We extract property profiles, dynamic pricing, room availability, and amenity data from Small Luxury Hotels of the World. 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 Profiles objects from slh.com. All fields typed and schema-versioned.
"hotel_id": "SLH-LDN-01", "name": "The Franklin London", "location": "Knightsbridge, London", "country": "United Kingdom", "star_rating": 5.0, "total_rooms": 35, "latitude": 51.4964
| # | hotel_id | name | location | country | description | star_rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Room Types objects from slh.com. All fields typed and schema-versioned.
"room_id": "RM-FRK-04", "room_name": "Junior Suite", "max_occupancy": 2, "bed_type": "King", "size_sqm": 32, "view_type": "Garden View"
| # | room_id | hotel_id | room_name | description | max_occupancy | bed_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Availability objects from slh.com. All fields typed and schema-versioned.
"hotel_id": "SLH-LDN-01", "room_id": "RM-FRK-04", "check_in_date": "2024-11-15", "check_out_date": "2024-11-18", "price": 450.0, "currency": "GBP", "is_available": true
| # | hotel_id | room_id | check_in_date | check_out_date | price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Amenities & Facilities objects from slh.com. All fields typed and schema-versioned.
"hotel_id": "SLH-LDN-01", "spa": true, "gym": true, "restaurant_count": 1, "bar": true, "wifi_included": true, "pet_friendly": true, "airport_transfer": false
| # | hotel_id | pool | spa | gym | restaurant_count | bar |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Destination Guides objects from slh.com. All fields typed and schema-versioned.
"destination_id": "DEST-UK-LON", "region": "Europe", "country": "United Kingdom", "title": "London", "best_time_to_visit": "May to September", "featured_hotels_count": 12
| # | destination_id | region | country | title | description | best_time_to_visit |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our SLH scraper navigates availability calendars, dynamic rate rules, and complex property hierarchies to deliver structured hospitality data.
Extract full hotel descriptions, total room counts, check-in policies, and geo-coordinates.
Capture daily rates across different room categories, occupancy levels, and booking windows.
Monitor room availability for specific dates, identifying sold-out periods and minimum stay requirements.
Map parent hotels to specific suites and villas, including square footage and bed configurations.
Categorise facilities including spa services, dining options, pool access, and pet policies.
Track loyalty program specific benefits and standard public rate comparisons.
Extract clean URLs for property galleries, room layouts, and destination imagery.
Scrape SLH destination guides, regional highlights, and recommended travel periods.
Run daily or hourly pricing updates to track rate fluctuations across peak seasons.
Brief in. Clean data out.
Provide target regions, specific property URLs, or date ranges. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for slh.com.
Schema validation, null-rate checks, price-outlier detection, and sample property records before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Hotel pricing is dynamic and heavily protected. We manage the session state and date-math required to extract reliable rates.
Booking engines monitor request velocity and IP reputation. We route traffic through residential proxy pools, ensuring high success rates when querying availability calendars.
Rates and availability are loaded asynchronously via internal APIs. We execute full browser sessions to trigger date selections and capture the resulting JSON payloads.
Accurate pricing requires maintaining session state across date selection, occupancy configuration, and room type filtering. Our pipelines hold cookie state precisely to ensure rate validity.
SLH properties display rates in local currencies. We extract the native currency, tax inclusions, and base rates to allow for unified downstream analysis.
Hospitality platforms update their booking flows frequently. We monitor selector health and payload structures to repair pipelines before data drops occur.
OTAs and luxury hotel groups monitor pricing strategies across independent boutique properties.
Investors track boutique hotel distribution, room capacity, and amenity standards by region.
Curated travel platforms integrate property details, high-resolution imagery, and descriptions.
Revenue managers correlate availability drops with rate increases to optimise pricing models.
Comparing INVITED benefits and public rates against rival luxury tier programs.
Analysing hotel density, seasonal pricing, and availability by specific global destinations.
"Small Luxury Hotels of the World represents the pinnacle of independent boutique properties. Extracting this data requires navigating complex availability calendars and dynamic rate rules."
Off-the-shelf scrapers fail on modern booking engines. Reliable hospitality data requires session persistence, date-math logic, and residential proxies to bypass rate limits. DataFlirt manages the extraction infrastructure so your analysts can focus on yield and market trends rather than maintaining fragile scripts.
Everything supported by our slh.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 and retry logic. Playwright manages JavaScript rendering and booking engine interactions.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions for calendar queries.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling for daily rate updates. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About slh.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available property details, amenities, and standard rates is generally permissible. DataFlirt extracts only public, non-authenticated data. We do not bypass login walls to extract member-specific INVITED program data or PII.
Yes. We configure pipelines to query specific check-in and check-out parameters across forward-looking windows, capturing rates and sold-out statuses.
We extract the native currency displayed by the property along with the exact numerical rate, ensuring accurate financial data prior to any downstream conversion.
We begin tracking time-series data from the moment your pipeline is commissioned. We do not maintain a retroactive database of past slh.com rates.
Yes. We extract the direct CDN URLs for property galleries, room layouts, and destination imagery, avoiding low-resolution thumbnails.
Pipelines can be scheduled for daily or hourly runs depending on your requirements. Data is pushed to your warehouse immediately upon run completion.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off property catalogue or continuous rate monitoring across all SLH destinations — we scope, build, and operate the pipeline.
