Platform · OnTheMarket

OnTheMarket Data Scraping

Its proposition is that properties appear here first. Which makes the timestamp, not the price, the thing worth collecting.

OnTheMarket data scraping collects UK property listings, asking prices, status changes and agent attribution. What makes it analytically distinct from the larger UK portals: its proposition involves properties appearing here before they reach the majors. So the first-seen timestamp is the signal — and a timestamp is only meaningful if you were already observing.

Every UK portal page argues that asking price is not a transaction. This one is about a different field entirely.

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onthemarket.jsonl LIVE FEED

{"portal":"onthemarket","listing_id":"ot-44120", "first_seen_at":"2026-08-19T08:14+01:00", "first_seen_observed":true, "asking_price":485000,"price_is_asking":true, "panel_schedule_id":"uk-portals-sync"} {"portal":"portal-major","first_seen_at":"2026-08-21T11:40+01:00", "portal_lead_hours":51.4, "note":"THAT is the proposition, measured. only a shared schedule gives it"} {"first_seen_observed":false, "caution":"already live at panel start. first-seen here is a collection artefact", "status_changed_at":"2026-08-24, withdrawn then relisted"}

3 of 684,220 listing rows · UKthe TIMESTAMP is the signal · lead from paired records · schema v1.0

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

How we handle OnTheMarket specifically

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

Portal: OnTheMarket — UK challenger
The proposition: Early listing exposure
So the signal is: first_seen_at, not price
The catch: A timestamp needs prior observation to mean anything
Cross-portal: Lead time is computed from paired records
Asking price: Not a transaction price. As on any portal
Duplicates: Same property via multiple agents. Clustered, not merged
Refresh: Daily minimum; sub-daily where lead time is the question

Platform specifics

Timing as the signal, and what it takes to measure it

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

first_seen_at is only as good as the collection that produced it

If the proposition is early exposure, the measurable version is: how long before a property appears on the larger portals does it appear here?

That is computable, and it has hard requirements:

You must have been observing before the listing appeared. A first-seen date on a listing that was already live when collection began is a collection artefact.
The other portals must be observed on the same schedule. A lead measured from records taken hours apart is partly a timing artefact.
Daily collection resolves lead only to the nearest day, which for a lead of hours is no resolution.
And a listing can be withdrawn and relisted, which resets an unguarded first-seen.

So first_seen_at carries first_seen_observed as a boolean, and where a listing was already live at panel start it is flagged rather than dated — the same discipline our Asda page applies to rollback start dates.

portal_lead_hours is computed only from paired records on a shared schedule, with panel_schedule_id shared across the portals in scope.

Agent attribution, duplicates and status

The same property, several listings

A property marketed by more than one agent produces more than one listing, and multi-agency arrangements are common in parts of the UK market.

We cluster rather than merge: property_cluster_id with cluster_confidence and cluster_basis, built from address, attributes and imagery signals where available. Each listing stays its own record, because agent, price and description can differ between them and merging destroys that.

Status is a sequence, not a state

Listed, under offer, sold subject to contract, withdrawn, relisted. Each transition is an event with a timestamp, retained rather than overwritten.

A withdrawal followed by a relisting at a different price is one of the more informative patterns in UK property data, and it is invisible in a feed that only carries current state — the argument our panel design page makes.

Asking price

An asking price is a marketing figure. price_is_asking is a constant true and we do not produce sold prices from portal listings, because a portal does not publish them.

Scope

What we collect on OnTheMarket, 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

first_seen_at with first_seen_observed as a boolean
Listings already live at panel start flagged rather than dated
portal_lead_hours computed only from paired records on a shared schedule
panel_schedule_id shared across portals in scope
property_cluster_id with confidence and basis, listings never merged
Status transitions as timestamped events, retained not overwritten
price_is_asking as a constant true
Agent attribution per listing
Price change events with timestamps

❌ What we do not, and why

A first-seen date presented for a listing already live at panel start
A cross-portal lead computed from unsynchronised observations
Duplicate listings merged into one property record
A sold price derived from an asking price
Vendor, buyer or enquirer data of any kind

Core OnTheMarket 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 / property_cluster_id	The listing, and its cluster
cluster_confidence / cluster_basis	A cluster, not a fact
first_seen_at / first_seen_observed	The signal, and whether we saw it start
portal_lead_hours / panel_schedule_id	From paired records on a shared schedule
asking_price / price_is_asking	A marketing figure, flagged as one
price_change_event / changed_at	Events, with timestamps
status / status_changed_at	A sequence, not a state
agent_name / agent_branch	Commercial entities
address_precision	As published. Never sharpened
property_attributes	Beds, type, tenure as published
observed_at	Timestamp

Use cases

What teams do with OnTheMarket data

Cross-portal listing lead measurement

First-seen timestamps against the larger UK portals on a shared schedule, which is the only way the early-exposure proposition becomes a number rather than a claim.

Withdrawal and relist detection

Status transitions retained as events, so a withdrawal followed by a relisting at a different price is visible rather than overwritten.

Multi-agency listing analysis

Clustered rather than merged listings, so the same property marketed by several agents at different prices stays visible as several records.

Agent activity tracking

Listing volume and price changes by agent and branch, as commercial entities rather than individuals.

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

Send us a OnTheMarket 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.

OnTheMarket is usually collected alongside its competitors

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

OnTheMarket data scraping: frequently asked questions

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

Because this portal's proposition involves properties appearing here before they reach the majors. That is a measurable claim, and the measurement is a timestamp.

Asking prices are broadly similar across portals for the same property, so price is where this portal is least distinctive.

Not having been observing before the listing appeared. A first-seen date on a listing that was already live when collection began is a collection artefact rather than a fact about the listing.

We flag those rather than dating them, and we carry a boolean saying which is which.

To whatever resolution the schedule supports. Daily collection resolves a lead only to the nearest day, which for a lead of hours is no resolution at all.

Where lead time is the question we recommend sub-daily, and the portals in scope share a schedule identifier.

Because agent, price and description can differ between listings of the same property, and merging destroys that.

We cluster with a confidence and a stated basis, and every listing stays its own record.

Not from a portal. A portal publishes asking prices, and an asking price is a marketing figure.

Where a market publishes transaction data separately, that is a different source with its own handling.

We quote individually. Refresh is the main driver here rather than listing volume, because lead-time resolution depends on it — and a cross-portal panel multiplies that.

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

See real OnTheMarket 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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