly updates on schedule, ensures changes are visible, and prevents failures during promotions or unexpected traffic surges.
Remove Duplicate Rate Records
Multiple rate plans can inflate listings. We merge room, board, and refund rules into one clean record. This reduces data size, speeds reporting, and keeps margin calculations clear, so decisions can be made faster under pressure.
What Breaks Booking Holdings Scrapers
Category
Common Failure in Other Setups:
GroupBWT Countermeasure:
Late fees appear at checkout, distorting parity and misaligning reports
Capture full itemized totals at the final step with a timestamp and UI version
Device or currency changes alter totals and break cross-market parity
Log locale, device, and FX at capture, normalize for like-for-like pricing
Package data splits flights, hotels, and fees into separate records
Merge all components into one schema with mapped fare and tax structures
Lost filter and sort context removes market and funnel traceability
Preserve all query parameters for accurate market and funnel comparisons
Reservation slots shift with events, hiding demand spikes and pricing
Record slot availability with event tags for stable demand and pricing logs
Missing add-on fees cause incomplete quotes for the true trip cost
Parse insurance, mileage, and surcharges as structured fields with coordinates
Missing filter paths obscure traveler intent in route price ladders
Capture all filter states to maintain a clean route and fare ladder tracking
Historical fare changes are lost, masking targeted undercutting trends
Store fare deltas by route for early detection of targeted pricing changes
Hidden parity breaks distort bidding and competitive pricing insights
Compare supplier totals with fees included to build accurate parity maps
Regional filters vanish, masking weekend spikes and seasonal demand
Preserve all filter metadata for clean regional and seasonal demand models
Cross-border itineraries lose leg-level detail and rank change signals
Log each leg’s pricing with rank shifts for early competitive market alerts
Local tax and payment rules are missed in BRL-focused itineraries
Capture local taxes, payment terms, and totals for accurate LATAM coverage
Booking.com
Common Failure in Other Setups
Late fees appear at checkout, distorting parity and misaligning reports
GroupBWT Countermeasure
Capture full itemized totals at the final step with a timestamp and UI version
Agoda
Common Failure in Other Setups
Device or currency changes alter totals and break cross-market parity
GroupBWT Countermeasure
Log locale, device, and FX at capture, normalize for like-for-like pricing
Priceline
Common Failure in Other Setups
Package data splits flights, hotels, and fees into separate records
GroupBWT Countermeasure
Merge all components into one schema with mapped fare and tax structures
KAYAK
Common Failure in Other Setups
Lost filter and sort context removes market and funnel traceability
GroupBWT Countermeasure
Preserve all query parameters for accurate market and funnel comparisons
OpenTable
Common Failure in Other Setups
Reservation slots shift with events, hiding demand spikes and pricing
GroupBWT Countermeasure
Record slot availability with event tags for stable demand and pricing logs
Rentalcars.com
Common Failure in Other Setups
Missing add-on fees cause incomplete quotes for the true trip cost
GroupBWT Countermeasure
Parse insurance, mileage, and surcharges as structured fields with coordinates
Momondo
Common Failure in Other Setups
Missing filter paths obscure traveler intent in route price ladders
GroupBWT Countermeasure
Capture all filter states to maintain a clean route and fare ladder tracking
Cheapflights
Common Failure in Other Setups
Historical fare changes are lost, masking targeted undercutting trends
GroupBWT Countermeasure
Store fare deltas by route for early detection of targeted pricing changes
HotelsCombined
Common Failure in Other Setups
Hidden parity breaks distort bidding and competitive pricing insights
GroupBWT Countermeasure
Compare supplier totals with fees included to build accurate parity maps
SWOODOO
Common Failure in Other Setups
Regional filters vanish, masking weekend spikes and seasonal demand
GroupBWT Countermeasure
Preserve all filter metadata for clean regional and seasonal demand models
checkfelix
Common Failure in Other Setups
Cross-border itineraries lose leg-level detail and rank change signals
GroupBWT Countermeasure
Log each leg’s pricing with rank shifts for early competitive market alerts
Mundi
Common Failure in Other Setups
Local tax and payment rules are missed in BRL-focused itineraries
GroupBWT Countermeasure
Capture local taxes, payment terms, and totals for accurate LATAM coverage
Governance-Centered Booking Data
01.
