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Platform · Hemnet

Hemnet Data Scraping

Swedish sold prices are published against the listing. That single fact makes this the most analytically useful property market we cover.

Hemnet data scraping collects Swedish property listings, asking prices and published final sale prices. That last part is what makes this market unusual: in most countries portal data gives you asking prices and nothing else, and the sold price is either unpublished or sits in a separate registry with a lag. In Sweden the asking-to-sold spread is directly observable on the same record.

Almost every other real-estate page in this project has to explain that asking prices are not transaction prices. Here that caveat mostly does not apply, and it changes what the dataset can answer.

Free pilot on your own Hemnet list, returned in 24 hours. No card, no trial clock — and you keep the sample data either way.

hemnet.jsonl LIVE FEED
{"listing_id":"hm-44120","municipality":"Example kommun", "housing_type":"bostadsratt", "asking_price":3450000,"currency":"SEK", "sold_price":3720000,"sold_date":"2026-08-14", "sold_price_published":true, "spread_pct":7.83, "monthly_fee":3480, "living_area_sqm":62,"supplementary_area_sqm":8, "days_to_sale":19, "note":"a REAL endpoint. most markets only see a listing disappear"} {"listing_id":"hm-88120","monthly_fee":6100, "asking_price":3450000, "fee_adjusted_price":"not_computed", "caution":"same price, very different proposition. capitalising the fee needs YOUR discount rate"} {"bid_history_available":false, "bid_history":"null", "note":"we do NOT reconstruct a bidding path between asking and sold"}
3 of 404,110 listing rows · Swedensold prices published · spread directly observable · schema v1.0

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to Hemnet or its owners. Hemnet 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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Hemnet at a glance

How we handle Hemnet specifically

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

Portal
Hemnet — Sweden
The unusual part
Final sale prices are published against listings
Consequence
Asking-to-sold spread is directly observable
Bidding
Open bidding is the norm rather than sealed offers
Housing type
Bostadsrätt and villa are different products
Monthly fee
Avgift on apartments materially changes total cost
Area basis
Living area and supplementary area recorded separately
Refresh
Daily, with sold prices appearing after completion
Platform specifics

A market where the transaction price is on the listing

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

Asking-to-sold spread, without a registry join

In most markets a portal gives you an asking price and a listing that eventually disappears. Whether it sold, and for how much, requires a separate registry source with different coverage and a lag measured in months.

Swedish practice publishes final sale prices against listings. That produces something directly measurable that almost nowhere else offers:

  • The spread between asking and sold, per property, without a join.
  • Whether a market is selling above or below asking, as an observation rather than an inference.
  • Time from listing to sale, with a real endpoint rather than a disappearance of unknown cause.

We record asking_price, sold_price, sold_date and derived spread_pct, with sold_price_published flagged — because not every listing publishes one, and the share matters.

The honest limit

Not all sales publish a price. We report sold_price_visible_share per batch, and the same caution applies as on our Domain page: a published-price subset may be self-selecting. It is a much larger and more representative subset here than in most markets, and it is still a subset.

Bostadsrätt and villa are different products, and the fee is the reason

Swedish housing splits into apartments held through a housing association (bostadsrätt) and freestanding houses (villa). They are not two sizes of the same thing.

  • A bostadsrätt carries a monthly fee to the association, covering building costs and sometimes heating, water and broadband.
  • The fee varies enormously between associations, and it materially changes total monthly cost.
  • Two apartments at the same price with different fees are different financial propositions.
  • The association's own finances affect the fee's future, and are not on the listing.

housing_type and monthly_fee are on every record and we never compare a price without the fee alongside. We do not compute a fee-adjusted price, because capitalising a monthly fee requires a discount rate and a horizon — both assumptions that belong with you.

Area

Living area and supplementary area are recorded separately. A basement or attic counted into a headline figure would inflate a per-square-metre comparison.

Open bidding, and what we still will not produce

Bidding is visible

Swedish sales commonly run open bidding, with the process more visible than in sealed-bid markets. Where bid history is published against a listing we capture it as a structured series with timestamps.

