Introducing our groundbreaking US Rental Estimation API, a sophisticated tool designed to revolutionize the real estate landscape. Powered by cutting-edge algorithms and vast datasets, this API provides unparalleled accuracy in estimating rental prices across diverse American markets. Whether you're a property developer, investor, or real estate agent, our API offers invaluable insights to inform your decisions.
With seamless integration capabilities, our API becomes an integral part of your applications, websites, or software platforms. Gain a competitive edge by offering your users precise rental estimates, enabling them to make well-informed choices about properties. Our API doesn't just provide numbers; it offers a deep analysis of market trends, neighborhood dynamics, and property features, ensuring a comprehensive understanding of the rental landscape.
What sets our API apart is its adaptability. Whether you're dealing with single-family homes, apartments, commercial spaces, or vacation rentals, our API delivers tailored estimations. It accounts for various factors such as location, amenities, local demand, and historical data, ensuring the most accurate projections possible.
Stay ahead in the real estate game with our US Rental Estimation API. Embrace the future of property analysis, and empower your users with the insights they need to thrive in the rental market.
Pass the address that you want to lookup, property type, and other filters that will allow you to get rental estimates.
Real Estate Investment Platforms: Real estate investment websites and apps can integrate the API to provide users with instant rental estimates for properties they are interested in. Investors can make data-driven decisions, maximizing their returns and minimizing risks.
Property Listing Websites: Online property listing platforms can incorporate the API to automatically suggest rental prices for property owners. Accurate estimates enhance the attractiveness of listings, helping property owners set competitive rental rates and attracting suitable tenants faster.
Financial Planning Tools: Personal finance and budgeting applications can utilize the API to help users estimate rental costs when planning their budgets. This feature can be especially useful for individuals or families relocating to new areas, aiding them in understanding the cost of living.
Market Research and Analytics: Market research firms and real estate analysts can employ the API to gather comprehensive data on rental trends. Analyzing this data over time provides valuable insights into market fluctuations, enabling businesses and policymakers to make informed decisions.
Property Management Software: Property management software solutions can integrate the API to assist landlords in setting optimal rental prices for their properties. By considering various factors like location, property type, and market demand, property managers can maximize rental income while ensuring occupancy rates remain high.
Besides the number of API calls available for the plan, there are no other limitations.
With this tool, you can get a rental estimate for the address. This tool is designed to improve the accuracy of your rental estimate.
Receive a vast list of estimated rentals across the USA.
Property Types
We use the following property types in our API, both for the propertyType
query parameter, as well as any property type fields, returned via our API as part of the property or listing records:
Single Family
(default): a detached, single-family propertyCondo
: a single unit in a condominium development or building, which is part of a homeowner’s association (HOA)Townhouse
: a single-family property that shares walls with other adjacent homes, and is typically part of a homeowner’s association (HOA)Duplex-Triplex
: a single unit/apartment within a residential multi-family building (2-4 units)Apartment
: a single unit/apartment within a commercial multi-family building or apartment complex (5+ units)Get Estimation - Endpoint Features
Object | Description |
---|---|
address |
[Required] The property address in the format of 'Street, City, State, Zip'. |
propertyType |
[Required] The type of the property. Supported values are: Single Family, Condo, Townhouse, Duplex-Triplex, Apartment |
bedrooms |