Spot Changes Before They Spread
DOM fingerprints flag layout shifts before scale.
Quarantine rows, alert owners, and roll back.
02.
Keep Data Structure Reliable
Schema registry versions, fields, and blocks exports.
Validation enforces types, enums, and required columns.
03.
Control Request Volume Safely
Rate-limit controls cap per-domain requests and pace.
Session tracking preserves trace as IPs and agents rotate.
04.
Track Every Export for Proof
Each export carries URL, selector, capture time, session.
Dashboards track data quality, coverage, and freshness.
Booking.com Data Extraction In 10 Steps
Each step sets owners, metrics, and gates for safe progress.
You reduce legal risk, control identity spend, and protect BI stability.
GroupBWT: Booking com Data Scraping
Services Company
We help you extract Booking.com data at enterprise scale, along with insights from every brand in the Booking Holdings group. Booking.com gets the most focus because it drives the most competition and revenue.
Our booking.com scraping services company applies brand-specific countermeasures that keep parity, availability, and pricing logic consistent across every feed.
Legal Boundaries Aligned
We collect only public Booking.com pages under regional laws. This ensures fast approvals and predictable audits for stable enterprise-scale data extraction.
Secure Data Management
Encryption, access control, and short retention windows protect Booking.com datasets. Every delivery follows strict travel data security rules and compliance.
Consistent Data Accuracy
Booking.com exports reach 98% field accuracy. Each record passes validation before release, so reports, dashboards, and models remain reliable for decisions.
Early Change Detection
We track Booking.com's structure to spot changes quickly. Automated quarantine and controlled fixes keep refresh stability across brands and markets.
Cost And Identity Control
We match Booking.com data volume to need. Rotation, scheduling, and proxy limits protect identity signals and keep extraction cost-efficient.
Pilot Then Scale Fast
Start with the Booking.com pilot in two markets. Prove value, then expand delivery to more regions while keeping operations clear and disruption-free.
Our Cases
Our partnerships and awards
What Our Clients Say
What do you like best?
Their deep understanding of our needs and how to craft a solution that provides more opportunities for managing our data. Their data solution, enhanced with AI features, allows us to easily manage diverse data sources and quickly get actionable insights from data.
What do you dislike?
It took some time to align the a multi-source data scraping platform functionality with our specific workflows. But we quickly adapted and the final result fully met our requirements.
What do you like best?
It was incredible how they could build precisely what we wanted. They were genuine experts in data scraping; project management was also great, and each phase of the project was on time, with quick feedback.
What do you dislike?
We have no comments on the work performed.
What do you like best?
GroupBWT is the preferred choice for competitive intelligence through complex data extraction. Their approach, technical skills, and customization options make them valuable partners. Nevertheless, be prepared to invest time in initial solution development.
What do you dislike?
GroupBWT provided us with a solution to collect real-time data on competitor micro-mobility services so we could monitor vehicle availability and locations. This data has given us a clear view of the market in specific areas, allowing us to refine our operational strategy and stay competitive.
What do you like best?
The company's dedication to understanding our needs for collecting competitor data was exemplary. Their methodology for extracting complex data sets was methodical and precise. What impressed me most was their adaptability and collaboration with our team, ensuring the data was relevant and actionable for our market analysis.
What do you dislike?
Finding a downside is challenging, as they consistently met our expectations and provided timely updates. If anything, I would have appreciated an even more detailed roadmap at the project's outset. However, this didn't hamper our overall experience.
What do you like best?
