RealEstate.com.au Scraper

Slug: fatihtahta/realestate-com-au-scraper

Overview

RealEstate.com.au Scraper collects structured property listing records from realestate.com.au, including listing identity, address, price display, property attributes, agency details, agent contacts, media, inspection information, and source context. Realestate.com.au is one of Australia's major property marketplaces, making its public sale, rental, and sold listing data useful for market research, lead generation, pricing analysis, and operational monitoring. The actor converts public listing information into repeatable JSON records that can be used consistently across analytics tools, CRMs, warehouses, and enrichment workflows. It is designed for dependable recurring data acquisition with configurable locations, listing channels, limits, and filters, while avoiding unsupported assumptions about completeness or availability. Use it when you need a structured, automation-ready dataset instead of manual listing review.

Why Use This Actor

• Market research and analytics: collect property listings for market intelligence, pricing bands, availability analysis, suburb comparisons, and operational reporting.
• Product and content teams: populate internal property experiences, comparison tools, editorial research, or directory-style content with structured extraction from public listings.
• Developers and data engineering teams: feed downstream systems with normalized JSON records, stable identifiers, source context, and repeatable collection settings.
• Lead generation and enrichment teams: build targeted datasets of public listings, agencies, and agents for lawful outreach, CRM enrichment, and segmentation workflows.
• Monitoring and competitive tracking teams: schedule recurring runs to track listing movement, price visibility, property mix, geographic coverage, and agency activity over time.

Common Use Cases

• Market intelligence: monitor supply, pricing, availability, locations, and property-type movement across Australian suburbs, regions, postcodes, or states.
• Lead generation: build targeted prospect lists from public listing, agency, and agent records.
• Competitive monitoring: track listing changes across agencies, suburbs, sale channels, rental categories, or property segments.
• Catalog and directory building: populate internal property databases with structured public records and media references.
• Data enrichment: add current public listing attributes to CRM, BI, warehouse, or analytics datasets.
• Recurring reporting: schedule periodic runs for dashboards, alerts, portfolio monitoring, or trend analysis.

Quick Start

1. Optionally choose one Australian location using location, such as a suburb, postcode, region, or state-level area.
2. Select the listing channel with deal_type: buy, rent, or sold.
3. Set a small limit, such as 25, for the first validation run.
4. Add optional filters such as price range, bedrooms, property type, amenities, sale method, rental requirements, or land area.
5. Run the actor in Apify Console and inspect the first dataset records to confirm the output matches your workflow.
6. Increase coverage, adjust filters, enable broader matching, or schedule recurring runs after validating the dataset shape.

Input Parameters

The actor can run without location. Add one location only when you want to narrow the listing channel, result volume, and property filters to a specific area.

