Platform · ImmoWeb

ImmoWeb Data Scraping

Belgian listings run in French and Dutch. Neither is the original, so choosing one loses the other permanently.

ImmoWeb data scraping collects Belgian property listings, asking prices, status and agency attribution. The handling that decides whether the data is usable: Belgium's language regions mean listings appear in French and Dutch, frequently both, and neither is the canonical version. Choosing one and normalising destroys the other, and it cannot be undone.

Our Sobeys page makes this argument for Quebec. Belgium is the harder version, because the language split runs through the market rather than through one region of it.

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immoweb.jsonl LIVE FEED

{"portal":"immoweb","listing_id":"ib-44120", "province":"Example province","language_region":"region-a", "title_fr":"as published, French","title_nl":"as published, Dutch", "language_published":"fr+nl", "asking_price":345000,"matched_on_title":false} {"title_fr":"null","title_nl":"as published, Dutch", "language_published":"nl", "note":"matching this with French text would fail SILENTLY"} {"epc_value":148,"epc_region_scale":"region-a scale", "registration_duty":"not_computed", "caution":"EPC scales differ by region. a cross-region comparison needs the scale"}

3 of 404,220 listing rows · Belgiumboth languages retained · EPC scales never normalised · schema v1.0

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to ImmoWeb or its owners. ImmoWeb and related marks belong to their respective owners, used here only to name the publicly accessible source this service collects from.

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ImmoWeb at a glance

How we handle ImmoWeb specifically

Platform-specific handling, not a generic retail template pointed at a different domain.

Portal: ImmoWeb — Belgium
The point: Listings in French and Dutch
Neither is: Canonical. Both are what was published
So: Both retained, with the published language recorded
Matching: On structure and attributes, never on titles
Regions: Language region is a dimension alongside province
Asking price: Not a transaction price
Refresh: Daily; status changes are the events worth catching

Platform specifics

Two languages, one market

These are the reasons a ImmoWeb dataset needs its own handling rather than a shared retail schema.

Neither language version is the original

Belgian listings are published in French, in Dutch, and frequently in both. The versions are not translations of a master — each is what the agency published for that audience.

Choosing one loses the other, and the lost one cannot be recovered from the kept one.
Descriptions genuinely differ beyond translation, since they were written for different readers.
Matching a Dutch listing using French text fails, and fails silently.
Machine translation into a name or description field is worse, because the error is undetectable to anyone who does not read the source.

We retain title_fr, title_nl, description_fr and description_nl as separate fields, populated where each is published, with language_published recording which versions exist.

Matching runs on structure — address precision, area, room count, price, attributes — never on titles. The argument is on our multilingual page in full.

Language region as a dimension

Belgium's language regions correspond to different property markets with different price levels and dynamics. language_region travels alongside province, and a national average is a computed rollup rather than a primary figure.

Belgian conventions, and what we do not collect

EPC

Energy performance certificates are mandatory on Belgian listings and the scales differ by region, which means an EPC value is not comparable across the language regions without its regional scale.

epc_value, epc_class and epc_region_scale travel together. We do not normalise across scales.

Registration duties

Transfer taxes differ by region and materially affect total acquisition cost. We do not compute them — rates depend on buyer circumstances we cannot observe. The asking price is the asking price.

Status and disappearance

Transitions as timestamped events. A listing disappearing may mean sold, withdrawn or a mandate ending, and the portal does not say which. disappearance_reason is not_determined.

What we do not collect

A translated title or description placed in a language field.
Vendor, buyer, tenant or enquirer data. Never.
A sold price from a portal listing.
An address sharpened beyond publication.

Scope

What we collect on ImmoWeb, and what we do not

The right column matters more than the left. Anyone can list fields; the limits are what tell you whether the dataset will hold up.

✅ What we collect

title_fr, title_nl, description_fr and description_nl as separate fields
language_published recording which versions exist
Matching on structure and attributes, never on titles
language_region alongside province, with national figures as rollups
epc_value, epc_class and epc_region_scale travelling together
No EPC normalisation across regional scales
No registration duty computed
Status transitions as timestamped events
disappearance_reason as not_determined

❌ What we do not, and why

One language chosen and the other discarded
A machine translation placed in a language field
An EPC value compared across regions without its scale
A transfer tax computed from unobservable buyer circumstances
Vendor, buyer, tenant or enquirer data

Core ImmoWeb fields

The full dictionary is agreed during scoping. These are the fields specific to this platform.

