Funda Property Discovery Scraper

Discover public Funda real estate listings from simple inputs: Dutch location, sale or rent, property type, and maximum results. The Actor searches Funda and returns structured Netherlands property rows with listing URLs, prices, areas, rooms, descriptions, images, timestamps, and optional workflow IDs.

Use it when you need repeatable Funda property discovery without manually creating search URLs, copying listing cards, or cleaning Dutch real estate fields by hand.

What does Funda Property Discovery Scraper do?

Funda Property Discovery Scraper converts a market query such as Amsterdam into a clean Apify dataset of public Funda listings.

It can:

• search Funda by Dutch city or market name
• collect sale or rental listings with operation
• request broad property types such as any, apartment, house, land, or commercial
• return listing identifiers, titles, URLs, prices, areas, rooms, addresses, descriptions, feature lists, images, and timestamps
• calculate pricePerM2 when both price and area are available
• append results to an existing dataset through datasetId
• copy a workflow identifier into every row with runId

This is a discovery Actor. You provide search criteria, not Funda search-result URLs.

Why use this Funda scraper?

Use case	How it helps
Dutch property lead discovery	Build listing datasets for Amsterdam, Rotterdam, Utrecht, The Hague, Eindhoven, Groningen, Haarlem, Maastricht, and other city-level searches.
Sale and rental monitoring	Schedule the same Funda search and compare new rows over time.
Market analysis	Compare price, pricePerM2, areaM2, bedrooms, bathrooms, and city across listings.
Agency and investor workflows	Feed normalized property rows into dashboards, CRM enrichment, or due-diligence workflows.
Multi-source real estate datasets	Combine Funda rows with other TroveVault property discovery Actors using datasetId and runId.

What data does it return?

Each dataset item represents one public Funda listing when the field is visible in search or detail data.

Field	Description
platform	Source platform, normally Funda.
listingId	Listing identifier when exposed or derived from the public URL.
title	Listing headline.
url	Public Funda listing URL.
operation	Requested operation, such as sale or rent.
propertyType	Requested property type.
price, currency, priceText	Numeric price when parseable, currency, and original display text.
pricePerM2	Calculated only when price and area are visible.
areaM2, bedrooms, bathrooms	Size and room attributes when available.
address, city, country	Parsed listing location.
description, features	Public description and feature list.
mainImage, images	Main image URL and gallery URLs when available.
listedAtText	Listing date or freshness text when exposed.
scrapedAt	ISO timestamp for when the row was collected.
runId	Optional workflow ID copied from input.

How do I run Funda Property Discovery Scraper?

1. Enter a Dutch city in Location, for example Amsterdam.
2. Choose Operation: sale or rent.
3. Choose Property Type: any, apartment, house, land, or commercial.
4. Set Maximum Items for the number of listings to save.
5. Start the Actor and export results as JSON, CSV, Excel, or through the Apify API.

For quick validation, start with maxItems: 3. For broader discovery, increase the limit after confirming the city and property type return the kind of listings you need.

What input does it accept?

{
  "location": "Amsterdam",
  "operation": "sale",
  "propertyType": "apartment",
  "maxItems": 25,
  "datasetId": "",
  "runId": "funda-amsterdam-sale-2026-08-17"
}

Input	Type	Required	Description
location	String	Yes	Dutch city to search. Examples: Amsterdam, Rotterdam, Utrecht, The Hague, Eindhoven, Groningen, Haarlem, Maastricht.
operation	String	Yes	Use sale for properties for sale or rent for rental listings. Default: sale.
propertyType	String	Yes	One of any, apartment, house, land, or commercial. Default: apartment.
maxItems	Integer	No	Maximum listings to save, from 1 to 1000. Default: 3.
datasetId	String	No	Existing Apify dataset ID to append results to in addition to the default run dataset.
runId	String	No	Workflow or parent run ID copied into rows and the RUN_SUMMARY record.

What output should I expect?

{
  "platform": "Funda",
  "listingId": "example-listing-id",
  "title": "Apartment for sale in Amsterdam",
  "url": "https://www.funda.nl/koop/amsterdam/appartement-example/",
  "operation": "sale",
  "propertyType": "apartment",
  "price": 625000,
  "currency": "EUR",
  "priceText": "EUR 625,000",
  "pricePerM2": 7812.5,
  "areaM2": 80,
  "bedrooms": 2,
  "bathrooms": 1,
  "address": "Amsterdam",
  "city": "Amsterdam",
  "country": "Netherlands",
  "description": "Public listing description when available.",
  "features": ["Balcony", "Energy label A"],
  "mainImage": "https://example.com/funda-image.jpg",
  "images": ["https://example.com/funda-image.jpg"],
  "listedAtText": null,
  "scrapedAt": "2026-08-17T10:00:00.000Z",
  "runId": "funda-amsterdam-sale-2026-08-17"
}

Null values mean Funda did not expose the field for that listing or the Actor could not parse it safely.

How can I use it through the Apify API?

curl -X POST "https://api.apify.com/v2/acts/trovevault~funda-property-discovery-scraper/runs" \
  -H "Authorization: Bearer <APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{
    "location": "Amsterdam",
    "operation": "sale",
    "propertyType": "apartment",
    "maxItems": 25,
    "runId": "funda-amsterdam-sale-2026-08-17"
  }'

Use the run details to access the default dataset, or pass datasetId to append Funda rows into a shared dataset used by a larger workflow.

How much does it cost?

This Actor uses Apify pay-per-event pricing. Runtime depends mostly on maxItems, source response speed, and whether detail pages are publicly accessible during the run.

Cost controls:

• test new searches with a small maxItems value
• use city-level locations instead of broad country searches
• split broad market research into separate city runs
• schedule only the searches you actively monitor

How do I troubleshoot common issues?

Issue	Likely cause	What to do
No listings returned	The city, operation, or property type has no public Funda matches at run time.	Try propertyType: "any", check spelling, and test a known city such as Amsterdam.
Fewer rows than maxItems	Funda exposed fewer matching listings or some rows could not be normalized safely.	Treat maxItems as a cap. Broaden the search or run another city.
pricePerM2 is null	Price or area was missing from the source row.	Use priceText and areaM2 when available; keep null-aware downstream logic.
Detail fields are missing	The public listing page did not expose descriptions, images, or features during the run.	Re-run later or use the listing URL for manual review.
Run is slow on a large batch	The source is responding slowly or many detail pages are being enriched.	Lower maxItems and split the job by city or operation.

What are the limitations?

• It reads public Funda pages only; it does not access accounts, broker dashboards, private data, or non-public feeds.
• City-level inputs are more stable than broad national searches.
• Commercial and land availability depends on Funda's public coverage for the selected city.
• Prices, availability, and listing details can change after scraping.
• pricePerM2 is calculated only when both source price and area are available.
• This Actor is for data collection and workflow automation; it is not legal, investment, or valuation advice.

FAQ

Can I provide a Funda search URL?
No. This Actor discovers listings from structured inputs: location, operation, propertyType, and maxItems.

Can it track listings over time?
Yes. Schedule the same input and compare datasets by url, listingId, priceText, and scrapedAt.

Can I combine Funda with other portals?
Yes. Use datasetId for a shared dataset and runId to label which workflow or batch produced each row.

Does it return every Funda listing?
No. It returns public listings that can be discovered and normalized for the selected search. Source coverage and availability can change.

Support

Open an issue on the Actor page with the input JSON, run ID, expected city, and a short description of the problem. Include a sample listing URL when the issue is about a missing or misparsed field.