Welcome to the All-New AirDNA API!

The AirDNA API provides direct access to our industry-leading data & analytics. Whether you’re looking to discover a property’s earning potential, compare markets side by side, or run comps to inform your revenue management strategy, you can do so with the endpoints found here.

The AirDNA API is divided into four packages, each with their own value and use cases:

• Market Data: Unlock market-level data to compare entire different locations side by side, and future data to how properties in that market are priced for upcoming days.
• Property Valuations & Comps: Conduct property-level research with advanced filtering and comp analysis to inform your acquisitions, benchmarking, pricing, and more.
• Rentalizer Lead Gen: Determine the earning potential, occupancy, and nightly rate for any address, anywhere in the world.
• Smart Rates Data: Use Smart Rates — AirDNA’s proprietary dynamic pricing solution – to receive recommended nightly rates for each of your properties.

For more information on our API and its use cases, Contact Sales to get started with an API Key.

All requests to AirDNA's APIs require an Authorization HTTP header with a Bearer token.

• You can obtain an API Key by contacting sales.

For example, if your API Key is a1b2c3d4e5f6g7h8i9j0k1l2, then your Authorization header will be:

Authorization: "Bearer a1b2c3d4e5f6g7h8i9j0k1l2"

The following example uses cURL to demonstrate how to perform a successful request. This assumes:

• Your API Key has not expired.
• Your account has been authorized to access the API Package that the endpoint belongs to.

Request

curl --header 'Authorization: Bearer a1b2c3d4e5f6g7h8i9j0k1l2' --location 'https://api.airdna.co/api/enterprise/v1/market/search?term=Paris%20Texas'

Response 200

{
    "payload": {
        "num_items": 1,
        "items": [
            {
                "id": 80382,
                "name": "Paris",
                "type": "market",
                "location_name": "Paris, Texas, US",
                "location": {
                    "region": null,
                    "city": "Paris",
                    "state": "Texas",
                    "country": "United States",
                    "country_code": "us"
                }
            }
        ]
    },
    "status": {
        "type": "success",
        "response_id": "API-S-011",
        "message": "Successfully fetched Markets for the requested term."
    }
}

The following example uses cURL to demonstrate what happens if you provide an invalid token.

Request

curl --header 'Authorization: Bearer invalidToken' --location 'https://api.airdna.co/api/enterprise/v1/market/search?term=Paris%20Texas'

Response 401

{
    "error": {
        "type": "invalid_credentials",
        "message": "Unauthorized"
    }
}

The following example uses cURL to demonstrate what happens if you omit a token.

Request

curl --location 'https://api.airdna.co/api/enterprise/v1/market/search?term=Paris%20Texas'

Response 401

{
    "error": {
        "type": "invalid_credentials",
        "message": "Authorization token is missing"
    }
}

Filtering is an essential feature to help you obtain data that is relevant to your business needs.

In the following sections, we will explain the do's and don'ts of filtering, and you'll also find a list of available filters that can be used to refine your queries.

⚠️ Notice

• Filters are not required for every data scenario, but we encourage using them when available.
• To use one or more filters on a supported endpoint, you will need to send an array of supported Filter Objects.
• The order of the filters does not matter.

The Filter Object is how you will use filters with supported endpoints.

The following table describes each of the required properties for any Filter Object.

Property	Data Type(s)	Description
"field"	"string"	The data attribute that you want to filter on.
"type"	"string"	The type of filter that you want to apply. "select" "multi_select" "lt" "lte" "gt" "gte" "range"
"value"	"string" "number" "boolean" "array"	The value(s) for the field that you want to filter on.

⚠️ Notice

• Each Property described in the table is required
• The supported values for "type" and "value" will depend on the "field" you are filtering on.

If you only need to use a single filter in your query, you can simply add it to the filters array.

[Example]: Basic Usage

In the following example, we use the filters array to retrieve a dataset where the Listings can accommodate a minimum of 8 people.

{
  "filters": [
    {
      "type": "gte"
      "field": "accommodates",
      "value": 8
    }
  ]
}

⚠️ Notice

Filters must be sent from the filters property via an array.

Some examples of how you might use this example filter:

• Exploring market Data:
  • Explore markets within a country that have listings that can accommodate a minimum of 8 people.
  • Explore submarkets within a country that have listings that can accommodate a minimum of 8 people.
• Exploring listing Data:
  • Explore listings within a country that can accommodate a minimum of 8 people.
  • Explore listings within a market that can accommodate a minimum of 8 people.
  • Explore listings within a submarket that can accommodate a minimum of 8 people.

