Harcourts Scraper — Australian Property Listings, Prices & Agents

Scrape Harcourts Australia (harcourts.com.au) property listings — search by buy / sold / rent (with location, price and bedroom filters) or pass individual property URLs. Every property comes back in one clean schema with address, beds/baths/car, price, agents, and photos. Pure HTTP, no browser.

Why use this scraper

• Any Harcourts search, filters and all — paste a buy / sold / rent URL with whatever filters you set (suburb, price range, bedrooms, bathrooms, property type) and the actor honours them and paginates through every matching result.
• Full property detail — address (split into suburb/state/postcode), bedrooms, bathrooms, car spaces, price, listing agents, and photos on every row.
• Agent contacts — each listing's agents (name, profile, photo) so you can build lead lists by office or region.
• Clean, flat output — one row per property; toggle flattening for CSV-ready columns or keep nested JSON for code.
• Pure HTTP, no browser — fast, cheap, reliable. Reads Harcourts' server-rendered pages directly.

Overview

The actor classifies each Harcourts URL (search / property / office), walks search results page by page (12 per page), fans out to each property, and normalises everything into a consistent PropertyRow. Ideal for buyers' agents, investors, PropTech teams, and B2B lead generation.

Supported inputs

Input URL shape	Example
Listing search	harcourts.com.au/au/listings/buy (also /sold, /rent)
Filtered search	harcourts.com.au/au/listings/buy?location=…&bedrooms=3&minPrice=…
Individual property	harcourts.com.au/au/office/{office}/listing/{id}-{slug}
Office page	harcourts.com.au/au/office/{office} (fans out to that office's listings)

Tip: run a search on the Harcourts website, then copy the URL from your browser's address bar — the filter parameters drop straight into startUrls.

Use cases

• Buyers' agents — monitor new / sold listings by suburb and price band; pull listing-agent contacts.
• Investors & analysts — track sold comparables and asking prices across regions.
• PropTech / data teams — feed structured Harcourts listings into valuation models, CRMs, dashboards.
• Lead generation — harvest agent + office contacts by area.

How it works

1. You provide one or more Harcourts URLs (search, property, or office).
2. The actor classifies each URL and walks search results with ?page=N pagination (filters preserved).
3. Each property is fetched and parsed (server-rendered HTML + JSON-LD).
4. Rows are normalised to one schema and streamed to your dataset — JSON or CSV.

Input configuration

Field	Type	Default	Description
startUrls	array	—	Harcourts URLs (search / property / office)
harvestEmails	boolean	true	Follow the office website + harvest contact emails
flatten	boolean	true	Flatten nested fields for CSV-friendly output
maxItems	integer	10000	Hard cap on rows collected
maxConcurrency	integer	8	Parallel detail fetches

Output overview

One row per property. Nested objects (address, office, agents) flatten to underscore keys (address_suburb, office_name) when flatten is on; arrays of objects become *_json strings. Disable flatten for full nested JSON.

Output samples

Flattened (flatten: true, default):

{
  "portal": "harcourts",
  "listingId": "40906443",
  "canonicalUrl": "https://harcourts.net/au/office/mandurah/listing/l40906443-49-willoughbridge-crescent-erskine-wa-6210",
  "listingMode": "sale",
  "propertyType": "House",
  "headline": "49 Willoughbridge Crescent, ERSKINE, WA 6210",
  "address_displayAddress": "49 Willoughbridge Crescent, ERSKINE, WA, 6210",
  "address_suburb": "ERSKINE",
  "address_state": "WA",
  "address_postcode": "6210",
  "bedrooms": 4,
  "bathrooms": 2,
  "priceDisplay": "From $895,000",
  "photosCount": 26,
  "office_name": "Mandurah",
  "agents_json": "[{\"name\":\"Keith Prevost\",\"profileUrl\":\"https://harcourts.net/...\"}]",
  "harvestedEmails": []
}

Key output fields

Field	Description
listingId, canonicalUrl	Identity
listingMode	sale / sold / rent
propertyType	House / Unit / Land / …
headline, description	Listing copy
address / address_*	display address, suburb, state, postcode
bedrooms, bathrooms, carspaces	Specs
priceDisplay	"From $895,000" / "Auction …" / "Offers Over …" / "Contact Agent"
photos[], photosCount	Listing photos
agents[] / agents_json	Each agent's name, profile URL, photo
office / office_*	Office name + profile URL
harvestedEmails[]	Emails from the office website (when enabled)

FAQ

Can I scrape a filtered search? Yes — paste any Harcourts search URL with its filters (location, price, bedrooms, etc.). They're preserved and paginated automatically.

Does it cover sold and rental listings? Yes — /au/listings/sold and /au/listings/rent work the same as /au/listings/buy.

Why are some emails empty? Email harvest follows the office website, which not all offices publish. Agent names + profile links are on every row regardless.

Support

Found a bug or need a field added? Open an issue on the actor's Apify Console page.

Explore more scrapers

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• Domain.com.au Scraper — residential + agents

Full portfolio: apify.com/memo23

⚠️ Disclaimer

This scraper accesses only publicly available data. Use the extracted data in compliance with Harcourts' Terms of Use, the Australian Privacy Act 1988, the Spam Act 2003, and all applicable laws. You are responsible for how you use scraped data — particularly personal information (agent names, contact details). This actor is not affiliated with, endorsed by, or connected to Harcourts International or any of its offices.

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