Doorstep Analytics provides short term rental (STR) datasets for your analytics projects and AI models. Support your research or MCP Server with accurate, detailed, clean and ready to ingest CSV files. Designed for data scientists, researchers and property and investment analysts.
How does it work?
Doorstep Analytics calls multiple public Airbnb API and HTML endpoints, then formats and aggregates this data into CSV files. This includes listing details, calendar availability, pricing, reviews, host and business details. We then augment Airbnb data with public data sources, such as OpenStreetMap.
CSV data is available instantly for pre-loaded locations, or you can request data for almost every town or city anywhere in the world.
The datasets exclude hotel listings on Airbnb. The web scraper is designed to fail forwards, and will skip API calls that repeatedly return errors. Pricing data is downloaded separately from listing data, and on rare occasions is not available for all listings that were recently added or removed.
How can I use the data?
Doorstep Analytics provides some location data for free. Other datasets are limited to 6,000 listings. If you purchase data, this helps with the web scraper running costs.
When you purchase data, you will have unlimited email support for any additional queries you may have. You are free to use paid datasets for any purpose, without attribution, including commercial use.
The free data provided on report pages and in CSV files, such as listing counts and graphs, is available under a Creative Commons Attribution (CC BY-SA 4.0) license, and can be used for any purpose, including commercial use, with attribution.
Contact
Doorstep Analytics is currently run as an individual non-profit project based in the UK, by data engineer Simon Salamian.
