Realestate.co.nz Scraper | $1.8 / 1k | Fast & Reliable

Overview

Realestate.co.nz Scraper captures structured property data from New Zealand’s leading real estate marketplace. It collects listing details such as titles, prices, locations, property types, bedrooms, bathrooms, land and floor areas, photos, open home schedules, and more. Realestate.co.nz aggregates nationwide listings across residential sales and rentals, making it an essential source for understanding market supply, pricing signals, and regional trends without manual browsing.

This actor automates the process from start to finish, ensuring dependable runs, consistent data quality, and significant time savings for teams that need fresh property intelligence at scale.

Why Use This Actor

• Market and pricing analysis: Track inventory shifts, asking prices, and featured listings across cities, districts, and suburbs.
• Lead generation and outreach: Build contact-ready datasets for agencies, investors, and property services based on targeted locations or direct listing links.
• Portfolio and product tracking: Monitor listings that match investment criteria, compare attributes, and export structured records to your own tools.
• Directory and data enrichment: Create clean, location-aware datasets for dashboards, research projects, or downstream enrichment.
• Repeatable automation: Schedule recurring runs to keep datasets current without manual effort.

Input Parameters

Parameter	Type	Description	Default
startUrls	array of strings	One or more Realestate.co.nz search, category, or individual listing URLs to capture. Use this when you already have target pages.	Prefilled example provided
city	array of strings	City names to fetch listings from (e.g., Auckland, Bay of Plenty). Leave empty to include all New Zealand listings.	—
district	array of strings	District names within the selected city (e.g., Auckland City, Manukau City).	—
suburbs	array of strings	One or more suburbs within the chosen district (e.g., Auckland Central, Avondale).	—
listing_type	string	Listing channel for query-built searches: sale, rental, or sold.	sale
sort_by	string	Result ordering for query-built searches: latest, featured, or latest-sale.	latest
min_price / max_price	integer	Sale/sold price range, or weekly rent range for rentals.	—
min_bedrooms / max_bedrooms	integer	Bedroom range.	—
min_bathrooms / max_bathrooms	integer	Bathroom range.	—
min_carparks	integer	Minimum number of carparks.	—
min_land_area / max_land_area	integer	Land area range in square metres.	—
min_floor_area / max_floor_area	integer	Floor area range in square metres.	—
has_swimming_pool	boolean	Only include listings with a swimming pool.	false
sale_property_types	array of strings	Sale/sold property type IDs such as House 1, Section 9, or Townhouse 4.	—
rental_property_types	array of strings	Rental property type IDs such as House 10, Unit 14, or Studio 12.	—
publication_date	string	Optional publication-date window. Use last_24_hours, last_3_days, last_7_days, last_30_days, or last_90_days to keep only recently published listings.	—
limit	integer	Maximum number of listings to save per input. Minimum is 1.	50000
get_valuations	boolean	Collect council CV, estimated value, valuation history, and sale history when available. This makes extra property-profile requests and may slow the run.	false
proxyConfiguration	object	Connection settings. The default residential proxy keeps runs stable.	Uses Apify Residential Proxy

Example Input

{
  "city": ["Auckland"],
  "district": ["Auckland City"],
  "suburbs": ["Blockhouse Bay"],
  "listing_type": "sale",
  "min_price": 200000,
  "min_bedrooms": 1,
  "max_bedrooms": 4,
  "sale_property_types": ["1", "9", "4"],
  "publication_date": "last_7_days",
  "limit": 200,
  "get_valuations": false
}

Example Output

Each dataset item represents one normalized property listing record. Source-specific details that do not fit a stronger real estate group are preserved under attributes or source_context.

