Airbnb Occupancy Scraper

Airbnb Occupancy Scraper

The Airbnb Occupancy Scraper is a focused data extractor that collects availability calendar entries (per date, per listing) from public Airbnb listing pages. It solves the challenge of measuring occupancy trends by automating a clean, repeatable pull of daily availability, making it an ideal Airbnb occupancy rate scraper for market research and performance tracking. Built for marketers, developers, data analysts, and researchers, it helps you build an Airbnb availability calendar scraper workflow at scale so you can monitor Airbnb booking occupancy data reliably over time.

What data / output can you get?

Each output record represents a single date for a single listing (room) with an availability flag. Results are saved to the Apify dataset during the run.

Data field	Description	Example value
room_id	Airbnb listing (room) ID associated with the date record	"35329051"
date	Calendar date extracted from the listing’s availability calendar (ISO format)	"2026-12-01"
available	Availability status for that date (boolean)	false

Notes:

• Data is flattened to one record per date per room for flexible filtering and analysis.
• Export your dataset to JSON or CSV directly from Apify for downstream analysis and reporting.

Key features

• 🔄 Smart proxy fallback Automatically switches connection strategy to improve reliability. The scraper starts direct, can enable Apify Proxy (datacenter), and falls back to residential proxy on repeated failures.

• 📦 Bulk room ID processing Process multiple Airbnb listing IDs in a single run. The actor loops through all provided roomIds and continues even if some rooms fail.

• 🧱 Structured, analysis-ready output Outputs a flat schema with room_id, date, and available fields, ideal for pipelines and dashboards focused on Airbnb listing occupancy analytics.

• ♻️ Resilient fetching with retries Implements retry logic and exponential backoff for network/transient errors, plus graceful error handling so remaining rooms continue.

• 🧠 Dynamic discovery under the hood Programmatically extracts the Airbnb API key from listing pages and discovers the required GraphQL operation ID before fetching availability.

• 💾 Real-time dataset writes on Apify Saves records continuously to the Apify dataset so you can monitor progress and export results whenever you need.

How to use Airbnb Occupancy Scraper - step by step

1. Create or log in to your Apify account.
2. Open the actor “airbnb-occupancy-scraper” on the Apify platform.
3. In the INPUT tab, add your Airbnb Room IDs under roomIds (string list). Example: 35329051, 769824007018240779.
4. Set month and year to define the starting period for retrieval (the actor fetches 12 months of data from that point).
5. (Optional) Configure proxyConfiguration. You can leave useApifyProxy disabled or enable Apify Proxy as needed.
6. Click Start to run the actor. You’ll see detailed logs as it discovers credentials, fetches calendars, and writes records.
7. When finished (or during the run), open the Dataset (OUTPUT) to preview results and export to JSON or CSV.

Pro Tip: Use multiple roomIds to create a short term rental occupancy scraper workflow that tracks Airbnb occupancy trends across markets or host portfolios.

Use cases

Use case name	Description
Market research + occupancy benchmarking	Analyze Airbnb occupancy rates across listings in a city or neighborhood to quantify supply-demand dynamics.
Revenue management + booking rate insights	Track availability to infer booking patterns and optimize pricing windows during high and low occupancy periods.
Competitor availability monitoring	Monitor competitor availability calendars for a continuous Airbnb occupancy monitoring tool that informs strategy.
Investment analysis for STRs	Evaluate historical availability to assess seasonality and potential performance of target vacation rental markets.
Portfolio health tracking for hosts	Aggregate per-date availability across multiple roomIds to understand booking velocity and coverage.
Data engineering + API pipelines	Feed the Airbnb occupancy dataset scraper output into analytics stacks or ETL jobs for automated reporting.

Why choose Airbnb Occupancy Scraper?

Built for precision and reliability, this Airbnb occupancy data extractor delivers structured availability data without manual effort.

