Case Study: Finding the "Tipping Point" Between STR and LTR

[Leo Li]

When evaluating a property for Short-Term Rental (STR) vs. Long-Term Rental (LTR), many investors focus on gross nightly rates. However, the real decision should be based on the "Tipping Point", which is the exact occupancy rate where the STR's higher overhead is actually justified by the net profit.

I recently modeled this for a 3,436 sqft property in the Inland Empire to see where that line is drawn in today's market.

The Financial Model:

- LTR Baseline: Based on 146 local 5BR comps, the median market rent is $4,100/month, netting roughly $3,854 after management fees.

- STR Crossover: To match that $3,854 net, this property requires a 71% occupancy rate at a base price of $343/night.

- The "Hidden" Friction: For a house this size, the operational costs are significant. We factored in about $200 in cleaning fees per stay, 15.5% for platform fees, and roughly $250 in utilities.

The 3-Year Outlook: Stability often wins over long horizons. Even at a "moderate" 70% occupancy, the 3-year cumulative income for the STR was $1,684 lower than the LTR ($141,242 vs. $142,906). This is due to the higher management intensity, estimated at 12 hours/month for STR vs. 2 hours for LTR as well as the consistent cash flow of a long-term lease.

The Takeaway: STR offers a great "Best-Case" upside (+$515/month at 80% occupancy), but the margin for error is thinner than most realize.

I'm looking for your feedback on this approach:

1. Do you use a similar "Break-Even Occupancy" metric when pitching a strategy to partners or clients?

2. What "hidden costs" (like specialized insurance or deep cleaning) do you feel are most often missed in these comparisons?

3. Would you find an analysis like this helpful for determining which strategy to use when deciding whether to list a property as a short-term or long-term rental?

[John Underwood]

You also have to look at seasonality for nightly rates and occupancy. 

Then all your expenses. 

There are specialized STR spreadsheets that help you analyze a potential property.

Several of these spreadsheets have already been posted on this forum so that people can search for and find these.