Comparables

Find the best rent comps for a property given its details among close by properties. Score different facets of all candidates and return the best ones. In order to get the best results, we leverage market demographics, detected quality, amenities, similarity of unit mixes, and more. - **Data completion**: feel free to complete the record with extra data only you have access to or if you want to override the data we have. For example, what would be the rent of the property if it was in a better condition? You can increase the quality of the property and see how the comps change. - **Extra Filters**: you can set extra filters. For example, you can set a maximum distance between the subject and the rent comps, a minimum number of units, a maximum number of units, a minimum year built, and a maximum year built. - **Exclusions**: you can exclude properties from the results. For example, you can exclude properties that are not good comps or properties that have already been selected. We will make sure we don't return them in the results. - **Already Selected**: you can also pass the ids of the properties that you want to force into the results. ### How to craft the payload: The endpoint accepts two types of payloads: **Option 1: Detailed Property (Recommended)** Use the result from `/property/{id}` endpoint as the `subject` field: ```typescript { subject: PropertyDetailsResponse, // from /property/{id} excluded_ids?: string[], // optional: exclude properties selected_ids?: string[] // optional: force include properties } ``` **Option 2: Simple Property** Use a simplified property object with basic information: ```typescript { simple_subject: { lat: number, // required: latitude lon: number, // required: longitude is_single_family: boolean, // required: property type is_apartment: boolean, // required: property type is_condo: boolean, // required: property type number_units?: number, // optional: total units year_built?: number, // optional: construction year number_stories?: number, // optional: building height avg_quality_prediction?: number, // optional: quality score (0-1) building_amenities?: string[], // optional: building features unit_amenities?: string[], // optional: unit features unit_mix?: Array<{ // optional: unit distribution bed: number, bath: number, count: number, avg_sqft: number }> }, excluded_ids?: string[], // optional: exclude properties selected_ids?: string[] // optional: force include properties } ``` **Recommendation**: Use Option 1 (detailed property) for best results. It provides comprehensive property information including market statistics, quality scores, unit details, and automatically detected values for missing fields. **When to use simple property**: Use Option 2 when you only have basic property information from your own systems and want to find similar properties based on fundamental characteristics like location, unit count, and amenities. ### Computing Similarities: If you are interested in simply getting similarities between properties, you can use the `comparables` endpoint. Pass the ids of the comps you want similarities for into the `selected_ids` field. And set `topN` to the same number of properties you are passing. We will return the similarities between the subject and the selected properties.