Airbnb Revenue Estimator

What it does

Project net annual income from a short-term rental property. Inputs: average nightly rate, occupancy rate, cleaning fee per turnover, host platform fee (Airbnb 14-16% combined host+guest, Vrbo 8-10%), property management %, supplies and utilities, maintenance reserve. Output: gross revenue, total expenses by category, net annual income, and effective net yield. Designed for buy-decisions on STR-targeted properties where the 4-5x revenue multiple over long-term rental can justify higher purchase prices.

Short-term rental economics differ from long-term rentals in three structural ways: (1) Revenue multiple — same property earns 2-4x more gross revenue as STR vs LTR, but expense ratio is also 2-3x higher (cleaning, supplies, utilities, platform fees, more wear-and-tear). Net is typically 40-80% higher than equivalent LTR. (2) Volatility — peak/off-season swings 5-10x in beach/ski markets; pandemic, regulation, market saturation can crater occupancy. (3) Regulatory risk — major STR markets (NYC, San Francisco, LA, Honolulu, New Orleans) have either banned or severely restricted short-term rentals; secondary markets (Charleston, Asheville, Branson, Sedona) implementing similar rules. Always check local STR regulations before buying.

Realistic occupancy expectations: Year 1 30-45% as you build review base from zero. Year 2-3 55-65% for established listings in healthy markets. Mature listings 65-75% in best markets, 80%+ for top-decile superhosts in tourist-destination markets with peak-season pricing. Beach/ski markets show extreme seasonality: 85%+ peak (July-August or December-March), 20-40% off-season — annual average might be 50-55%. Use AirDNA or MashVisor for market-specific data; avoid relying on platform-provided “earnings potential” figures (those are best-case, not realistic).

How to use it

1. Look up market data via AirDNA, MashVisor, or manually averaging 5-10 comparable Airbnb listings in the same zip code with same bedroom count.
2. Enter average nightly rate (use median of comparables).
3. Enter realistic occupancy — year-1 30-45%, established 55-65%, top-decile 65-75%.
4. Enter cleaning fee per turnover ($75-200 typical) and average stay length (2-3 nights average → ~10-15 turnovers/month at 50% occupancy).
5. Enter platform fee % (Airbnb ~3% host + 11-13% guest = ~14% combined; Vrbo similar; direct booking 0%).
6. Read net annual income. Compare to long-term rental scenarios and to the property's purchase price for yield calculation.

When to use this tool

• Pre-purchase analysis of STR-targeted properties — knowing realistic net income justifies the higher purchase price vs LTR comp.
• Yield comparison — STR vs LTR for same property, with realistic expense ratios.
• Existing-listing optimization — running scenarios where you raise rate or improve listing to boost reviews and occupancy.
• Market entry analysis — comparing different cities/neighborhoods for STR investment by running same property hypothetically in each.

When not to use it

• When the city has banned or severely restricted STRs — calculator shows revenue, doesn't model regulatory risk that could kill the listing.
• Highly seasonal markets without seasonal modeling — single occupancy number misses the peak/off-season swing that determines actual cash flow timing.
• When you need event-by-event analysis (Mardi Gras week, Super Bowl) — those require booked-rate-specific calculations, not annual averages.
• First-time hosts assuming smooth operation — first year typically 30-50% lower revenue than mature listing while you build reviews and learn pricing.

Common use cases

• Verifying a number or output before passing it on
• Quick calculation during a typical workday
• Pre-decision sanity-check on inputs and outputs
• Educational use — demonstrating the underlying concept