Property data, Global
Short-Term Rental Data
Active and historical short-term rental listings with occupancy, ADR, RevPAR, reviews and host detail, worldwide.
Listings from the major short-term rental platforms with performance metrics: occupancy, average daily rate, revenue estimates, review counts and ratings, amenities, host identity and, in the US, the matched parcel and owner.
Use it for underwriting an STR purchase, regulating or taxing STRs at the municipal level, or finding hosts to sell property management, insurance and cleaning services to.
Sample rows
Illustrative and synthetic. Real samples for your geography are a reply away.
| listing_id | platform | city | country | property_type | bedrooms | adr | occupancy_90d | revenue_ltm | reviews | host_id | property_id |
|---|---|---|---|---|---|---|---|---|---|---|---|
| S22••• | Airbnb | Nashville | US | Entire home | 4 | $412 | 68% | $9•,••• | 214 | H5••• | P8891••• |
| S07••• | Vrbo | Lisbon | PT | Apartment | 2 | €138 | 74% | €3•,••• | 97 | H1••• |
Schema
| Field | Type | Notes |
|---|---|---|
| listing_id | identifier | non-personal |
| platform | text | non-personal |
| city | text | non-personal |
| country | number | non-personal |
| property_type | text | non-personal |
| bedrooms | number | non-personal |
| adr | currency | non-personal |
| occupancy_90d | number | non-personal |
| revenue_ltm | currency | non-personal |
| reviews | number | non-personal |
| host_id | identifier | non-personal |
| property_id | identifier | non-personal |
Abridged. The full data dictionary ships with every sample and lists every field, its fill rate and its source.
Used for
- STR investment underwriting
- Municipal compliance and tax enforcement
- Host prospecting for services
- Tourism and hospitality analytics
How it is built
Listings are observed continuously; calendar availability and price are sampled to estimate occupancy and revenue. In the US, listings are matched to parcels to identify the owner behind the host.
Questions we get
Is the owner match reliable?
It is a probabilistic match on address, photos and host name. We report a confidence tier on every row.
Which countries?
Global. Depth is highest in North America, Western Europe, Australia and major Asian and Latin American cities.