Platform · SpareRoom

SpareRoom Data Scraping

A four-bedroom house let room by room is four listings, four rents and four tenancies. It is not one rental.

SpareRoom data scraping collects room and flatshare listings across the UK. The unit here is a room in a shared property, not the property itself — so a four-bedroom house let room by room generates four listings at four rents. Rent per room and rent per property are different numbers, and a rental index that mixes them is measuring two markets at once.

Every other UK rental source we cover has a property as the unit. This one does not, and the difference is not a detail — it is a separate rental market with its own economics.

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spareroom.jsonl LIVE FEED

{"listing_id":"sr-44120","city":"Manchester", "rent_amount":165,"rent_period":"weekly", "rent_normalised":715.00, "normalisation_basis":"weekly x 4.333 = monthly", "bills_included":"all", "advertiser_type":"agent", "property_cluster_id":"pc-2210","cluster_confidence":0.88, "note":"x4 would give 660 — a 7% understatement across the whole dataset"} {"listing_id":"sr-88120", "rent_amount":620,"rent_period":"monthly", "bills_included":"unstated", "bills_adjusted_rent":"not_estimated", "caution":"unstated is REAL. treating it as excluded understates inclusive listings"} {"occupant_details":"not_collected", "tenant_preferences":"not_collected", "advertiser_contact":"not_collected", "note":"listings describe real identifiable people. none of it belongs in a rental dataset"}

3 of 304,880 room rows · UKcommercial content only · no occupant data · schema v1.0

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

How we handle SpareRoom specifically

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

Source: SpareRoom — UK rooms and flatshares
The unit: A room, not a property
Consequence: Four-bed house let by room = four listings, four rents
Rent basis: Per person per week or month — and the period varies
Bills: Frequently included, which changes what the rent means
Deposits: Regulated in the UK. Captured where stated
Advertiser: Live-in landlord, agent, or current tenant — different markets
Refresh: Daily. Room listings turn over faster than property lets

Platform specifics

What a room-level rental market needs

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

Per room, per person, and per what period

Room rents are quoted per person, and the period is not consistent — some listings quote weekly, some monthly, and the difference is four-point-three weeks rather than four.

A naive weekly-to-monthly conversion using four weeks understates monthly rent by roughly 7%.
We record rent_amount with rent_period exactly as quoted.
Normalised values are derived, with normalisation_basis naming the conversion used.

Bills are the bigger issue

Room lets frequently include some or all bills in the rent. A room at £700 including bills and one at £620 excluding them are not what a simple comparison suggests.

We capture bills_included as a structured state — all, some, none or unstated — plus bills_detail_text as published. We do not estimate a bills-adjusted rent, because the estimate would depend on household size, usage and tariff, none of which we observe.

Unstated is a real value here and it is common. Treating unstated as excluded would systematically understate inclusive listings.

Who is advertising changes what the listing is

A room listing can come from a live-in landlord, a letting agent, a property company, or a current tenant looking to fill a room in their own house share.

Live-in landlord lets operate under different UK rules from standard tenancies and are priced differently.
Tenant-advertised rooms are usually a sublet or replacement within an existing tenancy.
Agent and company listings behave more like conventional rentals.

advertiser_type is recorded where the listing states it, and flagged unstated where it does not. A rental index that pools all four is blending markets with different regulation, different tenancy structures and different price levels.

The property behind the rooms

Several rooms in one house appear as separate listings. Where attributes and images support it we assign property_cluster_id with a confidence — the same approach as Idealista — so a property-level view is possible without pretending each room was a separate house.

We do not assert a cluster on location alone, because room listings frequently obfuscate the address to street or postcode level.

What we do not collect, and this source needs extra care

Room and flatshare listings carry more personal content than any other property source we cover, and the collection boundary matters more here than almost anywhere.