[Required] The number of bedrooms in the property |
bathrroms |
[Required] The number of bathrooms in the property. Supports fractions to indicate partial bathrooms |
squareFootage |
[Required] The total living area size of the property, in square feet |
{
"rent": 3350,
"rentRangeLow": 2790,
"rentRangeHigh": 3910,
"listings": [
{
"id": "5710-Prairie-Dunes-Ct,-Sparks,-NV-89436",
"formattedAddress": "5710 Prairie Dunes Ct, Sparks, NV 89436",
"longitude": -119.69765,
"latitude": 39.595997,
"city": "Sparks",
"state": "NV",
"zipcode": "89436",
"price": 3895,
"publishedDate": "2023-12-14T00:00:00.000Z",
"distance": 2.5198,
"daysOld": 244,
"correlation": 0.8649,
"address": "5710 Prairie Dunes Ct",
"bedrooms": 4,
"bathrooms": 3,
"propertyType": "single-family",
"squareFootage": 3381.0,
"yearBuilt": 2006
},
{
"id": "5781-Ambush-Ridge-Dr,-Sparks,-NV-89436",
"formattedAddress": "5781 Ambush Ridge Dr, Sparks, NV 89436",
"longitude": -119.692603,
"latitude": 39.597505,
"city": "Sparks",
"state": "NV",
"zipcode": "89436",
"price": 2995,
"publishedDate": "2024-08-06T02:27:53.876Z",
"distance": 2.5578,
"daysOld": 8,
"correlation": 0.855,
"address": "5781 Ambush Ridge Dr",
"bedrooms": 4,
"bathrooms": 3,
"propertyType": "single-family",
"squareFootage": 3142.0,
"yearBuilt": null
},
{
"id": "2893-Albazano-Ct,-Sparks,-NV-89436",
"formattedAddress": "2893 Albazano Ct, Sparks, NV 89436",
"longitude": -119.689736,
"latitude": 39.598478,
"city": "Sparks",
"state": "NV",
"zipcode": "89436",
"price": 2695,
"publishedDate": "2024-04-25T00:00:00.000Z",
"distance": 2.6015,
"daysOld": 111,
"correlation": 0.8529,
"address": "2893 Albazano Ct",
"bedrooms": 4,
"bathrooms": 3,
"propertyType": "single-family",
"squareFootage": 3115.0,
"yearBuilt": 2003
},
{
"id": "3050-Vincinato-Dr,-Sparks,-NV-89434",
"formattedAddress": "3050 Vincinato Dr, Sparks, NV 89434",
"longitude": -119.686603,
"latitude": 39.559443,
"city": "Sparks",
"state": "NV",
"zipcode": "89434",
"price": 2700,
"publishedDate": "2024-04-26T00:00:00.000Z",
"distance": 0.1839,
"daysOld": 110,
"correlation": 0.8513,
"address": "3050 Vincinato Dr",
"bedrooms": 4,
"bathrooms": 3,
"propertyType": "single-family",
"squareFootage": 2200.0,
"yearBuilt": null
},
{
"id": "1744-Golddust-Dr,-Sparks,-NV-89436",
"formattedAddress": "1744 Golddust Dr, Sparks, NV 89436",
"longitude": -119.709381,
"latitude": 39.568036,
"city": "Sparks",
"state": "NV",
"zipcode": "89436",
"price": 2600,
"publishedDate": "2024-06-15T03:25:42.463Z",
"distance": 1.4381,
"daysOld": 60,
"correlation": 0.8497,
"address": "1744 Golddust Dr",
"bedrooms": 4,
"bathrooms": 3,
"propertyType": "single-family",
"squareFootage": 2613.0,
"yearBuilt": null
},
{
"id": "3193-Vincinato-Dr,-Sparks,-NV-89434",
"formattedAddress": "3193 Vincinato Dr, Sparks, NV 89434",
"longitude": -119.685159,
"latitude": 39.561107,
"city": "Sparks",
"state": "NV",
"zipcode": "89434",
"price": 2850,
"publishedDate": "2024-01-01T00:00:00.000Z",
"distance": 0.0649,
"daysOld": 226,
"correlation": 0.8473,
"address": "3193 Vincinato Dr",
"bedrooms": 4,
"bathrooms": 3,
"propertyType": "single-family",
"squareFootage": 2071.0,
"yearBuilt": 2017
},
{
"id": "2631-Michelangelo-Ct,-Sparks,-NV-89434",
"formattedAddress": "2631 Michelangelo Ct, Sparks, NV 89434",
"longitude": -119.693703,
"latitude": 39.562278,
"city": "Sparks",
"state": "NV",
"zipcode": "89434",
"price": 2695,
"publishedDate": "2024-01-21T00:00:00.000Z",
"distance": 0.5265,
"daysOld": 206,
"correlation": 0.8403,
"address": "2631 Michelangelo Ct",
"bedrooms": 4,
"bathrooms": 3,
"propertyType": "single-family",
"squareFootage": 2071.0,
"yearBuilt": 2015
},
{
"id": "4932-High-Pass-Dr,-Sparks,-NV-89436",
"formattedAddress": "4932 High Pass Dr, Sparks, NV 89436",
"longitude": -119.690546,
"latitude": 39.582254,
"city": "Sparks",
"state": "NV",
"zipcode": "89436",
"price": 2695,
"publishedDate": "2024-05-27T00:00:00.000Z",
"distance": 1.5027,
"daysOld": 79,
"correlation": 0.8401,
"address": "4932 High Pass Dr",
"bedrooms": 4,
"bathrooms": 3,
"propertyType": "single-family",
"squareFootage": 2411.0,
"yearBuilt": 2006
},
{
"id": "1565-Iratcabal-Dr,-Sparks,-NV-89436",
"formattedAddress": "1565 Iratcabal Dr, Sparks, NV 89436",
"longitude": -119.714847,
"latitude": 39.582479,
"city": "Sparks",
"state": "NV",
"zipcode": "89436",
"price": 3400,
