We analyse a variety of online, offline and hidden data sources, including real estate portals, property marketplace platforms (like RightMove and AirBnB) and government statistics.
We’ve uncovered billions of data points to build our estimate models. We scan for changes and update our models every day.
We’ve collected and analysed current market rates, geospatial features and years of historical data across the country. Our mathematical models use this data to estimate the rental yields of thousands of properties and locations.
To estimate the returns for long term lets we create a localised subset of similar properties and build a dataset of their rental yields. We then filter for any outliers and atypical data points to calculate an average that closely resembles what a given property could make.
Our estimates for short term lets are derived from the daily rates, charges and occupancy levels of hundreds of thousands of holiday homes. We analyse the booking trends at different seasons and geographic levels to get comprehensive micro- and macro-level views of the rental market. We can then project this onto any given property to estimate its daily rate potential.