Custom data extraction from Zimmo.be, the Mediahuis-owned property portal covering Flanders, Brussels and Wallonia.
We build a crawler around your search scope rather than a generic spider: the property types, regions and price bands you actually care about. It walks result pages, opens each listing, normalizes the fields into one schema and re-checks the set on the schedule you choose - a single run, or daily, weekly or monthly. Changes are tracked, so you receive new, updated, reduced and removed listings instead of a flat dump. Output arrives as CSV, Excel or JSON, or straight into your database. Monitoring and repairs after site changes stay on our side.
We pull every field a listing exposes: reference and URL, title and full description in Dutch or French, asking price or rent, recorded price changes, transaction and property type, address detail, municipality, postcode and coordinates, habitable and plot surface, room and bathroom counts, construction year, energy label and condition, garden, terrace, garage and parking attributes, photo and floor plan URLs, virtual tour links, publication and update dates, and the publishing agency, notary or developer with office and contact details.
A single Zimmo.be card tells you what one seller wants today. A monitored feed tells you what the market is doing. Because listings stay visible over time and the portal surfaces price context, a longitudinal pull yields time on market, the size and timing of every price cut, relisting patterns and the share of stock that disappears without a visible reduction. Aggregating by the publishing party turns the same rows into an agency and notary map: who dominates which postcode, average asking price per office, portfolio size, rental versus sale mix and how quickly each office turns its stock over. None of that is stated anywhere on the page itself.
Zimmo.be is a Belgian property marketplace launched in 2008 and owned by the Flemish media group Mediahuis since 2013. It aggregates the online supply of estate agents, notaries and developers, and it sits second in the Belgian market behind Immoweb.
The portal grew largely by absorbing its rivals. In 2018 Mediahuis folded the classifieds site Hebbes.be into Zimmo, and in 2023 Zimmo acquired Logic-Immo.be from the IPM Group and redirected that domain into its own. Logic-Immo was strong in French-speaking Wallonia, so the deal turned a Flanders-centered site into a portal with real depth in Brussels and the south as well.
Zimmo runs in Dutch and French and covers Belgium end to end, with a smaller stream of foreign listings. The company describes its catalog as more than 125,000 property ads. Supply spans both sale and rental, from apartments and townhouses to villas and land, and listings are also distributed through Mediahuis titles such as Gazet van Antwerpen and Het Belang van Limburg.
Search works by municipality and postcode, by hand-drawn areas on the map, and by price, property type and surface, with saved searches and alerts for returning buyers. Zimmo also publishes price context on listings and runs the free Prijswijzer valuation tool, built with the geodata startup Rockestate, plus Multilist, an MLS-style sharing platform for agents.
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Developers
Customers worldwide
Pages extracted
Hours saved for our clients
€199 / one-time
setup fee - included
€169 / mo
setup fee €499
€229 / mo
setup fee €499
€349 / mo
setup fee €499
€549 / mo
setup fee €799
Belgian pricing is intensely local, and asking prices can diverge sharply between municipalities only a few kilometers apart. Zimmo.be is one of the few places where Flemish, Brussels and Walloon supply sits inside one index with one filter set, which makes it a natural base for market work. Agencies benchmark their own stock against everything nearby. Investors and proptech teams model yields, measure how long units stay online and catch price reductions early. Valuation and mortgage products use the feed as a live comparable set. Doing the same by hand means opening thousands of pages a week and still having no history.
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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
ScrapeIt builds web scrapers to order, and Zimmo.be is not a first encounter for us. It was one of five European property sites - alongside funda.nl, pararius.com, rentberry.com and rentola.com - in a single listing monitoring project for a growing European property portal, launched in three weeks. The harder half of that job was not extraction but standardization: reports from five very different sites had to arrive in one structure the client's analytics pipeline could read without adapters.
Yes. The portal runs in Dutch and French and covers Flanders, Brussels and Wallonia, the latter reinforced by the Logic-Immo integration. We collect either language version or both, with fields normalized into a single output schema.
Whatever your use case needs. Collection can be a one-time snapshot or a scheduled run - daily, weekly or monthly. Daily runs are the usual choice when you track price cuts and time on market on active stock.
CSV, Excel or JSON, whichever fits your workflow, or delivery directly into your database. If you already collect other property sites, we can match the Zimmo output to the structure you use today.
Yes, and that is a common request. We have run Zimmo alongside funda.nl, pararius.com, rentberry.com and rentola.com in one project, unifying five different listing structures into a single consistent set of reports.
The engineering effort sits in coverage and data quality rather than access, since property listings are published openly. We handle page rendering, pagination, field normalization and repairs whenever the site's markup or filters change.
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.
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