Parameter	Type	Description	Default
location	string	Optional Australian suburb, region, postcode, or state-level area to search. Leave empty to run without a locality filter.	–
deal_type	string	Listing channel. Allowed values: buy for properties for sale, rent for rental listings, sold for sold listings.	buy
limit	integer	Maximum number of listings to save. Minimum: 1. Leave empty to collect all available matching results.	–
min_price	integer	Minimum listing price in AUD. For rentals, values represent weekly rent in AUD. Minimum: 1.	–
max_price	integer	Maximum listing price in AUD. For rentals, values represent weekly rent in AUD. Minimum: 1.	–
has_price	boolean	When enabled, keeps only buy or sold listings that show a displayed price. Does not affect rental searches.	false
include_surrounding_areas	boolean	Includes listings from surrounding suburbs or nearby areas when available. Disable for a tighter location scope.	true
min_bedroom	string	Minimum bedrooms. Allowed values: studio, 1, 2, 3, 4, 5.	–
max_bedroom	string	Maximum bedrooms. Allowed values: studio, 1, 2, 3, 4, 5.	–
min_bathroom	string	Minimum bathrooms. Allowed values: 1, 2, 3, 4, 5.	–
min_parking	string	Minimum parking spaces. Allowed values: 1, 2, 3, 4, 5.	–
property_condition	string	Property lifecycle filter. Allowed values: new, established. Leave empty to include both.	–
outdoor_amenities	array of strings	Outdoor amenity filters. Allowed values: swimming_pool, garage, balcony, outdoor_area, undercover_parking, shed, fully_fenced, outdoor_spa, tennis_court.	–
indoor_amenities	array of strings	Indoor amenity filters. Allowed values: ensuite, dishwasher, study, built_in_robes, alarm_system, broadband, floorboards, gym, rumpus_room, workshop.	–
climate_amenities	array of strings	Climate, energy, and utility amenity filters. Allowed values: air_conditioning, solar_panels, heating, fireplace, high_energy_efficiency, water_tank, solar_hot_water.	–
accessibility_amenities	array of strings	Accessibility amenity filters. Allowed values: single_storey, step_free_entry, wide_doorways, elevator, roll_in_shower, bathroom_grab_rails, accessible_parking.	–
keyword	string	Short listing keyword, such as air con, water views, or renovated. Use for terms not covered by structured filters.	–
sale_method	string	Sale-specific filter for buy listings. Allowed values: private_treaty_sale, auction. Leave empty to include both sale methods.	–
rental_property_requirements	array of strings	Rental-specific requirements. Allowed values: furnished, pets_allowed, affordable_housing. Applies when deal_type is rent.	–
min_area	integer	Minimum land area in square metres. Applies to buy or sold searches. Minimum: 1.	–
max_area	integer	Maximum land area in square metres. Applies to buy or sold searches. Minimum: 1.	–
property_type	array of strings	Property type filters. Allowed values: retirement_living, house, land, townhouse, acreage, apartment_and_unit, rural, villa, block_of_units. Rental searches support a smaller set of property types, so unsupported values may not affect rental output.	–
maximize_coverage	boolean	Collects more listings that match the configured location and filters. Useful for broad production runs; disable for faster sampling.	true

Choosing Inputs

Use location only when you want to define the geographic scope of a run. A postcode or suburb is useful for localized monitoring; leaving it empty runs without a locality filter. Choose deal_type before applying filters because buy, rent, and sold result sets support different practical workflows and may expose different field availability.

Broader filters improve discovery and are better for market mapping. Narrower filters produce more targeted datasets for specific requirements, such as apartments with minimum bedrooms, rentals with pet access, or sold houses in a price band. Start with a small limit to validate the output shape, then increase it after confirming that the records match your use case. Leave optional filters empty when you want the actor to collect the widest matching set for the selected location and channel.

Example Inputs

Example 1: Local buy-market snapshot

{
  "location": "Sydney, NSW 2000",
  "deal_type": "buy",
  "limit": 50,
  "min_price": 800000,
  "max_price": 2500000,
  "min_bedroom": "2",
  "property_type": ["apartment_and_unit"],
  "include_surrounding_areas": true
}

Example 2: Rental listings with practical tenant requirements

{
  "location": "Richmond, VIC 3121",
  "deal_type": "rent",
  "limit": 75,
  "max_price": 950,
  "min_bedroom": "2",
  "rental_property_requirements": ["pets_allowed"],
  "outdoor_amenities": ["balcony"],
  "keyword": "renovated"
}

Example 3: Sold-property discovery with no location filter

{
  "deal_type": "sold",
  "limit": 100,
  "min_price": 500000,
  "max_price": 1200000,
  "property_type": ["house", "townhouse"],
  "maximize_coverage": true
}

Output

The actor writes normalized property listing records to the default Apify dataset. Each row uses the same grouped JSON envelope so the primary business fields are easy to read, while source-specific details remain preserved under attributes.source_details.

Record Envelope And Stable Identifiers

Each saved row has record_type: "property_listing". Use record_id as the primary idempotency key for upserts; it is based on the source listing identifier when available. Use source_context.listing_url, source_context.canonical_url, and fingerprint as secondary sync helpers.

