We extract property details, availability calendars, nightly rates, and Premier Host metrics from Vrbo. 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 Listings objects from vrbo.com. All fields typed and schema-versioned.
"property_id": "9842104ha", "headline": "Oceanfront Villa with Private Pool", "property_type": "Villa", "bedrooms": 4, "bathrooms": 3.5, "max_guests": 10, "premier_host": true, "rating": 4.9, "review_count": 142
| # | property_id | headline | property_type | bedrooms | bathrooms | max_guests |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Fees objects from vrbo.com. All fields typed and schema-versioned.
"property_id": "9842104ha", "date": "2026-07-15", "base_rate": 450.0, "currency": "USD", "cleaning_fee": 150.0, "service_fee": 65.0, "tax_amount": 45.0, "total_price": 710.0
| # | property_id | date | base_rate | currency | cleaning_fee | service_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Availability Calendar objects from vrbo.com. All fields typed and schema-versioned.
"property_id": "9842104ha", "date": "2026-07-15", "is_available": false, "price": 450.0, "minimum_stay": 3, "updated_at": "2026-05-12T10:15:00Z", "calendar_hash": "a8f9c2e4b"
| # | property_id | date | is_available | price | minimum_stay | booking_window |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from vrbo.com. All fields typed and schema-versioned.
"review_id": "rvw_8472910", "property_id": "9842104ha", "guest_name": "Sarah M.", "rating": 5, "review_date": "2026-04-20", "review_text": "Incredible views and very clean. The host was highly responsive.", "stay_date": "April 2026", "origin_country": "United States"
| # | review_id | property_id | guest_name | rating | review_date | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Host Intelligence objects from vrbo.com. All fields typed and schema-versioned.
"host_id": "hst_44921", "host_name": "Coastal Retreats Management", "member_since": "2018", "response_time": "within an hour", "response_rate": 98.5, "premier_host_badge": true, "total_properties": 14, "languages": "['English', 'Spanish']"
| # | host_id | host_name | member_since | response_time | response_rate | premier_host_badge |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Vrbo scraper handles complex GraphQL APIs, stateful pricing requests, and aggressive bot mitigation to extract accurate property and market data.
Extract headline, description, property type, exact coordinates, house rules, and cancellation policies for any listing.
Capture nightly base rates, seasonal adjustments, and hidden fee structures including cleaning and service fees.
Perform forward-looking 365-day availability scraping to calculate occupancy rates and booking velocity.
Extract and categorise structured amenities like pools, hot tubs, EV chargers, and pet policies.
Monitor host performance metrics, response rates, review averages, and total portfolio sizes.
Extract full text reviews, star ratings, stay dates, and host responses across all paginated views.
Track dynamic minimum length of stay requirements across different seasons and local events.
Extract bounding box coordinates and precise location markers for spatial analysis and market mapping.
Run daily or weekly diffs to track price elasticity, new listing creation, and market saturation.
Brief in. Clean data out.
Provide geographic bounding boxes, city names, or specific property IDs. We design the extraction schema together.
We configure Scrapy crawlers, Playwright sessions, proxy rotation, and GraphQL query interception for vrbo.com.
Schema validation, null-rate checks, price outlier detection, and sample property runs before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Expedia Group invests heavily in perimeter defence. Here is how we maintain reliable extraction pipelines.
Vrbo uses advanced perimeter defence. We route requests through residential IPs with realistic browser fingerprints and automated session management to prevent IP bans and CAPTCHA walls.
Pricing and availability are heavily dependent on stateful requests. We run headless browsers to trigger the exact pricing API calls required to render accurate nightly rates and fee breakdowns.
Rather than parsing complex DOM trees, our pipeline intercepts Vrbo's internal GraphQL responses for cleaner, faster, and more reliable data extraction.
For large geographic areas, we maintain a hash index of last-seen calendar states. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, schema drift, and coverage drops, responding before you notice.
Property managers track competitor pricing and availability to optimise their own nightly rates and maximise yield.
Investors analyse occupancy rates, gross yields, and seasonality to identify lucrative vacation rental markets.
OTAs and travel platforms monitor Vrbo inventory overlap, exclusive listings, and price parity.
Data science teams feed historical price and availability data into machine learning models for predictive pricing.
Urban planners and local governments track short-term rental density and housing market impact.
Hosts analyse which amenities correlate with higher occupancy and premium pricing in specific postcodes.
"Vrbo holds the definitive dataset for entire-home vacation rentals, but accessing historical occupancy and dynamic pricing requires serious infrastructure."
Extracting property data at scale means navigating GraphQL rate limits, stateful pricing requests, and aggressive bot mitigation. DataFlirt absorbs that complexity. We maintain the residential proxies, handle the JavaScript execution, and monitor the schema so your engineers can focus on the data.
Everything supported by our vrbo.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. Rotation happens per request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda and Kubernetes. Airflow handles scheduling, dependency management, and SLA alerting. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About vrbo.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated property, pricing, and review data. We do not extract personal guest data or circumvent authentication walls.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We intercept GraphQL responses directly to minimise unnecessary DOM parsing.
Yes. We simulate booking requests with specific dates and guest counts to trigger the pricing API, allowing us to extract the full breakdown of base rates, cleaning fees, service fees, and taxes.
We typically extract 365-day forward-looking calendars for each property, capturing block-out dates, booked dates, and dynamic minimum stay requirements.
We extract the latitude and longitude provided by the public map interface. While Vrbo sometimes obfuscates exact locations prior to booking, we capture the most precise coordinates publicly available.
Daily runs capture rate changes within 24 hours. For specific sub-markets, we can configure sub-hourly pipelines to monitor high-frequency pricing adjustments.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a specific postcode or a nationwide property catalogue, we scope, build, and operate the pipeline. Tell us what you need.
