Real Estate
See the market listing by listing.
Collect public property listings from portals and agency websites. Normalize locations and property attributes, then follow new listings, price changes and withdrawals over time.
What the dataset gives you.
An example of the real estate dataset. Each note points to the columns that answer it.
Follow asking-price changes
Keep a dated record of reductions and updates instead of overwriting the last price.
Previous priceAvoid double-counting
Match listings for the same property across portals and agencies.
Listing IDUnderstand local inventory
Compare new listings, withdrawals and available stock by area and property type.
Status
| Listing ID | Area | Property | Beds | Floor area | Asking price | Previous price | Days listed | Status |
|---|---|---|---|---|---|---|---|---|
| RE-1842 | Riverside | Riverside Court | 2 | 72 m² | £425,000 | £445,000 | 24 | Price reduced |
| RE-1843 | Riverside | Quay House | 2 | 81 m² | £460,000 | — | 1 | New listing |
| RE-1844 | Riverside | Bridge Apartments | 2 | 68 m² | £410,000 | £410,000 | 12 | Active |
| RE-1845 | North Quarter | Terraced house | 3 | 104 m² | £510,000 | — | 2 | New listing |
| RE-1846 | Old Town | First-floor apartment | 1 | 48 m² | £285,000 | £295,000 | 38 | Price reduced |
| RE-1847 | City Centre | Studio apartment | 0 | 31 m² | £210,000 | £210,000 | 45 | Listing removed |
Provenance
One listing, traced back to the portal.
Every row links to the listing it was read from, when it was read and which pipeline version read it. Each run publishes a new dataset version, so a reduction is kept as history instead of overwriting the last price.
Jason builds the pipeline and repairs it when a site changes. The scheduled runs repeat the same steps every time, so today’s row compares directly with the last one. There are no scrapers for your team to build or keep alive.
- Source page
- portal-a › riverside › re-1842
- Read at
- 07:10:05 UTC
- Pipeline
- v4.1
Checks
- Matched across Portal A and Portal B
- Floor area in m²
- Previous price kept
Dataset versions
- v57Today 07:10£425,000 Price reduced
- v56Yesterday 07:09£445,000 No change
- v5529 Sep 07:10£445,000 No change
- 25 SepPipeline v4.1 Portal B changed its search results page. Jason repaired the extraction and re-ran the day.
The dataset, and one way to look at it.
Every pipeline publishes a checked dataset. Want a view without a BI team? Jsonify renders one from the schema — or send the rows to Sheets, Snowflake or your agent.
Property market insights
property_listings · 3,842 active listings · updated 06:05
Median asking price
Median asking prices are down £13k across the period. Compare like-for-like property types before drawing conclusions.
Share of listings with parking
Latest changes
| Area | Property | Change |
|---|---|---|
| Riverside | Riverside Court · 2 bed | £445k → £425k |
| North Quarter | Terraced house · 3 bed | New listing |
| Old Town | First-floor apartment · 1 bed | £295k → £285k |
| City Centre | Studio apartment | Listing removed |
Illustrative dashboard with example data. Views are built around your dataset and use case.
Since 2023 we’ve extracted billions of data points for teams at Bacardi, PwC, Geopost and more.
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Philipp HodlPlug and Play VenturesFrom your sources to your dataset.
Choose the scope. Jsonify builds the pipeline, runs it on your schedule and repairs it when a source changes. See how it works →
- 01 / Sources
Areas & property typesYour market boundaries
- 02 / Collect in parallel
Read property portalsPrices and listing details
Read agency websitesLocal inventory and updates
- 03 / Process & verify
Deduplicate listingsMatch properties across sources
- 04 / Publish
Property listingsA history of market activity
Email reportSnowflakeXLSX
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