No advertiser names, photographs, phone numbers or contact details. Not landlords, not agents, not tenants.
No housemate descriptions. Listings frequently describe existing occupants — their ages, occupations, genders, lifestyles. We do not collect that text.
No preference criteria about who may apply. Where a listing states preferences about prospective tenants, we do not collect them.

What we collect is the commercial content of the advertisement: rent, period, bills, deposit, room and property attributes, location at the precision published, and availability dates.

This is a narrower collection than a naive extraction of the page, deliberately. A room listing contains real information about identifiable people living somewhere, and none of it belongs in a rental dataset.

Scope

What we collect on SpareRoom, 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

Room-level listings with rent amount and the period exactly as quoted
Normalised rent derived, with normalisation_basis naming the conversion
bills_included as all, some, none or unstated — unstated is real
bills_detail_text as published, never converted to an estimate
advertiser_type where stated, flagged unstated where not
property_cluster_id with confidence, where attributes and images support it
Deposit amount and terms where stated
Room and property attributes, and availability dates
Location at the precision the listing published

❌ What we do not, and why

Rent per room compared against rent per property
A bills-adjusted rent estimated from unobserved usage
A weekly-to-monthly conversion using four weeks
Housemate descriptions, occupant details or tenant preference criteria
Advertiser names, photographs, phone numbers or contact details

Core SpareRoom 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 / city / area	The listing and where it is
rent_amount / rent_period	Exactly as quoted
rent_normalised / normalisation_basis	Derived, with the conversion named
bills_included / bills_detail_text	Structured state plus published text
deposit_amount / deposit_terms	Where stated
advertiser_type	Live-in landlord, agent, company, tenant, or unstated
property_cluster_id / cluster_confidence	Rooms grouped to a property where supportable
room_type / room_size / property_bedrooms	As published
available_from / minimum_term	Availability terms
location_precision	Street or postcode level, as published
observed_at	Timestamp

Use cases

What teams do with SpareRoom data

Room-level rental indices

Rent per room with period and bills state recorded, kept separate from property-level rents so an index measures one market rather than two.

Shared-housing supply analysis

Room listings clustered to properties where supportable, so supply can be read as rooms or as properties without pretending each room was a separate house.

Bills-inclusive market segmentation

Inclusive and exclusive listings as distinct populations, since a comparison across them without the flag compares two different products.

Advertiser-type segmentation

Live-in landlord, agent, company and tenant lets separated, since they operate under different rules and price differently.

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

Send us a SpareRoom 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.

SpareRoom is usually collected alongside its competitors

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

SpareRoom data scraping: frequently asked questions

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

Because that is what is let. A four-bedroom house let room by room is four listings, four rents and four tenancies — it is not one rental.

Rent per room and rent per property are different numbers, and an index that mixes them is measuring two markets at once.

We record the amount and the period exactly as quoted, and derive a normalised value with the conversion named.

The detail that matters: a weekly-to-monthly conversion using four weeks understates monthly rent by roughly 7%, because a month is about 4.3 weeks. Getting that wrong across a whole dataset is a systematic error in one direction.

Captured as a structured state — all, some, none or unstated — plus the published detail text. Unstated is common and it is a real value; treating it as excluded would systematically understate inclusive listings.

We do not estimate a bills-adjusted rent, because the estimate depends on household size, usage and tariff, none of which we observe.

Because a live-in landlord let operates under different UK rules from a standard tenancy, and a tenant-advertised room is usually a sublet or replacement within an existing tenancy.

Pooling them blends markets with different regulation, tenancy structures and price levels.

No, and this source needs more care than any other property source we cover. Listings frequently describe existing occupants — ages, occupations, genders, lifestyles — and we do not collect that text.

We also do not collect tenant preference criteria, or any advertiser name, photograph or contact detail. What we collect is the commercial content: rent, bills, deposit, attributes, location and availability.

We quote individually on listing volume, areas in scope and refresh. Daily is usually right — room listings turn over faster than property lets.

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

See real SpareRoom 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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