Finn.no Property Scraper

Extract comprehensive Finn.no property listings with rich market details, broker contacts, viewing information, and neighborhood signals. Collect clean real-estate data for research, monitoring, lead generation, and relocation planning with a workflow built for fast, reliable runs.

Features

• Rich listing data - Collect pricing, area, ownership, bedroom, and status information from Finn.no property ads.
• Broker contact details - Save company names, agent names, phone numbers, emails, and homepage links when available.
• Neighborhood insights - Capture nearby transport, shopping, school, and recommendation data for each listing.
• Flexible search inputs - Start from a Finn search URL and refine results with keyword, location, and page limits.
• Clean output - Remove duplicates and empty values before saving records to the dataset.

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Use Cases

Market Research

Track asking prices, total prices, area sizes, and listing types across neighborhoods or cities. Use the dataset to compare inventory and identify pricing patterns.

Lead Generation

Build lists of active broker contacts, agency names, and listing URLs for outreach or sales research. The output is structured for easy export into business tools.

Relocation Planning

Compare homes by bedrooms, area, ownership type, viewing availability, and neighborhood context before moving. This helps narrow down the most suitable properties faster.

Portfolio Monitoring

Re-run the same Finn search regularly to monitor new listings, planned homes, and changes in available inventory. This is useful for investors and analysts who want recurring snapshots.

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Input Parameters

Parameter	Type	Required	Default	Description
startUrl	String	No	https://www.finn.no/realestate/homes/search.html	Finn homes-for-sale search URL. Use this to apply site-side filters before running the actor.
keyword	String	No	""	Optional text filter matched against listing titles, addresses, and ad text.
location	String	No	""	Optional text filter matched against listing location and address text.
results_wanted	Integer	No	20	Maximum number of dataset items to save.
max_pages	Integer	No	5	Safety cap for paginated search result pages.
proxyConfiguration	Object	No	{"useApifyProxy": false}	Optional proxy settings for larger or repeated runs.

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Output Data

Each dataset item can include the following fields:

Field	Type	Description
finnkode	String	Finn listing identifier.
url	String	Property ad URL.
listing_type	String	Listing type such as homes, project, or planned.
status	String	Listing status when visible.
title	String	Listing title.
address	String	Property address or map label.
asking_price	String	Advertised asking price.
total_price	String	Advertised total price.
shared_costs_month	String	Shared monthly costs when available.
municipal_fees_year	String	Municipal fees per year.
property_tax_year	String	Property tax per year.
property_type	String	Property category.
ownership_type	String	Ownership type.
bedrooms	Integer	Bedroom count.
rooms	Integer	Room count.
living_area_sqm	Integer	Internal living area in square meters.
usable_area_sqm	Integer	Usable area in square meters.
external_area_sqm	Integer	External area in square meters.
balcony_area_sqm	Integer	Balcony or terrace area in square meters.
lot_area_sqm	Integer	Plot size in square meters.
build_year	Integer	Construction year.
energy_label	String	Energy label.
broker_company	String	Broker company name.
broker_homepage_url	String	Broker website.
broker_logo_url	String	Broker logo URL.
agent_name	String	Agent name.
agent_title	String	Agent role or title.
agent_phone	String	Agent phone number.
agent_email	String	Agent email address.
next_viewing	String	Upcoming viewing text.
facilities	String	Facilities summary.
description	String	Main property description.
image_urls	Array	Listing image URLs.
ownership_history_url	String	Ownership-history link.
price_statistics_url	String	Price-statistics link.
area_profile_url	String	Neighborhood profile link.
nearby_public_transport	Array	Nearby transport options.
nearby_shopping	Array	Nearby shopping options.
nearby_schools	Array	Nearby school options.
neighborhood_recommended_for	Array	Neighborhood profile tags.
reference	String	Broker reference value.
last_modified	String	Last modified timestamp on the ad.
scraped_at	String	ISO timestamp for dataset write time.