Example

{
  "record_type": "property_listing",
  "record_id": "123456789",
  "source_context": {
    "source_name": "realestate.com.au",
    "source_domain": "www.realestate.com.au",
    "source_url": "https://www.realestate.com.au/buy/in-2000/list-1",
    "canonical_url": "https://www.realestate.com.au/property-apartment-nsw-exampleville-123456789",
    "listing_url": "https://www.realestate.com.au/property-apartment-nsw-exampleville-123456789",
    "seed_id": "example-seed-001",
    "seed_type": "query",
    "seed_value": "2000",
    "page_index": 1,
    "external_ids": {
      "listing_id": "123456789"
    }
  },
  "entity": {
    "id": "123456789",
    "url": "https://www.realestate.com.au/property-apartment-nsw-exampleville-123456789",
    "display_name": "Modern city apartment with harbour glimpses",
    "external_ids": {
      "listing_id": "123456789",
      "pretty_url": "property-apartment-nsw-exampleville-123456789"
    }
  },
  "listing": {
    "title": "Modern city apartment with harbour glimpses",
    "description": "Light-filled two bedroom apartment in a well-maintained city building with open-plan living, a covered balcony, secure parking, and easy access to transport.",
    "transaction_type": "buy",
    "url": "https://www.realestate.com.au/property-apartment-nsw-exampleville-123456789",
    "pretty_url": "property-apartment-nsw-exampleville-123456789",
    "short_url": "https://www.realestate.com.au/123456789",
    "product_depth": "signature",
    "is_featured": false,
    "is_standard": false,
    "is_midtier": false,
    "is_signature": true
  },
  "pricing": {
    "price_text": "Price guide $1,250,000"
  },
  "location": {
    "address": "12/34 Example Street, Exampleville, NSW, 2000",
    "short_address": "12/34 Example Street",
    "suburb": "Exampleville",
    "state": "NSW",
    "postal_code": "2000",
    "coordinates": {
      "latitude": -33.865143,
      "longitude": 151.2099
    }
  },
  "property": {
    "property_type": "apartment",
    "bedrooms": 2,
    "bathrooms": 2,
    "parking_spaces": 1,
    "construction_status": "established"
  },
  "media": {
    "main_image_url": "https://cdn.example.com/realestate/example-property/main.jpg",
    "image_urls": [
      "https://cdn.example.com/realestate/example-property/image-01.jpg",
      "https://cdn.example.com/realestate/example-property/image-02.jpg"
    ]
  },
  "contact_details": {
    "agency_phone": "02 5550 1234",
    "agency_email": "sales@example.com",
    "agency_website": "https://www.example.com/agency/sydney",
    "contact_agent_url": "https://agent-contact.realestate.com.au/contact-agent/listing/123456789",
    "contacts": [
      {
        "name": "Amelia Hart",
        "phone": "0412 345 678",
        "profile_url": "https://www.realestate.com.au/agent/123456"
      }
    ]
  },
  "relationships": {
    "agency": {
      "id": "EXAMPLE1",
      "name": "Example Realty - Sydney",
      "url": "https://www.realestate.com.au/agency/example-realty-sydney-EXAMPLE1",
      "phone": "02 5550 1234",
      "email": "sales@example.com",
      "website": "https://www.example.com/agency/sydney"
    },
    "agents": [
      {
        "id": "123456",
        "name": "Amelia Hart",
        "phone": "0412 345 678",
        "url": "https://www.realestate.com.au/agent/123456",
        "photo": "https://cdn.example.com/realestate/example-agents/amelia-hart.jpg"
      }
    ]
  },
  "attributes": {
    "source_flags": {
      "show_agency_logo": true,
      "is_linked_external_child_listing": false,
      "is_external_child_listing": false
    },
    "links": {
      "pretty_url": {
        "href": "https://www.realestate.com.au/property-apartment-nsw-exampleville-123456789"
      },
      "short": {
        "href": "https://www.realestate.com.au/123456789"
      }
    },
    "source_details": {
      "listing_id": "123456789",
      "pretty_url": "property-apartment-nsw-exampleville-123456789",
      "channel": "buy",
      "product_depth": "signature",
      "price": {
        "display": "Price guide $1,250,000"
      }
    }
  },
  "fingerprint": "example-fingerprint-001"
}

