Finn Scraper — Listings, Prices, Sellers & GPS

Finn.no Scraper 🇳🇴 — Norway Classifieds Listings, Prices, Sellers & GPS

The most reliable way to scrape Finn.no — Norway's largest classifieds marketplace — at scale with zero accounts, no cookies and no API key required. This Finn scraper converts any Norwegian search keyword or marketplace URL into a rich, structured dataset: price in NOK, seller type (private vs. commercial retailer), location with precise GPS coordinates, ISO publish date, brand name, technical specifications and attributes, photo galleries, and the full plain-text ad description with optional detail enrichment.

Export everything to JSON, CSV, Excel, or API in one automated run — ready for spreadsheets, databases, dashboards, price-tracking bots, and AI pipelines.

Built for e-commerce resellers, flippers and arbitrage hunters, B2B sales & lead generation teams targeting Norwegian retail businesses, price-monitoring & economic researchers, used-car dealerships and automotive analysts, and developers who need clean classifieds intelligence through an automated API.

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⚡ At a glance

Feature	Specification
Target Website	Finn.no (Norway)
Search Methods	Search terms (keywords), Start URLs with pre-set filters
Data Enrichment	Price (NOK), seller classification, GPS latitude/longitude, brand, full descriptions
Pagination Support	Unlocked deep multi-page crawling (1,000+ items per search term)
Typical Run Time	~10–18 seconds for 100 listings; ~45–60 seconds for 500 listings
Proxy Support	Apify Proxy Datacenter enabled by default (Residential NO available)
Export Formats	JSON, CSV, XML, Excel (XLSX), HTML Table, Apify Dataset API
Deduplication	Automatic unique ad ID deduplication across all search sources

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🔎 Why scrape Finn.no?

Finn.no is Norway's undisputed marketplace monopoly — the single online destination where Norwegians buy and sell automobiles, consumer electronics, designer furniture, sports gear, boats, real estate, and everyday second-hand goods. For virtually any consumer product, Finn represents the true live market supply, realistic clearing prices, and the distribution between private hobbyist sellers and established commercial retail shops.

Manually gathering this market intelligence is extremely inefficient. Finn displays approximately 50 listings per page, and common search terms easily span hundreds of pages. Each item card disperses the asking price, municipality name, image assets, seller status badges, and technical tags across a dynamic web layout. Manually copying listings into a spreadsheet is impractical and quickly outdated.

This Finn.no scraper completely automates market harvesting. Provide any search keyword (e.g., iphone, volvo v70, sofa, sykkel) or paste a pre-filtered Finn search URL. The actor traverses result pages, parses all structured attributes, eliminates duplicate listings, and delivers a normalized data table ready for immediate analysis.

Core use cases for automated Finn.no scraping:

• 💰 Second-Hand Price Benchmarking — track asking prices for used smartphones, gaming consoles, designer furniture, outdoor gear, and auto parts across Norway.
• 🎯 Norwegian Retailer Lead Generation — filter out private consumer listings (sellerType: retailer) to build targeted B2B merchant directories in specific vertical niches.
• 📈 Market Supply & Liquidity Tracking — monitor inventory velocity, average price movements, and regional supply changes over time.
• 🚗 Automotive Intelligence & Appraisal — collect vehicle model titles, odometer readings, asking prices, and geographic coordinates for valuation algorithms.
• 🗺️ Geographic Market Mapping — visualize supply density across Norwegian counties using exact latitude and longitude coordinates on every listing.
• 🤖 AI & E-Commerce Repricing — feed verified second-hand pricing data into machine learning models and dynamic repricing systems.

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✨ What this Finn scraper does

• 🔎 Keyword Search Across All Categories — enter keywords like iphone, volvo v70, sofa, sykkel, or rolex to discover live listings across any category.
• 🔗 Direct Start URLs — copy search URLs directly from your web browser; all category, location, and price filters are preserved and scraped faithfully.
• 🔁 Unlocked Deep Pagination — automatically paginates through consecutive pages (?page=1, ?page=2, …) to gather hundreds to thousands of de-duplicated listings per execution.
• 💰 Clean Numeric Pricing — captures exact price as a clean number alongside currency (NOK), ready for calculations and financial models.
• 👤 Seller Type Classification — explicitly separates private sellers from commercial retailer dealers on every listing.
• 📍 Location & GPS Coordinates — extracts human-readable municipal locations alongside exact lat and lng floating-point coordinates.
• 🕒 Standardized Timestamps — converts native posting timestamps into standardized ISO 8601 publishedDate records.
• 🏷️ Brand & Custom Attributes — captures declared product brands and nested attribute dictionaries (e.g., storage capacity, color, year).
• 🚚 Transactional Badges — records boolean flags for shipping availability (isShippable), 1-click purchase (canBuyNow / Kjøp nå), and free delivery (sellerPaysShipping).
• 🖼️ Full Photo Assets — retrieves primary thumbnail links alongside arrays of high-resolution product photography.
• 📝 Full Ad Descriptions — optional detail enrichment extracts full ad descriptions directly from item pages.
• ⚡ High Throughput & Low Cost — pure HTTP extraction over datacenter proxies; scrapes 500 listings in ~30–40 seconds.

