Airbnb Market Report — ADR & Occupancy Scenarios

Turn public Airbnb search data into a short-term rental market report for any city: median nightly rate (ADR) and percentiles, seasonality across the months ahead, supply mix by room type, the ratings landscape, and monthly revenue scenarios at 50, 65 and 80% occupancy. The questions AirDNA answers for $40 a month, answered on demand 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).

Data in the report: ADR, seasonality, occupancy scenarios

• 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.

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.

Input example

{
  "location": "Lisbon, Portugal",
  "currency": "EUR",
  "sampleMonths": 3,
  "maxListingsPerSample": 60
}

The defaults work as-is: just set your city.

Output example (report item)

{
  "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 }
}

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.

Independence notice

This is an unofficial tool and is not affiliated with, endorsed by, or sponsored by Airbnb. It reads public Airbnb search results only, and outputs no host personal data.