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How to Scrape UK Property Listings from Rightmove at Scale

May 3, 2026  ·  6 min read

Rightmove is the UK’s number one property portal, with more than 900,000 active sale and rental listings on any given day and the majority of UK estate agents publishing their stock through it. For property analysts, estate agents, proptech founders, and investors, it is the single most important surface for structured UK property data: prices, addresses, bedroom counts, bathroom counts, agent details, and listing URLs. None of this is available through a public API. The only way to work with Rightmove data at scale is to extract it programmatically.

This post covers why Rightmove data matters, what makes bulk extraction technically difficult, and how to pull clean structured listings without building and maintaining your own scraper.

Why Rightmove data matters

• Estate agency competitive intelligence — Estate agents monitor their patch — how many properties competitors have listed, average asking price, time on market, and how quickly stock turns over. Rightmove’s area pages are the shared shopfront where most UK buyers and renters start their search, making it the most important surface for local market monitoring. Tracking a postcode manually each week is not sustainable; automated extraction lets agencies run this as a recurring data pipeline.
• Investor and BTL deal sourcing — Buy-to-let investors and property sourcers use Rightmove to identify undervalued listings, calculate gross yields against rental comparables, and track price reductions across whole regions. Bulk extraction of listings filtered by location, property type, and price band surfaces the active deal flow in a given market faster than any manual browsing workflow.
• Market analysis and price indices — Analysts, journalists, and proptech companies use Rightmove listing data to count active stock in a region, understand distribution of asking prices by bedroom count, and track how quickly new listings appear and existing ones reduce. Structured listing data across thousands of UK postcodes builds a snapshot of the UK property market that is hard to assemble from any other public source.
• Lead generation for proptech and mortgage brokers — Companies that sell to landlords, sellers, or buyers use Rightmove listing data to identify active vendors and infer when someone is in-market. Bulk extraction by area and price band produces a fresh, structured list of properties for sale or rent each week.
• Relocation and corporate moves — Relocation agencies pulling shortlists for corporate clients want consistent structured data across many areas at once — not 50 browser tabs. Automated extraction reduces a multi-day shortlisting exercise to a single dataset.

Why bulk extraction is hard

Rightmove is a large, well-instrumented commercial site, and extracting data at scale runs into the same set of problems any high-traffic property portal presents:

• Aggressive anti-bot infrastructure — Repeat requests from a single IP get throttled or blocked. Naive scripts hit a wall within minutes.
• Geo-restricted content — Rightmove serves UK users; requests from non-UK IPs return different responses and miss data.
• Pagination and result caps — Search result pages cap at a fixed number of results, so wide queries (e.g. all of London) need to be split into smaller geographic windows to capture the full set.
• Page structure changes — Listing layouts and the underlying markup change without warning. Anything brittle breaks within weeks and requires constant maintenance.
• Address and price normalisation — Raw output is inconsistent: prices appear as “Guide Price £425,000” or “OIRO £500,000”, addresses are partial, and bedroom counts are sometimes embedded in titles. Clean structured output requires a normalisation layer.
• Compliance considerations — Anyone scraping any UK portal needs to respect rate limits, public data only, and reasonable use. A managed solution handles this so the buyer does not have to.

For most teams, building and maintaining this pipeline is not the work they want to do. They want clean rows in a CSV.

How to extract Rightmove listings without writing a scraper

The fastest path is to call our managed Rightmove actor on Apify. Pass a location, optional filters, and a result cap; receive a structured dataset back. No proxies to manage, no markup to chase, no anti-bot to fight.

Input

Field	Type	Example	Description
location	string	"London"	City, town, postcode, or borough.
propertyType	string	"flat"	flat, house, bungalow, etc. Optional.
maxResults	number	500	Cap on listings returned. Default 100.

Output (one row per listing)

Field	Example
price	"£425,000"
address	"Camden High Street, London NW1"
bedrooms	2
bathrooms	1
url	"https://www.rightmove.co.uk/properties/…"

Example call

{
  "location": "Manchester",
  "propertyType": "flat",
  "maxResults": 250
}

Output arrives as a structured dataset you can export to CSV, JSON, or Excel directly from the Apify console, or pull via the dataset API into your own pipeline. Schedule it weekly and you have a continuously refreshed view of any postcode in the UK.

When to use a managed actor vs build your own

Build your own if Rightmove is your single product and you have a dedicated engineer to maintain it. Use a managed actor if Rightmove data is an input to something else — analysis, lead gen, a dashboard, a report — and you would rather pay a small per-result fee than own the maintenance burden. Most teams fall into the second bucket.

Try the actor on Apify and pull your first batch of listings in a few minutes. If you need a custom shape for the output or a different filter set, get in touch and we will adjust the actor.