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🎯 Use cases

• E-Commerce Resellers & Arbitrageurs — identify underpriced consumer goods and monitor resale margins across electronics, fashion, and luxury watches.
• B2B Sales Teams — extract active retail shops, boutiques, and used-car dealerships across Norway for sales outreach.
• Used-Car Dealerships — capture asking prices, mileage, equipment levels, and dealer identities across the Norwegian auto sector.
• PropTech & Regional Marketplaces — aggregate Norwegian classifieds inventory to power vertical search portals and buyer alert bots.
• Logistics & Supply Chain Planners — map regional supply availability across Oslo, Bergen, Trondheim, Stavanger, and Tromsø using GPS coordinates.
• Data Analysts & Economists — build comprehensive historical datasets tracking inflation, consumer purchasing power, and second-hand retail health in Norway.

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📥 Input parameters

Configure runs in the Apify Console or pass JSON parameters via the API. All parameters are optional:

Parameter	Type	Default	Description
searchTerms	array	["iphone"]	Keywords to search across Finn categories (e.g., iphone, volvo v70, spisebord). Each term is scraped independently.
startUrls	array	[]	Direct Finn search URLs with pre-applied filters (e.g., specific subcategories, price brackets). Overrides search terms.
sellerType	string	""	Filter by seller classification: "" (Any seller), "private" (Private individuals), or "retailer" (Commercial businesses/dealers).
priceMin	integer	null	Minimum price threshold in NOK (inclusive).
priceMax	integer	null	Maximum price threshold in NOK (inclusive).
maxItems	integer	0 (prefill: 100)	Maximum number of listings to collect. Set to 0 for unlimited extraction.
maxPagesPerSearch	integer	0	Maximum result pages to scrape per query (~50 listings per page). Set to 0 for unlimited pagination.
fetchDetails	boolean	false	Visit each individual listing page to collect the full plain-text ad description.
proxyConfiguration	object	Datacenter	Apify Proxy configuration. Datacenter proxies work reliably out of the box.

Input JSON example — Consumer electronics in Oslo

{
  "searchTerms": ["iPhone 15 Pro", "MacBook Pro M3"],
  "sellerType": "private",
  "priceMin": 5000,
  "maxItems": 150
}

Input JSON example — Used vehicles with dealer filter

{
  "searchTerms": ["Volvo XC60", "Audi e-tron"],
  "sellerType": "retailer",
  "fetchDetails": false,
  "maxItems": 200
}

Input JSON example — Start URL with specific category filter

{
  "startUrls": ["https://www.finn.no/recommerce/forsale/search?q=spisebord"],
  "maxItems": 500
}

Input JSON example — Nationwide B2B retailer lead sourcing

{
  "searchTerms": ["sykkelverksted", "urmaker", "bruktbil"],
  "sellerType": "retailer",
  "fetchDetails": false,
  "maxItems": 250
}

Input JSON example — Fast preview run (empty default)

{
  "maxItems": 50
}

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📤 Output dataset

Every listing scraped is saved as an individual record in the Apify default dataset.

Sample record (core listing)

{
  "id": "378942109",
  "url": "https://www.finn.no/recommerce/forsale/item/378942109",
  "title": "Apple iPhone 15 Pro 128GB Blå Titan - Som ny",
  "price": 9200,
  "currency": "NOK",
  "tradeType": "Til salgs",
  "sellerType": "private",
  "location": "0371 Oslo",
  "lat": 59.9328,
  "lng": 10.7061,
  "publishedDate": "2026-11-09T18:42:10.000Z",
  "brand": "Apple",
  "isShippable": true,
  "sellerPaysShipping": false,
  "canBuyNow": true,
  "labels": ["Fiks ferdig", "Brukt"],
  "imageUrl": "https://images.finncdn.no/dynamic/1280w/2026/11/vertical-0/09/9/378/942/109_1.jpg",
  "images": [
    "https://images.finncdn.no/dynamic/1280w/2026/11/vertical-0/09/9/378/942/109_1.jpg",
    "https://images.finncdn.no/dynamic/1280w/2026/11/vertical-0/09/9/378/942/109_2.jpg"
  ],
  "attributes": {
    "storage": "128 GB",
    "color": "Blå Titan",
    "condition": "Som ny"
  },
  "description": null,
  "searchTerm": "iphone",
  "scrapedAt": "2026-11-10T14:45:12.180Z"
}

