# Airbnb Market Report — ADR & seasonality by city (`davidbenittah/airbnb-market-report`) Actor Turn public Airbnb search data into a short-term rental market report: median nightly rates (ADR), seasonality across future months, supply mix, quality landscape and revenue scenarios. - **URL**: https://apify.com/davidbenittah/airbnb-market-report.md - **Developed by:** [David](https://apify.com/davidbenittah) (community) - **Categories:** Real estate, Travel - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $25.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Airbnb Market Report — ADR & Seasonality by City Turn public Airbnb search data into a **short-term rental market report** for any city or area: median nightly rate (ADR), price percentiles, **seasonality across future months**, supply mix by room type, quality landscape, and transparent monthly revenue scenarios. Built for people evaluating a short-term rental investment or pricing their own listing — the questions AirDNA answers for $40+/month, answered on demand from live public data, for the cost of one run. ### What it does 1. Price-samples your market for several **future months** (one dated sample stay per month, starting next month) using public Airbnb search results. 2. Normalizes every listing to a comparable **nightly rate** (stay total ÷ nights) in your currency. 3. Outputs one `market_report` item plus the most-reviewed listings of the market (`top_listing` items). ### The report contains - **ADR**: median, P25/P75, min/max nightly rate across all sampled listings. - **Monthly table**: ADR stats per sampled month — this is your seasonality curve (high/low season and spread %). - **Supply mix**: share and median ADR per room type (entire home / private room / ...). - **Quality landscape**: average guest rating, median review count, Superhost share — how hard the competition is. - **Revenue scenarios**: median ADR × 30 nights × 50% / 65% / 80% occupancy. These are labeled scenarios, not measurements — occupancy is the one number public search data cannot prove, so the report never pretends otherwise. ### Input example ```json { "location": "Lisbon, Portugal", "currency": "EUR", "sampleMonths": 3, "maxListingsPerSample": 60 } ```` The defaults work as-is: just set your city. ### Output example (report item) ```json { "type": "market_report", "location": "Lisbon, Portugal", "currency": "EUR", "generatedFromListings": 142, "adr": { "adrMedian": 108.8, "adrP25": 84.5, "adrP75": 152.3, "adrMin": 38, "adrMax": 420 }, "monthly": [ { "month": "2026-08", "adrMedian": 131.0, "listings": 60 }, { "month": "2026-09", "adrMedian": 112.4, "listings": 58 }, { "month": "2026-10", "adrMedian": 96.1, "listings": 57 } ], "seasonality": { "highSeasonMonth": "2026-08", "lowSeasonMonth": "2026-10", "spreadPct": 36 }, "supplyMix": { "Entire home/apt": { "count": 118, "sharePct": 83, "adrMedian": 115.2 } }, "quality": { "avgRating": 4.82, "medianReviewsCount": 74, "superhostSharePct": 44 }, "monthlyRevenueScenarios": { "occupancy50pct": 1632, "occupancy65pct": 2122, "occupancy80pct": 2611 } } ``` ### How to use it - **Evaluating a market**: run once per candidate city, compare `adrMedian`, `spreadPct` and `superhostSharePct` side by side. - **Pricing your listing**: your room type's `adrMedian` in `supplyMix` is the market anchor; the monthly table tells you when to raise or drop. - **Tracking a market**: schedule it monthly — each run re-samples the months ahead. ### Fair use & data - Uses only **public Airbnb search results** (no login). - **No host personal data** in the output — host names, photos and profiles are deliberately dropped; only an aggregate Superhost share survives. - Inputs are hard-capped (6 months, 200 listings per sample) so runs stay bounded and predictable. ### FAQ **Is the occupancy real?** No — and nobody's public number is. Occupancy scenarios are clearly labeled multipliers on measured ADR. What IS measured: dated prices, supply, ratings. **Why do monthly listing counts differ?** Airbnb returns what is actually bookable for those dates — that variation is itself a market signal (availability tightens in high season). **Which months are sampled?** Always the 10th of each future month, for `nightsPerSample` nights, so runs are comparable. # Actor input Schema ## `location` (type: `string`): The market to analyze, as you would type it in the Airbnb search bar, e.g. 