Funda Data: Two Years of Monthly Home Sales by Franchise Territory
Every month a marketing agency gets the homes sold on Funda in the previous month, split by the postcodes of each franchise branch.
Funda scraper for Dutch homes for sale, for rent and sold
A Funda listing pairs the asking price with cadastral data, the energy label and, once sold, the date of sale. Our Funda scraper delivers it per Funda ID.
Plans from €169 a month · Free project assessment · Reply within 1 business day
CSV · Excel · JSON · XML · FTP · SFTP · Amazon S3 · Google Cloud
funda.nlwhat you get
Typical fields for property portals
addresspriceproperty_typebedroomsarea_m2agentlisted_at
Delivery
API, JSON feed or CSV, XLSX and JSON files
ScheduleOne-time, monthly, weekly, daily or 3 times a day
How we scrape Funda for you
- You send
Funda pages, filters, fields and a schedule
- We run the scrapers
Built, monitored and repaired by our team
- You receive the data
API, JSON feed or CSV, XLSX and JSON files
You tell us which part of the Dutch market you need: municipalities, neighbourhoods, postcodes or a radius around a town; koop, huur or nieuwbouw; available homes, sold homes or both; and the fields. We build the Funda crawler, run it once or on your schedule, and keep it working. When Funda changes its page structure, the repair is ours to make, not yours.
Funda sometimes stops a visitor at a check page before it shows a listing, so request pacing, proxy rotation, page rendering and CAPTCHA handling are part of the service. Each project starts with a free assessment, you can order a sample first, and the dataset comes with documentation that maps every Dutch label to its column.
Funda data scraper: fields per listing
Our Funda data scraper reads the full Kenmerken (Features) block of each listing, not only the summary line under the photos. A row is one Funda ID on one run date; cadastral parcels and photos go to child tables, because one home can sit on several parcels.
- IdentityFunda ID, URL, offer type (koop or huur), street and house number, postcode, town and the neighbourhood named under the address, kind of house (single-family home, corner house, row house) and building type: resale property or newly built.
- Transfer of ownershipasking price with its k.k. marker (costs paid by the buyer), asking price per m², status - available, Verkocht onder voorbehoud (Sold under reservation in the English version) or sold - and the acceptance terms, such as in consultation.
- Rentalsrental price per month with the note on service charges, deposit and the rental agreement, for example indefinite duration.
- Surface areas and volumeliving area, other space inside the building, exterior space attached to the building, external storage, plot size and volume in cubic metres.
- Layoutrooms and bedrooms, bathrooms and separate toilets, bathroom facilities, number of stories, the floor an apartment is on, and facilities such as solar panels or mechanical ventilation.
- Construction and energyyear built or construction period, type of roof, energy label, insulation, heating, hot water and the boiler with its make and year.
- Cadastral dataeach parcel's designation (municipality, section and number), its area and the ownership situation: full ownership or leasehold.
- Exterior and parkinglocation (along a waterway, on a quiet road), garden type, back garden size with depth, width and orientation, shed or storage, type of parking.
- Agent and mediathe listing agent's office and the contact named on the listing, description text, photo links and flags for floor plan, 360° photos and video.
Labels come as Funda prints them in Dutch or English and are mapped to one column set, so a Utrecht rental and an Enkhuizen sale share a schema.
Funda sold prices, search pages and repeated runs
Three layers sit outside the Kenmerken block, and each changes what a dataset can answer.
- Sold listingsa home marked Verkocht stays on Funda with its last asking price and a sales history: listed since, date of sale and term in days. That is what Funda sold prices mean in practice: the final asking price and the speed of sale, not the price in the deed, and we name the column accordingly.
- Search pagesevery place search shows a count of matching homes and cards with price, address, living area, plot size, bedrooms, energy label, a one-line pitch, the agent and the New badge. Cards marked Advertentie (Advertisement) and those in the Toppositie block are flagged, because Funda says the default order depends partly on paid placement options.
- Neighbourhood blockeach listing names its neighbourhood with the number of residents, the share of families with children and the average asking price per m² there.
Repeated runs add the time dimension. Daily or weekly snapshots record each asking price, the step from available to sold under reservation to sold, and the run on which a listing left search, which together give a price series and days on market per Funda ID.
How Funda is organised for data buyers
- Source
- funda.nl
- Category
- property portals
- Delivery
- API, JSON feed, CSV, XLSX
- Plans
- From €169 a month
We collect Funda listings for sale, for rent, newly built and sold, one row per listing keyed on the numeric Funda ID that ends every listing URL, on a daily, weekly or monthly schedule. Files arrive as CSV, XLSX or JSON, or through our API, a JSON feed, SFTP or Amazon S3. Plans start from EUR 169 a month, or EUR 199 for a one-time extract. Our case study Funda Data: Monthly Sold Homes by Territory shows one such schedule: a monthly file of sold homes.
