Performs a property search using geometric shapes and advanced filtering criteria.
This endpoint enables flexible market analysis by finding properties within custom-defined boundaries
and applying multi-dimensional filters to refine results based on property characteristics.
NOTE: This new endpoint needs to be activated for your account and is charged at a higher rate. Please contact us to activate.
Core Functionality
The search combines geographic boundaries (defined by coordinate polygons) with property-specific filters
such as construction year, building size, unit mix characteristics, and property type classifications.
This allows for precise market analysis within irregular geographic areas like neighborhoods, custom
market areas, or specific zones of interest.
Geographic Boundaries
Coordinate Format: Geographic boundaries are defined using GeoJSON-style coordinate arrays.
The format follows the pattern: number[][][][] where:
- Outer array: Contains multiple polygons (for complex shapes with holes or multiple areas)
- Second level: Contains individual polygons
- Third level: Contains coordinate rings (first ring is exterior, subsequent rings are holes)
- Inner arrays: Individual coordinate pairs as
[longitude, latitude]
Example coordinate structures:
Filtering System
Range Filters: Most numeric filters use a standardized range format with three properties:
min: Minimum value (inclusive). Use null to omit minimum constraint
max: Maximum value (inclusive). Use null to omit maximum constraint
allow_null: Whether to include properties with missing data for this field (default: false)
Property Type Filters: Boolean filters for different property classifications:
is_student: Student housing complexes (detected via amenities, naming patterns, pricing)
is_senior: Senior living communities
is_affordable: Properties with affordable housing units (uses LIHTC database and other sources)
Unit Mix Filters: Advanced filtering based on unit composition and pricing:
- Filter by unit counts, square footage, rent levels, and rent per square foot
- Available for overall property and by bedroom count (studio through 4-bedroom)
- Uses historical market data to calculate averages
Result Limits: Each request is capped at 2,500 properties to ensure optimal performance.
If you hit this limit, consider:
- Narrowing your geographic boundary
- Adding more restrictive filters (year built, unit count, etc.)
- Splitting large areas into multiple searches
Geographic Scope: Searches are optimized for metropolitan areas. Very large rural areas
may return fewer relevant results due to lower property density.
Data Freshness: Property data is continuously updated, but some filters (especially unit mix)
rely on historical market data that may have varying collection periods across markets.
Usage Recommendations
For Market Analysis:
- Use generous geographic boundaries initially, then refine with property filters
- Combine year built and unit count filters to focus on comparable property classes
- Leverage unit mix filters to find properties with similar tenant profiles
For Competitive Analysis:
- Start with broader search area around subject property
- Use property type filters to exclude non-competing assets
- Apply unit mix filters to match target demographics
For Site Selection:
- Define custom geographic boundaries around areas of interest
- Use year built filters to identify redevelopment opportunities or new construction
- Apply unit mix filters to understand existing supply characteristics
Each request is limited to a maximum of 2,500 results. If you hit this limit, consider refining your filters
to narrow the search and reduce the result count.