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Usage Examples

Default Run

Use the standard Finn homes-for-sale search page:

{
  "startUrl": "https://www.finn.no/realestate/homes/search.html",
  "results_wanted": 20,
  "max_pages": 2
}

City-Focused Search

Use a finished Finn search URL for a specific area or filter combination:

{
  "startUrl": "https://www.finn.no/realestate/homes/search.html?location=1.20061",
  "results_wanted": 50,
  "max_pages": 4
}

Keyword And Location Filter

Combine built-in filters with your own search URL:

{
  "startUrl": "https://www.finn.no/realestate/homes/search.html",
  "keyword": "garasje",
  "location": "Trondheim",
  "results_wanted": 30,
  "max_pages": 5
}

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Sample Output

{
  "finnkode": "454908221",
  "url": "https://www.finn.no/realestate/homes/ad.html?finnkode=454908221",
  "listing_type": "homes",
  "status": "Til salgs",
  "title": "Stilfull og oppgradert vertikaldelt halvpart med 3 soverom og 2 bad. Stor terrasse og garasje.",
  "address": "Amalienlyst 1A, 7047 Trondheim",
  "asking_price": "5 850 000 kr",
  "total_price": "5 997 340 kr",
  "shared_costs_month": "400 kr",
  "property_type": "Tomannsbolig",
  "ownership_type": "Eier (Selveier)",
  "bedrooms": 3,
  "rooms": 5,
  "living_area_sqm": 127,
  "usable_area_sqm": 153,
  "external_area_sqm": 26,
  "balcony_area_sqm": 33,
  "lot_area_sqm": 1489,
  "build_year": 1958,
  "broker_company": "DNB Eiendom AS",
  "broker_homepage_url": "https://dnbeiendom.no",
  "agent_name": "Islam Zelimkhanovich Gerikhanov",
  "agent_title": "Daglig leder / Senior Eiendomsmegler",
  "agent_phone": "46 21 50 58",
  "agent_email": "islam.zelimkhanovich.Gerikhanov@dnbeiendom.no",
  "next_viewing": "Mandag, 23. mars 18:30-19:30",
  "area_profile_url": "https://www.finn.no/areaprofile/454908221",
  "nearby_public_transport": [
    "Buss: 5 min",
    "Jernbanestasjon: 13 min"
  ],
  "nearby_shopping": [
    "Dagligvare: 14 min",
    "Kjøpesenter: 15 min"
  ],
  "nearby_schools": [
    "Barneskole: 15 min",
    "Kombinertskole: 16 min"
  ],
  "neighborhood_recommended_for": [
    "Familier med barn",
    "Etablerere",
    "Godt voksne"
  ],
  "reference": "823260099",
  "scraped_at": "2026-03-19T00:00:00.000Z"
}

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Tips for Best Results

Use A Finished Finn Search URL

• Configure area, property type, bedroom count, price range, or ownership filters directly on Finn.no.
• Paste the final Finn URL into startUrl to keep the run precise and stable.

Keep Validation Runs Small

• Use results_wanted: 20 for quick testing.
• Keep max_pages low unless you need a wider inventory sample.

Use Proxies For Larger Runs

• The default flow works without a proxy for standard runs.
• Add proxy settings if you plan to run frequent or high-volume jobs.

Expect Missing Fields Occasionally

• Some listings expose more detail than others.
• The actor keeps only populated values, so output stays clean even when source pages vary.

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Integrations

Connect the dataset to:

• Google Sheets - Export listings for reporting and collaboration.
• Airtable - Build searchable property databases.
• Make - Trigger workflows from new listings.
• Zapier - Automate follow-up actions.
• Webhooks - Send output to custom endpoints.

Export Formats

• JSON - Best for APIs and structured processing.
• CSV - Best for spreadsheets and quick analysis.
• Excel - Best for business reporting.
• XML - Best for system integrations.

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Frequently Asked Questions

Can I scrape a specific city or area?

Yes. The recommended workflow is to configure the search directly on Finn.no and pass the finished URL in startUrl.

Does the actor collect rich property details?

Yes. The output includes pricing, area, ownership, broker contacts, viewing details, and neighborhood information when Finn exposes it.

Are duplicate or empty values kept?

No. The actor removes duplicate, empty, and null-like values before saving each item.

Can I collect project and planned listings?

Yes. If those listings appear in the Finn search results you provide, the actor saves the available fields for them too.

How many listings can I collect?

You can collect as many as the search returns, subject to results_wanted and max_pages.

What should I use for testing?

Start with results_wanted: 20 and a small max_pages value to validate the search before running larger jobs.

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Support

For issues or feature requests, use the Apify Console for the actor.

Resources

• Apify Documentation
• Apify API Reference
• Scheduling Runs

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Legal Notice

This actor is designed for legitimate data collection purposes. Users are responsible for ensuring compliance with website terms of service and applicable laws. Use collected data responsibly and respect rate limits.