Krogsveen.no Property Scraper

Extract complete property listings from Krogsveen.no for market research, portfolio tracking, and lead generation. Collect clean, structured real estate data including prices, location details, areas, bedrooms, and listing links. Built for fast, reliable, automated data collection at scale.

Features

• Structured property extraction — Collect listing data in a clean, analysis-ready format.
• Rich listing details — Include pricing breakdowns, location fields, area metrics, and status values.
• Configurable collection size — Control output volume with results_wanted and max_pages.
• Flexible filtering — Apply advanced filter values through input configuration.
• Optional extended fields — Enable richer outputs such as image URLs and long pricing text.
• Automation-ready output — Export to dataset and connect to downstream tools.

Use Cases

Real Estate Market Monitoring

Track active and upcoming property listings in one place. Compare pricing, areas, and listing trends over time to identify market movements quickly.

Lead Generation Pipelines

Build consistent datasets for prospecting workflows. Use location and listing details to power outreach, segmentation, and CRM enrichment.

Investment Analysis

Collect structured listing data for opportunity scanning and valuation benchmarking. Analyze price-per-area and neighborhood-level inventory signals.

Competitor and Agency Intelligence

Monitor listing activity and changes in target regions. Use regular runs to keep internal dashboards up to date.

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Input Parameters

Parameter	Type	Required	Default	Description
startUrl	String	No	https://www.krogsveen.no/kjope/boliger-til-salgs	Start page URL for collection.
results_wanted	Integer	No	20	Maximum number of listings to collect.
max_pages	Integer	No	10	Safety cap for page-equivalent collection range.
collectDetails	Boolean	No	true	Include extended fields such as images and long pricing text.
proxyConfiguration	Object	No	Apify Proxy Residential preset	Proxy settings for reliability.

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Output Data

Each dataset item contains:

Field	Type	Description
id	String	Unique listing identifier.
address	String	Formatted address string.
streetAddress	String	Street-level address.
apartmentNumber	String or Null	Apartment/unit number when available.
city	String	City name.
zipCode	String	Postal code.
price	Number	Main listing price value.
totalPrice	Number or Null	Total price including applicable costs.
purchaseCosts	Number or Null	Purchase-related costs when included.
commonCosts	Number or Null	Shared/common costs when available.
rentPerMonth	Number or Null	Monthly rent/common fee when available.
propertyType	String	Property type label.
ownershipType	String	Ownership model label.
ownershipTypeCode	Number or Null	Ownership code from source.
bedrooms	Number or Null	Number of bedrooms.
habitableArea	Number or Null	Main living/usable area value.
primaryRoomArea	Number or Null	Primary room area if provided.
totalArea	Number or Null	Total usable area value.
plotArea	Number or Null	Plot/land area if provided.
latitude	Number or Null	Latitude coordinate.
longitude	Number or Null	Longitude coordinate.
status	String or Number	Listing status label/value.
statusCode	Number or Null	Status code when available.
projectId	String or Null	Related project identifier if present.
localAreaName	String or Null	Local area/neighborhood label.
images	Array or Null	Image URL list when extended details are enabled.
url	String	Listing page URL.
_source	String	Source identifier.
scrapedAt	String	ISO timestamp of extraction.

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Usage Examples

Basic Collection

Collect a default batch of listings:

{
  "startUrl": "https://www.krogsveen.no/kjope/boliger-til-salgs",
  "results_wanted": 20
}

Larger Run

Collect a larger dataset for analysis:

{
  "startUrl": "https://www.krogsveen.no/kjope/boliger-til-salgs",
  "results_wanted": 200,
  "max_pages": 10,
  "collectDetails": true
}

Advanced Filtering

Apply custom filtering using query parameters directly in the start URL:

{
  "startUrl": "https://www.krogsveen.no/kjope/boliger-til-salgs?minPrice=3000000&maxPrice=8000000&propertyTypes=Leilighet",
  "results_wanted": 100,
  "collectDetails": true
}

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Sample Output

{
  "id": "AE0F7BC9-9332-4917-B742-F44BEBE7D98F",
  "address": "Sandakerveien 22C, 0473 OSLO",
  "city": "OSLO",
  "zipCode": "0473",
  "price": 5650000,
  "totalPrice": 5802290,
  "propertyType": "Eierleilighet",
  "ownershipType": "Selveier",
  "bedrooms": 1,
  "habitableArea": 48,
  "status": "UPCOMING",
  "url": "https://www.krogsveen.no/kjope/boliger-til-salgs/AE0F7BC9-9332-4917-B742-F44BEBE7D98F",
  "images": [
    "https://cdn.sanity.io/images/u9ed36i9/production/example-1539x1024.jpg"
  ],
  "scrapedAt": "2026-02-24T12:04:48.763Z"
}

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Tips for Best Results

Start With a Small Test

• Begin with results_wanted: 20 to validate filters and output structure.
• Increase volume after confirming field coverage.

Use Stable Start URLs

• Use listing/search URLs that consistently return results.
• Keep query parameters intentional to avoid empty runs.

Enable Extended Details When Needed

• Keep collectDetails: true when images and rich pricing text matter.
• Disable it for lighter, faster runs when only core fields are needed.

Use Proxy for Production Reliability

• Residential proxies improve consistency for scheduled high-volume runs.
• Keep proxy settings enabled in production workflows.

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Integrations

Connect your dataset with:

• Google Sheets — Build reporting sheets and summaries.
• Airtable — Create searchable listing databases.
• Make — Automate downstream enrichment and alerts.
• Zapier — Trigger actions from new listing data.
• Webhooks — Push fresh data to internal systems.

Export Formats

• JSON — Programmatic processing and APIs.
• CSV — Spreadsheet and BI workflows.
• Excel — Stakeholder-ready reporting.
• XML — Legacy system compatibility.

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Frequently Asked Questions

How many listings can I collect?

You can collect large volumes. Use results_wanted to set the target size and max_pages as a safety cap.

Why are some fields null?

Some listings do not provide every field in source data. The actor already applies fallback mapping to maximize populated values.

Can I filter by custom criteria?

Yes. Use query parameters in startUrl (for example price range or property type filters).

Can I include images in the dataset?

Yes. Keep collectDetails enabled to include image URLs and other extended fields.

Is this actor suitable for scheduled monitoring?

Yes. It is designed for recurring runs and structured outputs suitable for monitoring pipelines.

What should I do if a run returns no data?

Verify the start URL and filters first, then run with proxy enabled for better reliability.

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Support

For issues, bug reports, or feature requests, use the Apify Console issue and support channels.

Resources

• Apify Documentation
• Apify API Reference
• Apify Schedules

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Legal Notice

This actor is intended for legitimate data collection and analysis. You are responsible for complying with target site terms, local laws, and applicable data-use policies.