Boligsiden.dk Property Scraper: Extract Danish Real Estate Listings

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What Is Boligsiden.dk?

Boligsiden.dk is one of Denmark's most comprehensive real estate platforms, aggregating residential property listings from agencies nationwide. It covers homes for sale, rental properties, and market statistics across Danish municipalities. For anyone conducting property market research, investment analysis, or competitive intelligence, manually collecting listing data is impractical at scale. The Boligsiden.dk Property Scraper automates this, delivering clean, structured records from search result pages.

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Overview

The Boligsiden Property Scraper processes paginated search result URLs from Boligsiden.dk and extracts structured listing data for each property. It is suited for:

• Real estate investors monitoring pricing trends by area
• Proptech developers building Danish property aggregators
• Market analysts tracking days-on-market and price change patterns
• Researchers studying housing supply and demand across Danish regions

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Input Format

The scraper accepts a JSON configuration object with three parameters:

{
  "urls": ["https://www.boligsiden.dk/tilsalg?page=2"],
  "ignore_url_failures": true,
  "max_items_per_url": 20
}

Field	Type	Default	Description
urls	array	—	One or more Boligsiden.dk property search/list page URLs. Supports pagination URLs (e.g., ?page=2). Add URLs one by one or via bulk edit.
max_items_per_url	integer	20	Maximum number of property listings to collect per URL. Increase for broader datasets.
ignore_url_failures	boolean	true	If true, the scraper continues running when individual URLs fail, rather than halting the entire run. Recommended for bulk jobs.

Tip: To collect across multiple pages, add each paginated URL separately — e.g., ?page=1, ?page=2, ?page=3. Filter by property type or municipality using Boligsiden's search filters before copying the URL.

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Output Format

Sample output

{
  "address": {
    "_links": {
      "self": {
        "href": "/addresses/0a3f50b6-89b3-32b8-e044-0003ba298018"
      }
    },
    "address_i_d": "0a3f50b6-89b3-32b8-e044-0003ba298018",
    "allow_new_valuation_info": false,
    "city": {
      "name": "Gram",
      "slug": ""
    },
    "city_name": "Gram",
    "days_on_market": {
      "realtors": null
    },
    "gstkvhx": "05100085__22_______",
    "has_multiple_cases": false,
    "house_number": "22",
    "is_on_market": false,
    "is_public": true,
    "municipality": {
      "municipality_code": 0,
      "name": "",
      "slug": ""
    },
    "place": {
      "bbox": null,
      "coordinates": {
        "lat": 0,
        "lon": 0,
        "type": ""
      },
      "id": 0,
      "name": "Arnum",
      "slug": ""
    },
    "place_name": "Arnum",
    "province": {
      "name": "",
      "province_code": "",
      "region_code": 0,
      "slug": ""
    },
    "road": {
      "municipality_code": 0,
      "name": "Birkevej",
      "road_code": 0,
      "road_i_d": "",
      "slug": ""
    },
    "road_name": "Birkevej",
    "slug": "birkevej-22-6510-gram-05100085__22_______",
    "slug_address": "birkevej-22-6510-gram",
    "zip": {
      "name": "Gram",
      "slug": "",
      "zip_code": 6510
    },
    "zip_code": 6510
  },
  "address_type": "villa",
  "case_id": null,
  "coordinates": {
    "lat": 55.250797,
    "lon": 8.967432,
    "type": "EPSG4326"
  },
  "days_listed": {
    "days": 0
  },
  "housing_area": 112,
  "image": {
    "image_sources": [
      {
        "alt": "Et gult murstenshus med en skråttag står stille ved siden af en brolagt indkørsel. Omgivet af grønne buske og træer under en blå himmel.",
        "size": {
          "height": 400,
          "width": 600
        },
        "url": "https://images.boligsiden.dk/images/case/5e4d0d08-b38c-4036-a708-d4adcace571b/600x400/3e35cd93-e8f5-4e2c-a3c6-c55ec88e1741.webp"
      }
    ]
  },
  "label": "new_on_boligsiden",
  "monthly_expense": 1030,
  "number_of_rooms": 4,
  "per_area_price": 5417,
  "price_cash": 650000,
  "price_change_percentage": 0,
  "realtor": {
    "_links": {
      "self": {
        "href": "/realtors/45d737eb-0a1d-49f7-bc28-6f35cacf931d"
      }
    },
    "association_of_danish_realtors_member": false,
    "association_of_elo_member": false,
    "broadcast": {
      "target": 0
    },
    "contact_information": {},
    "distinction": "realtor",
    "is_new": false,
    "name": "Mikkelsens Ejendomskontor",
    "preferred": false,
    "rating": {},
    "ratings": {
      "buyer": {},
      "seller": {}
    },
    "realtor_branch": {
      "distinction": "",
      "logo": {
        "image_sources": [
          {
            "size": {
              "height": 40,
              "width": 60
            },
            "url": "https://images.boligsiden.dk/images/realtor_branch/e19d6e83-f692-48a6-9541-6c8efddc555b/60x40/ebf6ab97-5c35-44d6-97c9-ce9977ded67b.gif"
          }
        ]
      },
      "name": "",
      "realtor_branch_i_d": ""
    },
    "realtor_i_d": "45d737eb-0a1d-49f7-bc28-6f35cacf931d",
    "slug": "mikkelsens-ejendomskontor-45d737eb0a1d49f7bc286f35cacf931d"
  },
  "slug": "birkevej-22-6510-gram-05100085__22_______",
  "slug_address": "birkevej-22-6510-gram",
  "time_on_market": {
    "current": {
      "days": 0
    },
    "total": {
      "days": 0,
      "realtors": [
        {
          "days": 0,
          "realtor_id": "45d737eb-0a1d-49f7-bc28-6f35cacf931d",
          "realtor_name": "Mikkelsens Ejendomskontor"
        }
      ]
    }
  },
  "year_built": 1972
}

