We extract property listings, dynamic pricing, availability calendars, provider offers, and amenities from HomeToGo. 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 Properties objects from hometogo.com. All fields typed and schema-versioned.
"property_id": "htg_892144", "title": "Luxury Villa with Private Pool", "property_type": "Villa", "location": "Mallorca, Spain", "max_guests": 8, "bedrooms": 4, "bathrooms": 3, "average_rating": 4.8
| # | property_id | title | property_type | location | latitude | longitude |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Availability objects from hometogo.com. All fields typed and schema-versioned.
"property_id": "htg_892144", "check_in_date": "2026-07-10", "check_out_date": "2026-07-17", "nights": 7, "total_price": 2450.0, "currency": "EUR", "price_per_night": 350.0, "is_available": true
| # | property_id | check_in_date | check_out_date | nights | total_price | price_per_night |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Providers & Offers objects from hometogo.com. All fields typed and schema-versioned.
"property_id": "htg_892144", "provider_name": "Booking.com", "offer_price": 2450.0, "discount_pct": 5, "is_instant_book": true, "cancellation_policy": "Free cancellation before Jul 1", "deep_link": "https://www.booking.com/hotel/es/villa-mallorca..."
| # | property_id | provider_name | provider_url | offer_price | discount_pct | is_instant_book |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Amenities objects from hometogo.com. All fields typed and schema-versioned.
"property_id": "htg_892144", "has_pool": true, "has_wifi": true, "air_conditioning": true, "parking": true, "pet_friendly": false, "kitchen": true
| # | property_id | has_pool | has_wifi | air_conditioning | parking | pet_friendly |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Reviews objects from hometogo.com. All fields typed and schema-versioned.
"property_id": "htg_892144", "total_reviews": 124, "overall_rating": 4.8, "cleanliness_rating": 4.9, "location_rating": 4.7, "provider_source": "Airbnb", "summary_text": "Exceptional stay with great amenities."
| # | property_id | total_reviews | overall_rating | cleanliness_rating | location_rating | value_rating |
|---|---|---|---|---|---|---|
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Our HomeToGo scraper handles every layer of the platform: property metadata, dynamic pricing across dates, provider aggregation, and availability calendars — with JavaScript rendering and anti-bot circumvention built in.
Title, location, property type, guest capacity, bedrooms, bathrooms, and full amenity lists scraped accurately per listing.
Extract open and booked dates up to 12 months in advance. Map seasonal occupancy trends across entire regions.
Capture pricing variations across Airbnb, Vrbo, Booking.com, and direct managers for the exact same property.
Extract nightly rates, total prices, cleaning fees, and tax breakdowns for specific check-in and check-out dates.
Extract precise latitude and longitude coordinates to map inventory density and location-based pricing premiums.
Collect total review counts, overall scores, and sub-ratings (cleanliness, location, value) aggregated from underlying providers.
Extract arrays of image URLs for property galleries, useful for computer vision models and listing quality analysis.
Set local currencies via session headers to extract native pricing without relying on flawed downstream conversion rates.
Run one-off bulk exports or configure continuous pipelines at daily or weekly cadences with change-detection diffing.
Brief in. Clean data out.
Provide target regions, property IDs, or URL patterns. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and date-handling logic.
Schema validation, null-rate checks, price-outlier detection, and sample payloads before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Meta-search engines invest heavily in bot mitigation and dynamic rendering. Here's how we stay resilient.
HomeToGo relies heavily on client-side rendering for pricing and availability. We run full Playwright browser sessions with JavaScript execution, lazy-load triggering, and XHR interception to capture data that headless HTTP clients miss entirely.
We use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management to bypass rate limits and IP bans.
Standard pagination maxes out at a few hundred results. We use dynamic geo-bounding box subdivision to traverse map areas systematically, ensuring 100% extraction of dense urban property catalogues.
Pricing requires strict date parameters. Our pipeline manages complex session states, injecting precise check-in and check-out dates into the search context to extract accurate quote data.
For large property catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs — reducing compute cost and downstream processing load.
Property managers track competitor pricing, occupancy rates, and seasonal trends to optimise their own daily rates.
Real estate analysts monitor supply growth, average daily rates (ADR), and revenue per available rental (RevPAR) across regions.
Vacation rental platforms benchmark their inventory overlap, pricing parity, and fee structures against aggregated market data.
Private equity firms evaluate short-term rental yields and market saturation before acquiring property portfolios.
Travel startups use aggregated provider data to build meta-search layers or niche booking experiences.
Data science teams train pricing algorithms on historical availability and rate fluctuations extracted from the platform.
"HomeToGo aggregates the fragmented vacation rental market into a single view — but accessing that cross-provider pricing data programmatically requires purpose-built infrastructure."
Most engineering teams underestimate the complexity of scraping meta-search engines. Extracting accurate pricing requires rendering complex JavaScript, managing session state across date searches, and handling map-based pagination. DataFlirt absorbs this operational overhead so your analysts can focus on yield management.
Everything supported by our hometogo.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 XHR interception. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across target regions. Rotation happens per-request with sticky sessions where required to maintain currency and locale consistency.
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 hometogo.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from HomeToGo is generally permissible under applicable law. DataFlirt targets only public, non-authenticated property metadata, pricing, and availability. We do not extract personal data, circumvent authentication walls, or violate GDPR. Clients should review HomeToGo's ToS and consult legal counsel for specific use cases.
We programmatically inject check-in, check-out, and guest count parameters into the session state before executing the search. This forces HomeToGo to return exact quotes and availability for the requested dates.
Yes. HomeToGo limits standard list pagination. We circumvent this by programmatically subdividing the target region into smaller geographic bounding boxes, traversing the map to extract the entire inventory.
Pipelines can be configured to run daily or weekly depending on your requirements. For specific high-priority properties, we can configure sub-hourly polling to track real-time price fluctuations.
We extract the provider names, offer prices, and deep links as they appear on HomeToGo. If you require deeper extraction directly from Airbnb or Vrbo, we build dedicated pipelines for those sources.
Absolutely. We provide a sample run of up to 1,000 properties for a specific region as part of the pre-engagement scoping process — so you can validate schema fit, field completeness, and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off regional property dump or continuous availability tracking across 100,000 listings — we scope, build, and operate the pipeline. Tell us what you need.