That supports something rare: observing how bidding progressed rather than only its outcome.

Where bid history is not published, the field is null with a reason. We do not reconstruct a bidding path from the asking and sold prices — the shape between two endpoints is exactly what the data would need to contain.

What we do not collect

  • Bidder identity. Bid amounts and timestamps only, never who bid.
  • Buyer or seller identity, in any form.
  • Agent individual details. Agency is a commercial entity.

Sweden publishes a great deal about property transactions. We collect the commercial facts and not the people, which in a market this transparent is a boundary worth stating rather than assuming.

Scope

What we collect on Hemnet, 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

  • Asking price, sold price and sold date on the same record
  • spread_pct derived, with sold_price_published flagged
  • sold_price_visible_share per batch, since the subset is still a subset
  • housing_type and monthly_fee on every record
  • Living area and supplementary area recorded separately
  • Bid history as a structured series with timestamps where published
  • Null with a reason where bid history is not published
  • Agency name as a commercial entity
  • Time from listing to sale, with a real endpoint

❌ What we do not, and why

  • A fee-adjusted price computed from an assumed discount rate
  • A bidding path reconstructed between asking and sold
  • Bidder, buyer or seller identity in any form
  • Supplementary area folded into a headline area figure
  • Individual agent details

Core Hemnet fields

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

Field What it is on this platform
listing_id / agency_name / municipality / area The listing, agency and geography
housing_type bostadsratt or villa. Different products
asking_price / sold_price / sold_date / spread_pct The spread, directly observable
sold_price_published / sold_price_visible_share Whether, and the batch share
monthly_fee Materially changes total cost on an apartment
living_area_sqm / supplementary_area_sqm Recorded separately
bid_history Structured series with timestamps, where published
bid_history_available Flagged, and null with a reason where not
rooms / build_year / floor As published
days_to_sale With a real endpoint, unlike most markets
observed_at Timestamp
Use cases

What teams do with Hemnet data

Asking-to-sold spread by area

Both prices on the same record, so whether a market is selling above or below asking is an observation rather than an inference — which is not available in most countries without a registry join and a months-long lag.

Bidding progression analysis

Bid history as a timestamped series where published, supporting analysis of how bidding progressed rather than only what it ended at.

Apartment total-cost comparison

Monthly fee alongside price on every bostadsrätt record, since two apartments at the same price with different fees are different financial propositions.

Genuine time-to-sale

A real sale endpoint rather than a listing disappearance of unknown cause, which is what every other portal market has to settle for.

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

Send us a Hemnet 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.

Hemnet is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Hemnet 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 Hemnet-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

Hemnet data scraping: frequently asked questions

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

Yes, where published — Swedish practice publishes final sale prices against listings, which almost no other market does. That makes the asking-to-sold spread directly observable without a registry join.

The limit: not every listing publishes one. We report sold_price_visible_share per batch, and the same caution applies as anywhere — a published-price subset may be self-selecting, even though it is much larger and more representative here than elsewhere.

Because a bostadsrätt carries a fee to the housing association covering building costs and sometimes heating, water and broadband, and it varies enormously between associations.

Two apartments at the same price with different fees are different financial propositions. We never deliver a price without the fee alongside.

No. Capitalising a monthly fee requires a discount rate and a horizon, and both are assumptions that belong with you rather than embedded in a feed.

Where it is published against a listing, yes — as a structured series with timestamps. That supports observing how bidding progressed rather than only its outcome, which is rare.

Where it is not published the field is null with a reason. We do not reconstruct a bidding path from the asking and sold prices, because the shape between two endpoints is exactly what the data would need to contain.

Living area and supplementary area are recorded separately. Folding a basement or attic into a headline figure would inflate a per-square-metre comparison.

We quote individually on listing volume, municipalities and refresh. Sold prices appear after completion, so a programme wanting the spread needs to run long enough to capture both ends.

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

See real Hemnet 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.

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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