• ✅ Accurate, structured output focused on availability status per date
• 🔁 Robust fallback logic to handle blocks and transient failures
• 📊 Scales across many listings with room-by-room resilience
• 👨‍💻 Developer-friendly output fields for easy downstream use
• 🔒 Public data only; no login or cookies required
• 💡 Better than ad‑hoc tools: reliable Apify infrastructure and dataset storage
• 📤 Easy export to JSON or CSV from the Apify dataset

In short, it’s an Airbnb market occupancy analysis tool designed to be more stable and maintainable than brittle browser extensions or manual workflows.

Is it legal / ethical to use Airbnb Occupancy Scraper?

Yes — when used responsibly. This actor extracts availability information from publicly accessible Airbnb listing pages and does not access private or authenticated data.

Guidelines for responsible use:

• Only collect publicly available calendar data.
• Comply with platform terms and applicable regulations (e.g., GDPR/CCPA).
• Avoid excessive request rates and respect fair-use principles.
• Consult your legal team for edge cases or jurisdiction-specific questions.

Input parameters & output format

Example JSON input

{
  "roomIds": ["35329051", "769824007018240779"],
  "month": 12,
  "year": 2026,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}

Parameter reference:

• roomIds (array of string) — List one or more Airbnb room IDs to scrape occupancy data for. Required: Yes. Default: none.
• month (integer) — Month to fetch occupancy data for (1–12). Required: No. Default: 12.
• year (integer) — Year to fetch occupancy data for. Required: No. Default: 2026.
• proxyConfiguration (object) — Choose which proxies to use. If Airbnb rejects the proxy, fallback to residential proxy will be used automatically. Required: No. Prefill: { "useApifyProxy": false }.

Example JSON output (one record per date per room)

[
  { "room_id": "35329051", "date": "2026-12-01", "available": false },
  { "room_id": "35329051", "date": "2026-12-02", "available": true },
  { "room_id": "769824007018240779", "date": "2026-12-01", "available": false }
]

Notes:

• available is boolean. If the API returns a null availability value for a date, it is treated as false in the output.
• Records are saved as they are processed, enabling incremental export during long runs.

FAQ

Is there a free trial?

Yes. This actor listing includes a trial period measured in minutes on Apify. You can start a run to evaluate the Airbnb booking occupancy data scraper before subscribing.

Do I need to log in or provide cookies?

No. The Airbnb occupancy API data used by this actor is derived from public listing pages. The actor extracts required metadata (like an API key) directly from the room page and does not log in.

How many listings can I scrape in one run?

You can provide multiple roomIds in a single input. The actor processes each listing sequentially and continues even if some rooms fail, making it suitable for Airbnb occupancy trends scraper use cases.

What date range does it cover?

For each room_id, the actor requests 12 months of availability starting from the specified month and year. This supports both upcoming and historical month ranges.

What fields are included in the output?

Each output record contains room_id, date, and available. This simple schema makes it a focused Airbnb nights booked scraper alternative for occupancy analysis based on availability.

Can I export to CSV or integrate with my tools?

Yes. Results are stored in the Apify dataset, which you can export to JSON or CSV. From there, you can connect to BI tools, data pipelines, or use it as an Airbnb occupancy rate tool for analytics.

How does the proxy fallback work?

The actor starts with a direct connection or Apify Proxy (if enabled), then falls back to more robust options on repeated failures. It manages retries and exponential backoff to maintain reliability as an Airbnb occupancy monitoring tool.

Is historical data supported?

Yes. Set month and year to a past period to fetch calendar data starting at that point. The actor pulls 12 months from the chosen start date.

Closing CTA / Final thoughts

The Airbnb Occupancy Scraper is built for structured, reliable extraction of per-date availability from Airbnb listings. With resilient proxy fallback, multi-listing support, and clean output fields, it powers market analysis and benchmarking across cities, neighborhoods, or host portfolios.

Marketers, analysts, researchers, and developers can use the Apify dataset to export JSON/CSV and build dashboards or automation pipelines. Start collecting accurate availability data today and turn it into actionable Airbnb occupancy analytics at scale.