GroupBWT excels at providing tailored data scraping solutions perfectly suited to our specific needs for competitor analysis and market research. The flexibility of the platform they created allows us to track a wide range of data, from price changes to product modifications and customer reviews, making it a great fit for our needs. This high level of personalization delivers timely, valuable insights that enable us to stay competitive and make proactive decisions
What do you dislike?
Given the complexity and customization of our project, we later decided that we needed a few additional sources after the project had started.
What do you like best?
What we liked most was how GroupBWT created a flexible system that efficiently handles large amounts of data. Their innovative technology and expertise helped us quickly understand market trends and make smarter decisions
What do you dislike?
The entire process was easy and fast, so there were no downsides
What do you like best?
Their deep understanding of our needs and how to craft a solution that provides more opportunities for managing our data. Their data solution, enhanced with AI features, allows us to easily manage diverse data sources and quickly get actionable insights from data.
What do you dislike?
It took some time to align the a multi-source data scraping platform functionality with our specific workflows. But we quickly adapted and the final result fully met our requirements.
What do you like best?
It was incredible how they could build precisely what we wanted. They were genuine experts in data scraping; project management was also great, and each phase of the project was on time, with quick feedback.
What do you dislike?
We have no comments on the work performed.
What do you like best?
GroupBWT is the preferred choice for competitive intelligence through complex data extraction. Their approach, technical skills, and customization options make them valuable partners. Nevertheless, be prepared to invest time in initial solution development.
What do you dislike?
GroupBWT provided us with a solution to collect real-time data on competitor micro-mobility services so we could monitor vehicle availability and locations. This data has given us a clear view of the market in specific areas, allowing us to refine our operational strategy and stay competitive.
What do you like best?
The company's dedication to understanding our needs for collecting competitor data was exemplary. Their methodology for extracting complex data sets was methodical and precise. What impressed me most was their adaptability and collaboration with our team, ensuring the data was relevant and actionable for our market analysis.
What do you dislike?
Finding a downside is challenging, as they consistently met our expectations and provided timely updates. If anything, I would have appreciated an even more detailed roadmap at the project's outset. However, this didn't hamper our overall experience.
What do you like best?
GroupBWT excels at providing tailored data scraping solutions perfectly suited to our specific needs for competitor analysis and market research. The flexibility of the platform they created allows us to track a wide range of data, from price changes to product modifications and customer reviews, making it a great fit for our needs. This high level of personalization delivers timely, valuable insights that enable us to stay competitive and make proactive decisions
What do you dislike?
Given the complexity and customization of our project, we later decided that we needed a few additional sources after the project had started.
What do you like best?
What we liked most was how GroupBWT created a flexible system that efficiently handles large amounts of data. Their innovative technology and expertise helped us quickly understand market trends and make smarter decisions
What do you dislike?
The entire process was easy and fast, so there were no downsides
FAQ
What proof can Legal and Finance review before any pilot?
Provide a masked record with totals, fees, locale, device, and lineage. Attach a compact validation report with pass rates and null counts. Include a short log that shows selector paths and capture times.
How do layout changes get contained without breaking exports?
Run guarded checks on a small URL set and compare structural diffs first. Quarantine suspect rows and keep the prior parser live. Alert the owner channel and track the fix time to closure.
Which numbers prove stability and cost control to executives?
Publish coverage, freshness, accuracy, and completion rates per run. Show the success rate and cost per one thousand successful requests. Add an error budget and display the monthly burn-down.
What fields and metadata must every record include?
Keep canonical fields for rooms, plans, totals, and fees. Include source address, selector path, locale, device, capture time, session, and lineage. Log the UI version so comparisons stay consistent.
How is access governed across environments?
Use least-privilege roles and per-project isolation. Rotate secrets through a vault and record read events. Encrypt at rest and in transit with managed keys.
You have an idea?
We handle all the rest.
How can we help you?
