21 endpoints
100+ fields per listing
Up to 60 months history
JSON responses
Property-level data, search, and analytics across 20M+ listings. These endpoints provide individual property intelligence from single lookups to batch processing, three modes of geospatial search, 60 months of historical metrics, and 365 days of forward pricing. For advanced query techniques, see the advanced filtering guide.
Retrieve comprehensive property data including amenities, reviews, pricing, host details, and performance analytics for any listing.
The get_listing endpoint is your gateway to property-level intelligence. Pass an Elasticsearch document ID to receive a complete snapshot of any Airbnb listing including physical attributes (bedrooms, bathrooms, accommodates), location data, host information, amenities, pricing details, review scores, and calculated performance metrics like occupancy rate, ADR, and annual revenue. With over 100 data fields per listing, this is the foundation for building property analysis tools, competitive intelligence dashboards, and investment evaluation platforms.
Key differentiator:
Returns pre-calculated analytics (occupancy, ADR, RevPAR, annual revenue) alongside raw property data -- no secondary computation required.
Fetch detailed data for up to 25 listings in a single API call for efficient bulk analysis.
The batch_listings endpoint eliminates the N+1 problem of listing-by-listing data fetching. Submit up to 25 listing IDs in a single POST request and receive the same comprehensive data available from get_listing for each property. This endpoint is essential for property managers monitoring portfolio performance, developers building comparison tools, and analysts conducting competitive set analysis.
Key differentiator:
25-listing batch processing in a single call -- most competitors require individual lookups per property.
Discover comparable Airbnb listings near any property based on location, size, and capacity.
The comparables endpoint answers the question every investor and host asks: "What are similar properties earning nearby?" Provide a listing ID or coordinates plus optional filters (bedrooms, bathrooms, accommodates), and the API returns a curated set of comparable listings ranked by relevance. Each comparable includes full property details and performance metrics, enabling apples-to-apples comparison.
Key differentiator:
Attribute-matched comparables with full performance data -- not just proximity-based results.
Access up to 60 months of time-series performance data for any individual listing.
The listing_metrics endpoint provides the historical performance backbone for property analysis. Request time-series data for any listing and receive monthly metrics including occupancy rate, average daily rate, RevPAR, revenue, and booking patterns spanning up to 60 months. This longitudinal view reveals seasonal patterns, growth trajectories, and performance anomalies that snapshot data misses.
Key differentiator:
60 months of property-level time-series data -- competitors typically offer 12-24 months.
Get forward-looking nightly rates for any listing, up to 365 days into the future.
The listing_future_rates endpoint provides forward-looking pricing intelligence by returning the nightly rate a host has set for each upcoming date, up to 365 days ahead. This is not a forecast -- it is the actual listed price on Airbnb's calendar. This data powers dynamic pricing algorithms, competitive rate monitoring tools, and booking pacing dashboards.
Key differentiator:
365-day forward calendar with actual listed prices -- not model estimates.
Search for Airbnb listings within any named market with powerful filtering and sorting.
The search_by_market endpoint is the primary discovery tool for market-level analysis. Submit a market ID along with optional filters -- bedrooms, bathrooms, accommodates, property type, room type, amenities, host details, ratings, pricing, and performance metrics -- to receive a paginated list of matching listings with complete property data and performance metrics.
Key differentiator:
Advanced filtering and sorting on dozens of attributes -- not limited to basic location-based search.
Find all Airbnb listings within a specified radius of any GPS coordinate.
The search_by_radius endpoint enables address-level competitive analysis. Provide GPS coordinates and a radius in miles, and receive all matching listings within that circle. Combined with filters for property attributes, performance thresholds, and amenities, this creates a powerful tool for hyperlocal market analysis and neighborhood-level competitive density assessment.
Key differentiator:
Arbitrary radius search (1-100 miles) with full filter support -- competitors limit to predefined market boundaries.
Search listings within any custom-drawn polygon boundary for precise area analysis.
The search_by_polygon endpoint represents the most advanced geospatial search capability available in any STR data API. Define a custom boundary as an array of latitude/longitude coordinate pairs, and the API returns all listings contained within that polygon. This enables analysis of custom-defined neighborhoods, school districts, zoning areas, or any geographic region that does not align with standard market boundaries.
Key differentiator:
No competitor offers freeform polygon search -- only AirROI lets you draw your own market boundary.