{
  "record_type": "property_listing",
  "record_id": "43036571",
  "source_context": {
    "source_name": "Realestate.co.nz",
    "source_domain": "realestate.co.nz",
    "source_url": "https://platform.realestate.co.nz/search/v1/listings?filter%5Bsuburb%5D%5B%5D=2776&page%5Boffset%5D=0&page%5Blimit%5D=10",
    "listing_url": "https://www.realestate.co.nz/43036571/residential/sale/32-donovan-street-blockhouse-bay",
    "seed_type": "listing",
    "search_filters": {
      "suburb": "2776"
    },
    "search_paging": {
      "limit": 10,
      "offset": 0
    },
    "external_ids": {
      "listing_no": "1672920",
      "website_slug": "/43036571/residential/sale/32-donovan-street-blockhouse-bay"
    }
  },
  "entity": {
    "title": "Timeless 1950s home with dual title potential",
    "description": "Built in 1953, this solid and well-maintained home offers classic mid-century appeal combined with outstanding future potential.",
    "url": "https://www.realestate.co.nz/43036571/residential/sale/32-donovan-street-blockhouse-bay",
    "status": "active",
    "category": "House",
    "external_ids": {
      "listing_id": "1672920"
    }
  },
  "listing": {
    "listing_id": "1672920",
    "listing_type": "res_sale",
    "listing_status": "active",
    "listing_category_code": "res_sale",
    "listing_subtype": "House",
    "published_at": "2026-04-17T11:19:04",
    "is_featured": true,
    "auction": {
      "date": "2026-05-02",
      "time": "13:30:00",
      "location": "Onsite"
    },
    "open_houses": [
      {
        "start": "2026-05-02T14:00:00+12:00",
        "end": "2026-05-02T14:30:00+12:00"
      }
    ]
  },
  "pricing": {
    "price_text": "Auction"
  },
  "location": {
    "full_address": "32 Donovan Street, Blockhouse Bay, Auckland City, Auckland",
    "address": "32 Donovan Street, Blockhouse Bay",
    "suburb": "Blockhouse Bay",
    "district": "Auckland City",
    "region": "Auckland",
    "country": "New Zealand",
    "coordinates": {
      "lat": -36.9221307,
      "lng": 174.7033677
    }
  },
  "property": {
    "property_type": "House",
    "bedrooms": 3,
    "bathrooms": 1,
    "garages": 1,
    "floor_area": 98,
    "floor_area_unit": "sqm",
    "land_area": 677,
    "land_area_unit": "SQM"
  },
  "media": {
    "main_image_url": "/listings/43036571/5b80da40138d38c7b145b267cb804130",
    "photos": [
      {
        "order": 1,
        "base_url": "/listings/43036571/5b80da40138d38c7b145b267cb804130",
        "variants": {
          "thumbnail": ".crop.31x40.jpg",
          "large": ".resize.1024x768.jpg"
        }
      }
    ]
  },
  "relationships": {
    "agents": [
      {
        "id": "12345",
        "name": "Sample Agent",
        "email": "agent@example.com",
        "phone_mobile": "+64 21 000 0000"
      }
    ],
    "agencies": [
      {
        "id": "67890",
        "name": "Example Realty"
      }
    ]
  },
  "attributes": {
    "education": {
      "schools": []
    },
    "matched_listings": []
  }
}

• record_type and record_id identify each saved property row.
• source_context keeps source provenance, input filters, paging, listing URL, and source identifiers.
• entity, listing, pricing, location, and property hold the core real estate facts.
• media, contact_details, and relationships preserve photos, agents, agencies, and contact channels when the source returns them.
• pricing and attributes include council CV, estimated values, sale history, and valuation history when get_valuations is enabled and the source provides those fields.
• attributes keeps meaningful source-specific details such as school context, broadband data, matched listings, and valuation history.

Notes & Limitations

• Use responsibly and respect Realestate.co.nz’s terms of service and any applicable legal requirements.
• Begin with smaller limits to confirm inputs before scaling up.
• Avoid storing or using personal data without the proper legal basis.

Support

Questions or custom needs? Open an issue on the Issues tab of the actor page in Apify Console and it will be resolved around the clock.

Happy Scraping,

• Fatih