"publishedDate": "2024-07-28T03:59:19.336Z",
"distance": 2.2125,
"daysOld": 17,
"correlation": 0.8393,
"address": "1565 Iratcabal Dr",
"bedrooms": 4,
"bathrooms": 3,
"propertyType": "single-family",
"squareFootage": 2644.0,
"yearBuilt": null
},
{
"id": "1285-Glendora-Ln,-Sparks,-NV-89436",
"formattedAddress": "1285 Glendora Ln, Sparks, NV 89436",
"longitude": -119.72002,
"latitude": 39.587065,
"city": "Sparks",
"state": "NV",
"zipcode": "89436",
"price": 2900,
"publishedDate": "2024-03-15T00:00:00.000Z",
"distance": 2.6301,
"daysOld": 152,
"correlation": 0.8392,
"address": "1285 Glendora Ln",
"bedrooms": 4,
"bathrooms": 3,
"propertyType": "single-family",
"squareFootage": 2803.0,
"yearBuilt": 1997
},
{
"id": "2598-Piero-Ct,-Sparks,-NV-89434",
"formattedAddress": "2598 Piero Ct, Sparks, NV 89434",
"longitude": -119.69416,
"latitude": 39.56293,
"city": "Sparks",
"state": "NV",
"zipcode": "89434",
"price": 2836,
"publishedDate": "2024-06-28T03:17:22.336Z",
"distance": 0.5589,
"daysOld": 47,
"correlation": 0.8375,
"address": "2598 Piero Ct",
"bedrooms": 4,
"bathrooms": 3,
"propertyType": "single-family",
"squareFootage": 2003.9999999999998,
"yearBuilt": null
},
{
"id": "5390-Cactus-Quartz-Ct,-Sparks,-NV-89436",
"formattedAddress": "5390 Cactus Quartz Ct, Sparks, NV 89436",
"longitude": -119.688623,
"latitude": 39.590295,
"city": "Sparks",
"state": "NV",
"zipcode": "89436",
"price": 5000,
"publishedDate": "2024-01-02T00:00:00.000Z",
"distance": 2.0325,
"daysOld": 225,
"correlation": 0.8326,
"address": "5390 Cactus Quartz Ct",
"bedrooms": 4,
"bathrooms": 3,
"propertyType": "single-family",
"squareFootage": 2435.0000000000005,
"yearBuilt": 2022
},
{
"id": "2552-Cosimo-Ct,-Sparks,-NV-89434",
"formattedAddress": "2552 Cosimo Ct, Sparks, NV 89434",
"longitude": -119.695426,
"latitude": 39.553539,
"city": "Sparks",
"state": "NV",
"zipcode": "89434",
"price": 2995,
"publishedDate": "2024-08-13T00:00:00.000Z",
"distance": 0.8069,
"daysOld": 1,
"correlation": 0.8318,
"address": "2552 Cosimo Ct",
"bedrooms": 4,
"bathrooms": 2.5,
"propertyType": "single-family",
"squareFootage": 2520.0,
"yearBuilt": null
},
{
"id": "1976-Trestle-Ct,-Sparks,-NV-89434",
"formattedAddress": "1976 Trestle Ct, Sparks, NV 89434",
"longitude": -119.706116,
"latitude": 39.544447,
"city": "Sparks",
"state": "NV",
"zipcode": "89434",
"price": 2650,
"publishedDate": "2024-01-09T00:00:00.000Z",
"distance": 1.6525,
"daysOld": 218,
"correlation": 0.8259,
"address": "1976 Trestle Ct",
"bedrooms": 4,
"bathrooms": 3,
"propertyType": "single-family",
"squareFootage": 2137.0,
"yearBuilt": 1987
},
{
"id": "1085-Caboose-Ct,-Sparks,-NV-89434",
...
curl --location --request GET 'https://zylalabs.com/api/2827/us+rental+estimation+api/2939/get+estimation?address=5500 Grand Lake Drive, San Antonio, TX, 78244&propertyType=Condo&bedrooms=2&bathrroms=2&squareFootage=1600' --header 'Authorization: Bearer YOUR_API_KEY'
Header | Description |
---|---|
Authorization
|
[Required] Should be Bearer access_key . See "Your API Access Key" above when you are subscribed. |
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The US Rental Estimation API is a powerful tool that utilizes advanced algorithms and extensive datasets to provide accurate rental price estimates for properties across the United States. It offers developers a programmatic interface to integrate precise rental estimations into their applications, websites, and software solutions.
The API calculates rental estimates by analyzing various factors including property location, size, amenities, historical rental data, and local market demand. Advanced algorithms process this information to generate accurate and up-to-date rental price predictions.
The type of the property. Supported values are: Single Family, Condo, Townhouse, Multi-Family, Apartment. [optional]
No, the API covers rental estimations for properties across the entire United States. It offers nationwide coverage, enabling users to obtain accurate rental price predictions for different states, cities, and neighborhoods.
The API's data is regularly updated to ensure accuracy and relevance. It relies on real-time market data and historical trends, with updates occurring at frequent intervals to reflect the dynamic nature of the real estate market.
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