We extract property metadata, room types, dynamic pricing, availability grids, and Marriott Bonvoy reward rates from W Hotels. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Property Metadata objects from whotels.com. All fields typed and schema-versioned.
"hotel_id": "BOMWH", "name": "W Mumbai", "brand": "W Hotels", "city": "Mumbai", "check_in_time": "15:00", "check_out_time": "12:00", "total_rooms": 350, "pet_policy": "Pets Welcome"
| # | hotel_id | name | brand | address | city | country |
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Complete list of extractable fields for Room Rates & Availability objects from whotels.com. All fields typed and schema-versioned.
"hotel_id": "BOMWH", "room_id": "FAB-KING-01", "room_name": "Fabulous Room, 1 King", "check_in_date": "2026-10-15", "check_out_date": "2026-10-16", "currency": "INR", "base_rate": 18500.0, "available": true, "rate_type": "Standard Retail Rate"
| # | hotel_id | room_id | room_name | check_in_date | check_out_date | currency |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Room Types & Amenities objects from whotels.com. All fields typed and schema-versioned.
"room_id": "WOW-SUITE-01", "name": "WOW Suite, 1 Bedroom Suite", "max_occupancy": 3, "bed_type": "King", "square_footage": 950, "view_type": "Ocean View", "balcony": true, "accessible": false
| # | room_id | hotel_id | name | description | max_occupancy | bed_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Marriott Bonvoy Redemption objects from whotels.com. All fields typed and schema-versioned.
"hotel_id": "BOMWH", "check_in_date": "2026-10-15", "points_required": 45000, "cash_upgrade_fee": 0.0, "point_savers_active": false, "available_for_points": true, "currency": "INR", "scraped_at": "2026-05-12T09:14:00Z"
| # | hotel_id | check_in_date | points_required | cash_upgrade_fee | point_savers_active | redemption_category |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Dining & Facilities objects from whotels.com. All fields typed and schema-versioned.
"hotel_id": "BOMWH", "venue_name": "W Lounge", "venue_type": "Bar", "cuisine": "International", "dress_code": "Smart Casual", "reservations_required": false, "pool_type": "WET Deck Outdoor", "fitness_center": "FIT Gym 24/7"
| # | hotel_id | venue_name | venue_type | cuisine | dress_code | opening_hours |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our W Hotels scraper handles the complexities of Marriott Bonvoy's platform: dynamic availability calendars, geo-specific pricing, and heavy JavaScript rendering - with full anti-bot circumvention built in.
Hotel metadata, exact coordinates, contact details, policies, and amenity lists scraped across the global W Hotels portfolio.
Capture base rates, total rates, taxes, and resort fees for specific date ranges and occupancies.
Extract point redemption requirements, cash upgrade fees, and PointSavers availability for any given date.
Iterate through booking calendars to map out sold-out dates, minimum length of stay requirements, and seasonal closures.
Extract detailed room metadata including square footage, bed types, view categories, and accessibility features.
Route requests through specific regional proxies to capture localised pricing and tax variations.
Capture cancellation windows, deposit requirements, and guarantee policies tied to specific rate codes.
Monitor volatile rates and inventory drops with hourly or minute-by-minute pipeline executions.
Bypass Akamai and PerimeterX protections using advanced TLS fingerprinting and residential proxy rotation.
Brief in. Clean data out.
Provide hotel IDs, geographic regions, date ranges, and occupancies. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, session management, and calendar iteration logic.
Schema validation, null-rate checks, price-outlier detection, and date-range verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Hospitality platforms invest heavily in scraping detection and employ complex dynamic rendering. Here is how we stay resilient.
Marriott Bonvoy properties sit behind strict web application firewalls. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management to bypass Akamai and PerimeterX blocks.
W Hotels booking calendars and dynamic rate displays are heavily JavaScript-rendered. We run full Playwright browser sessions to trigger date selections and hydrate price widgets, capturing data that headless HTTP clients miss entirely.
Extracting rates requires querying specific check-in and check-out combinations. Our pipeline automates this traversal across 30, 90, or 365-day windows, handling minimum stay restrictions and sold-out edge cases smoothly.
Rates and taxes often vary based on the searcher's location. We route requests through specific geographic proxy pools to ensure you capture the exact pricing presented to users in your target markets.
Hospitality booking engines update frequently. Our selector strategy uses multiple fallback chains per field, ensuring that a minor frontend update to the W Hotels site does not break your data pipeline.
Competitor hotel brands and revenue managers monitor W Hotels' dynamic pricing to adjust their own daily rates and maintain market parity.
Hospitality analysts track room availability and pricing trends to gauge market demand and seasonal occupancy rates in key cities.
OTAs and metasearch engines enrich their platforms with accurate property metadata, room descriptions, and amenity lists.
Travel optimisers and points brokers track Marriott Bonvoy redemption rates to identify high-value reward opportunities and PointSavers deals.
Revenue teams correlate W Hotels' rate changes with local events and flight data to refine their own yield management algorithms.
Real estate investment trusts monitor property expansion, room categorisation, and pricing power to evaluate asset performance.
"W Hotels operates on highly dynamic pricing models tied to Marriott Bonvoy - extracting this requires precise session management and geographic routing."
Most teams underestimate the investment required: reliable hospitality scraping requires residential proxies, full JavaScript rendering for calendar widgets, and strict date-range iteration. DataFlirt absorbs that complexity so your engineers can focus on the analysis - not the infrastructure.
Everything supported by our whotels.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across global regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About whotels.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing, availability, and property information is generally permissible. DataFlirt targets only public, non-authenticated data. We do not extract personal guest data, circumvent authentication walls, or violate privacy laws. Clients should review Marriott's ToS and consult legal counsel for their specific use cases.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour to bypass enterprise WAFs like Akamai. We monitor for blocking patterns and trigger pool rotation automatically.
Yes. We extract the required points, cash upgrade fees, and availability for reward bookings across specified date ranges.
We can configure pipelines to poll specific properties and dates at high frequencies, achieving sub-60-minute latency for critical rate monitoring. Broader catalogue refreshes are typically run on a daily cadence.
Yes. You define the check-in and check-out parameters, length of stay, and occupancy details. Our pipeline iterates through the booking calendar to extract rates for those exact criteria.
Our smallest packages start at a defined list of properties and date ranges with weekly delivery. For continuous high-frequency rate tracking, we price based on query volume and delivery frequency. Contact us for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off property catalogue dump or a continuous rate-monitoring feed across specific dates - we scope, build, and operate the pipeline. Tell us what you need.
