Boligsiden is the leading source of reliable real estate data in Denmark. With over 60,000 active listings and millions of historical records, it offers a rich foundation for analysis, market tracking, or building your own tools.
Using our Boligsiden scraper, we collect the data you need — from prices and addresses to sales history and property features. Clean, structured, and ready to use.
You don’t need to build a scraper or figure out APIs. We handle everything.
Just tell us what data matters — regions, price brackets, property types, or archived listings — and we’ll scrape Boligsiden data to match your needs. Delivered in a clean format that fits your workflow, whether for dashboards, reports, or analytics.
Boligsiden is trusted for its depth — not just what's on the market now, but how it got there.
Our scraper collects structured data from Boligsiden, including property descriptions, exact addresses with zip codes, DKK pricing, floor plans, map coordinates, energy ratings, listing timestamps, and how listings change over time.
Perfect for market research, portfolio analysis, benchmarking across regions, or building smarter pricing models.
When we scrape Boligsiden data, we don’t stop at surface-level details. Our extraction includes supplementary signals that help you interpret the context of each property:
These insights make it easier to track market shifts, prioritize opportunities, and refine your analysis with data that goes beyond basic listings.
Boligsiden is Denmark’s most trusted real estate platform — both for current listings and historical property insights. Launched in 2006, it’s operated by the Danish Real Estate Association (DE) and aggregates listings from over 90% of real estate agencies across the country.
With over 60,000 active listings and millions of archived records, Boligsiden offers unmatched transparency into how the housing market evolves — from pricing and availability to long-term sales trends.
The site operates under the domain boligsiden.dk, is available entirely in Danish, and all prices are listed in DKK (Danish krone). Whether you're analyzing urban developments in Copenhagen or rural pricing shifts in Jutland, Boligsiden provides the full picture — with detailed property data, interactive maps, and tools for tracking price trends over time. It’s one of the most trusted platforms in Denmark for both buyers and analysts alike.
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Developers
Customers
Pages extracted
Hours saved for our clients
Customized scraping setup for Boligsiden — faster and cheaper than building a solution from scratch.
Data limits (rows): up to 10%
Iterations: up to 3
Custom requirements: Yes
Data lifetime: up-to-date
Data quality checks: Yes
Delivery deadline: 1-2 working days
Output formats: CSV, JSON, XLSX
Delivery options: e-mail
Boligsiden isn’t just another property portal — it’s a reflection of how the Danish housing market moves and matures. With our Boligsiden scraper, you don’t just get current ads — you access a structured timeline of pricing, sales activity, and property characteristics across Denmark.
By tapping into this data, you get more than listings — you get a timeline of prices, locations, and behaviors that define the local real estate market. Whether you're comparing cities, tracking investment zones, or analyzing price fluctuations — this is the source professionals trust.
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ScrapeIt is a data service company. We collect real estate data from websites like Boligsiden, Immoweb, ERA Belgium, and more — the way you need it.
No tools to set up. No code to write. Just tell us what data you want — we’ll scrape it, clean it, and send it in a format ready for your analysis or product.
Absolutely. We fine-tune our parsing logic based on the listing type — house, apartment, or land — so nothing important gets lost.
Yes. You can request data only from the cities or regions that matter to you.
You can build anything from pricing dashboards to historical sales archives. The data is structured for flexible use.
Yes. We export your data in the format that fits your workflow.
1. Make a request
You tell us which website(s) to scrape, what data to capture, how often to repeat etc.
2. Analysis
An expert analyzes the specs and proposes a lowest cost solution that fits your budget.
3. Work in progress
We configure, deploy and maintain jobs in our cloud to extract data with highest quality. Then we sample the data and send it to you for review.
4. You check the sample
If you are satisfied with the quality of the dataset sample, we finish the data collection and send you the final result.
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