Field Reference

Property Listing Record

record_type (string, required): Stable row type. Current value is property_listing.

record_id (string, required): Source listing identifier and recommended primary upsert key.

source_context (object, required): Public provenance, including source_name, source_domain, source_url, canonical_url, listing_url, seed context, page index, and source external IDs when available.

entity (object, required): Stable listing identity, display name, canonical public URL, and external IDs.

listing (object, required): Listing headline, description, transaction type, public URLs, status badges, and source presentation flags.

pricing (object, optional): Displayed price fields such as price_text.

location (object, optional): Address, suburb, state, postal code, and coordinates when shown by the source.

property (object, optional): Property type, bedroom, bathroom, parking, study, size, and construction fields.

media (object, optional): Primary image URL and listing gallery URLs.

contact_details (object, optional): Agency contact values, contact-agent URL, and normalized contact entries.

relationships (object, optional): Related agency, agent, and primary lister objects.

attributes (object, optional): Source-specific values that do not belong in the normalized groups. attributes.source_details preserves the cleaned source listing payload, including detailed lister records, source links, flags, calculator metadata, inspection or auction data, property feature sections, and media component objects when available.

fingerprint (string, required): Actor-generated fingerprint for deduplication and change tracking.

Data Quality, Guarantees, And Handling

• Structured records: results are normalized into predictable JSON objects for downstream use.
• Best-effort extraction: fields may vary by region, session, availability, listing channel, or source-side experiments.
• Optional fields: null-check optional fields in downstream code, especially contact details, media, events, coordinates, and agency metadata.
• Deduplication: use id as the strongest stable key, with url and fingerprint as secondary helpers when appropriate.
• Freshness: results reflect the publicly available data at run time.
• Repeated runs: use the recommended idempotency key when syncing data into warehouses, CRMs, search indexes, or monitoring systems.

Tips For Best Results

• Start with a small limit to validate the output shape before scaling up.
• Use one geography or segment per run when you need cleaner reporting and easier comparison.
• Leave optional filters empty when the goal is broad discovery.
• Add filters gradually to understand how each field changes coverage.
• Use deal_type to separate buy, rent, and sold workflows into distinct datasets.
• Enable maximize_coverage for production collection when you want broader matching results.
• Use id for deduplication when storing records over time.

How to Run on Apify

1. Open the Actor in Apify Console.
2. Configure the available input fields for the optional target location, listing channel, and filters.
3. Set the maximum number of outputs to collect with limit.
4. Click Start and wait for the run to finish.
5. Open the dataset and review the first records.
6. Download results in JSON, CSV, Excel, or other supported formats.

Scheduling & Automation

Scheduling

Automated Data Collection

Schedule runs to keep property listing datasets fresh for monitoring, reporting, and enrichment workflows. Use separate schedules for distinct locations or listing channels when you need cleaner operational boundaries.

• Navigate to Schedules in Apify Console
• Create a new schedule, such as daily, weekly, or custom cron
• Configure input parameters
• Enable notifications for run completion
• Add webhooks for automated processing

Integration Options

• CRM enrichment: sync public listing, agency, and agent attributes into account, lead, or opportunity records.
• BI dashboards: monitor pricing, availability, property mix, geographic coverage, and channel movement over time.
• Data warehouses: store recurring snapshots for historical analysis, modeling, and operational reporting.
• Google Sheets or Airtable: review smaller location-specific datasets with sales, research, or operations teams.
• Webhooks: trigger validation, notification, ingestion, or alerting workflows after each completed run.
• Data enrichment pipelines: join current public listing attributes with existing CRM, portfolio, or analytics datasets.

Export Formats And Downstream Use

Apify datasets can be exported from the Console or consumed by downstream systems for operational use. Choose the format that best matches the receiving system and review workflow.

