230,000 Daily Rows Standardized Across 5 EU Property Sites
Monitoring of real estate listings on funda.nl, pararius.com, rentberry.com, rentola.com, and zimmo.be to support the growth of a European property portal.
Learn MoreLamudi is one of the leading real estate platforms in fast-growing markets like the Philippines and Indonesia.
Instead of browsing through hundreds of listings manually, leave it to us. With our Lamudi scraper, we’ll collect accurate and up-to-date data from the platform - fast, clean, and tailored to your request.
Plans from €169/month · Free project assessment · Reply within 1 business day
We use our own tools to scrape Lamudi data. You tell us what you're looking for, and we extract exactly that: residential projects in Jakarta, condos in Manila, or new listings from verified developers.
You’ll receive structured data, filtered to match your needs. Whether you're tracking price trends, analyzing local housing supply, or building your own real estate platform - we handle the backend so you can focus on results.
Lamudi listings offer more than just a price and a photo. We extract detailed property specs, including unit type (e.g. condo, townhouse, apartment), number of bedrooms and bathrooms, floor area, lot size, and availability status (for sale or for rent).
Each listing includes a full address - with city, neighborhood, street name, zip code, and nearby landmarks. We also capture currency (PHP or IDR), furnishing level, listing date, developer or agent name, and whether the post is verified or boosted.
The result is structured housing data you can trust - clean, complete, and easy to work with.
Beyond standard fields, we scrape Lamudi data to collect valuable context that makes your dataset far more actionable and insightful. This includes:
This extended data is ideal for market research, valuation modeling, or building your own local housing database - especially in fast-growing markets like the Philippines and Indonesia.
Lamudi is a global real estate platform focused on high-growth markets. Launched in 2013, Lamudi operates under regional domains rather than a single global site. Visiting lamudi.com redirects users to local platforms such as lamudi.com.ph (Philippines) or lamudi.co.id (Indonesia), reflecting its focus on country-specific real estate markets.
Each localized version is tailored to regional preferences, offering residential and commercial listings for sale and rent. Users can filter by city, neighborhood, developer, or property type, and explore tools like interactive maps, developer profiles, and real-time updates on new projects.
Listings appear in local currencies (e.g. PHP or IDR) and languages, with support for mobile apps, virtual tours, and direct messaging with agents. Whether you're targeting condos in Manila or investment projects in Jakarta, Lamudi remains a trusted source for granular, region-specific housing data.
Get a QuoteDevelopers
Customers worldwide
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€199 / one-time
setup fee - included
€169 / mo
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€229 / mo
setup fee €499
€349 / mo
setup fee €499
€549 / mo
setup fee €799
If you're working with property data in emerging markets, Lamudi is a must-have source - but collecting that data manually is slow and inefficient. Lamudi is rich in localized property listings, yet not designed for large-scale extraction.
Our Lamudi scraper gives you direct access to the structure, listings, and details you need - without the friction of manual collection. It’s a faster way to get reliable housing data, organized for practical use.
Monitoring of real estate listings on funda.nl, pararius.com, rentberry.com, rentola.com, and zimmo.be to support the growth of a European property portal.
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Daily detection of new private property listings in Switzerland on Homegate.ch and ImmoScout24.ch, giving the agency first access to high-value leads.
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Scraping residential listings from Immobilienscout24.de in Germany and Mallorca, including complete data and resized images.
Learn MoreLearn how to use web scraping to solve data problems for your organization
Real estate teams work in a fragmented data landscape. The sites that drive demand in Boston look nothing like the ones that matter in Berlin, São Paulo, Dubai, or Mumbai.
Real estate teams are operating in a data environment that is bigger, faster, and more fragmented than ever. Listings go live and disappear in hours, price cuts happen quietly, and the portals that matter most in each country are rarely the same global “top 5.”
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
At ScrapeIt, we focus on one thing: delivering the exact data you need, without distractions. For platforms like Lamudi, Magicbricks, Imobiliare.ro, and Adondevivir, we’ve already done the groundwork - so you don’t have to deal with crawling, formatting, or cleanup.
We provide what works: housing data, filtered to your goals, and delivered in a way that fits your process.
Yes. We offer flexible export options - whether you need structured output in CSV, Excel, or JSON, we’ll deliver it the way your team prefers.
Absolutely. Our extractor is custom-built for Lamudi’s structure. It’s stable, tested, and maintained by our team.
We focus on precision. Our parsing process is tailored to Lamudi’s layout, ensuring that property specs, location details, and listing metadata are captured cleanly and consistently.
Yes. Whether you're targeting listings from developers, brokers, or owners, we can isolate results by company, service type, or even listing label (e.g. verified, premium).
Lamudi doesn’t offer reviews for individual listings, but in some regions, it shows reviews for projects or locations. If such data is available, we can extract and include it in your dataset.
Step 1 - Make a Request
You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.
Step 2 - Configuring Custom Web Crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Step 3 - Collect and Deliver
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Step 4 - Maintain and Support
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
Scrapeit Sp. z o.o.
10/208 Legionowa str., 15-099, Bialystok, Poland
NIP: 5423457175
REGON: 523384582