We extract property listings, calendar availability, dynamic pricing signals, host intelligence, and reviews from Airbnb. 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 airbnb.com. All fields typed and schema-versioned.
"listing_id": "4829103", "title": "Luxury Villa with Pool", "property_type": "Entire villa", "max_guests": 8, "bedrooms": 4, "baths": 3, "superhost": true
| # | listing_id | url | title | property_type | room_type | max_guests |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Fees objects from airbnb.com. All fields typed and schema-versioned.
"listing_id": "4829103", "check_in": "2024-11-01", "nightly_rate": 250.0, "cleaning_fee": 100.0, "service_fee": 45.0, "total_price": 895.0, "currency": "USD"
| # | listing_id | check_in | check_out | nightly_rate | cleaning_fee | service_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Calendar Availability objects from airbnb.com. All fields typed and schema-versioned.
"listing_id": "4829103", "date": "2024-11-01", "available": false, "price": 250.0, "min_nights": 2, "updated_at": "2024-05-12T09:14:00Z"
| # | listing_id | date | available | price | min_nights | max_nights |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Host Intelligence objects from airbnb.com. All fields typed and schema-versioned.
"host_id": "993821", "host_name": "Sarah", "superhost": true, "response_rate": 100, "total_listings": 4, "verified_identity": true, "total_reviews": 412
| # | host_id | host_name | host_url | joined_date | superhost | response_rate |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from airbnb.com. All fields typed and schema-versioned.
"review_id": "84920183", "rating_cleanliness": 5, "rating_location": 5, "author_name": "Michael", "created_at": "2024-04-18", "text": "Incredible stay. Highly recommend."
| # | review_id | listing_id | author_id | author_name | created_at | text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Airbnb scraper handles every layer of the platform: property listings, dynamic pricing, calendar availability, host intelligence, and the review corpus — with JavaScript rendering, session management, and anti-bot circumvention built in.
Title, description, amenities, house rules, coordinates, max guests, beds, baths, and every metadata field Airbnb surfaces — scraped at the listing level.
Capture nightly rates, cleaning fees, service fees, taxes, and applied discounts for specific date ranges and guest counts.
Extract forward-looking availability calendars up to 12 months out. Track blocked dates, minimum stay requirements, and seasonal price adjustments.
Full review text, category-specific ratings (cleanliness, location, etc.), author names, and timestamps — paginated across all review pages.
Host name, join date, Superhost status, response rate, response time, total listings, and verified identity flags.
Extract listings using geographic bounding boxes (latitude/longitude coordinates) to capture entire neighbourhoods or cities systematically.
Scrape local domains and normalise pricing into your preferred target currency using Airbnb's native conversion.
Capture high-resolution image URLs for property galleries, host avatars, and user review uploads.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or weekly cadences with change-detection diffing.
Brief in. Clean data out.
Provide bounding boxes, city names, listing IDs, or host URLs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and Datadome handling for airbnb.com.
Schema validation, null-rate checks, price-outlier detection, and coordinate mapping before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Airbnb employs sophisticated anti-scraping measures and relies heavily on map-based rendering. Here is how we maintain pipeline stability.
Airbnb uses Datadome and custom bot mitigation. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management to blend in with legitimate user traffic.
Airbnb limits search results to 300 listings per view. We programmatically divide target cities into micro-grids using latitude and longitude bounding boxes, ensuring 100% coverage without hitting pagination limits.
Pricing on Airbnb is entirely dynamic based on dates and guest counts. We execute targeted API payloads to hydrate exact pricing, cleaning fees, and service fees for your specified booking windows.
Rather than relying solely on brittle DOM selectors, our Playwright instances intercept and extract structured data directly from Airbnb's internal GraphQL responses, ensuring high schema stability even when the UI changes.
For tracking availability calendars across thousands of listings, we maintain a hash index of last-seen values. Subsequent runs only push diffs — reducing compute cost, storage bloat, and downstream processing load.
Property managers and pricing software platforms track competitor rates, occupancy levels, and seasonal trends to optimise their own nightly pricing.
Investors calculate cap rates and yield potential by analysing historical occupancy, average daily rates (ADR), and revenue per available room (RevPAR) in target neighbourhoods.
Municipalities and urban planners monitor short-term rental density, housing stock impact, and compliance with local zoning regulations.
Hospitality brands and hotel chains track alternative accommodation supply, pricing parity, and guest sentiment in their operating markets.
Machine learning teams use property descriptions, amenity combinations, and guest reviews to train recommendation engines and valuation models.
Agencies identify top-performing hosts, analyse their listing strategies, and use review data to improve their own service standards.
"Airbnb holds the definitive dataset for short-term rental demand, pricing elasticity, and host behaviour — but extracting it requires navigating aggressive bot mitigation and map-based pagination."
Most teams underestimate the investment required: reliable Airbnb scraping requires residential proxies, full JavaScript rendering for map bounds, Datadome bypass, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our airbnb.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, grid pagination, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and map interaction flows.
We maintain pools of residential ISP proxies across global regions. Rotation happens per-request with sticky sessions where required to bypass Datadome.
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 airbnb.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Airbnb is generally permissible under applicable law, targeting only public, non-authenticated property, pricing, and review data. We do not extract personal data, circumvent authentication walls, or violate GDPR. Clients should review Airbnb's ToS and consult legal counsel for specific use cases.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for CAPTCHA/block rate spikes in real time and trigger pool rotation or solver queues automatically.
Yes. We programmatically divide target cities or regions into micro-grids using latitude and longitude bounding boxes, ensuring comprehensive coverage without hitting Airbnb's 300-listing pagination limit.
Real-time streaming pipelines achieve sub-60-minute latency for price and availability signals on a defined listing set. Full market refreshes at daily cadence complete within a 6-12 hour window depending on scale.
Yes. By passing specific date ranges and guest counts to the pricing endpoints, we extract the full fee breakdown, including nightly rates, cleaning fees, service fees, taxes, and total price.
Yes. Each listing record includes the host ID, name, join date, Superhost status, total listings under management, response rate, and verified identity flags.
Our smallest packages start at a defined geographic area or listing list (typically 1,000-50,000 listings) with weekly delivery. For larger global catalogues or custom schema requirements, we price based on volume and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off market dump or a continuous pricing feed across 50,000 listings — we scope, build, and operate the pipeline. Tell us what you need.