---

📊 Field coverage & dictionary

🛍️ Item overview & pricing

Field Name	Type	Coverage	Description
id	String	🟢 High (100%)	Unique Finn listing identifier (ad ID).
title	String	🟢 High (100%)	Full advertisement headline.
url	String	🟢 High (100%)	Direct canonical link to the item on Finn.no.
price	Number	🟢 High (98%)	Asking price as a clean number (null if "Gis bort" / free).
currency	String	🟢 High (100%)	Currency identifier (predominantly NOK).
tradeType	String	🟢 High (100%)	Transaction type (e.g., Til salgs, Gis bort, Ønskes kjøpt).

👤 Seller & geographic data

Field Name	Type	Coverage	Description
sellerType	String	🟢 High (100%)	Seller classification: private (individual) or retailer (dealer/shop).
location	String	🟢 High (99%)	Municipality and postal area text (e.g., 0371 Oslo, 5003 Bergen).
lat	Number	🟢 High (96%)	Geographic latitude coordinate.
lng	Number	🟢 High (96%)	Geographic longitude coordinate.
publishedDate	String	🟢 High (100%)	ISO 8601 timestamp when the listing was created.

🏷️ Product specifications & media

Field Name	Type	Coverage	Description
brand	String	🟡 Conditional (65%)	Disclosed product brand (e.g., Apple, Volvo, IKEA).
attributes	Object	🟢 High (85%)	Key-value dictionary of product specifications (storage, model, size).
imageUrl	String	🟢 High (98%)	Primary hero image URL.
images	Array	🟢 High (98%)	Array of all high-resolution gallery image URLs.
description	String	🟡 Conditional (100% when details on)	Plain-text ad description from item page (null when details off).
isShippable	Boolean	🟢 High (100%)	true if item supports Norwegian parcel shipping.
canBuyNow	Boolean	🟢 High (100%)	true if item supports Finn's "Fiks ferdig" direct purchase checkout.
labels	Array	🟢 High (95%)	Promotional and condition badges attached to the card.
searchTerm	String	🟢 High (100%)	Search keyword responsible for discovering the record.
scrapedAt	String	🟢 High (100%)	ISO 8601 timestamp when the data was extracted.

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⚡ Performance & execution benchmarks

Listings Requested	Details Mode	Concurrency	Average Run Time	Memory Usage
100 listings	❌ No	N/A	10–15 seconds	~110 MB
500 listings	❌ No	N/A	30–40 seconds	~135 MB
1,000 listings	❌ No	N/A	65–85 seconds	~170 MB
2,500 listings	❌ No	N/A	2.5–3.5 minutes	~220 MB
100 listings	✅ Yes	5	30–45 seconds	~150 MB
500 listings	✅ Yes	5	2.0–3.0 minutes	~210 MB

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💡 Best practices for scraping Finn.no

1. Focus on keyword specificity: Use specific model names (volvo v70 d4, iphone 15 pro max) rather than generic terms (bil, telefon) to maximize high-relevance matches.
2. Retailer lead generation: Set sellerType: "retailer" to immediately strip out private sellers and generate qualified directories of Norwegian dealers, boutiques, and merchants.
3. Preserving browser filters: Apply complex category, condition, and distance filters directly on finn.no, copy the browser URL, and paste it into startUrls.
4. Optimizing run speed: Keep fetchDetails: false unless you specifically require the full advertisement copy. The default list mode retrieves price, seller type, GPS, brand, and photos at 5x higher speed.
5. Geographic clustering: Group exported datasets by postal code or location (e.g., Oslo, Bergen, Trondheim) to calculate localized price differentials and identify regional arbitrage opportunities.

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🌐 The Nordic classifieds ecosystem

Finn.no is part of the Schibsted / Adevinta recommerce family, sharing underlying architectural patterns with the leading marketplaces across Northern Europe:

Portal	Country	Local Currency	Dominant Categories
Finn.no	Norway	NOK	Automotive, Electronics, Furniture, Boats
Blocket.se	Sweden	SEK	Cars, Electronics, Home & Garden
Tori.fi	Finland	EUR	Consumer Goods, Vehicles, Housing
DBA.dk	Denmark	DKK	Second-Hand Goods, Bicycles, Design

By pairing this actor with our regional Nordic scrapers, multi-national retail analysts can monitor consumer price indices and second-hand inventory across Scandinavia seamlessly.

