How to Use Real Estate Web Scraping to Gain Valuable Insights
Real estate web scraping: a powerful tool for data collection and analysis. Learn how to choose the right data collection method and benefit from real estate web scraping
We collect structured real estate data from Hemnet — already scraped, parsed, and ready to use. Whether you're tracking property trends, comparing Stockholm neighborhoods, or feeding your analytics tools, we deliver comprehensive listing info including prices, addresses, property descriptions, and more — without any setup on your end.
ScrapeIt handles the entire extraction process from Hemnet, helping you scrape Hemnet data without any hassle. We deliver real estate information that’s already filtered, structured, and formatted for use. You don’t need to manage any scripts, proxies, or logins — we take care of the technical side and send you the results. Whether you need CSV files for Excel, JSON feeds for automation, or datasets formatted for dashboards, we customize delivery to match your workflow.
From hemnet.se — Sweden’s largest real estate portal — our Hemnet scraper collects structured information directly from each property listing. This includes the listing title, full street address, postal code, price, property type, living area in square meters, and total number of rooms. We also capture agent and agency details, listing dates, and high-resolution image links. On top of that, Hemnet provides unique fields like energy performance, time on market, and user interest levels — all of which can be included in your export, tailored to your project’s goals.
Hemnet isn’t just a list of homes — it’s a behavioral lens into how Swedes search, compare, and decide on property. With ScrapeIt, you can tap into user interaction signals like how many times a listing has been saved, how long it’s been active, or whether it's trending within a certain region. We also monitor shifts in seller strategies — like when listings are relisted, re-priced, or moved between visibility tiers. In areas with heavy demand, Hemnet surfaces insights into market pressure and listing performance that go well beyond what’s visible at first glance — and we make sure those layers aren’t left behind.
Hemnet is Sweden’s most visited property portal and the default starting point for anyone searching for real estate in the country. Founded in 1998, it now attracts over 40 million visits per month, with nearly 2 million weekly users — making hemnet.se a critical platform for buyers, sellers, and real estate agents alike.
Around 90% of all residential properties sold in Sweden appear on Hemnet, covering everything from resale homes and rentals to new developments and commercial listings. The site also offers mortgage calculators, energy efficiency data, neighborhood insights, and tools that support decision-making for both individuals and professionals.
Hemnet continuously evolves its offering with features like Hemnet Max (for boosted visibility), agent dashboards, and customized marketing tools for sellers. Its commitment to data-driven UX, coupled with high platform trust, has positioned it as one of the most information-rich and influential real estate ecosystems in Europe.
Get a QuoteDevelopers
Customers
Pages extracted
Hours saved for our clients
Customized scraping setup for Hemnet — 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
Sweden’s housing market is competitive and fast-moving — and Hemnet holds the most complete picture of it. With a Hemnet scraper, you can monitor property values by region, track price changes over time, and compare listings across hundreds of districts and postal codes. This data is essential for real estate analytics, CRM integrations, competitive intelligence, and bulk content population. Whether you're building tools for buyers, aggregating market snapshots, or feeding internal dashboards, structured exports from Hemnet give you a reliable, scalable foundation to work with.
Learn how to use web scraping to solve data problems for your organization
Real estate web scraping: a powerful tool for data collection and analysis. Learn how to choose the right data collection method and benefit from real estate web scraping
Amazon provides valuable information gathered in one place: products, reviews, ratings, exclusive offers, news, etc. So scraping data from Amazon will help solve the problems of the time-consuming process of extracting data from e-commerce.
The use of sentiment analysis tools in business benefits not only companies but also their customers by allowing them to improve products and services, identify the strengths and weaknesses of competitors' products, and create targeted advertising.
At ScrapeIt, we specialize in delivering high-quality real estate data without the usual friction. You don’t need to touch code or manage infrastructure — we scrape Hemnet data and other real estate platforms to collect, structure, and deliver the exact information you need. Our scrapers are built to align with your goals, whether that means weekly updates, focused regional datasets, or API-ready exports. Behind every delivery is a real team that fine-tunes the process to fit your tools, timelines, and use case — efficiently and accurately.
Absolutely. Hemnet listings often display dynamic elements like price history, bidding status, or time-on-market — we track and include them in your export if needed.
Yes — we can deliver fresh datasets daily, weekly, or at intervals aligned with your internal processes or reporting cycles.
Of course. Whether you're focused on Stockholm suburbs, rural listings in Dalarna, or selected postal codes, we tailor the extraction to your exact scope.
We provide outputs in CSV, Excel, or JSON — fully structured and ready for your tools, APIs, or custom applications.
No. ScrapeIt handles the entire data collection process. You don’t need access credentials or scraping infrastructure — just the results.
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.
Scrapeit Sp. z o.o.
10/208 Legionowa str., 15-099, Bialystok, Poland
NIP: 5423457175
REGON: 523384582