Proptech & listing platforms
Aggregating and normalizing listings across portals to power search and discovery.
Daily sync across 100+ listing sources
Real estate data
Property listing data, delivered to spec
Production-grade listing data: composable, not packaged. Build it yourself on Zyte API, or have it delivered to spec by Zyte Data. Same foundation, your choice of who runs the pipeline.
The basics
What is real estate data?
Real estate data is the structured record of a property as it's listed for sale or rent online: its address, price, specs, media, status and the agent or office behind it. It's collected from public listing pages across portals, brokerage sites, and agent directories, then normalized into a consistent schema. Because the same property can appear differently on every site, and its price and status change constantly, the value is in keeping that record accurate and current, not in the raw page.
Who uses it
Use cases across industries
The same data type, put to work differently.
Valuation & appraisal
Comparable listings and price history feeding automated valuation models (AVMs).
Comps refreshed within 24 hoursInvestment & market analytics
Price trends, vacancy rates, and market direction as signals for underwriting and acquisition.
Region-level coverage across 50+ marketsProperty management & rentals
Rent pricing and availability tracking across competing listings for dynamic pricing.
Rent comps updated dailyBrokerages & agent networks
Office and agent roster data for lead generation and territory mapping.
Agent + office records linked and deduplicatedConsultancies & researchers
Market-wide listing studies without standing up scraping infrastructure in-house.
Project-scoped feeds delivered in weeksThe hard part
Why real estate data is hard at scale
The problem is rarely a single listing. It's keeping thousands of them flowing, correctly, while the sites underneath keep changing.
Site changes break parsers overnight
Zyte validates every feed run against your agreed schema.
Price and status render in JavaScript
Zyte renders pages the way a real browser does, so client-side price and status changes are captured reliably — not a stale placeholder.
The same property, priced differently everywhere
Zyte timestamps every price it collects and flags which listing is most current, so a stale syndicated price is never mistaken for today's.
Anti-bot defenses are dynamic
When a request is blocked, Zyte automatically re-routes and retries with a different approach, and persistent blocks escalate to the team running your feed.
Schemas fragment across portals
Zyte resolves each source into one consistent schema, so a listing is a listing no matter how many portals it came from.
The cost of getting it wrong
What poor data quietly costs the business
Bad web data doesn't announce itself — it shows up later, in a valuation or offer made on a number that was already wrong.
Revenue impact
27%Value a property against week-old comps and roughly a quarter of your estimates are already off.
Analytics integrity
1 in 8A silent coverage drop hides one in eight listings — dashboards still look complete.
Model reliability
3–6 wksAn AVM retrained on a gappy feed drifts for weeks before anyone traces the cause.
Regulatory exposure
€20MCollecting personal agent data or ignoring site terms risks GDPR penalties up to €20M.
See the Schema
The request you send and the data that comes back. Pick the standard schema or a custom one mapped to your model, and read the response as a table or JSON.
Zyte API
REQUEST
POST https://api.zyte.com/v1/extract
{
"url": "https://example-portal.com/listing/12345",
"product": false,
"realEstate": true
}RESPONSE
Standard Real estate data schema
Field
Type
Example
url
string
https://example-portal.com/listing/12345[https://example-portal.com/listing/12345]
listingId
string
12345
address
object
{ ... }
— city
string
Seattle
— region
string
WA
— postcode
string
98101
— latitude / longitude
number
47.6097 / -122.3331
listPrice
number
875000
currency
string
USD
pricePerSqft
number
725.00
priceHistory
array
[{"date":"2026-04-01","value":899000}]
beds
number
3
baths
number
2
areaSqft
number
1208
lotSqft
number
3000
yearBuilt
number
1987
propertyType
string
Single-family
listingStatus
enum
for_sale
publishedAt / updatedAt
date
2026-04-28 / 2026-05-20
images
array
[url1, url2, ...]
mainAgent
object
{ name, company, license }
Reviews
What our users say
I have been working with Zyte's team for the last few months, and their team is fantastic. I appreciate their development speed and quality, and they run a very robust platform, producing very satisfactory results. I love the ease of the initial setup with Zyte, as they took care of all the development, and we only needed to communicate what data we needed and set up the necessary processes on our end.
David P.
Frequently asked questions
How fresh can real estate data be?
Price and status are typically delivered daily or several times a day; full listing attributes are usually re-crawled weekly. Real-time and on-event delivery is available where a use case needs it. We scope frequency per portal to how often that site actually changes.
How do you handle site changes that break extraction?
Every feed run is validated against your agreed schema, so a layout change on the source site surfaces as a coverage alert — not a silent gap in your data.
What about anti-bot measures and blocks?
Zyte's infrastructure re-routes and retries automatically when a request is blocked, adapting to each portal's defenses without you managing proxies or headless browsers.
What formats and delivery methods do you support?
JSON Lines and CSV are standard, with separate files for offices and agents when a project involves directory or roster data. Delivery via S3, GCS, SFTP, or API pull, on the schedule you need.
How do you approach compliance for real estate data?
We collect only what's publicly available, respect site terms, and take particular care with any personal data tied to agents or private sellers. Legal review is available for projects that touch credentials or personal data.
How long does setup take?
Standard-schema feeds from common portals can start within days. Projects with custom fields — agent/co-agent blocks, deed history, MLS-specific attributes — typically take one to a few weeks depending on scope.
What does a real estate data feed cost?
Pricing depends on the number of sources, listing volume, refresh frequency, and how much of the schema is custom. Talk to our data experts for a quote scoped to your markets.
Can I see a sample before committing?
Yes — we can provide a sample JSONL or CSV extract from a portal you care about so you can validate coverage and schema fit before scoping a full feed.