Aggregate analytics, time-series metrics, and demand signals for any market worldwide. From summary snapshots to 60-month time-series across every key STR metric -- occupancy, ADR, RevPAR, revenue, booking lead time, length of stay, active supply, and forward-looking booking pacing. For geospatial techniques, see the geospatial search tutorial.
Get a comprehensive overview of key STR metrics for any market in one call.
The market_summary endpoint delivers a high-level snapshot of market conditions in a single request. Receive aggregate metrics including total active listings, median annual revenue, average occupancy rate, average daily rate, RevPAR, booking lead time, average length of stay, and supply trends. The foundation for market screening tools, investment dashboards, and automated reporting systems.
Key differentiator:
Complete market health check in one call with pre-calculated metrics -- no assembly required.
Retrieve all time-series performance metrics for a market in a single comprehensive call.
The market_metrics_all endpoint is the power tool for market analysis. A single call returns all available monthly time-series metrics for any market, spanning up to 60 months of historical data. This includes occupancy rates, average daily rates, RevPAR, total revenue, active listing counts, booking lead times, and average length of stay -- all segmented by month with percentile breakdowns.
Key differentiator:
All metrics in one call with 60-month depth and native currency -- competitors require multiple API calls and offer less history.
Track monthly occupancy rate trends for any market over time.
Returns occupancy rate as a monthly time-series for a specified market and date range. Essential for demand analysis, seasonal pattern detection, and understanding market cyclicality. Supports up to 60 months of historical data with percentile breakdowns for deeper insight into market distribution.
Key differentiator:
Granular monthly occupancy with 15+ years of data depth for long-term trend analysis.
Monitor average daily rate (ADR) trends for any market over time.
Returns ADR as a monthly time-series for a specified market and date range. Essential for pricing strategy, rate benchmarking, and understanding competitive pricing dynamics. Supports native currency for non-USD markets, enabling accurate cross-border analysis.
Key differentiator:
ADR in local currency with multi-year historical context for pricing decisions.
Analyze Revenue Per Available Room (RevPAR) trends for any market.
Returns RevPAR as a monthly time-series -- the gold-standard metric combining occupancy and pricing performance in a single indicator. RevPAR captures the interplay between pricing power and demand, making it the most comprehensive single metric for market evaluation.
Key differentiator:
RevPAR time-series with 15+ years of depth -- the deepest RevPAR dataset in the industry.
Track total market revenue over time to understand market size and growth.
Returns aggregate market revenue as a monthly time-series. Shows the total revenue generated by all listings in a market, revealing growth trajectories, market sizing data, and total addressable market signals for investment analysis.
Key differentiator:
Market-wide revenue aggregation for TAM analysis and growth trend detection.
Understand how far in advance guests book in any market.
Returns average booking lead time as a monthly time-series. Reveals booking behavior patterns and advance demand signals that inform pricing and availability strategies. Markets with longer lead times enable earlier yield management decisions.
Key differentiator:
Booking lead time analytics -- most competitors do not track this metric.
Track average guest length-of-stay trends for any market.
Returns average length of stay as a monthly time-series. Identifies markets with extended stays versus weekend demand patterns, informing minimum-night strategies, property targeting, and operational planning for turnover management.
Key differentiator:
Length-of-stay trends for identifying midterm rental and extended-stay opportunities.
Monitor supply growth and active listing counts over time for any market.
Returns the count of active listings as a monthly time-series. Essential for supply/demand analysis, market saturation detection, and investment timing. Rising supply without proportional demand growth signals potential compression in occupancy and rates.
Key differentiator:
Supply-side time-series for detecting market saturation before it impacts returns.
See forward-looking booking velocity data to predict future market demand.
The market_future_pacing endpoint provides the most forward-looking demand intelligence in the STR data industry. While most metrics look backward, pacing data shows the rate at which future dates are being booked. This reveals demand signals weeks or months before they appear in trailing metrics. Property managers use pacing to adjust pricing dynamically; investors use it to validate market momentum before committing capital.
Key differentiator:
Forward-looking demand signal -- the only API providing market-level booking pacing data.
Find market IDs by name using text search across AirROI's global market taxonomy.
Text search across AirROI's market hierarchy -- countries, states, cities, neighborhoods, and subdivisions. Returns market IDs needed for all market-level API calls. This is the entry point for any location-based workflow, resolving human-readable names to the identifiers required by analytics endpoints.