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🔁 Deep pagination & scaling

• Automated page traversal: The actor reads the search metadata and systematically iterates through all available result pages up to maxItems.
• Deduplication guarantee: Every listing is de-duplicated by its unique id across all queries and Start URLs, ensuring zero duplicate records in your dataset.
• Unlimited extraction: Setting maxItems: 0 and maxPagesPerSearch: 0 allows the scraper to gather the entire active catalog matching your query.

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🔄 Automation & webhook integrations

You can seamlessly connect this actor to automated pipelines using Apify integrations:

• Google Sheets: Automatically append newly scraped Finn listings to a shared spreadsheet for instant team access.
• Slack & Discord Alerts: Send real-time webhook notifications whenever a rare item (e.g., vintage watch or underpriced vehicle) is discovered.
• Make (Integromat) & Zapier: Build zero-code workflows that sync commercial retailer leads (sellerType: retailer) directly into HubSpot, Salesforce, or Pipedrive.
• Amazon S3 & BigQuery: Stream thousands of categorized second-hand records into data lakes for historical trend analysis.

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💻 Programmatic integration

Node.js / JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({
    token: 'YOUR_APIFY_TOKEN',
});

const run = await client.actor('haketa/finn-scraper').call({
    searchTerms: ['iphone 15 pro'],
    sellerType: 'private',
    priceMin: 6000,
    priceMax: 11000,
    maxItems: 100,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Retrieved ${items.length} Finn listings:`);
console.table(items.slice(0, 5), ['title', 'price', 'sellerType', 'location']);

Python

from apify_client import ApifyClient

client = ApifyClient('YOUR_APIFY_TOKEN')

run_input = {
    'searchTerms': ['Volvo V90'],
    'sellerType': 'retailer',
    'maxItems': 150,
}

run = client.actor('haketa/finn-scraper').call(run_input=run_input)

dataset_items = client.dataset(run['defaultDatasetId']).list_items().items
print(f"Collected {len(dataset_items)} vehicle records from Finn:")
for item in dataset_items[:5]:
    print(f"- {item.get('title')}: {item.get('price')} NOK ({item.get('location')})")

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❓ Frequently Asked Questions (FAQ)

How fresh is the data?

Every execution pulls live data directly from Finn.no servers. Results reflect current listings and asking prices at the moment of execution.

Are GPS coordinates included for all listings?

Approximately 95–97% of listings on Finn include geographic latitude and longitude coordinates derived from municipal postal codes.

Can I tell private hobby sellers apart from commercial shops?

Yes. Every listing is tagged with sellerType set to either private or retailer. This allows sales teams to immediately filter out private consumers and extract commercial businesses for B2B lead generation.

Can I schedule automated monitoring runs?

Yes. You can configure scheduled runs using the Apify Console Scheduler (e.g. hourly or daily) and receive automatic notifications via webhooks, Slack, or email when new items appear.

Do I need to provide residential proxy credentials?

No. Apify Datacenter proxies are configured automatically and handle all requests reliably without rate limits.

What happens if an item is listed for free (Gis bort)?

When an item is given away for free under Finn's "Gis bort" category, tradeType is set to Gis bort and the numeric price attribute returns null or 0.

Can I scrape full photo galleries?

Yes. Every record includes imageUrl for the primary thumbnail and an images array containing full-resolution URLs for every photo uploaded by the seller.

How does deduplication work across multiple search terms?

Every listing on Finn possesses a unique numeric ad ID. The scraper tracks all discovered IDs during a run and ensures each item is written to the dataset only once, even if it matches multiple keywords.

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📋 Changelog

Version 1.2 — November 2026

• Deep Pagination Unlocked: Upgraded pagination loop to support deep crawling past 1,000+ listings without artificial limits.
• Fast Prefill Sampling: Configured quick default prefill (100 items) for rapid sub-20 second evaluation runs.
• Schema & View Alignment: Verified dataset view compatibility and set maxPagesPerSearch default to 0 (unlimited).
• Attribute Parsing Enhancements: Improved extraction for nested technical specifications and shipping flags.

Version 1.1 — October 2026

• GPS Coordinates Normalization: Added structured parsing for latitude and longitude coordinates.
• Seller Classification: Enhanced detection for commercial retailer vs. private seller badges.

Version 1.0 — Initial Release

• Core Search Engine: Direct scraping of Finn.no marketplace listings by keyword and URL.
• Universal Export: JSON, CSV, and Excel compatibility.