'Lisbon, Portugal' or 'Nice, France'. ## `currency` (type: `string`): 3-letter currency code for all rates in the report (e.g. USD, EUR). ## `sampleMonths` (type: `integer`): How many future months to price-sample (1 sample stay per month, starting next month). More months = better seasonality picture, higher cost. Hard maximum: 6. ## `nightsPerSample` (type: `integer`): Length of the sample stay used to collect dated prices (nightly rate = stay total / nights). ## `maxListingsPerSample` (type: `integer`): Safety cap on listings collected per sampled month. Hard maximum: 200. ## `adults` (type: `integer`): Guest count used for the sample stays — affects which listings and prices Airbnb returns. ## `topListingsCount` (type: `integer`): Besides the report item, also output the N most-reviewed listings of the market (0 to disable). ## Actor input object example ```json { "location": "Lisbon, Portugal", "currency": "USD", "sampleMonths": 3, "nightsPerSample": 3, "maxListingsPerSample": 60, "adults": 2, "topListingsCount": 20 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "location": "Lisbon, Portugal" }; // Run the Actor and wait for it to finish const run = await client.actor("davidbenittah/airbnb-market-report").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "location": "Lisbon, Portugal" } # Run the Actor and wait for it to finish run = client.actor("davidbenittah/airbnb-market-report").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "location": "Lisbon, Portugal" }' | apify call davidbenittah/airbnb-market-report --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=davidbenittah/airbnb-market-report", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Airbnb Market Report — ADR & seasonality by city", "description": "Turn public Airbnb search data into a short-term rental market report: median nightly rates (ADR), seasonality across future months, supply mix, quality landscape and revenue scenarios.", "version": "1.0", "x-build-id": "LgTcfz6CHrrmClo13" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/davidbenittah~airbnb-market-report/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-davidbenittah-airbnb-market-report", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/davidbenittah~airbnb-market-report/runs": { "post": { "operationId": "runs-sync-davidbenittah-airbnb-market-report", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/davidbenittah~airbnb-market-report/run-sync": { "post": { "operationId": "run-sync-davidbenittah-airbnb-market-report", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "location" ], "properties": { "location": { "title": "City or area", "type": "string", "description": "The market to analyze, as you would type it in the Airbnb search bar, e.g. 'Lisbon, Portugal' or 'Nice, France'." }, "currency": { "title": "Currency", "type": "string", "description": "3-letter currency code for all rates in the report (e.g. USD, EUR).", "default": "USD" }, "sampleMonths": { "title": "Months to sample", "minimum": 1, "maximum": 6, "type": "integer", "description": "How many future months to price-sample (1 sample stay per month, starting next month). More months = better seasonality picture, higher cost. Hard maximum: 6.", "default": 3 }, "nightsPerSample": { "title": "Nights per sample stay", "minimum": 1, "maximum": 7, "type": "integer", "description": "Length of the sample stay used to collect dated prices (nightly rate = stay total / nights).", "default": 3 }, "maxListingsPerSample": { "title": "Max listings per sample", "minimum": 10, "maximum": 200, "type": "integer", "description": "Safety cap on listings collected per sampled month. Hard maximum: 200.", "default": 60 }, "adults": { "title": "Guests (adults)", "minimum": 1, "maximum": 16, "type": "integer", "description": "Guest count used for the sample stays — affects which listings and prices Airbnb returns.", "default": 2 }, "topListingsCount": { "title": "Top listings to include", "minimum": 0, "maximum": 100, "type": "integer", "description": "Besides the report item, also output the N most-reviewed listings of the market (0 to disable).", "default": 20 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```