Key differentiator:
Hierarchical market taxonomy spanning 190+ countries with subdivision-level granularity.
Resolve GPS coordinates to the matching AirROI market for location-based workflows.
Pass latitude and longitude to receive the corresponding market ID and metadata. The bridge between geolocation and market analytics. Essential for applications that start from a physical address or map location and need to access market-level performance data.
Key differentiator:
Instant coordinate-to-market resolution -- the fastest way to connect any location to STR market intelligence.
ML-powered revenue projections based on 20M+ property data points. The estimate_revenue endpoint bridges raw data and actionable projections, delivering comp-based estimates with 95%+ accuracy for any location globally. Try the free interactive calculator to see it in action.
Generate instant Airbnb revenue projections for any property based on location and attributes.
The estimate_revenue endpoint turns any property description into a revenue projection. Submit location coordinates and property attributes (bedrooms, bathrooms, accommodates), and receive ML-driven projections for annual revenue, monthly revenue estimates, expected occupancy rate, projected ADR, and a set of comparable properties used in the estimate. The underlying model is trained on billions of data points from 20M+ properties, delivering 95%+ accuracy.
Key differentiator:
Comp-based revenue model with transparent methodology -- see exactly which comparable properties inform the estimate.
Two complete API call examples showing request and response. Every endpoint follows the same consistent JSON pattern -- predictable structures across all 21 endpoints.
curl -X POST "https://api.airroi.com/markets/summary" \
-H "x-api-key: YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"country_code": "us",
"state": "florida",
"city": "miami-beach"
}'{
"market": "Miami Beach, Florida",
"active_listings": 4218,
"median_annual_revenue": 62400,
"average_occupancy": 0.684,
"average_adr": 289.50,
"average_revpar": 198.42,
"avg_booking_lead_time_days": 34,
"avg_length_of_stay_nights": 4.2,
"currency": "USD"
}curl "https://api.airroi.com/listings/comparables\ ?latitude=25.7907&longitude=-80.1300\ &bedrooms=2&bathrooms=1&accommodates=4" \ -H "x-api-key: YOUR_API_KEY"
{
"comparables": [
{
"listing_id": "1238217617",
"name": "Ocean View 2BR Suite",
"annual_revenue": 71200,
"occupancy_rate": 0.73,
"adr": 267.00,
"distance_miles": 0.4,
"bedrooms": 2
},
{
"listing_id": "9876543210",
"name": "Beachfront Condo w/ Pool",
"annual_revenue": 68500,
"occupancy_rate": 0.71,
"adr": 264.00,
"distance_miles": 0.6,
"bedrooms": 2
}
],
"total_comparables": 18
}All endpoints return structured JSON with consistent pagination, error handling, and metadata patterns. Responses are UTF-8 encoded with standard HTTP status codes. List endpoints include pagination metadata, and every response follows a predictable structure so your parsing logic works across all 21 endpoints without modification.
Yes. Rate limits are per-API-key and scale with your usage tier. Standard accounts have generous limits suitable for most development and production workloads. Rate limit headers are returned in every response so your application can adapt. Enterprise customers receive custom rate limits for high-throughput applications.
Yes. AirROI offers three geospatial search methods: market-based search (predefined city and neighborhood boundaries), radius search (circle of 1-100 miles around any GPS coordinate), and polygon search (custom-drawn boundaries with 3+ coordinate points). Polygon search is unique to AirROI -- no competitor offers this capability. All three methods share the same filtering and sorting options.
Yes. The listing_future_rates endpoint returns up to 365 days of forward nightly rates for individual listings -- actual listed prices, not forecasts. The market_future_pacing endpoint shows aggregate booking velocity for markets, a leading demand indicator that trailing metrics miss. Together, these endpoints enable pricing strategies informed by real market signals.
You can retrieve all listings in a market through the search_by_market endpoint with pagination. For a conversational, single-request approach to full market exports, AirROI's MCP Server offers an export_market tool that returns every listing in one call — ideal for bulk analysis and data warehousing workflows.
AirROI's API is a REST API providing programmatic access to the world's largest short-term rental dataset. It covers 20M+ Airbnb and vacation rental properties across 190+ countries with 15+ years of historical data. The 21 endpoints span property details, market analytics, geospatial search, revenue projections, and forward-looking demand data.
Everything you need to integrate short-term rental data into your application — from endpoint docs to competitive benchmarks.
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