Serviced Accommodation ROI Calculator

Serviced accommodation (SA) means short-stay rentals via Airbnb/Booking.com - higher nightly rates than long-term rental but more management intensive and variable. Typical city SA: 60-75% occupancy, 80-200/night. Annual gross tends to exceed equivalent long-term rental income, but expenses are higher (cleaning, management 15-25%, voids, supplies).

300k property, 75k deposit. 100/night × 60% × 30 = 1,800/month gross. - 20% management 360 - 400 fixed costs = 1,040 net. Annual 12,480. Cash-on-cash on 75k deposit: 16.6%. Returns compared to long-term rental's ~6%. Trade-offs include more work, higher variability, and regulatory risk.

SA regulations tightening. 90-day annual limit in some regions, Cornwall restrictions noted. Increasing council scrutiny observed. Rate of return differences versus long-term rental reflect: higher management, higher maintenance, regulatory uncertainty, void risk. Active operators with multiple properties often run dedicated SA companies; others may prefer long-term rental simplicity.

Run it with sensible defaults

Using property price of 300,000, deposit of 75,000, nightly rate of 100, occupancy of 60%, the calculation works out to 16.64%. The defaults illustrate a starting point scenario.

The levers in this calculation

The inputs — Property Price, Deposit, Nightly Rate, Occupancy %, and Management % — do not pull with equal force. Not every input has equal weight. Adjusting one input at a time toward extreme values shows which ones move the result most.

How the math works

Monthly rev = nightly × occupancy × 30. Management cost = revenue × mgmt %. Net = revenue - mgmt - fixed. ROI = annual net ÷ deposit × 100.

Where this fits in planning

This is a scenario calculator, not a forecast. Use it to test sensitivities before committing: what happens if the rate is 2% lower than expected, what happens if you extend the holding period. The value is in the scenarios you run, not the single answer from the defaults.

What this doesn't capture

Steady-rate math ignores real-world volatility. Actual returns are lumpy; sequence-of-returns risk matters most in drawdown; fees and taxes drag on compound growth; and behaviour changes in drawdowns can reduce outcomes below the projection. The number represents one scenario rather than a forecast.