Get the expense benchmarks for a property given its details. Our models use all property details (characteristics, #stories, amenities, location, etc.) to compute the estimates.
The list of units and floorplans available at the property.
Alternative names or aliases for the building.
The quality scores for various aspects of the property, including both general areas and specific features.
The city where the property is located.
Date when the property details were last updated or created.
The unique identifier of the property. It is a stringified UUIDv5. This value can occasionally change if multiple properties get merged into one.
Latitude coordinate of the property’s location.
Longitude coordinate of the property’s location.
Analysis of the property’s pricing patterns and strategies.
The state where the property is located.
The primary street address of the property.
Alternate or commonly used names or aliases for the street address.
The postal code for the property’s location.
Administrative fee charged by the property.
Amenity fee charged by the property, if applicable.
Application fee charged to apply for residency.
List of amenities available in the building.
The name of the building or property.
Contact phone number for the building management or leasing office.
Website URL for the property or management company.
Deposit required for having cats.
Monthly rent charge for having cats.
One-time fee for having cats.
The FIPS code of the property’s location.
Historical concession offers or promotions available at the property, along with extracted values from the text.
Beta Subject to change in near future. The demographics for the property’s location, if available.
Deposit required for having dogs.
Monthly rent charge for having dogs.
One-time fee for having dogs.
Indicates if the property is an apartment complex.
Indicates if the property consists of condominiums.
Indicates if the property is a senior living community.
Indicates if the property is a single-family home.
Indicates whether we have identified the property as a student housing complex. Detected based on the presence of certain amenities, unit naming conventions, price points, and other factors.
Name of the company managing the property.
An array representing the market embedding vector, used for advanced analysis. If you want to compare two markets, you can use the cosine similarity between their market embeddings. Note: this vector is subject to change a couple of times a year as we improve our models.
Maximum security deposit required (may vary by unit).
Minimum security deposit required.
Metropolitan Statistical Area the property belongs to, if applicable.
Number of stories or levels in the property.
Predicted or estimated range for the number of stories in the building based on facade images.
Total number of units in the property.
A prediction of the number of units based on images, number of floors, amenities, location, year built, and the number of units we have seen so far. NOTE: This is an approximation to understand the property’s size when the exact number of units is not available, do not use it as a variable in your financial models.
Monthly charge for covered parking, if available.
Monthly charge for parking in a garage, if available.
Monthly charge for parking in a surface lot, if available.
An array representing the property embedding vector, used for advanced analysis. If you want to compare two properties, you can use the cosine similarity between their property embeddings. Note: this vector is subject to change a couple of times a year as we improve our models.
Analysis of the property’s public reviews over the past 24 months.
Fee for using storage facilities on the property.
A url to the street view image of the property.
List of amenities available in the units.
When it’s a custom property, this field will be populated with the user_id of the user who created the property.
Year the property was originally built.
Predicted or estimated construction period or era based on listing images.
The expense benchmarks.