Every listing counted once, with price per square metre.
Property portals publish a large, fast-moving view of supply and asking prices. We collect sale and rental listings, remove duplicates posted by several agents, and standardise size, price and location, so you can track the market at building and district level.
The same apartment is often listed by several agents on several portals, at slightly different prices and sizes. Raw listing counts overstate supply, and inconsistent units such as square feet and square metres distort price comparisons.
You get a clean listing dataset with one record per property, standardised price per square metre and days on market. Supply, asking prices and rental yields can be tracked by district, building and property type.
Everything needed to run it in production.
Portal coverage
Sale and rental listings from leading property portals and developer sites in each target market.
Listing de-duplication
Duplicate listings across agents and portals are merged using location, size, layout, images and price.
Unit standardisation
Sizes converted to square metres and prices to price per square metre, with original values retained.
Location hierarchy
Listings are assigned to city, district, community and building, with coordinates where available.
Listing lifecycle
First-seen and last-seen dates, price changes and days on market are tracked for every listing.
Property attributes
Bedrooms, bathrooms, furnishing, amenities, completion status and off-plan or ready flags.
What lands in your systems.
| district | city | type | bedrooms | size_sqm | asking_price | currency | days_on_market |
|---|---|---|---|---|---|---|---|
| Jumeirah Village Circle | Dubai | Apartment, sale | 1 | 72 | 1,150,000 | AED | 21 |
| Al Malqa | Riyadh | Villa, sale | 5 | 360 | 3,400,000 | SAR | 48 |
| The Pearl | Doha | Apartment, rent (yearly) | 2 | 118 | 132,000 | QAR | 15 |
| Tanjong Pagar | Singapore | Condominium, rent (monthly) | 2 | 75 | 5,800 | SGD | 9 |
| Salamanca | Madrid | Apartment, sale | 3 | 110 | 895,000 | EUR | 37 |
Illustrative rows. Your schema, field names and formats are agreed during scoping.
Who uses it, and for what.
Real estate investors track asking prices and rents by district to estimate yields. Days on market indicates where demand is strengthening or softening.
Developers and agencies benchmark new launches against comparable listings nearby. Price per square metre gives a like-for-like reference.
Lenders and valuers compare asking prices with valuations across their portfolio. Areas of rapid price change are flagged for review.
PropTech teams build automated valuation models on clean, de-duplicated listings. Standardised units and locations improve model accuracy.
- Scope. Tell us the sources, fields and frequency. We confirm feasibility within a day.
- Free sample. A real sample from your own target source, in your format.
- Build. Engineers build extractors tuned to each source. No generic templates.
- Validate. Automated and manual QA on every run before anything ships.
- Deliver and monitor. Scheduled delivery, monitored pipelines, fast fixes when sites change.
Related services
Industries that use it
How do you remove duplicate listings?
We compare location, size, layout, price and image similarity to identify the same property listed by several agents or on several portals. Duplicates are merged into one record that keeps each source listing ID.
Are these asking prices or transaction prices?
Listings show asking prices and rents. Where public transaction registries exist, we can collect those separately so you can compare asking and achieved prices.
Do you collect agent contact details?
We collect agency names by default for market share analysis. Individual agent contact details are excluded unless there is a clear and lawful reason agreed during scoping.
Can you cover off-plan projects?
Yes. Off-plan listings are flagged, with developer, project name and expected completion date captured where published.