Each property listing returns a record with 18 fields:

Location & Identity

Field	Meaning
Address	Full street address of the property
Address Type	Classification of the address (e.g., road, place)
Slug	URL-friendly identifier for the listing
Slug Address	URL-friendly version of the property address
Coordinates	Geographic coordinates (latitude/longitude) for mapping
Case ID	Unique listing identifier assigned by Boligsiden

Property Characteristics

Field	Meaning
Housing Area	Living area in square metres (m²)
Number Of Rooms	Total room count as listed
Year Built	Year the property was originally constructed
Label	Property type label (e.g., Villa, Rækkehus, Ejerlejlighed)
Image	URL of the primary listing photo

Pricing & Financials

Field	Meaning
Price Cash	Asking price in DKK
Per Area Price	Price per m² (DKK/m²) — useful for cross-listing comparison
Monthly Expense	Estimated monthly ownership cost (e.g., HOA, utilities)
Price Change Percentage	Percentage change from original asking price — indicates negotiation activity

Market Timing

Field	Meaning
Days Listed	Number of days since the listing was first published
Time On Market	Human-readable representation of listing age (e.g., "3 months")

Agent Information

Field	Meaning
Realtor	Name of the agency or agent handling the sale

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How to Use

1. Find search URLs — Go to boligsiden.dk/tilsalg, apply filters (region, property type, price range), then copy the resulting URL.
2. Add pagination — For larger datasets, copy URLs for multiple pages (e.g., ?page=1 through ?page=10).
3. Configure input — Paste URLs into the urls array and set max_items_per_url to match your target volume.
4. Run and export — Start the scraper and download results as JSON, CSV, or Excel.

Common issues:

• Ensure URLs point to list/search pages, not individual property detail pages.
• If results are unexpectedly low, check whether Boligsiden's filters are reflected in the URL (some filters may be session-based).

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Use Cases & Business Value

• Investment screening: Identify underpriced listings using Per Area Price vs. local averages
• Market timing analysis: Use Days Listed and Price Change Percentage to find motivated sellers
• Geographic intelligence: Map listings using Coordinates for spatial analysis
• Agency benchmarking: Track which realtors are most active in specific areas

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Conclusion

The Boligsiden.dk Property Scraper turns Denmark's largest real estate portal into a structured data source — no manual copying, no browser automation setup required. With pricing, location, market timing, and property characteristics all in one record, it's a practical tool for anyone working with Danish real estate data.