Data On Demand, one-stop data solution
Markets Local sources. Your time zone.

Teams in five regions rely on us for local-language, multi-currency data.

Global coverage
Company A decade of data expertise.

An in-house team of 20+ engineers and analysts serving clients in 12+ countries.

About us
Services and mobility

Property listings, de-duplicated and priced per square metre.

Property portals hold the most current view of asking prices and supply, but the same unit is often listed several times by different agents. We extract listings, remove duplicates, standardise areas and prices, and deliver a clean record of the market by district.

Business challenges

What makes this industry hard to track.

01

Duplicate listings

One property is often advertised by several agents on several portals. Without de-duplication, supply is overstated and prices are skewed.

02

Inconsistent location data

Addresses, community names and coordinates are entered differently. Listings need to be mapped to a consistent district hierarchy.

03

Units and measures

Areas appear in square metres or square feet, and rents may be quoted weekly, monthly or annually. Everything must be normalised.

04

Price changes and withdrawals

Reductions and withdrawn listings carry market signals, but only if listing history is kept.

What you can track

Eight data points our clients rely on.

Asking price or rent

Listed price with rent period normalised to monthly or annual.

Price per square metre

Price divided by normalised built-up area.

Property attributes

Type, bedrooms, bathrooms, area, floor, furnishing and amenities.

Location

District, community and coordinates where published.

Days on market

Time from first seen to removal, with any relisting noted.

Price history

Each price change with its date and size.

Agent and developer

Listing agency or developer, useful for market share analysis.

Off-plan projects

New launches, payment plans and stated handover dates.

Sample dataset

An illustrative extract.

Illustrative de-duplicated listing extract from property portals
First seenSourceCity / districtTypeArea (sq m)Asking priceCurrencyListing
2026-03-02Portal ADubai / Dubai Marina2-bed apartment1122450000AEDSale
2026-03-04Portal BMelbourne / Richmond3-bed townhouse1681395000AUDSale
2026-03-05Portal CSão Paulo / Pinheiros1-bed apartment483900BRLRent (monthly)
2026-03-06Portal DAustin / East Austin3-bed house1493100USDRent (monthly)
2026-03-06Portal ERotterdam / Kralingen2-bed apartment78425000EURSale

Illustrative rows. Sources, markets and fields are agreed with you during scoping.

Use cases

How teams put it to work.

District price indices

Monthly asking price and rent per square metre by district and property type, built on de-duplicated listings.

Supply and absorption

New listings, withdrawals and days on market over time, showing where supply is building or clearing.

Off-plan launch tracking

A record of new project launches, pricing and payment plans for developers, lenders and investors.

FAQ

Questions about real estate and proptech data

Can’t find your answer? Ask an engineer

How do you remove duplicate listings?

We compare location, size, price, attributes and images across listings and portals to identify the same property. Each unique property gets one record, with links to all its listings retained.

Do you collect agent contact details?

We collect agency names for market share analysis and minimise personal data such as individual agents' phone numbers. The scope is set against the privacy laws of each market.

Can you include public transaction data?

Where land departments or registries publish transaction data openly, we can extract it and join it to listings. That lets you compare asking prices with recorded prices.

How is location standardised?

We map each listing to an agreed district and community hierarchy, using coordinates where available. Unmatched locations are flagged for review.

Start with proof

See your own data before you commit.

Name the sources and fields you need. Within 24–48 hours you receive a real sample from your target sites, in your format, free of charge.

Request a free sample Talk to a data engineer Sample in 24–48 hours · NDA on request · Any format, any schedule