Airbnb Price Monitor · Nightly Rate Tracker

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Track nightly prices across any Airbnb market. Paste a city search URL — get avg, min, max, and median rates per listing plus a market-level summary by month.

No login. No API key. No account required.

Who is this for?

What you get by default — listing name, property type, ratings, avg/min/max/median nightly rate, price breakdown by calendar month (priceByMonth), discount detection for weekly and monthly stays, and a market-level summary (average price per month across all listings) in the run log.

For per-listing occupancy and full calendar data — use a listing URL directly. Calendar mode returns day-by-day prices, occupancy rate, and coverage rate over the full period.

What it extracts

Per listing

Market summary (in run log)

At the end of every city scan, the run log prints:

─── Market Summary ──────────────────────────────────────────
 Listings withprices:2845/2859(100%)
 Multi-date samples :913 listings have 2+ price points
 Sample distribution :0×→14,1×→1932,2×→528,3×→182 …
 Avg market price/month:
2026-06: avg 175EUR/night(721 listings sampled)
2026-07: avg 147EUR/night(1211 listings sampled)
2026-08: avg 166EUR/night(1060 listings sampled)
─────────────────────────────────────────────────────────────

Quick start

1. Open the Actor in Apify Console and click Try for free
2. Paste an Airbnb search URL (e.g. https://www.airbnb.com/s/Barcelona--Spain/homes) in the URLs field
3. Click Start — results appear in the Dataset tab within a few minutes
4. Use the Overview view to compare listings side by side, or Flat prices for a day-by-day spreadsheet

Input

Input examples

Scan an entire city market:

{
"urls":["https://www.airbnb.com/s/Lisbon--Portugal/homes"],
"monthsAhead":3
}

Monitor specific competitor listings:

{
"urls":[
"https://www.airbnb.com/rooms/12345678",
"https://www.airbnb.com/rooms/87654321"
],
"monthsAhead":6
}

Mix search + direct listing in one run:

{
"urls":[
"https://www.airbnb.com/s/Nice--France/homes",
"https://www.airbnb.com/rooms/99999999"
],
"monthsAhead":2,
"currency":"EUR"
}

How it works

City search URL (market scan)

1. URL normalisation — strips user locale, injects locale=en&currency=<selected> for consistent price strings
2. Multi-window discovery — runs 78 parallel search windows (2-night, 5-night, and 7-night stays × Monday + Friday check-ins × one window per week over the period). The three stay lengths matter: Airbnb only shows listings that are available and meet the minimum-nights requirement — a listing with minNights = 5 is invisible in 2-night searches.
3. Parallel page fetching — within each window, all result pages (up to 5) are fetched in parallel; windows run in bounded batches of 15 to control memory
4. Price extraction — nightly rate parsed from Airbnb's embedded JSON (pricePerNight from structured display); fallback computes price from total ÷ nights when the qualifier is "total"
5. Price deduplication — for listings found in multiple windows, the 2-night (baseline) price is preferred per check-in week to avoid inflating priceByMonth averages
6. Rate-limit retry — blocked windows are retried once after a 3-second pause
7. Stats computation — avg, min, max, median, monthly breakdown, discount detection, pricing strategy (when ≥ 5 samples)
8. Dataset push — one row per listing; market summary printed to run log

Direct listing URL (calendar mode)

1. Listing page fetch — extracts GPS coordinates and city from the listing HTML
2. Calendar API — calls PdpAvailabilityCalendar for each month in the period (10 listings in parallel), returns per-day price, availability, and minNights
3. Stats computation — same as above plus occupancyRate (% days already booked) and coverageRate (% bookable days with a price)

Data quality — what "1 sample" means

In city scan mode, most listings have 1–3 price samples. This is not a limitation of the Actor — it reflects how Airbnb works: a listing only appears in a search window when it is available and meets the minimum stay for those specific dates. A listing that is fully booked for the summer appears in only one or two of the 78 windows.

For deep per-listing analysis across all dates, use a direct listing URL — the calendar mode returns prices for every available day over the full period.

Performance and cost

Runs are purely HTTP (no browser) — low memory (256 MB default), high concurrency.

Proxy cost: $10/GB). Without a proxy, large scans (200+ listings) may hit Airbnb rate-limiting. Add Apify Residential proxies in the Proxy section for reliable results.

Output sample

City scan listing:

{
"listingId":"25497233",
"listingUrl":"https://www.airbnb.com/rooms/25497233",
"listingName":"Charming studio near Montmartre",
"propertyType":"Apartment in Paris",
"city":"Paris",
"rooms":1,"beds":1,"bathrooms":1,
"rating":4.85,"reviewCount":142,
"currency":"EUR",
"dateFrom":"2026-06-15",
"dateTo":"2026-08-31",
"priceSamples":4,
"avgPricePerNight":118,
"minPricePerNight":95,
"maxPricePerNight":145,
"medianPricePerNight":112,
"weeklyDiscountPct":12,
"pricingStrategy":"dynamic",
"priceByMonth":[
{"month":"2026-06","avgPricePerNight":95,"minPricePerNight":95,"maxPricePerNight":95,"pricedDays":1},
{"month":"2026-07","avgPricePerNight":118,"minPricePerNight":110,"maxPricePerNight":125,"pricedDays":2},
{"month":"2026-08","avgPricePerNight":145,"minPricePerNight":145,"maxPricePerNight":145,"pricedDays":1}
],
"scrapedAt":"2026-06-01T16:00:00.000Z",
"prices":[
{"checkin":"2026-06-15","checkout":"2026-06-17","pricePerNight":95,"nights":2,"isBaseline":true},
{"checkin":"2026-07-07","checkout":"2026-07-09","pricePerNight":110,"nights":2,"isBaseline":true}
]
}

Direct listing (calendar mode) — additional fields:

{
"bookableDays":72,
"occupancyRate":41,
"coverageRate":86,
"priceSamples":62
}

Dataset views

Pricing

You pay only for listings where a price was successfully returned — not for the run itself.

Typical cost:

Local development

npminstall
# Edit storage/key_value_stores/default/INPUT.json with your test URLs
apify run

Set HTTPS_PROXY in your shell (or use Apify's proxy URL) to avoid rate-limiting locally:

$HTTPS_PROXY="http://groups-RESIDENTIAL:TOKEN@proxy.apify.com:8000" apify run

Output is written to storage/datasets/default/ and a local storage/output.csv.

Related Actors

• Airbnb Calendar Availability Scraper — occupancy rates, blocked/available days, and min/max nights for any market
• Airbnb Property Details Scraper — full listing pages: description, amenities, host info, GPS, photos
• Airbnb Pro Host Business Email Scraper — business emails and company data for professional Airbnb hosts

Support

Custom scraper or tailored automation? Contact corentin@outreacher.fr.