• JSON: for APIs, applications, and data pipelines
• CSV or Excel: for spreadsheet workflows and manual review
• API access: for automated ingestion into internal systems
• BI and warehouses: for reporting, dashboards, and historical analysis

Performance

Estimated run times:

• Small runs (< 1,000 outputs): ~3-5 minutes
• Medium runs (1,000-5,000 outputs): ~5-15 minutes
• Large runs (5,000+ outputs): ~15-30 minutes

Execution time varies based on filters, result volume, and how much information is returned per record. Highly filtered runs can finish faster, while broad discovery or detail-rich records may take longer.

Limitations

• Availability depends on what realestate.com.au publicly exposes at run time.
• Some optional fields may be missing on sparse listings, older listings, or records with limited public detail.
• Very broad searches may take longer or require higher limits.
• Source-side changes can affect field availability, naming, or record shape.
• Regional, account, or availability differences may change visible results.
• Rental, buy, and sold listings may expose different fields and filter behavior.

Troubleshooting

No results returned: check filter combinations, location spelling, listing channel, and whether the target site has matching public records.

Fewer results than expected: broaden filters, raise limit, enable include_surrounding_areas, or verify that enough matching listings are publicly available.

Some fields are empty: optional fields depend on what each listing publicly provides.

Run takes longer than expected: reduce scope, lower limit for validation, or split broad collection into smaller location segments.

Output changed: compare the current output with the field reference and include a small sample if support is needed.

FAQ

What data does this actor collect?

It collects public RealEstate.com.au property listings, including listing details, price display, location, property attributes, agency information, agent details, media, inspection or auction data when available, and source context.

Can I filter by location, category, date, price, or other criteria?

You can filter by location, listing channel, price, displayed price availability, surrounding areas, bedrooms, bathrooms, parking, property condition, property type, amenities, keyword, sale method, rental requirements, and land area. The schema does not include date-window inputs.

Why did I receive fewer results than my limit?

The limit is a maximum, not a guarantee. Fewer records can occur when the selected location, channel, or filters have fewer matching public listings.

Can I schedule recurring runs?

Yes. Use Apify schedules to run the actor daily, weekly, or on a custom cron pattern.

How do I avoid duplicates across runs?

Use id as the primary deduplication and upsert key. url and fingerprint can help with secondary matching or change tracking.

Can I export the data to CSV, Excel, or JSON?

Yes. Apify datasets support JSON, CSV, Excel, and other export formats from the dataset view.

Does this actor collect private data?

The actor is intended to collect publicly available listing information from RealEstate.com.au. Users are responsible for using the data lawfully and respecting privacy obligations.

What should I include when reporting an issue?

Include the input used, the run ID, expected versus actual behavior, and a small output sample when relevant. Redact any sensitive operational notes before sharing.

Compliance & Ethics

Responsible Data Collection

This actor collects publicly available real estate listing information from https://www.realestate.com.au for legitimate business purposes, including:

• Real estate research and market analysis
• Listing, agency, and agent monitoring workflows
• CRM, BI, and data enrichment workflows

Users are responsible for ensuring that their use of the collected data complies with applicable laws, regulations, and the target site's terms. This section is informational and not legal advice.

Best Practices

• Use collected data in accordance with applicable laws, regulations, and the target site's terms
• Respect individual privacy and personal information
• Use data responsibly and avoid disruptive or excessive collection
• Do not use this actor for spamming, harassment, or other harmful purposes
• Follow relevant data protection requirements where applicable, such as GDPR and CCPA

Support

For help, use the actor page or Issues. Include the input used with sensitive values redacted, the run ID, expected versus actual behavior, and a small output sample if it helps explain the issue. Avoid sharing unnecessary personal information in support requests.

This Actor is not affiliated with, endorsed by, or sponsored by Pty Limited (REA Group (realestate.com.au)) or any of its subsidiaries. All trademarks mentioned are the property of their respective owners.