We extract residential listings, commercial properties, auction results, and agent intelligence from domain.com.au. 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 domain.com.au. All fields typed and schema-versioned.
"property_id": "2018493211", "status": "For Sale", "property_type": "House", "street_address": "42 Wallaby Way", "suburb": "Sydney", "state": "NSW", "postcode": "2000", "price_guide": "Contact Agent", "bedrooms": 4, "bathrooms": 2, "parking_spaces": 2, "land_area_sqm": 450
| # | property_id | url | status | property_type | street_address | suburb |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Auction Results objects from domain.com.au. All fields typed and schema-versioned.
"property_id": "2018493211", "suburb": "Surry Hills", "state": "NSW", "auction_date": "2026-05-16", "result_type": "Sold Prior to Auction", "sold_price": 1850000, "agency_name": "Ray White", "property_type": "Terrace"
| # | property_id | street_address | suburb | state | auction_date | auction_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Agent Profiles objects from domain.com.au. All fields typed and schema-versioned.
"agent_id": "49218", "full_name": "Jane Doe", "agency_name": "McGrath Estate Agents", "role": "Principal", "phone_number": "0412345678", "active_listings_count": 14, "sold_listings_count": 87, "average_sale_price": 1450000
| # | agent_id | full_name | agency_name | agency_id | role | phone_number |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Property History objects from domain.com.au. All fields typed and schema-versioned.
"property_id": "2018493211", "event_type": "Sold", "event_date": "2021-08-14", "price": 1250000, "agency_name": "Belle Property", "days_on_market": 24, "property_type": "House"
| # | property_id | street_address | event_type | event_date | price | agency_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Suburb Insights objects from domain.com.au. All fields typed and schema-versioned.
"suburb": "Richmond", "postcode": "3121", "state": "VIC", "property_type": "House", "median_price": 1420000, "clearance_rate": 72.5, "average_days_on_market": 31, "rental_yield_pct": 2.8
| # | suburb | postcode | state | property_type | median_price | clearance_rate |
|---|---|---|---|---|---|---|
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Our Domain scraper handles every layer of the platform: property search results, individual listings, agent directories, and historical sales records. We manage map hydration, JavaScript rendering, and anti-bot circumvention.
Address, beds, baths, description, images, floorplans, and property features scraped at the listing level.
Capture weekend auction results, clearance rates, sold prices, and passed-in status across all states.
Extract agent contact details, active listings, historical sales performance, and agency market share.
Historical sales records, past rental campaigns, and price changes for individual addresses.
Median house prices, unit prices, rental yields, and days on market data aggregated by postcode.
Extract primary and secondary school zones associated with specific property listings.
Parse office, retail, and industrial listings including floor space, zoning, and lease terms.
Bypass pagination limits by programmatically iterating through geographic bounding boxes.
Run one-off bulk exports or configure continuous pipelines at hourly or daily cadences with change-detection diffing.
Brief in. Clean data out.
Provide postcodes, property types, agent IDs, or geographic bounds. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for domain.com.au.
Schema validation, null-rate checks, price-outlier detection, and sample listings before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Domain.com.au employs strict rate limiting and bot protection. Here is how we maintain pipeline stability and ensure complete data capture.
Domain's bot detection monitors traffic origin and TLS fingerprints. Our crawlers use Australian residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management to blend in with normal consumer traffic.
Domain caps search results at 50 pages. We bypass this by dynamically generating granular geographic bounding boxes and filtering by narrow price brackets, ensuring every listing in a target area is captured without hitting pagination walls.
Many listings only reveal precise coordinates or boundary data via map interactions. We execute full Playwright browser sessions to hydrate map components and intercept the underlying API responses containing exact latitude, longitude, and polygon data.
We maintain a hash index of last-seen values per listing. Subsequent runs only push diffs, allowing you to track price guide revisions, under-offer status changes, and auction result updates in near real-time without processing full database dumps.
Every run emits structured logs to our observability stack. We alert on null-rate spikes in critical fields like price guides or agent details, and respond to layout changes before you notice missing data.
AVM providers ingest historical sales, land sizes, and recent comparable sales to train automated valuation algorithms.
Institutional investors track rental yields, days on market, and clearance rates to identify high-growth suburbs and optimal entry points.
Real estate aggregators and analytics dashboards use listing data to power market insights and buyer intelligence tools.
Real estate networks monitor competitor market share, agent performance, and listing volumes across specific postcodes.
Professionals track price guide adjustments, prolonged campaigns, and withdrawn auctions to identify motivated vendors.
Consultancies correlate housing density, property types, and demographic data to model infrastructure requirements.
"Domain.com.au holds the definitive record of Australian property transactions, but extracting it at scale requires bypassing sophisticated map-based pagination and aggressive rate limits."
Most teams underestimate the investment required: reliable Domain scraping requires Australian residential proxies, full JavaScript rendering for map clusters, CAPTCHA handling, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our domain.com.au 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 map interactions. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies localised to Australia. 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 domain.com.au scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Domain is generally permissible under Australian law, provided it does not breach copyright or specific terms of service regarding commercial reuse. DataFlirt targets only public, non-authenticated listing, pricing, and agent data. Clients should review Domain's ToS and consult legal counsel for specific use cases.
We use Australian residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for 403/CAPTCHA rate spikes in real time and trigger pool rotation or solver queues automatically.
Yes. Instead of relying on broad suburb searches that hit the 50-page cap, our crawlers generate granular geographic bounding boxes and iterate through narrow price brackets to capture every listing in a target area.
We run dedicated auction pipelines on Saturday evenings and Sunday mornings to capture preliminary and finalised weekend results across all major capital cities.
Yes. Our change detection system maintains a hash of listing states. We can emit alerts or updated records whenever a price guide drops, a property goes under offer, or an auction date changes.
Our smallest packages start at a defined set of postcodes or specific property types with weekly delivery. For national coverage or real-time streaming, we price based on volume and delivery frequency.
Yes. We extract publicly visible agent names, agency affiliations, office numbers, and public email addresses associated with specific listings and agent profile pages.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily feed of Sydney auction results or a national historical sales database, we scope, build, and operate the pipeline. Tell us what you need.