Field	What it is on this platform
portal / listing_id / province / language_region	The listing and its market
title_fr / title_nl / language_published	Both retained. Neither canonical
description_fr / description_nl	Written for different readers, not translations
asking_price / price_is_asking / currency	A marketing figure, flagged
epc_value / epc_class / epc_region_scale	Together, or not comparable
living_area_sqm / area_basis	With its measurement basis
matched_on / matched_on_title	Structure, not titles
status / status_changed_at / disappearance_reason	Events, and what we cannot know
address_precision	As published. Never sharpened
agency_name	A commercial entity
observed_at	Timestamp

Use cases

What teams do with ImmoWeb data

Bilingual listing analysis

Both language versions retained, so a listing is analysed and matched without discarding the version an agency actually published for one of its audiences.

Language region market comparison

Language region alongside province, since Belgium's regions correspond to different property markets with different price levels and dynamics.

EPC analysis done correctly

Energy values with their regional scale, since the scales differ and a cross-region comparison without them compares different measurements.

Status lifecycle tracking

Transitions retained as events with the disappearance reason undetermined, since a portal does not say whether a listing sold or a mandate ended.

The 24-hour sample — run on your sources, not ours

Send us a ImmoWeb item or category list. We run real collection against it and return the output within 24 hours, with the platform-specific fields populated so you can check them yourself rather than take our word for it.

Real extraction from your actual sources
Returned within 24 hours
Coverage and QA note included
You keep the data either way
No card, no trial clock
Named engineer on the call

Get my free sample Book a 20-min scoping call Reply within one business day. Reference calls available under NDA.

How we engage

Three ways to engage us

Same collection pipeline and QA underneath. The difference is who holds the schedule and how the data reaches you.

Managed service (most common)

We own the collection, the QA and the delivery. You receive clean data on a schedule and never touch a scraper.

Dedicated engineer assigned to your account
Site changes fixed by us, not reported to you
Scheduled delivery to your warehouse or S3
Named contact on Slack or email

Best fit: Teams who need the data, not the infrastructure.

API access

The same collection pipeline exposed as an authenticated REST endpoint your systems query directly.

On-demand and scheduled endpoints
Rate limits agreed to your load profile
Sandbox keys for integration testing
Versioned schema with deprecation notice

Best fit: Product and engineering teams building on live data.

One-time or project extraction

A defined pull for a specific question — market sizing, diligence, a pitch, a one-off audit.

Fixed scope agreed in writing upfront
Single delivery with full QA report
Methodology documented for your records
Converts to managed if you want continuity

Best fit: Research, strategy and diligence work with a deadline.

Pricing

Every engagement is quoted individually, because the honest answer depends on your scope: how many sources, how many records, how often, and how the data reaches you. We scope it with you, run a free pilot on your own sources, and then quote a fixed monthly figure — no per-request metering and no overage billing when volumes move. Request a quote and you will have a number after one call.

ImmoWeb is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. ImmoWeb data becomes useful when it sits next to the competitor set on one schema, refreshed on one schedule, so a price index or availability comparison is genuinely like-for-like.

That is what real estate data covers, and a ImmoWeb-only engagement can be expanded into it without rebuilding. If you already know you need several platforms, start there instead — it is the same pipeline and usually the better scoping conversation.

FAQ

ImmoWeb data scraping: frequently asked questions

Platform-specific questions, including what cannot be collected here.

Because neither is the original. Each is what the agency published for that audience, and descriptions genuinely differ beyond translation because they were written for different readers.

Choosing one loses the other permanently, and matching a Dutch listing using French text fails silently.

As an additional field if you want it, never as a replacement. A machine translation placed in a description field destroys what was published, and the error is undetectable to anyone who does not read the source.

Because Belgium's language regions correspond to different property markets with different price levels and dynamics. A national average is a computed rollup rather than a primary figure.

Not without their regional scale, and we do not normalise across them. The scales differ, so a value from one region and a value from another are different measurements.

Value, class and scale travel together.

No. Registration duties differ by region and depend on buyer circumstances we cannot observe.

The asking price is the asking price, and computing a total would put an assumption about a buyer into a price column.

We quote individually on geography, listing volume and refresh. Bilingual field handling adds a little but it is what makes the data usable across both language regions.

One scoping call, a free pilot within 24 hours, then a fixed monthly quote. Request a quote.

See real ImmoWeb data before you commit to anything

Send us an item or category list. We return the output within 24 hours with the platform-specific fields populated.

Get a free sample Talk to an engineer

Free pilot, no card, no obligation. If we cannot collect a field you need on this platform, the sample shows you that too.

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