The ability to combine multiple filters is a key element that allows you to obtain data that meets your specific Business needs.

⚠️ Notice

• Each field can only have one filter applied in any given query.

[Example #1]: Using Numeric Constraints

In the following example, we filter data where the Listings' bedrooms have a minimum=2 and maximum=6.

Instead of trying to use both gte and lte filters, you can instead use the range filter.

❎ INVALID

Applying multiple filters on the same field is unsupported.

{
  "filters": [
    {
      "type": "gte"
      "field": "bedrooms",
      "value": 2
    },
    {
      "type": "lte"
      "field": "bedrooms",
      "value": 6
    }
  ]
}

✅ VALID

The supported way of using both gte and lte filtering is to use the range filter.

{
  "filters": [
    {
      "type": "range"
      "field": "bedrooms",
      "value": [2, 6]
    }
  ]
}

[Example #2]: Filtering Exact Values

There may be some circumstances where you want each field to match an exact value. For this purpose, we have the select filter.

In the following example, we filter data where Listings have exactly 2 bedrooms AND accommodates 4 people.

{
  "filters": [
    {
      "type": "select"
      "field": "bedrooms",
      "value": 2
    },
    {
      "type": "select"
      "field": "accommodates",
      "value": 4
    }
  ]
}

[Example #3]: Filtering A Field To Multiple Exact Values

You may also want to filter data where each field matches one or more values. For this purpose, we have the multi_select filter.

In the following example, we filter data where Listings can accommodate exactly 4 people, AND that the data belongs to two distinct markets (59380 and 73044).

{
  "filters": [
    {
      "type": "select"
      "field": "accommodates",
      "value": 4
    },
    {
      "type": "multi_select"
      "field": "market_id",
      "value": [59380, 73044]
    }
  ]
}

Use this filter to only include results where the market's investability score matches the requested parameters.

Use this to filter results where the market's total active listing_count matches the requested parameters.

Use this filter to only include results that belong to the provided market(s).

Use this filter to only include results where the market_type matches the requested types.

Use this filter to only include results where the market's regulation score matches the requested parameters.

Use this filter to only include results where the market's rental_demand score matches the requested parameters.

Use this filter to only include results where the market's revenue_growth score matches the requested parameters.

Use this filter to only include results where the market's seasonality score matches the requested parameters.

Use this filter to only include results where the number of accommodates (guests) matches the requested parameters.

Use this filter to only include results where the number of bathrooms matches the requested parameters.

Use this filter to only include results where the number of bedrooms matches the requested parameters.

Use this filter to only include results where the days_available_ltm matches the requested parameters.

Use this to filter results where the listings' listing_type matches the requested value(s).

• For markets or submarkets, this means returning only markets/submarkets that have listings with the requested value(s) for listing_type.
• For listings, this means returning only listings with the requested value(s) for listing_type.

Use this to filter results where the listings' occupancy in the last 12 months matches the requested parameters.

Use this to filter results where the listings' price_tier matches the value(s).

• For markets or submarkets, this means returning only markets/submarkets that have listings with the requested value(s) for price_tier.
• For listings, this means returning only listings with the requested value(s) for price_tier.

Use this to filter results where the listings' property_type matches the requested parameters.

Use this filter to only include results where the listings' ratings matches the requested parameters.

Use this to filter results where the listings' real_estate_type matches the requested value(s).

• For markets or submarkets, this means returning only markets/submarkets that have listings with the requested value(s) for real_estate_type.
• For listings, this means returning only listings with the requested value(s) for real_estate_type.

Use this filter to only include results where the listings' reviews_count matches the requested parameters.

Whether you're looking to discover trending markets, learn about a market's historical performance, or gauge its future outlook, these endpoints can support your research.

Historical Market Data

We provide between 12 and 60 months of monthly historical data for the following key metrics:

• Booking Data
  • Occupancy
  • Booking Demand
  • Booking Lead Time
  • Average Length of Stay
• Pricing Data
  • Average Revenue
  • Average Daily Rate
  • RevPAR (Revenue Per Available Rental)

Explore Markets

• In addition to our historical data, our endpoints can help you explore and evaluate markets using a combination of the following:
  • Market Filters
  • Listing Filters
• To find the market_id for a known Market, you can use our Market Search endpoint.