Funda (funda.nl) is a housing portal for the Netherlands on which estate agents publish homes for sale and for rent. It has been online since 2001 and runs in Dutch, with an English version under /en/. The top menu splits it into Kopen (buy), Huren (rent), Nieuwbouw (newly built) and Verkopen (sell), and a listing URL spells out the same logic: offer type, town, property type with the street, then the ID. Search starts from a place - town, neighbourhood or postcode - with a radius, filters for price, property type, Days on Funda and floor area, and a running count of homes found.
Each listing names the agent office behind it, and Funda's menu points buyers and sellers to NVM agents. A listing does not vanish when the home sells: it moves from available to Verkocht onder voorbehoud and then to Verkocht, keeping its features, cadastral data and agent. That is why one site serves both current supply and recent sales.
25Developers
500+Customers
1.5BPages extracted
15,000+Hours saved for our clients
Funda scraping plans and pricing
Delivery: CSV, JSON or XLSX files, our API or a JSON feed. MCP server on request.
Full plan detailsFunda scraping: who uses the data and how
Funda puts a price, a surface and a legal status on the same page, so its data answers questions that need all three at once.
- Valuation and comparablesasking price per m² of living area against the neighbourhood average shown on the same page, adjusted for energy label, year built and plot size. Sold listings add the last asking price and the term, a direct read on how fast a type of home sells in a postcode.
- Leasehold and ownershipAmsterdam taglines such as "eeuwigdurend afgekochte erfpacht" (perpetually bought-off leasehold) show why the ownership situation matters; the cadastral data separates leasehold homes from full ownership before anyone compares house prices.
- Sustainabilityenergy label, insulation, heating and solar panels per home show where the stock still depends on a gas boiler, a list installers, lenders and energy advisers ask for.
- Agent market shareevery listing names its agent office, so listings and sales per office and town are a count away, and franchise networks map them onto their own territories.
- Rental yieldrental price, deposit and agreement type from the huur section set against asking prices for similar homes in the koop section.
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Land for sale across Turkey from Sahibinden and HepsiEmlak for a land investor: 226,000 plots in the first file and 86,200 HepsiEmlak rows.
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About ScrapeIt
ScrapeIt is a managed web scraping agency: we design, run and repair the crawlers and deliver the data. Since 2024 we have sent a marketing agency the homes sold on Funda in the previous month, split by the postcodes of each branch of a real estate franchise network - street, house number, postcode, town and price, with new builds and duplicates removed, one Excel tab per branch sorted by price, by FTP and e-mail on the first Monday. Funda had more than 70,000 for-sale listings when it joined that project. Personal data is handled under GDPR.
FAQ
Still unsure? Write to info@scrapeit.io
Do you offer a Funda API for listing and sold data?
Yes. The ScrapeIt Funda API returns the Funda ID, address, asking price, energy label, status and date of sale as JSON from an endpoint we host, refreshed on the schedule you set. The same rows also come as CSV or XLSX files, a JSON feed or a load into your database.
Is it legal to scrape Funda?
Yes. Search pages, listing pages with their features and cadastral data, and sold listings with their sales history are open to any visitor of funda.nl. We collect only publicly available data - everything a visitor can see on Funda - and we collect it legally. Agent offices are named; private persons are left out by default.
Can you scrape Funda sold prices and dates of sale?
Yes, as Funda shows them. A sold listing keeps its last asking price, the listed-since date, the date of sale and the term in days, so you get the time to sell per home. The figure is the last asking price, not the price in the deed, and the column is labelled that way.
Is there Funda price history, and how do you build it?
A listing shows its current asking price, so the dated series comes from our runs. With daily or weekly runs we record each asking price, every move from available to sold under reservation to sold, and the date a listing leaves search. The first run is your baseline, so start before the period you want to analyse.
What does a Funda dataset for one city look like?
One row per Funda ID with the fields above, plus child tables for cadastral parcels and photos. A city run can cover koop, huur and newly built, split by neighbourhood or postcode, and arrives as XLSX, CSV or JSON by SFTP, Amazon S3 or e-mail.
How it works
- 1
Make a request
You share your needs, expectations, and desired timeframe. We'll suggest the best solution based on your request and budget.
- 2
We configure the crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
- 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.
- 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.
Request a quote
Tell us which sites, which fields and how often. A couple of lines is enough to start.
- We reply within 1 business day
- A sample dataset before the full run
- We sign an NDA on request
- Delivery by API, JSON feed or files